Facile Fabrication of a Nanocomposite Electrode for Enhanced Electrochemical Performance

Facile Fabrication of a Nanocomposite Electrode for Enhanced Electrochemical Performance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Facile Fabrication of a Nanocomposite Electrode for Enhanced Electrochemical Performance Dessalew Berihun Adam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7148554/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A novel Nanocomposite electrode composed of zinc oxide (ZnO), copper oxide (CuO), reduced graphene oxide (rGO), and poly(acrylonitrile-co-acrylic acid) (PANINS), denoted as ZnO/CuO/rGO/PANINS, was synthesized via a one-step in situ polymerization strategy for non-enzymatic glucose detection. The PANINS polymer was uniformly coated onto the ZnO/CuO/rGO framework, enhancing the structural integrity and conductivity of the resulting electrode. Structural and physicochemical characterizations were conducted using UV-visible spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) to evaluate the optical properties, functional groups, and crystallinity of the synthesized Nanocomposite. Electrochemical performance was assessed using cyclic voltammetry (CV) and amperometry in 0.1 M NaOH electrolyte. The modified glassy carbon electrode (GCE) exhibited significantly enhanced current responses compared to unmodified and non-PANINS-modified counterparts, attributed to the synergistic catalytic activity of the Nanocomposite components. The active surface area increased from 0.001 cm² (bare GCE) to 0.199 cm² (ZnO/CuO/rGO/PANINS-modified GCE). The sensor demonstrated a lower onset potential and higher peak current for glucose oxidation, indicating improved electro catalytic activity. Amperometric analysis revealed a linear detection range of 2-10 mM glucose, with a high sensitivity of 5660 μA mM - ¹ cm - ², a low detection limit of 0.00054 μM, and a rapid response time of 3 seconds. The sensor also exhibited excellent selectivity toward glucose in the presence of common interfering species, along with good reproducibility (RSD = 2.89 %), repeatability (RSD = 4.2 %), and long-term stability, retaining 89.5 % of its initial current response after 10 days. The sensor’s applicability was validated in real blood samples, showing strong correlation with standard spectrophotometric methods. These results suggest that the ZnO/CuO/rGO/PANINS Nanocomposite is a promising platform for the development of high-performance, non-enzymatic electrochemical glucose sensors. Nanocomposite Electrochemical glucose sensor Sensitivity Cyclic voltammetry Stability Reproducibility Non-enzymatic detection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction A chronic metabolic disease known as diabetes is typified by high blood glucose levels, which can cause serious health issues that impact several organ systems. According to the World Health Organization (WHO), 422 million people worldwide are estimated to have diabetes, making it a serious public health issue [ 1 ]. Long-term hyperglycemia-related complications of diabetes include cardiovascular disease, neuropathy, retinopathy, amputations, hypertension, and dyslipidemia. These issues constitute serious chronic illnesses and offer a serious public health concern on a worldwide scale [ 2 ]. In addition to being crucial for the diagnosis of diabetes, glucose monitoring and management are important for a number of other industries, such as wastewater treatment, environmental monitoring, and the food and textile sectors. Accurate glucose detection is essential in these situations to maintain quality control, enhance fermentation, and evaluate the health of the ecosystem [ 3 ]. Consequently, the food, chemical, biological, and clinical diagnostics sectors have all shown a great deal of interest in glucose level monitoring. Recent developments in this area have prompted research into extremely precise glucose detection techniques, including as colorimetric assays, electrochemical sensors, surface-enhanced Raman scattering, and fluorescence approaches [ 4 – 6 ]. Because of their affordability, ease of synthesis, and adaptability in detecting a variety of analytes, electrochemical sensors have attracted a lot of interest in both research and industry applications. These sensors use electrochemical principles to deliver quick, accurate, and targeted measurements in a variety of settings, such as food safety, medical diagnostics, and environmental monitoring [ 7 ]. Electrochemical sensors are ideal for on-site analysis due to minimal sample preparation and rapid results, with advancements in bifunctional catalysts and nanomaterials enhancing their detection limits, sensitivity, and selectivity. Enzyme-based glucose sensors, particularly those utilizing glucose oxidase, exhibit high selectivity and biocompatibility but face challenges such as high production costs, instability, limited lifespan, suboptimal kinetics, and environmental sensitivity, indicating a need for further research to enhance their performance and adaptability [ 8 , 9 ]. Researchers are exploring non-enzymatic electrochemical glucose sensors to address existing limitations. These sensors offer advantages such as affordability, reliability, simplicity, stability, and reproducibility. Their technology is based on the direct oxidation of glucose at the electrode surface, enhanced by non-biological recognition elements, which improves sensor performance and enables efficient electrochemical glucose detection without biological catalysts [ 10 , 11 ]. The development of non-enzymatic glucose sensors encounters challenges such as high working potentials, erratic redox reactions, and slow electron transfer kinetics. Recent research has concentrated on synthesizing novel nanomaterials with high electrical conductivity and enhanced catalytic activity to overcome these obstacles, as their favourable properties including large surface area and low charge transfer resistance make them ideal electrode materials [ 12 ]. A range of nanostructures, including nanowires, quantum dots, and core-shell configurations, can be synthesized from carbon-based compounds, metals, and polymers, offering enhanced properties like increased surface area and improved conductivity. Despite these advantages, only a limited number have been utilized for nonenzymatic glucose detection, although optimization of parameters such as nanoparticle concentration and surface charge holds potential for diverse electrochemical applications [ 13 ]. Historically, a variety of enzyme-free glucose sensors have been developed utilizing metal nanoparticles such as Pt ([ 14 ]), metal oxide nanoparticles (NiO) [ 15 ], CuO [ 16 ], and composites materials [ 17 ], Ag-CuO [ 18 ], ZnO/CuO[ 19 ]. These materials particularly, ZnO/CuO-based multifunctional monohybrids are favored for non-enzymatic glucose sensors due to their excellent catalytic performance, high electron transfer, non-toxicity, and versatility in applications like sensing, catalysis, and energy storage. Their effectiveness stems from the extended electron depletion layer created by p-n junctions and their natural abundance [ 20 ]. To enhance the electrocatalytic performance of these nanocomposites, a prevalent strategy involves the synthesis of composite materials by integrating conductive components, including carbon-based nanomaterials (e.g., graphene, reduced graphene oxide) or conductive polymers (such as polyaniline (PANI) and polypyrrole) [ 21 ]. Graphene oxide (GO) and reduced graphene oxide (rGO), synthesized from discharged dry cell electrodes, present a cost-effective alternative to graphene for electrochemical applications due to their advantageous properties such as high electrical conductivity and substantial specific surface area. These characteristics enhance electrochemical activity in glucose oxidation and contribute to the durability of nanocomposite materials by preventing the aggregation of active nanomaterials during redox and catalytic processes [ 7 ]. Conductive polymers, particularly polyaniline, have enabled the development of hybrid nanostructures due to their high electrical conductivity and excellent thermal and chemical stability. Polyaniline nanostructures are noted for their environmental resilience, substantial surface area, advantageous redox behavior, and ease of fabrication, promoting various applications. Additionally, interfacial interactions among metal oxides, carbon materials, and polymer matrices enhance material properties, increase active site exposure, improve stability, and boost electro-catalytic activity [ 22 ]. Numerous composite materials, particularly carbon-based materials and metal oxides incorporated onto polyaniline (PANI) arrays, exhibit heightened sensitivity to glucose. For instance, the nanoparticle-modified polyaniline nanofibers, specifically those modified with nickel and copper oxides, denoted as NiO/CuO/PANI, have been documented in the literature as exhibiting significant glucose sensitivity [ 7 , 23 ]. In this study, we developed a non-enzymatic glucose sensor by modifying a glassy carbon electrode (GCE) with a composite of ZnO/CuO, reduced graphene oxide (rGO), and polyaniline nanosheets (PANINS), designated as ZnO/CuO/rGO/PANINS/GCE. The electrochemical performance for glucose oxidation was evaluated using cyclic voltammetry (CV) and amperometric methods. The electrocatalytic behavior of the modified GCE demonstrated a broad linear response range, low detection limit, high sensitivity, and good selectivity, establishing it as an effective enzyme-free glucose sensor. 2. Experimental 2.1. Chemicals and reagent In the present study, all chemicals and reagents were procured from Sigma-Aldrich and additional suppliers. The materials employed included microcrystalline natural graphite powder (99.995% purity), absolute ethanol (C₂H₅OH, 99.7%), ammonium persulfate ((NH₄)₂S₂O₈, 98%), aniline (C₆H₅NH₂, 99.8%, analytical grade), potassium ferricyanide (K₃[Fe(CN)₆], 99%), and alumina powder with particle sizes of 1 mm, 0.3 mm, and 0.05 mm. Moreover, other reagents utilized in the experiments encompassed glucose (C₆H₁₂O₆, molar mass 180.156 g/mol), sodium carbonate (Na₂CO₃), sodium hydroxide (NaOH), copper(II) nitrate trihydrate (Cu(NO₃)₂·H₂O), potassium nitrate (KNO₃), and zinc nitrate hexahydrate (Zn(NO₃)₂·6H₂O, molar mass 297.37 g/mol, 96.103% purity), sourced from Blulux Laboratories Ltd, India. Additionally, hydrochloric acid (HCl, 37%) and sulfuric acid (H₂SO₄, 98%, Merck) were employed, along with potassium permanganate (KMnO₄). Unless stated otherwise, all other reagents used in the experiments were of analytical grade and did not require further purification. Deionized water, with a resistivity of 18.25 MΩ, was utilized for all solution preparations. Prior to experimentation, all experimental solutions were purged with high-purity argon gas (99.999% purity), obtained from Merck, Germany, for approximately five minutes, and the gas flow was maintained throughout the experiments to eliminate dissolved oxygen. Recovery of graphite powder from used dry cell battery Zinc-carbon dry cell batteries were sourced from a commercial vendor for the purpose of electrode material recovery. Initially, the electrodes were meticulously extracted from the batteries to facilitate further processing. To eliminate potential contaminants, including manganese dioxide (MnO 2 ), metallic particles, and residual carbon, the electrodes underwent a thorough cleansing process. This involved repeated mechanical agitation and rinsing with distilled water. Following the purification stage, the electrodes were subjected to drying and then mechanically processed to achieve a fine graphite powder through grinding and crushing techniques. Despite these efforts, residual inorganic materials remained embedded within the graphite matrix. To address this issue, the obtained graphite powder was immersed in a beaker containing a hydrochloric acid (HCl) and nitric acid (HNO 3 ) mixture at a volumetric ratio of 3:1. The mixture was then heated for several hours to facilitate the dissolution of remaining impurities. Subsequent to the acid treatment, the solution was centrifuged to separate the solid graphite powder from the liquid phase. The purified graphite was further rinsed multiple times with distilled water to ensure neutralization and removal of any acidic residues, allowing the pH to return to a normal range. The final recovered graphite powder, designated as [ G (R)], was dried in an oven at a controlled temperature of 60°C for a duration of 24 hours [ 24 ]. This careful and systematic series of steps aimed to enhance the purity and usability of the recovered graphite for potential applications in various research and industrial settings. 2.2 Synthesis of GO and rGO Graphene oxide (GO) was synthesized from recovered graphite powder denoted as [G(R)] utilizing the Hummers method, a well-established chemical approach for the oxidation of graphite [ 24 ]. The synthesis of graphite oxide was performed utilizing a modified Hummers' method, which involves a series of steps aimed at the exfoliation and oxidation of graphite flakes. Initially, a mixture of 1 g of recovered graphite powder and 1 g of sodium nitrate (NaNO 3 ) was introduced into 50 ml of 98% concentrated sulfuric acid (H 2 SO 4 ). This mixture underwent ultra-sonication for a duration of 3–4 hours to facilitate the separation and exfoliation of graphite flakes, thereby yielding a more accessible substrate for subsequent chemical reactions. In order to promote the oxidation of the exfoliated graphite flakes, an additional 50 ml of 98% concentrated H 2 SO 4 was incrementally added to the initial reaction mixture. Following this, 6 g of potassium permanganate (KMnO 4 ) was introduced slowly while maintaining vigorous stirring for a period of 4 hours, ensuring that the temperature remained below 20°C to avoid excessive heat generation which could lead to undesirable side reactions. To terminate the oxidation reaction and to quench the reactive species, 100 ml of deionized (DI) water was carefully added to the mixture at ambient temperature over a span of 2 hours. This step was crucial to stabilize the reaction environment. Subsequently, an additional 200 ml of hot DI water was incorporated, and the mixture was stirred for another 2 hours at a temperature of 90°C to further facilitate the oxidation process and to promote the dissolution of products into the aqueous phase. To remove any unreacted potassium permanganate and to assist in the complete reduction of the resulting manganese oxides, 20 ml of hydrogen peroxide (H2O2) was introduced into the reaction system. This addition not only served as a titrant for the unreacted KMnO4 but also effectively catalyzed the completion of the oxidation reaction. Upon completion of the reaction sequence, the final mixture was subjected to centrifugation to separate the solid graphite oxide from the liquid phase. The solid precipitate was then rigorously washed with deionized water multiple times to ensure the removal of residual reactants and byproducts. The resultant graphite oxide (GO) was subsequently dried at 60°C for a period of 24 hours to yield a stable product. In order to obtain reduced graphene oxide (rGO), the synthesized graphite oxide was further processed in accordance with established methodologies documented in current scientific literature, which outline the reduction techniques necessary to achieve the desired properties of rGO. This process typically involves chemical or thermal reduction steps that effectively restore some of the sp² hybridization lost during the oxidation of graphite [ 25 ]. A dispersion of graphene oxide (GO) at a concentration of 30 mg in 30 mL of deionized water was prepared and subsequently introduced into a sealed vessel with a total volume of 60 mL. Following this, a stoichiometric amount of sodium borohydride was added to achieve a concentration of 0.04 M. Additionally, a 1 M sodium hydroxide solution was introduced to the system to adjust the pH and facilitate the reduction process. The resultant mixture was subjected to thermal treatment at a constant temperature of 90°C for a duration of 1 hour to promote the reduction of graphene oxide to reduced graphene oxide (rGO). Following the thermal reduction phase, the mixture was processed using centrifugation at a suitable rotational speed in order to separate the reduced graphene oxide from the aqueous phase and unreacted species. The resultant precipitate was collected and subsequently dried at a controlled temperature of 60°C for 24 hours to ensure the removal of residual moisture and achieve a stable powder form. 3.4.2. Synthesis of ZnO Nanoparticles Zinc oxide (ZnO) nanoparticles (NPs) were synthesized via a precipitation method, building upon established protocols in the literature. In this process, zinc nitrate hexahydrate (Zn(NO 3 ) 2 ·6H 2 O) and sodium carbonate (Na 2 CO 3 ) were utilized as the primary reactants. For the preparation of the reactant solutions, a specific quantity of zinc nitrate hexahydrate, precisely 29.747 g, was dissolved in 200 mL of deionized water to achieve a concentration of 0.1 mol. Concurrently, a sodium carbonate solution was prepared by dissolving 12.7188 g of Na 2 CO 3 in 240 mL of deionized water, yielding a concentration of 0.12 mol. Subsequently, the zinc nitrate solution was gradually introduced into the sodium carbonate solution while maintaining continuous stirring for a duration of 2 hours. This controlled addition was essential to facilitate the homogeneous mixing of the reactants and promote the formation of zinc carbonate precipitate through the following reaction: Zn(NO 3 ) 2 +Na 2 CO 3 → ZnCO 3 ↓+2NaNO 3 After the reaction period, the resultant white precipitate, consisting predominantly of zinc carbonate (ZnCO 3 ), was allowed to settle for 24 hours. Following this maturation period, the precipitate was collected by filtration using Whatman filter paper, ensuring the removal of any unreacted materials and by-products. To enhance the purity and homogeneity of the obtained precipitate, it was subjected to thorough washing three times with deionized water, followed by ethanol. This washing procedure aimed to alleviate any residual ionic species and ensure a cleaner product in subsequent processing steps. The washed precipitate was then dried at 100°C for 6 hours, which facilitated the formation of a zinc oxide precursor. The precursor material was subsequently subjected to thermal treatment through calcination in a furnace at a temperature of 300°C for a duration of 2 hours. This thermal process aimed to decompose the zinc carbonate into zinc oxide, yielding the final product: nano-ZnO particles [ 26 ]. 3.4.4. Synthesis of ZnO/CuO Nanocomposites Zinc oxide/copper oxide (ZnO/CuO) nanocomposites were synthesized in a stoichiometric ratio of 1:1 utilizing copper(II) nitrate trihydrate (Cu(NO 3 ) 2 ·3H 2 O) and zinc nitrate hexahydrate (Zn(NO 3 ) 2 ·6H 2 O) as precursors through a co-precipitation method. Initially, 100 mL of deionized water was employed to dissolve the metal nitrates, creating a homogeneous solution with a concentration of 0.2 M for both metal ions. Subsequent to the preparation of the precursor solution, a 1 M sodium hydroxide (NaOH) solution was incrementally introduced into the 0.2 M metal nitrate solution under vigorous stirring. This process was meticulously monitored until the pH reached 14, a condition conducive to the precipitation of metal oxides. The alkaline solution was then maintained at a temperature of 80°C using a magnetic stirrer, promoting the formation of a black precipitate, indicative of the formation of ZnO/CuO nanocomposites due to the interaction of the metal ions in the alkaline medium [ 27 ]. Following the synthesis, the resultant black precipitate was subjected to vacuum filtration to separate it from the aqueous phase. The filtered precipitate was then thoroughly washed 2–3 times with deionized water to remove any unreacted precursors and residual ions. This washing step was succeeded by rinsing the precipitate with ethanol to enhance purity and facilitate the removal of any remaining organic contaminants. The washed precipitate was dried overnight in a laboratory oven at a controlled temperature of 80°C to eliminate moisture. To achieve the desired crystalline structure and enhance the thermal stability of the nanocomposites, the dried precipitate was subsequently calcined at 450°C for a duration of 3 hours. This calcination process promotes the complete conversion of the precursors into ZnO/CuO nanocomposites, resulting in materials with potentially useful morphological and electronic properties for various applications. 3.4.5. Synthesis of ZnO/CuO/rGO monohybrids The ZnO/CuO/reduced Graphene Oxide (rGO) monohybrids was synthesized using a modified approach based on the protocol described in the referenced literature [ 28 , 29 ]. In a systematic approach towards the synthesis of ZnO/CuO/reduced graphene oxide (rGO) monohybrids, 5 mg of rGO was initially dispersed in 60 mL of ethanol utilizing ultra-sonication for a duration of 2 hours. The sonication process facilitates the dispersion of rGO by disrupting agglomerated particles, thus contributing to a more homogeneous distribution within the solvent. Concurrently, a separate beaker was utilized to prepare a uniform suspension of 6.3 g of the synthesized ZnO/CuO nanocomposite in 100 mL of deionized water. The suspension was subjected to magnetic stirring at a controlled temperature of 55°C for 2 hours. This heating and stirring process promotes complete dissolution of the nanocomposite and enhances the dispersion stability of the resulting suspension, ensuring that the nanocomposite particles are uniformly distributed throughout the aqueous medium. Following the preparation of both the rGO and the ZnO/CuO solutions, the latter was incrementally added to the former in a dropwise fashion while maintaining continuous stirring under a nitrogen atmosphere. The nitrogen environment was employed to minimize oxidation and ensure that the reactive components remained stable throughout the synthesis process. Subsequently, the temperature of the resulting mixture was equilibrated to room temperature to facilitate the interaction between the rGO and the ZnO/CuO nanocomposite. Once the two solutions were combined, the resultant suspension underwent centrifugation to separate the monohybrids from the supernatant. This step was followed by extensive washing with deionized water and ethanol, aimed at eliminating any unreacted materials and residual impurities from the synthesis. Finally, the purified ZnO/CuO/rGO nanohybrids were subjected to a drying process at 80°C overnight to facilitate the removal of any solvent residues and to yield a stable monohybrid material. This rigorous synthetic protocol aimed to ensure optimal integration of rGO with the ZnO/CuO nanocomposite, potentially enhancing the material's properties for subsequent applications. 3.4.6. Synthesis ZnO/CuO/rGO/PANINS As shown in Fig. 1 , the synthesis of ZnO/CuO/rGO/PANINS was accomplished through a modified procedure adapted from the method delineated in reference. Initially, 1.0 g of a composite material comprising zinc oxide (ZnO), copper oxide (CuO), and reduced graphene oxide (rGO) was dispersed in distilled water. This mixture was subjected to magnetic stirring for a duration of 1 hour at ambient temperature to ensure the formation of a homogeneous nanosuspension. Subsequently, 1.5 mL of aniline, 5.8 mL of hydrochloric acid (HCl), and 2.76 g of sodium dodecyl sulfate (SDS) were introduced into the nanosuspension as surfactants, with the process being conducted in an ice bath to control the exothermic nature of the reaction. The stirring continued for an additional 30 minutes to facilitate proper mixing and incorporation of the surfactants into the suspension. In a separate 10-mL beaker, an aqueous solution of ammonium persulfate (APS) was prepared by dissolving 1.469 g of APS in pure water. This APS solution was then carefully added to the previously prepared mixture. Upon addition, a noticeable colour change from light blue to dark green was observed, indicative of the onset of polymerization. The dark green suspension was stirred continuously for a total of 3 hours to ensure complete reaction and interaction among the components. Following the stirring phase, the mixture was allowed to mature and polymerize for a period of 48 hours, providing sufficient time for the polymerization process to reach completion. The resultant ZnO/CuO/rGO/PANINS composite was subjected to centrifugation to separate the solid product from the liquid phase. The collected product was thoroughly washed with distilled water and ethanol to eliminate unreacted monomers and any residual surfactants. Finally, the purified composite was dried in an oven at 60°C to yield the final ZnO/CuO/rGO/PANINS material for subsequent characterization and application. 2.3. Materials characterization The synthesized materials, which include (ZnO), (ZnO/CuO), and ZnO/CuO/rGO), were systematically characterized using a suite of analytical techniques to elucidate their structural, morphological, and optical properties. X-ray diffraction (XRD) analysis was performed employing a Bruker D2 Phaser diffractometer, utilizing a copper Kα radiation source (λ = 1.5405 Å) at an operating voltage of 30 kV and a current of 10 mA. The diffraction patterns were recorded over a 2θ range of 10° to 80°, enabling the determination of phase composition and crystallite structure. Morphological characterization was carried out using scanning electron microscopy (SEM) equipped with energy-dispersive X-ray (EDX) capabilities. The SEM analysis was performed with a JEOL JSE-6700F microscope, operating at an accelerating voltage of 15 kV, which facilitated the examination of surface topology and particle size distribution, while EDX provided elemental composition analysis. The optical properties of the synthesized materials were investigated through UV-visible spectroscopy. This technique allowed for the assessment of the materials’ absorption characteristics and electronic transitions, contributing to the understanding of their potential applications in optoelectronic devices. Fourier transform infrared (FTIR) spectroscopy was also employed to further characterize the materials. FTIR absorption spectra were acquired using a Shimadzu IRTracer-100 spectrometer, covering a spectral range of 4000 to 400 cm -1 . This analysis was instrumental in identifying various functional groups and chemical bonds present in the samples, as well as in revealing information on the molecular interactions within the composites. 2.2. Surface modification and electrochemical measurements Surface modification on a glass carbon electrode as a substrate following our previous work [ 29 ]: the glassy carbon electrode (GCE) was polished with 1, 0.3, and 0.05 µM alumina powder to clean the surface. Between each polishing step, the electrodes were rinsed with distilled water. After polishing, the electrodes were sonicated in a 1:1 mixture of nitric acid (HNO3), ethanol, and deionized water for 5 minutes and dried at room temperature. Next, an 8 µL suspension of ZnO/CuO/rGO/PANINS was applied on bare GCE and placed in an air oven at 35°C until the film was completely dry. Control modified electrodes containing ZnO/GCE, CuO/GCE, ZnO/CuO/GCE, ZnO/CuO/rGO were prepared by the same experimental procedure The following is a summary of the experimental results [ 27 ]. All experiments were conducted at room temperature. Cyclic voltammetry (CV) and amperometric detection were performed on a three-electrode system using a BAS100B Electrochemical Bioanalyzer with Windows™ software. The system included a platinum wire as a counter electrode, a leak-free silver/silver chloride reference electrode, and a modified GCE as the working electrode. Prior to the experiment, the solution was purged with pure N2 gas to remove dissolved oxygen. For amperometric detection of glucose, glucose was continuously added under magnetic stirring at various glucose concentrations at an applied potential of 0.6 V in an electrochemical cell containing a magnetically stirred NaOH electrolyte. Interference tests were performed under the same conditions as glucose measurements, incorporating interfering compounds. Human serum samples were analyzed using the standard addition method. Glucose concentrations in human blood samples were measured using a glucose monitoring kit. Samples were diluted to 0.1 mM (10 mL) with 0.1 M NaOH solution. Then, 0, 0.5, and 1 mM glucose solutions were added to the diluted samples and recovery was determined by CV measurement (n = 3). To assess the reproducibility, repeatability, and stability of the ZnO/CuO/rGO/PANINS GCE nanocomposite-based electrode, multiple electrodes were prepared and tested under similar environmental conditions. In order to determine reproducibility, glucose detection was conducted five times using a single electrode, which was thoroughly washed with deionized water after each test. The standard deviation of the electrochemical current response was then calculated. The sensor demonstrated reproducibility, as all five electrodes yielded consistent results when tested for glucose detection. The electrochemical response of each sensor was recorded, along with its standard deviation. Additionally, the long-term stability of the sensor was assessed by monitoring the current response to glucose over a period of 10 days. The stability of the ZnO/CuO/rGO/PANINS nanocomposite-modified electrode in the presence of glucose was evaluated every 2 days for the duration of the 10-day period. The modified electrodes were stored under ambient conditions, and their current responses were recorded accordingly. The effectiveness of the proposed sensor was tested by measuring the glucose levels in human blood samples. The concentration of blood glucose was determined spectrophotometrically after conducting three measurements. Prior to electrochemical analysis, the blood samples were centrifuged at 3000 rpm for 15 minutes to eliminate any precipitated proteins or other particles. A serum sample of 0.1 ml was then mixed with a 10 ml solution of 0.1 M NaOH for dilution. Electrochemical assessments were conducted using ZnO/CuO/rGO/GCE modified electrodes at the optimal applied potential. The accuracy of the method was verified by examining the recoveries as well. All tests and experiments were conducted at room temperature. The sample recoveries were calculated using the following formula. $$\:\%\:Recovery=\:\frac{concentration\:of\:spiked-cocentration\:of\:unspiked}{concentration\:of\:added\:amount\:}\:x\:100\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:1$$ 3. Results and Discussion 3.1. Physical characterizations 3.1.1. XRD Analysis X-ray diffraction (XRD) is a commonly employed non-destructive analytical technique utilized to investigate crystallite size, orientation, and the average spacing of atomic layers within materials. In this study, XRD analyses were conducted to verify the formation of synthesized materials including graphene oxide (GO), reduced graphene oxide (rGO), zinc oxide/copper oxide (ZnO/CuO), zinc oxide/copper oxide/reduced graphene oxide (ZnO/CuO/rGO), and zinc oxide/copper oxide/reduced graphene oxide/panins (ZnO/CuO/rGO/PANINS). Figure 2 (a) illustrates the XRD patterns for GO and rGO, exhibiting distinct Bragg peaks at a 2θ value of 10.5° (001), which corresponds to an interplanar spacing (d) of 0.94 nm. This finding suggests the successful presence of oxidized graphite, which is characterized by various functional groups attached to its surface. The effective reduction of GO to rGO, achieved through the application of sodium borohydride (NaBH4) as a reducing agent, is substantiated by the broad XRD signals, featuring reflection peaks at 2θ values of 25.7° and 45.89°, indicating an interplanar spacing of 0.35 nm. The observed diffraction planes (011) and (004) align closely with values reported in existing literature, thereby confirming the removal of oxygen-containing functional groups from the interstitial spaces within the graphite nanostructures [ 31 ]. Figure 2 (b) displays distinct peaks at diffraction angles of 31.7°, 34.4°, 36.4°, 47.6°, 56.7°, 62.9°, and 67.9°, which are indicative of the crystalline planes (100), (002), (101), (102), (110), (103), and (200) of zinc oxide (ZnO) nanoparticles. These peaks are consistent with the standard reference pattern listed in the Joint Committee on Powder Diffraction Standards (JCPDS) card number 36-1451 [ 32 ]. The remaining peaks occur at 32.41°, 35.61°, 38.81°, 48.91°, and 61.61°, corresponding to the corresponding faces (110), (111), (200), (202), and (113) of the CuO nanoparticle (JCPDS card number 45–0397). A peak is observed at 24.4° corresponding to the (001) plane of rGO, confirming that GO was successfully reduced by the tour method; the 2θ reflection peak of PANINS appears at 20.5° and the corresponding plane is (101) [ 7 ].These results indicate that ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites were successfully formed. The crystal sizes of the nanocomposites ZnO, CuO, ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS were measured to be 20.25 nm, 17.85 nm, 16.81 nm, 16.18 nm, and 18.05 nm, respectively. ZnO/CuO/rGO nanocomposites were smaller than the average particle size of the ZnO/CuO nanocomposites; the ternary ZnO/CuO/rGO nanocomposites had the smallest particle size due to the synergistic effect of ZnO, CuO, and rGO in the composite system and thus and exhibited the highest surface area. However, the crystallite size of ZnO/CuO/rGO/PANINS increased because sodium dodecyl sulfate (SDS) reduces double distillation water, which significantly affects electrochemical and catalytic activity. ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanomaterials, the crystal sizes, d-spacing of the individual materials, and the distinct shifts are listed in Table 3 . \(\:\varvec{D}=\frac{\varvec{K}\varvec{\lambda\:}}{\varvec{\beta\:}\mathbf{c}\mathbf{o}\mathbf{s}\varvec{\theta\:}}\:(1\) ) $$\:\varvec{d}=\frac{\varvec{n}\varvec{\lambda\:}}{2\varvec{s}\varvec{i}\varvec{n}\varvec{\theta\:}}$$ 2 where ‘D’ is the average crystallite size, ‘d’ is interplanar spacing, ‘θ’ is Bragg’s angle, ‘λ’ is the wavelength of X-ray and ‘β’ is the full width half maximum (FWHM). Table 1 Crystal parameters of GO, rGO, CuO/ZnO, ZnO/CuO/rGO and ZnO/CuO/rGO/PANINS Sample Name 2θ FWHM Crystal size (average) nm Average crystal size d-spacing hkl GO 9.85 1.0085 1.0085 7.90 0.06613 011 rGO 24.24 1.2618 1.0618 13.29 0.16177 001 45.89 1.06538 0.45538 0.3003 004 ZnO 31.91 1.40446 5.88323 20.25 0.2118 100 34.67 0.5183 16.057 0.22952 002 36.40 0.40634 20.5809 0.24064 101 56.80 0.23462 38.4932 0.36638 110 CuO 32.69 2.18391 3.79085 0.21678 100 36.09 0.36375 22.9438 0.23605 111 38.94 0.32033 26.3053 17.85 0.25681 202 56.88 0.49111 18.3965 0.36686 113 ZnO/CuO 32.15 0.53199 15.541 16.81 0.21333 100 36.00 0.59879 13.9502 0.23807 101 38.09 0.36353 23.1189 0.25138 200 57.04 0.61973 14.6459 0.37256 110 ZnO/CuO/rGO 32.93 0.32729 25.3111 16.18 0.21835 100 36.93 1.5434 5.42671 0.244 101 38.90 0.34436 24.4663 0.25653 200 56.72 0.94772 9.52601 0.36593 110 ZnO/CuO/rGO/PANINS 32.93 0.22999 36.0193 18.05 0.21835 100 36.83 1.04889 7.98281 0.24335 101 38.90 0.454409 18.541 0.25653 200 56.35 0.93283 9.66126 0.36373 110 3.1.2. Surface morphology analysis The as-synthesized ZnO nanoparticles, ZnO/CuO nanocomposites, and ZnO/CuO/rGO nanohybrid' surface morphology were studied using SEM at various magnifications, as presented in Fig. 3 . Figures 3 (a, b) and 3(c, d) are the SEM images of ZnO and CuO/ZnO samples. When minor ZnO nanoparticles are present, the surface morphology of the CuO nanoplatelets changes, suggesting that the ZnO nanoparticles are uniformly dispersed on the CuO nanoplatelet surface. The existence of ZnO on the CuO nanostructure forms a CuO/ZnO hetero junction with a complex shape and clearly promotes dynamic adsorption of the reacting molecules. On the other hand, the SEM micrograph of the ZnO/CuO/rGO nanohybrid in Fig. 3 (e, f) shows that the ZnO nanoparticles and CuO plates are uniformly distributed and interconnected on the rGO sheet nanostructure. Furthermore, the SEM images reveal the distinct morphological characteristics and structural evolution of the synthesized materials. The first ZnO nanoparticles, shown in Fig. 3 (a) and (b), display aggregated clusters with irregular shapes and sizes, exhibiting a rough, granular surface texture with significant particle agglomeration. Upon incorporation of CuO to form CuO/ZnO nanocomposites, as depicted in images c and d, a remarkable transformation in morphology is observed. The composite structure develops into a more sophisticated flower-like or hierarchical arrangement, characterized by distinctive plate-like or leaf-like projections extending from the central structures. This modification proves enhanced dispersion suggesting successful integration of the two metal oxide components. The final stage of the composite synthesis, involving the addition of reduced graphene oxide (rGO) to form CuO/ZnO/rGO (Fig. 3 (e) and (f)), exhibits the most complex morphological features. The resulting structure reveals an interconnected network architecture where the metal oxide components appear to be effectively anchored onto the rGO sheets. This arrangement creates a layered structure with visible porosity, showing potential enhancement in surface area compared to its precursor materials. The SEM analysis confirms the successful synthesis of the hybrid material, showing good integration between all components. The progressive evolution of morphology throughout the synthesis stages suggests that the final composite structure may offer improved performance characteristics for various applications, attributed to its hierarchical organization and enhanced structural features. 3.1.3. UV-Vis Analysis UV-visible absorption spectra of ZnO NPs, ZnO/CuO NCs, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanohybrid materials were recorded at room temperature and are shown in Fig. 4 . In Fig. 4 (a), a sharp absorption peak at 368 nm corresponding to a band gap of 3.1 eV indicates the presence of ZnO nanostructures, and the ZnO [ 33 ]. Figure 4 (b) shows the formation of ZnO/CuO binary nanocomposites with an absorption peak at 372 nm and a reduced band gap of 2.75 eV. This represents a decrease in the band gap from 3.1 eV for ZnO nanoparticles to 2.75 eV for the ZnO/CuO binary nanocomposite. In Fig. 4 (c), the absorption peak at 374 nm indicates the presence of ZnO/CuO/rGO ternary nanocomposites, and the band gap is further reduced to 2.68 eV. Both the ZnO/CuO binary nanocomposite and the ZnO/CuO/rGO ternary nanocomposite show enhanced in the visible light region with an enhanced absorbance in the visible region [ 34 ]. The spectra of the ternary nanocomposites showed a broad elevated background in the visible region, mainly due to the presence of rGO. In particular, the absorbance of the ZnO/CuO/rGO nanocomposite is increased compared to that of the ZnO nanoparticles and the ZnO/CuO binary nanocomposite. Furthermore, it is observed that the band gap of ZnO decreases when coupled with ZnO, CuO, and rGO. In Fig. 4 (d), the spectrum of ZnO/CuO/rGO/PANINS shows a broad absorption peak at 438 nm attributed to the formation of ZnO/CuO/rGO/PANINS and also a characteristic PANINS peak around 280 nm associated with the benzenoid π-π* transition [ 35 ]. These two peaks are related to the π-π* transition of the conjugated polymer and the highest occupied energy level of the benzenoid ring to the lowest occupied energy level of the quinoid ring due to charge transfer excitation [ 7 ]. The formation of ZnO/CuO/rGO/PANINS in acidic media shifts the absorption band of the benzenoid ring to the quinoid ring.[ 7 ]. The spectra of the quaternary nanocomposites showed a broad elevated background in the visible region, mainly due to the presence of PANINS; increased absorbance of ZnO/CuO/rGO/PANINS nanocomposites compared to ZnO, ZnO/CuO, and ZnO/CuO/rGO was observed. The optical band gap energy of each synthesized material is Tauc. αhυ = A(hυ - Eg)^(1/2) (1) where α is the absorption coefficient, hυ is the photon energy, A is a proportionality constant that varies with the material, and n is the optical transition index of the semiconductor, where n is 1/2 for direct band gap semiconductors and 2 for indirect band gap semiconductors. Thus, the estimated band gaps of ZnO NPs, ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites are 3.1 eV, 2.75 eV, 2.68 eV, etc., respectively. It was also observed that the band gap of ZnO decreases when coupled with CuO, rGO, and PANINS. 3.1.4. FTIR analysis FTIR spectra are used to identify the presence of functional groups and types of bonding in the synthesized samples. Figure 5 shows the FTIR spectra of pure ZnO NPs, ZnO/CuO NCs, and ZnO/CuO/rGO nanocomposites in the range of 400-4,000 cm-¹ The broad band observed between 3,400 and 3,500 cm-¹ is due to stretching vibrations of O-H bonds on the sample surface The peak at 3,233 cm-¹ indicates the presence of N-H stretching vibrations, and the band around 1,650 cm-¹ is related to the O-H bending mode of adsorbed water molecules. Furthermore, the sharp FTIR band at 442 cm-¹ corresponds to Zn-O bond vibrations, confirming the formation of ZnO nanoparticles (Tan et al.) In the case of ZnO/CuO nanocomposites, the bands at 488 cm-¹ and 444 cm-¹ correspond to Cu-O and Zn-O stretching vibration modes [ 33 , 34 ]. The peak position of ZnO/CuO nanocomposite shifted between 700 and 400 cm-¹ compared to the pure material, indicating the interaction between Zn and Cu ions, confirming the formation of metal oxide nanocomposites. FTIR of ZnO/CuO/rGO nanohybrid spectrum, a peak at 435 cm-¹ was observed, indicating metal oxide bonding in the ZnO/CuO nanocomposite, with a decrease in the intensity of oxygenated groups and a blue shift compared to ZnO/CuO, confirming that the nanomaterial is strongly bonded to rGO. ([ 34 ]).The peak of rGO at 1,635 cm⁻¹ corresponds to the sp² hybridization of carbons. To confirm the quality of ZnO/CuO/rGO/PANNS, the strong peak at 3440 cm-1 is attributed to N-H stretching; the prominent peaks observed at 1350, 1486, and 1580 cm-1 are due to C-N stretching vibrations, -C = C stretching vibrations in the benzenoid ring, and -C = C stretching vibrations in the quinoid ring, respectively corresponds to In addition, the peak at 796 cm-1 is attributed to C-Cl stretching, indicating the presence of emeraldine salts; the rGO peak at 1635 cm-1 corresponds to sp2 hybridization of carbon, which shifts to 433 cm-1, indicating the formation of metal oxide nanocomposites and incorporation of CuO within ZnO nanoparticles. For ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANNS nanocomposites, peaks around 440 cm-1, 435 cm-1, and 433 cm-1 were observed, respectively. These shifts are due to the insertion of CuO, rGO, and PANNS. The slight changes in the FTIR band shifts observed in each spectrum are due to differences in the composition of the synthesized nanocomposites [ 36 ]. 3.2. Electrochemical Characterization 3.2.1. Electrochemical Oxidation of Glucose on Modified Electrode Glucose is the most common electro active bio compound and is readily oxidized, making it the basis for electrochemical measurements. In this study, cyclic voltammetry was used to electrochemically oxidize 2 mM glucose on ZnO/CuO/rGO/PANINS/GCE. In addition, the oxidation of glucose on GCE modified with ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites was investigated in 0.1 M NaOH solution, both in the absence and in presence of glucose. This was accomplished by cyclic voltammetry at a scan rate of 50 mV/sec within a potential window of 0.4 V to 1 V. Figure 6 shows cyclic voltammograms of glucose on modified GCE with and without 2 mM glucose in 0.1 M NaOH solution. The voltammogram Fig. 6 a obtained on bare GCE shows no significant redox behaviour in the absence or presence of glucose, which indicates the lack of electro catalytic activity of bare GCE. However, electrodes modified with ZnO/CuO/GCE, ZnO/CuO/rGO/GCE, and ZnO/CuO/rGO/PANINS/GCE (Fig. 6 a-d) showed high peak currents at potentials of + 0.8 V, + 0.67 V, and + 0.6 V, respectively [ 22 ]. ZnO/CuO/rGO/GCE exhibited a larger peak current than ZnO/CuO-modified GCE at the same scan rate. This is due to the larger specific surface area, faster electron transfer rate, and lower charge transfer resistance of rGO. rGO facilitates the glucose oxidation process by providing uniformly distributed catalytic sites that accelerate the electro catalytic activity of the ZnO/CuO metal oxide nanocomposite [ 37 ]. ZnO is one of the most attractive functional semiconductor materials that can be used as an effective mechanical support and electron conduction pathway due to its strong electron transfer capability and mechanical flexibility [ 19 ]. ZnO acts as a good mechanical support and enhances the intrinsic properties of p-type CuO. P-n junction formation in the ZnO-CuO heterostructure provides fast electron transfer capability and causes increased sensitivity. In addition, cationic polymers increase the electrostatic interaction between the heterostructure and the CuO surface, facilitating the attraction of glucose molecules [ 38 ]. As shown in Fig. 6 (e), the anodic peak currents of electrodes modified with ZnO/CuO/rGO/PANINS were higher than those of ZnO/CuO/rGO and ZnO/CuO modified GCE, respectively. This is because PANINS exhibit better properties that help expose more active sites, increase stability, and improve electro catalytic activity performance. Incorporation of these layers into ZnO/CuO/rGO improves catalytic activity in glucose oxidation. 3.2.2. Effect of Scan Rate on the Electrochemical Oxidation of Glucose As shown in Fig. 19, the effect of scan rate on the oxidation of glucose in 0.1 M NaOH solution containing 2 mM glucose on a ZnO/CuO/rGO/PANINS electrode was examined using cyclic voltammetry at various scan rates from 10 to 100 mV/s. The voltammogram curves show that the peak potential shifts toward more positive values as the scan rate increases. The thickness of the diffusion layer depends mainly on the scan rate; the slower the scan rate, the thicker the diffusion layer. However, as the scan rate increases, the thickness of the diffusion layer decreases and the variable flux at the electrode surface decreases significantly. Plotting peak current (ipa) against the square root of current density shows a proportional relationship with the square root of scan rate (υ^1/2). Linear correlations with regression coefficients exceeding 0.99 were obtained at the electrodes, indicating that diffusion effects primarily affect the charge transport mechanism. 3.2.3. Optimization of Experimental Conditions The effect of NaOH concentration on amperometric readings for 2 mM glucose detection was investigated. Various concentrations of sodium hydroxide (NaOH) solutions were used to determine the optimal electrolyte concentration. Because hydroxide anion groups are involved in the catalytic process of glucose, the number of hydroxide ions in the electrolytic cell has a significant effect on the electro catalytic oxidation of glucose. In this study, the effect of NaOH concentration on the performance of electrodes designed for glucose detection was investigated through CV experiments with varying NaOH concentrations. Figure 20 shows the synthesis and characterization of ZnO/CuO/rGO/PANINS nanocomposites for non-enzymatic electrochemical glucose sensor, and shows that the peak current in the CV graph increases when the NaOH concentration is varied from 0.005 M to 0.1 M. However, further increasing the NaOH concentration decreases the peak current of the CV graph. As a result, the concentration of sodium hydroxide for glucose detection using the developed electrode is 0.1 M [ 39 , 40 ]. The effect of pH on the electrochemical response of ZnO/CuO/rGO/PANINS/GCE for glucose sensing was evaluated using cyclic voltammetry in the range of pH 9–14, as depicted in the figure. It appears that no text has been provided to paraphrase. Please share the text! The supporting electrolyte used was a 0.1 M NaOH solution, the pH of which greatly affects the electrochemical properties of glucose. Various NaOH solutions with pH of 9, 10, 11, 12, 13, and 14 were carefully prepared. Cyclic voltammetry (CV) curves for pH 9 and 10 showed no cathodic or anodic peaks were not shown. However, the CV curve at pH 13 showed significantly higher intensity than the others due to the moderate involvement of OH ions, which promoted a faster electro oxidation process. Conversely, the peak current decreased at pH 14, possibly due to the increased involvement of OH- ions, which inhibited the electro oxidation reaction between the modified ZnO/CuO/rGO/PANINS/GCE electrode and glucose. In Fig. 21, it is clear that the peak current at pH 13 exceeds the other pH levels. Therefore, pH 13 was selected for the sodium hydroxide solution used for glucose oxidation by the electrode (Baghayeri et al.) The amperometric response of ZnO/CuO/rGO/PANINS modified GCE was performed to evaluate the current response to glucose. In this study, the optimal potential for amperometric detection of the electrode was investigated in the potential range of 0.45 to 0.65 V. As shown in Fig. 22, the anodic current response increased rapidly from 0.45 to 0.6 V, and the amperometric current response to glucose decreased as the applied potential was increased to + 0.65 V. The highest sensitivity was observed at an operating potential of 0.6 V. Therefore, 0.6 V was chosen as the operating potential for subsequent experiments. At lower detection potentials, the effect of easily oxidized chemical species was greatly reduced (Toghill& Compton, 2010). 3.2.3. Glucose Detection via Amperometry Electro catalytic oxidation of glucose in ZnO/CuO/rGO/PANINS/GCE was studied using amperometry. Glucose standards were added sequentially to 10 mL of 0.1 M NaOH in a continuously stirred solution, the applied potential was set at + 0.6 V, and the glucose concentration was varied from 2 to 10 mM. Figure 11 A shows the amperometric response of the current over time from 2 mM to 10 mM in 0.1 M NaOH solution. After the continuous addition of glucose, modified ZnO/CuO/rGO/PANINS/GCE showed an increase in amperometric current response in relation to glucose concentration. After glucose addition, the time required to achieve 90% of steady-state current was less than 3 seconds, indicating rapid and sensitive glucose oxidation on ZnO/CuO/rGO/PANINS/GCE. The shape of the current-time step curve depends mainly on the glucose concentration in the electrolyte solution. Figure 11 B shows the calibration graph for ZnO/CuO/rGO/PANINS/GCE, where the slope of the calibration graph determined the glucose concentration versus current and sensitivity µAmM-1 cm − 2 divided by the surface area of the working electrode along with the active surface area of the electrode (equations are given below). The graph showed improved linearity between 2 and 10 mM, with the following significant sensitivities, 5660 µA mM − 1 Cm − 2 , with a limit of detection (LOD) of 0.00054 µM (S/N = 3). The minimum detection threshold for glucose, along with its sensitivity and linear range, were analyzed in relation to the current literature, as shown in Table 4 PANINS showed strong catalytic activity, and integration of these membranes into ZnO/CuO/rGO improved catalytic activity and LOD during glucose oxidation ZnO/CuO/ The extensive surface area of rGO/PANINS/GCE contributes to the formation of additional active sites for electro catalytic activity. This indicates that our ZnO/CuO/rGO/PANINS/GCE can serve as an effective and sustainable non-enzymatic glucose sensor. Active surface area = Ip / (2.69 x 10^5 x n^ (2/3) x D^ (1/2) x ϑ^ (1/2) x C) where Ip is the maximum current, C is the overall glucose solution concentration, n is the number of electrons transferred, D is the diffusion coefficient (1.8 × 10 − 3 ), and ϑ is the scan rate. The active surface areas of the bare electrode and ZnO/CuO/rGO/PANINS/GCE were calculated to be 0.001 cm2 and 0.199 cm 2 , respectively, measured at 50 mVs − 1 in a 0.1 M NaOH solution containing 2 mM glucose concentration. Table 2 Comparison of the analytical performance of the ZnO/CuO/rGO/PANINS sensor with other recently published non-enzymatic glucose sensors. Sensing substrate Electrode E(V) Sensitivity µAmMcm − 2 Linear range LOD (µM) Reference NiO/PANI GCE 0.6 606.13 1-100 µM 0.19 [ 23 ] CuO/PANI FTO - 1359 0.25–4.6 µM 0.24 [ 41 ] NiCo 2 O 4 @PANI GCE 0.34 4.55mAmM − 1 cm − 2 0.015-4.735mM 0.3833 [ 42 ] PANINS@RGO SPE - 3448.27 1–4000 µM 0.03 [ 7 ] NiO/CuO/rGO GCE 0.5 1046 5µM-4.85 mM 0.5 [ 43 ] NiO/Au/PANI/RGO GCE 0.55 - 0.09–6mM 0.23 [ 22 ] ZnO − CoO/rGO GCE 0.45 168.7 − 10-11.205mM 1.3 [ 44 ] TiO 2 -RGO-PANI GCE 7.46 2–180mM - [ 45 ] CuO/rGO/Cu 2 O/Cu GCE 0.65 3401.1 0.5–8.266µM 0.1 [ 46 ] PANI/ZnO/MWCNT GCE - 7.8307AmM − 1 cm − 2 0.1-1mM 0.1mM [ 47 ] NiO-NPs @PANINS SPE 0.78 5625 1–10 mM 0.06 [ 48 ] ZnO/CuO/rGO/PANINS GCE 0.6 5660 2–10 mM 0.0005 This work 3.2.4. Analysis of Interference The ability to prevent interference was extremely important for the sensor. The main problem with non-enzymatic sensors is interference from various organic compounds in the blood. These compounds have the potential to oxidize at a similar potential to glucose. Uric acid (UA), ascorbic acid (AA), maltose, sucrose, and dopamine in physiological fluids significantly interfere with the direct electrochemical oxidation of glucose on various electrodes, especially in non-enzymatic sensors. In this analysis, interference tests involving 2 mM glucose and 0.1 mM interfering substance were evaluated at a potential of 0.6 V in 0.1 M NaOH to investigate the selectivity of ZnO/CuO/rGO/PANINS/GCE electrodes. The sensor response shows no clear amperometric signal for uric acid (UA), ascorbic acid (AA), or dopamine. It showed no clear effect on glucose and great selectivity for typical interfering substances. Furthermore, the addition of maltose and sucrose caused only minor changes in the observed currents. However, when 1 mM glucose was added, the observed currents responded. The results for glucose were several times greater than those for maltose and sucrose, suggesting that the effect may not be significant. 3.2.4. Stability, Reproducibility, and Repeatability of ZnO/CuO/rGO/PANINS Sensor The stability of ZnO/CuO/rGO/PANINS-modified GCE was evaluated by monitoring the current response to 2.0 mM glucose over a 10-day period; ZnO/CuO/rGO/PANINS-modified GCE was exposed to air and its current response was evaluated every 2 days. The sensor showed strong stability, maintaining 89.5% of its original response after 10 days of storage. To verify the reproducibility of the proposed method, the relative standard deviation (RSD) of six consecutive measurements of the peak current of 2 mM glucose at the ZnO/CuO/rGO/PANINS/GCE modified electrode was 2.89%, indicating the robust reproducibility of the method. For reproducibility evaluation, the response currents of five ZnO/CuO/rGO/PANINS-modified GCEs fabricated under identical conditions were compared; the RSD of the current response to 2 mM glucose was 4.2%, indicating adequate reproducibility between electrodes. These results confirm that ZnO/CuO/rGO/PANINS-modified GCE exhibits stability, excellent reproducibility, and repeatability. 4.2.8 Analysis of Glucose in Actual Samples To evaluate the efficacy of the ZnO/CuO/rGO/PANINS modified electrode, it was used to measure glucose levels in human serum samples. Using a commercially available spectrophotometer, the glucose level in a diabetic blood sample was measured in triplicate to be 125 mg/dL (6.937 mM). As shown in the figure, 0.5 mL of serum sample was mixed with 10 mL of 0.1 M NaOH solution. The amperometric i-t method was performed before and after glucose was added to the blood sample at a voltage of 0.6 V to evaluate the current response using the standard addition method. Glucose measurements were made using diluted samples, and recovery tests of standard glucose solutions (2, 4, and 6 mM) were performed in parallel with diluted human blood samples within the linear operating range. Results obtained from the improved electrode were comparable to those obtained from spectrophotometry and additional values in the clinical diagnostic laboratory. The glucose levels obtained from the calibration curve using this improved electrode closely matched those obtained from spectrophotometry in the clinical diagnostic laboratory, with only a 1.7% discrepancy, as shown in Table 5 The RSD ranged from 2.62–3.85%, and the recovery of glucose from the standard addition to serum samples ranged from 100.55–102.65%. This indicates that the proposed modified electrode can effectively measure glucose in real samples. Table 3 Working condition and Amperometric determination of glucose spiked in human blood samples (n = 3) Concentration of Original Blood Sample (mM) Glucose added(mM) Glucose Detected (mM) RSD (%) Recovery (%) 6.937mM 0 6.92 3.85 - 2 8.99 3.35 102.65 4 10.99 2.62 101.32 6 12.97 2.87 100.55 4. Conclusion In conclusion, this study successfully developed a non-enzymatic electrochemical glucose sensor utilizing synthesized ZnO/CuO/rGO/PANINS nanocomposites. The structural and optical properties of the synthesized nanocomposites were systematically characterized using advanced techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and ultraviolet-visible spectroscopy (UV-Vis), affirming their composite nature and confirming the effective integration of materials. The cyclic voltammetry (CV) results demonstrated a significant enhancement in electrochemical activity with the incorporation of PANINS into the ZnO/CuO/rGO framework, resulting in improved electrical performance characterized by higher current responses, increased exposed surface area, and accelerated electron transfer rates. These features collectively facilitated efficient glucose oxidation during Amperometric tests. The ZnO/CuO/rGO/PANINS/glassy carbon electrode (GCE) exhibited remarkable catalytic activity, demonstrating high stability, selectivity, sensitivity, and reproducibility, thereby positioning it as a superior alternative to previously reported non-enzymatic glucose sensors. This work not only adds to the existing body of knowledge on electrochemical sensors but also presents a promising approach for the development of advanced glucose monitoring devices. Declarations Ethics Approval: The study received ethical approval from the Kotebe University of Education Research Ethics Review committee, in accordance with the Ethiopia National Research Ethics Review Guideline (Fifth Edition). Declaration of consent Written informed consent was obtained from all participants who took part in the study, after explaining the purpose and significance of the research. Data collection proceeded only after obtaining fully informed verbal consent from the participants, and confidentiality measures were implemented to protect their privacy by excluding their names and personal identification information. Funding Declaration The authors declare that no external funding was received for the conduct of this study. Author Contribution Dessalew Berihun Adam: conceptualization to final analysis Data availability statement: The Data Availability statement of this manuscript, indicating that data can be requested from the corresponding author. References Alemu, H., W. Hailu, and A. Adane, Prevalence of chronic kidney disease and associated factors among patients with diabetes in northwest Ethiopia: a hospital-based cross-sectional study . Current Therapeutic Research, 2020. 92: p. 100578. Baghelani, M., et al., Non-invasive continuous-time glucose monitoring system using a chipless printable sensor based on split ring microwave resonators . Scientific Reports, 2020. 10(1): p. 12980. Organization, W.H., Global diffusion of eHealth: making universal health coverage achievable: report of the third global survey on eHealth . 2017: World Health Organization. Roy, A., et al., Electroless deposition of Pd nanostructures for multifunctional applications as surface-enhanced Raman scattering substrates and electrochemical nonenzymatic sensors . ACS Applied Nano Materials, 2019. 2(4): p. 2503–2514. Teymourian, H., A. Barfidokht, and J. Wang, Electrochemical glucose sensors in diabetes management: an updated review (2010–2020) . Chemical Society Reviews, 2020. 49(21): p. 7671–7709. Li, G., et al., Low-cost voltammetric sensors for robust determination of toxic Cd (II) and Pb (II) in environment and food based on shuttle-like α-Fe2O3 nanoparticles decorated β-Bi2O3 microspheres . Microchemical Journal, 2022. 179: p. 107515. Kailasa, S., et al., High sensitive polyaniline nanosheets (PANINS)@ rGO as non-enzymatic glucose sensor . Journal of Materials Science: Materials in Electronics, 2020. 31: p. 2926–2937. Zimmet, P., et al., Diabetes mellitus statistics on prevalence and mortality: facts and fallacies . Nature Reviews Endocrinology, 2016. 12(10): p. 616–622. Mao, Q., et al., Depositing reduced graphene oxide on ZnO nanorods to improve the performance of enzymatic glucose sensors . Materials Science in Semiconductor Processing, 2021. 121: p. 105391. Park, S.P., et al., Glucose-based resistive random access memory for transient electronics . Journal of Information Display, 2019. 20(4): p. 231–237. Deshmukh, M.A., B.-C. Kang, and T.-J. Ha, Non-enzymatic electrochemical glucose sensors based on polyaniline/reduced-graphene-oxide nanocomposites functionalized with silver nanoparticles . Journal of Materials Chemistry C, 2020. 8(15): p. 5112–5123. Li, C., et al., Screen-printing preparation of high-performance nonenzymatic glucose sensors based on Co3O4 nanoparticles-embedded N-doped laser-induced graphene . ACS Applied Nano Materials, 2022. 5(11): p. 16655–16663. Zhang, E., et al., Porous Co3O4 hollow nanododecahedra for nonenzymatic glucose biosensor and biofuel cell . Biosensors and Bioelectronics, 2016. 81: p. 46–53. Sun, K.G. and S.H. Hur, Highly sensitive non-enzymatic glucose sensor based on Pt nanoparticle decorated graphene oxide hydrogel . Sensors and Actuators B: Chemical, 2015. 210: p. 618–623. Liu, H., et al., Three-dimensional porous NiO nanosheets vertically grown on graphite disks for enhanced performance non-enzymatic glucose sensor . Electrochimica Acta, 2015. 174: p. 745–752. Reitz, E., et al., CuO nanospheres based nonenzymatic glucose sensor . Electroanalysis: An International Journal Devoted to Fundamental and Practical Aspects of Electroanalysis, 2008. 20(22): p. 2482–2486. Wang, G., et al., Enzyme-free amperometric sensing of glucose using Cu-CuO nanowire composites . Microchimica Acta, 2010. 168: p. 87–92. Zheng, B., et al., A sensitive AgNPs/CuO nanofibers non-enzymatic glucose sensor based on electrospinning technology . Sensors and Actuators B: Chemical, 2014. 195: p. 431–438. Cai, B., et al., Synthesis of ZnO–CuO porous core–shell spheres and their application for non-enzymatic glucose sensor . Applied physics A, 2015. 118: p. 989–996. Karuppiah, C., et al., A simple hydrothermal synthesis and fabrication of zinc oxide–copper oxide heterostructure for the sensitive determination of nonenzymatic glucose biosensor . Sensors and Actuators B: Chemical, 2015. 221: p. 1299–1306. Fang, L., et al., 3D porous structured polyaniline/reduced graphene oxide/copper oxide decorated electrode for high performance nonenzymatic glucose detection . Journal of Electroanalytical Chemistry, 2019. 841: p. 1–9. Ghanbari, K. and Z. Babaei, Fabrication and characterization of non-enzymatic glucose sensor based on ternary NiO/CuO/polyaniline nanocomposite . Analytical biochemistry, 2016. 498: p. 37–46. Azharudeen, A.M., et al., Fabrication, characterization of polyaniline intercalated NiO nanocomposites and application in the development of non-enzymatic glucose biosensor . Arabian Journal of Chemistry, 2020. 13(2): p. 4053–4064. Roy, I., et al., Synthesis and characterization of graphene from waste dry cell battery for electronic applications . RSC advances, 2016. 6(13): p. 10557–10564. Ramachandran, R., et al., Synthesis of graphene platelets by chemical and electrochemical route . Materials Research Bulletin, 2013. 48(10): p. 3834–3842. Salahuddin, N.A., M. El-Kemary, and E.M. Ibrahim, Synthesis and characterization of ZnO nanoparticles via precipitation method: effect of annealing temperature on particle size . Nanosci. Nanotechnol, 2015. 5(4): p. 82–88. Shinde, R.S., et al., Synthesis and characterization of ZnO/CuO nanocomposites as an effective photocatalyst and gas sensor for environmental remediation . Journal of Inorganic and Organometallic Polymers and Materials, 2022: p. 1–22. Yousaf, S., et al., Hierarchically porous CuO microspheres and their r-GO based nanohybrids for electrochemical supercapacitors applications . Journal of Materials Research and Technology, 2020. 9(6): p. 14158–14167. Hussein, B.A., et al., A sensitive non-enzymatic electrochemical glucose sensor based on a ZnO/Co 3 O 4/reduced graphene oxide nanocomposite . Sensors & Diagnostics, 2023. 2(2): p. 347–360. Kailasa, S., et al., NiO nanoparticles -decorated conductive polyaniline nanosheets for amperometric glucose biosensor . Materials Chemistry and Physics, 2020. 242: p. 122524. Habte, A.T. and D.W. Ayele, Synthesis and characterization of reduced graphene oxide (rGO) started from graphene oxide (GO) using the tour method with different parameters . Advances in Materials Science and Engineering, 2019. 2019(1): p. 5058163. Basavegowda, N., et al., Bimetallic p-ZnO/n-CuO nanocomposite synthesized using Aegle marmelos leaf extract exhibits excellent visible-light-driven photocatalytic removal of 4-nitroaniline and methyl orange . Photochemical & Photobiological Sciences, 2022. 21(8): p. 1357–1370. Meena, P.L., et al., Facile synthesis of ZnO/CuO/Ag2O ternary metal oxide nanocomposite for effective photodegradation of organic water pollutants . Water Science and Technology, 2021. 84(9): p. 2615–2634. Tantubay, K., P. Das, and M.B. Sen, Ternary reduced graphene oxide–CuO/ZnO nanocomposite as a recyclable catalyst with enhanced reducing capability . Journal of Environmental Chemical Engineering, 2020. 8(4): p. 103818. Tovide, O., et al., Graphenated polyaniline-doped tungsten oxide nanocomposite sensor for real time determination of phenanthrene . Electrochimica Acta, 2014. 128: p. 138–148. Aghaei, M., S. Sajjadi, and A.H. Keihan, Sono-coprecipitation synthesis of ZnO/CuO nanophotocatalyst for removal of parathion from wastewater . Environmental Science and Pollution Research, 2020. 27: p. 11541–11553. Anand, V.K., et al., Highly sensitive and reusable Cu + 2/polyaniline/reduced graphene oxide nanocomposite ink-based non-enzymatic glucose sensor . Applied Physics A, 2020. 126: p. 1–11. Hassan, M.H., et al., Recent advances in enzymatic and non-enzymatic electrochemical glucose sensing . Sensors, 2021. 21(14): p. 4672. Bano, S., et al., The non-enzymatic electrochemical detection of glucose and ammonia using ternary biopolymer based-nanocomposites . New Journal of Chemistry, 2021. 45(18): p. 8008–8021. Alizadeh, T. and S. Mirzagholipur, A Nafion-free non-enzymatic amperometric glucose sensor based on copper oxide nanoparticles–graphene nanocomposite . Sensors and Actuators B: Chemical, 2014. 198: p. 438–447. Esmaeeli, A., et al., Copper oxide-polyaniline nanofiber modified fluorine doped tin oxide (FTO) electrode as non-enzymatic glucose sensor . Sensors and Actuators B: Chemical, 2018. 266: p. 294–301. Yu, Z., et al., Facile synthesis of NiCo2O4@ Polyaniline core–shell nanocomposite for sensitive determination of glucose . Biosensors and Bioelectronics, 2016. 75: p. 161–165. Li, S.-J., et al., Facile synthesis of NiO/CuO/reduced graphene oxide nanocomposites for use in enzyme-free glucose sensing . International Journal of Electrochemical Science, 2016. 11(8): p. 6747–6760. Wang, M., et al., Fabrication of a novel ZnO–CoO/rGO nanocomposite for nonenzymatic detection of glucose and hydrogen peroxide . Ceramics International, 2018. 44(5): p. 5250–5256. Du, J., et al., Titanium dioxide–graphene–polyaniline hybrid for nonenzymatic detection of glucose . Nano, 2019. 14(07): p. 1950093. Zhao, C., et al., Hydrothermal deposition of CuO/rGO/Cu 2 O nanocomposite on copper foil for sensitive nonenzymatic voltammetric determination of glucose and hydrogen peroxide . Microchimica Acta, 2017. 184: p. 2341–2348. Mohajeri, S., A. Dolati, and K. Yazdanbakhsh, Synthesis and characterization of a novel non-enzymatic glucose biosensor based on polyaniline/zinc oxide/multi-walled carbon nanotube ternary nanocomposite . Journal of Electrochemical Science and Engineering, 2019. 9(3): p. 207–222. Kailasa, S., et al., NiO nanoparticles-decorated conductive polyaniline nanosheets for amperometric glucose biosensor . Materials Chemistry and Physics, 2020. 242: p. 122524. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7148554","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500609752,"identity":"50018596-3a32-4997-bbd0-1be09c88ab66","order_by":0,"name":"Dessalew Berihun Adam","email":"data:image/png;base64,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","orcid":"","institution":"Kotebe University of Education","correspondingAuthor":true,"prefix":"","firstName":"Dessalew","middleName":"Berihun","lastName":"Adam","suffix":""}],"badges":[],"createdAt":"2025-07-17 11:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7148554/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7148554/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89375924,"identity":"b9b7bacb-7cd5-4f3e-b6df-9232471d0fdb","added_by":"auto","created_at":"2025-08-19 11:03:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":418591,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of ZnO/CuO/rGO/PANINS\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/3f2ec6984fe06d400be450bc.png"},{"id":89375923,"identity":"6fb5f9b1-c69b-4cc8-a64a-7eca9772a8d4","added_by":"auto","created_at":"2025-08-19 11:03:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125229,"visible":true,"origin":"","legend":"\u003cp\u003eXRD diffraction patterns of (a) GO and rGO (b) ZnO Nps, CuO Nps, ZnO/CuO NCs, ZnO/CuO/rGO and ZnO/CuO/rGO/PANINS nanohybrid.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/9062e8ddbe135c0be012117a.png"},{"id":89376925,"identity":"f8c8cb0e-c0d5-41d2-b7c9-4fae232585a4","added_by":"auto","created_at":"2025-08-19 11:19:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":613024,"visible":true,"origin":"","legend":"\u003cp\u003eFE-SEM images of (a) ZnO NPs, (b) CuO/ZnO NCs, (c) CuO/ZnO/rGO nanohybrid and (d) ZnO/CuO/rGO/PANINS nanohybrid.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/d04be9749d0bf886196bb2d7.png"},{"id":89375925,"identity":"1fae5446-a79d-4bb1-88b5-1821565e07d7","added_by":"auto","created_at":"2025-08-19 11:03:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17122,"visible":true,"origin":"","legend":"\u003cp\u003eUV/Visible absorption spectra of (a) ZnO NPs, (b), ZnO/CuO NCs, (c) ZnO /CuO/rGO and (d) ZnO/CuO/rGO/PANINS nanohybrid.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/506d9e5086b865a45cb49640.png"},{"id":89376927,"identity":"2b99dc9c-ecde-40be-8dbe-50f62378fda8","added_by":"auto","created_at":"2025-08-19 11:19:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":29282,"visible":true,"origin":"","legend":"\u003cp\u003eFT-IR spectrum of ZnO NPs, ZnO/CuO NCs, and ZnO/CuO/rGO and ZnO/CuO/rGO/PANINS nanohybrid.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/b01ea660836acb32c251b130.png"},{"id":89376772,"identity":"8d7a1ca7-a009-4bdf-a0db-8c7826336657","added_by":"auto","created_at":"2025-08-19 11:11:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":358231,"visible":true,"origin":"","legend":"\u003cp\u003eCyclic voltammograms of (A) bare GCE, (B) ZnO/CuO/GCE, (C) ZnO/CuO/rGO/GCE, (D) ZnO/CuO/rGO/PANINS/GCE in absence and presence of 2 mM glucose and (E) studied electrodes under the presence of 2mM glucose in 0.1 M NaOH at 50mVs\u003csup\u003e-1\u003c/sup\u003e Scan rate.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/0469be1dbe0c670059ca20f1.png"},{"id":89375930,"identity":"9663b6d0-220e-4d77-99a6-7a952650049e","added_by":"auto","created_at":"2025-08-19 11:03:17","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":112602,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Cyclic voltammograms of ZnO/CuO/rGO/PANINS/GCE examined at various scan rates (10–100 mVs\u003csup\u003e-1\u003c/sup\u003ein 0.1 M NaOH and (B) Plot of the peak current to the square root of the scan rates.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/125f57784a9705bc05501eca.png"},{"id":89377936,"identity":"6b6b1545-2e7b-4a7c-8ec8-032b5a7be1a1","added_by":"auto","created_at":"2025-08-19 11:27:17","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":15872,"visible":true,"origin":"","legend":"\u003cp\u003eCyclic voltammograms of ZnO/CuO/rGO/PANINS/GCE versus at different concentration of NaOH (0.005M - 0.15M) upon addition of 2 mM glucose at scan rate of 50mVs\u003csup\u003e-1\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/bd40a725fe9f2685b69cbce6.png"},{"id":89376776,"identity":"7d178779-2572-4f72-b71c-10cb6ab9d409","added_by":"auto","created_at":"2025-08-19 11:11:17","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":19415,"visible":true,"origin":"","legend":"\u003cp\u003eCyclic voltammograms of ZnO/CuO/rGO/PANINS/GCE versus PH of NaOH (9-14) upon addition of 2mM glucose at scan rate of 50mVs\u003csup\u003e-1\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/d6e20504c814cce62e79e0df.png"},{"id":89376773,"identity":"0f41524c-3023-4347-ad3f-423c43f35a34","added_by":"auto","created_at":"2025-08-19 11:11:17","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":14771,"visible":true,"origin":"","legend":"\u003cp\u003eAmperometric i-t graphs ZnO/CuO/rGO/PANINS/GCE to the successive injections of 2 mM glucose at different applied potentials from 0.45 V - 0.6V\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/95c573f1fac6eee2bf7c6558.png"},{"id":89376778,"identity":"f4052918-8eeb-4f0e-9476-18eaff9c20ed","added_by":"auto","created_at":"2025-08-19 11:11:17","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":79537,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Amperometric i-t curve of ZnO/CuO/rGO/PANINS/GCE electrode to successive additions of glucose solution into a stirred system of 0.1 M NaOH (pH 13.0) at +0.6 V. (B) The linear calibration plots of the corresponding current versus glucose concentration.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/5daf28b9c975a03ea6289703.png"},{"id":89377937,"identity":"a1b58d87-b700-4e3a-8224-cd619d346d8e","added_by":"auto","created_at":"2025-08-19 11:27:17","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":17105,"visible":true,"origin":"","legend":"\u003cp\u003eAmperometric response of the ZnO/CuO/rGO/PANINS/GCE in 0.1 M NaOH (pH 13) upon the successive addition of Glucose (1mM),Uric acid (0.1mM), Ascorbic acid (0.1mM), Maltose (0.1mM),Sucrose (0.1mM), Dopamine (0.1mM), and 1 mM Glucose, respectively.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/fccc349560f0424b2ec2a655.png"},{"id":89375939,"identity":"e30ea90e-cc6f-4ac4-b512-d4f5d89c8b94","added_by":"auto","created_at":"2025-08-19 11:03:17","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":188948,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Stability for 10 days (B) Repeatability (C) Reproducibility of the ZnO/CuO/rGO/PANINS/GCE in 0.1 M NaOH with addition of 2 mM glucose.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/b8ae3039a98181bab6b022eb.png"},{"id":89376782,"identity":"48214bc9-87a1-426d-bfb8-89954c87ddbf","added_by":"auto","created_at":"2025-08-19 11:11:17","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":136826,"visible":true,"origin":"","legend":"\u003cp\u003e( A). The amperometric i-t response of before and after the addition of glucose to the blood samples at an applied potential of 0.6 V. B Calibration plot of obtained current versus serum samples\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/3e33e9da36b31e35cc48e0c3.png"},{"id":89880579,"identity":"8c949f92-379f-4520-8e10-c05f3bfd4706","added_by":"auto","created_at":"2025-08-26 05:47:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3292739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7148554/v1/0b7d7387-5e0d-4f00-a483-9e6d2fa012a4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Facile Fabrication of a Nanocomposite Electrode for Enhanced Electrochemical Performance","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eA chronic metabolic disease known as diabetes is typified by high blood glucose levels, which can cause serious health issues that impact several organ systems. According to the World Health Organization (WHO), 422\u0026nbsp;million people worldwide are estimated to have diabetes, making it a serious public health issue [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Long-term hyperglycemia-related complications of diabetes include cardiovascular disease, neuropathy, retinopathy, amputations, hypertension, and dyslipidemia. These issues constitute serious chronic illnesses and offer a serious public health concern on a worldwide scale [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition to being crucial for the diagnosis of diabetes, glucose monitoring and management are important for a number of other industries, such as wastewater treatment, environmental monitoring, and the food and textile sectors. Accurate glucose detection is essential in these situations to maintain quality control, enhance fermentation, and evaluate the health of the ecosystem [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsequently, the food, chemical, biological, and clinical diagnostics sectors have all shown a great deal of interest in glucose level monitoring. Recent developments in this area have prompted research into extremely precise glucose detection techniques, including as colorimetric assays, electrochemical sensors, surface-enhanced Raman scattering, and fluorescence approaches [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Because of their affordability, ease of synthesis, and adaptability in detecting a variety of analytes, electrochemical sensors have attracted a lot of interest in both research and industry applications. These sensors use electrochemical principles to deliver quick, accurate, and targeted measurements in a variety of settings, such as food safety, medical diagnostics, and environmental monitoring [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Electrochemical sensors are ideal for on-site analysis due to minimal sample preparation and rapid results, with advancements in bifunctional catalysts and nanomaterials enhancing their detection limits, sensitivity, and selectivity. Enzyme-based glucose sensors, particularly those utilizing glucose oxidase, exhibit high selectivity and biocompatibility but face challenges such as high production costs, instability, limited lifespan, suboptimal kinetics, and environmental sensitivity, indicating a need for further research to enhance their performance and adaptability [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Researchers are exploring non-enzymatic electrochemical glucose sensors to address existing limitations. These sensors offer advantages such as affordability, reliability, simplicity, stability, and reproducibility. Their technology is based on the direct oxidation of glucose at the electrode surface, enhanced by non-biological recognition elements, which improves sensor performance and enables efficient electrochemical glucose detection without biological catalysts [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe development of non-enzymatic glucose sensors encounters challenges such as high working potentials, erratic redox reactions, and slow electron transfer kinetics. Recent research has concentrated on synthesizing novel nanomaterials with high electrical conductivity and enhanced catalytic activity to overcome these obstacles, as their favourable properties including large surface area and low charge transfer resistance make them ideal electrode materials [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A range of nanostructures, including nanowires, quantum dots, and core-shell configurations, can be synthesized from carbon-based compounds, metals, and polymers, offering enhanced properties like increased surface area and improved conductivity. Despite these advantages, only a limited number have been utilized for nonenzymatic glucose detection, although optimization of parameters such as nanoparticle concentration and surface charge holds potential for diverse electrochemical applications [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHistorically, a variety of enzyme-free glucose sensors have been developed utilizing metal nanoparticles such as Pt ([\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]), metal oxide nanoparticles (NiO) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], CuO [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and composites materials [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Ag-CuO [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], ZnO/CuO[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These materials particularly, ZnO/CuO-based multifunctional monohybrids are favored for non-enzymatic glucose sensors due to their excellent catalytic performance, high electron transfer, non-toxicity, and versatility in applications like sensing, catalysis, and energy storage. Their effectiveness stems from the extended electron depletion layer created by p-n junctions and their natural abundance [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To enhance the electrocatalytic performance of these nanocomposites, a prevalent strategy involves the synthesis of composite materials by integrating conductive components, including carbon-based nanomaterials (e.g., graphene, reduced graphene oxide) or conductive polymers (such as polyaniline (PANI) and polypyrrole) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGraphene oxide (GO) and reduced graphene oxide (rGO), synthesized from discharged dry cell electrodes, present a cost-effective alternative to graphene for electrochemical applications due to their advantageous properties such as high electrical conductivity and substantial specific surface area. These characteristics enhance electrochemical activity in glucose oxidation and contribute to the durability of nanocomposite materials by preventing the aggregation of active nanomaterials during redox and catalytic processes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConductive polymers, particularly polyaniline, have enabled the development of hybrid nanostructures due to their high electrical conductivity and excellent thermal and chemical stability. Polyaniline nanostructures are noted for their environmental resilience, substantial surface area, advantageous redox behavior, and ease of fabrication, promoting various applications. Additionally, interfacial interactions among metal oxides, carbon materials, and polymer matrices enhance material properties, increase active site exposure, improve stability, and boost electro-catalytic activity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNumerous composite materials, particularly carbon-based materials and metal oxides incorporated onto polyaniline (PANI) arrays, exhibit heightened sensitivity to glucose. For instance, the nanoparticle-modified polyaniline nanofibers, specifically those modified with nickel and copper oxides, denoted as NiO/CuO/PANI, have been documented in the literature as exhibiting significant glucose sensitivity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, we developed a non-enzymatic glucose sensor by modifying a glassy carbon electrode (GCE) with a composite of ZnO/CuO, reduced graphene oxide (rGO), and polyaniline nanosheets (PANINS), designated as ZnO/CuO/rGO/PANINS/GCE. The electrochemical performance for glucose oxidation was evaluated using cyclic voltammetry (CV) and amperometric methods. The electrocatalytic behavior of the modified GCE demonstrated a broad linear response range, low detection limit, high sensitivity, and good selectivity, establishing it as an effective enzyme-free glucose sensor.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Chemicals and reagent\u003c/h2\u003e\u003cp\u003eIn the present study, all chemicals and reagents were procured from Sigma-Aldrich and additional suppliers. The materials employed included microcrystalline natural graphite powder (99.995% purity), absolute ethanol (C₂H₅OH, 99.7%), ammonium persulfate ((NH₄)₂S₂O₈, 98%), aniline (C₆H₅NH₂, 99.8%, analytical grade), potassium ferricyanide (K₃[Fe(CN)₆], 99%), and alumina powder with particle sizes of 1 mm, 0.3 mm, and 0.05 mm. Moreover, other reagents utilized in the experiments encompassed glucose (C₆H₁₂O₆, molar mass 180.156 g/mol), sodium carbonate (Na₂CO₃), sodium hydroxide (NaOH), copper(II) nitrate trihydrate (Cu(NO₃)₂\u0026middot;H₂O), potassium nitrate (KNO₃), and zinc nitrate hexahydrate (Zn(NO₃)₂\u0026middot;6H₂O, molar mass 297.37 g/mol, 96.103% purity), sourced from Blulux Laboratories Ltd, India. Additionally, hydrochloric acid (HCl, 37%) and sulfuric acid (H₂SO₄, 98%, Merck) were employed, along with potassium permanganate (KMnO₄). Unless stated otherwise, all other reagents used in the experiments were of analytical grade and did not require further purification. Deionized water, with a resistivity of 18.25 MΩ, was utilized for all solution preparations. Prior to experimentation, all experimental solutions were purged with high-purity argon gas (99.999% purity), obtained from Merck, Germany, for approximately five minutes, and the gas flow was maintained throughout the experiments to eliminate dissolved oxygen.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRecovery of graphite powder from used dry cell battery\u003c/b\u003e\u003c/p\u003e\u003cp\u003eZinc-carbon dry cell batteries were sourced from a commercial vendor for the purpose of electrode material recovery. Initially, the electrodes were meticulously extracted from the batteries to facilitate further processing. To eliminate potential contaminants, including manganese dioxide (MnO\u003csub\u003e2\u003c/sub\u003e), metallic particles, and residual carbon, the electrodes underwent a thorough cleansing process. This involved repeated mechanical agitation and rinsing with distilled water. Following the purification stage, the electrodes were subjected to drying and then mechanically processed to achieve a fine graphite powder through grinding and crushing techniques. Despite these efforts, residual inorganic materials remained embedded within the graphite matrix. To address this issue, the obtained graphite powder was immersed in a beaker containing a hydrochloric acid (HCl) and nitric acid (HNO\u003csub\u003e3\u003c/sub\u003e) mixture at a volumetric ratio of 3:1. The mixture was then heated for several hours to facilitate the dissolution of remaining impurities. Subsequent to the acid treatment, the solution was centrifuged to separate the solid graphite powder from the liquid phase. The purified graphite was further rinsed multiple times with distilled water to ensure neutralization and removal of any acidic residues, allowing the pH to return to a normal range. The final recovered graphite powder, designated as [ G (R)], was dried in an oven at a controlled temperature of 60\u0026deg;C for a duration of 24 hours [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This careful and systematic series of steps aimed to enhance the purity and usability of the recovered graphite for potential applications in various research and industrial settings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Synthesis of GO and rGO\u003c/h2\u003e\u003cp\u003eGraphene oxide (GO) was synthesized from recovered graphite powder denoted as [G(R)] utilizing the Hummers method, a well-established chemical approach for the oxidation of graphite [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The synthesis of graphite oxide was performed utilizing a modified Hummers' method, which involves a series of steps aimed at the exfoliation and oxidation of graphite flakes. Initially, a mixture of 1 g of recovered graphite powder and 1 g of sodium nitrate (NaNO\u003csub\u003e3\u003c/sub\u003e) was introduced into 50 ml of 98% concentrated sulfuric acid (H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e). This mixture underwent ultra-sonication for a duration of 3\u0026ndash;4 hours to facilitate the separation and exfoliation of graphite flakes, thereby yielding a more accessible substrate for subsequent chemical reactions. In order to promote the oxidation of the exfoliated graphite flakes, an additional 50 ml of 98% concentrated H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e was incrementally added to the initial reaction mixture. Following this, 6 g of potassium permanganate (KMnO\u003csub\u003e4\u003c/sub\u003e) was introduced slowly while maintaining vigorous stirring for a period of 4 hours, ensuring that the temperature remained below 20\u0026deg;C to avoid excessive heat generation which could lead to undesirable side reactions. To terminate the oxidation reaction and to quench the reactive species, 100 ml of deionized (DI) water was carefully added to the mixture at ambient temperature over a span of 2 hours. This step was crucial to stabilize the reaction environment. Subsequently, an additional 200 ml of hot DI water was incorporated, and the mixture was stirred for another 2 hours at a temperature of 90\u0026deg;C to further facilitate the oxidation process and to promote the dissolution of products into the aqueous phase. To remove any unreacted potassium permanganate and to assist in the complete reduction of the resulting manganese oxides, 20 ml of hydrogen peroxide (H2O2) was introduced into the reaction system. This addition not only served as a titrant for the unreacted KMnO4 but also effectively catalyzed the completion of the oxidation reaction. Upon completion of the reaction sequence, the final mixture was subjected to centrifugation to separate the solid graphite oxide from the liquid phase. The solid precipitate was then rigorously washed with deionized water multiple times to ensure the removal of residual reactants and byproducts. The resultant graphite oxide (GO) was subsequently dried at 60\u0026deg;C for a period of 24 hours to yield a stable product. In order to obtain reduced graphene oxide (rGO), the synthesized graphite oxide was further processed in accordance with established methodologies documented in current scientific literature, which outline the reduction techniques necessary to achieve the desired properties of rGO. This process typically involves chemical or thermal reduction steps that effectively restore some of the sp\u0026sup2; hybridization lost during the oxidation of graphite [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A dispersion of graphene oxide (GO) at a concentration of 30 mg in 30 mL of deionized water was prepared and subsequently introduced into a sealed vessel with a total volume of 60 mL. Following this, a stoichiometric amount of sodium borohydride was added to achieve a concentration of 0.04 M. Additionally, a 1 M sodium hydroxide solution was introduced to the system to adjust the pH and facilitate the reduction process. The resultant mixture was subjected to thermal treatment at a constant temperature of 90\u0026deg;C for a duration of 1 hour to promote the reduction of graphene oxide to reduced graphene oxide (rGO).\u003c/p\u003e\u003cp\u003eFollowing the thermal reduction phase, the mixture was processed using centrifugation at a suitable rotational speed in order to separate the reduced graphene oxide from the aqueous phase and unreacted species. The resultant precipitate was collected and subsequently dried at a controlled temperature of 60\u0026deg;C for 24 hours to ensure the removal of residual moisture and achieve a stable powder form.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e3.4.2. Synthesis of ZnO Nanoparticles\u003c/h2\u003e\u003cp\u003eZinc oxide (ZnO) nanoparticles (NPs) were synthesized via a precipitation method, building upon established protocols in the literature. In this process, zinc nitrate hexahydrate (Zn(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;6H\u003csub\u003e2\u003c/sub\u003eO) and sodium carbonate (Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e) were utilized as the primary reactants. For the preparation of the reactant solutions, a specific quantity of zinc nitrate hexahydrate, precisely 29.747 g, was dissolved in 200 mL of deionized water to achieve a concentration of 0.1 mol. Concurrently, a sodium carbonate solution was prepared by dissolving 12.7188 g of Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e in 240 mL of deionized water, yielding a concentration of 0.12 mol. Subsequently, the zinc nitrate solution was gradually introduced into the sodium carbonate solution while maintaining continuous stirring for a duration of 2 hours. This controlled addition was essential to facilitate the homogeneous mixing of the reactants and promote the formation of zinc carbonate precipitate through the following reaction:\u003c/p\u003e\u003cp\u003eZn(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e+Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e \u0026rarr; ZnCO\u003csub\u003e3\u003c/sub\u003e\u0026darr;+2NaNO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003cp\u003eAfter the reaction period, the resultant white precipitate, consisting predominantly of zinc carbonate (ZnCO\u003csub\u003e3\u003c/sub\u003e), was allowed to settle for 24 hours. Following this maturation period, the precipitate was collected by filtration using Whatman filter paper, ensuring the removal of any unreacted materials and by-products. To enhance the purity and homogeneity of the obtained precipitate, it was subjected to thorough washing three times with deionized water, followed by ethanol. This washing procedure aimed to alleviate any residual ionic species and ensure a cleaner product in subsequent processing steps. The washed precipitate was then dried at 100\u0026deg;C for 6 hours, which facilitated the formation of a zinc oxide precursor. The precursor material was subsequently subjected to thermal treatment through calcination in a furnace at a temperature of 300\u0026deg;C for a duration of 2 hours. This thermal process aimed to decompose the zinc carbonate into zinc oxide, yielding the final product: nano-ZnO particles [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e3.4.4. Synthesis of ZnO/CuO Nanocomposites\u003c/h2\u003e\u003cp\u003eZinc oxide/copper oxide (ZnO/CuO) nanocomposites were synthesized in a stoichiometric ratio of 1:1 utilizing copper(II) nitrate trihydrate (Cu(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;3H\u003csub\u003e2\u003c/sub\u003eO) and zinc nitrate hexahydrate (Zn(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;6H\u003csub\u003e2\u003c/sub\u003eO) as precursors through a co-precipitation method. Initially, 100 mL of deionized water was employed to dissolve the metal nitrates, creating a homogeneous solution with a concentration of 0.2 M for both metal ions. Subsequent to the preparation of the precursor solution, a 1 M sodium hydroxide (NaOH) solution was incrementally introduced into the 0.2 M metal nitrate solution under vigorous stirring. This process was meticulously monitored until the pH reached 14, a condition conducive to the precipitation of metal oxides. The alkaline solution was then maintained at a temperature of 80\u0026deg;C using a magnetic stirrer, promoting the formation of a black precipitate, indicative of the formation of ZnO/CuO nanocomposites due to the interaction of the metal ions in the alkaline medium [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Following the synthesis, the resultant black precipitate was subjected to vacuum filtration to separate it from the aqueous phase. The filtered precipitate was then thoroughly washed 2\u0026ndash;3 times with deionized water to remove any unreacted precursors and residual ions. This washing step was succeeded by rinsing the precipitate with ethanol to enhance purity and facilitate the removal of any remaining organic contaminants. The washed precipitate was dried overnight in a laboratory oven at a controlled temperature of 80\u0026deg;C to eliminate moisture. To achieve the desired crystalline structure and enhance the thermal stability of the nanocomposites, the dried precipitate was subsequently calcined at 450\u0026deg;C for a duration of 3 hours. This calcination process promotes the complete conversion of the precursors into ZnO/CuO nanocomposites, resulting in materials with potentially useful morphological and electronic properties for various applications.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e3.4.5. Synthesis of ZnO/CuO/rGO monohybrids\u003c/h2\u003e\u003cp\u003eThe ZnO/CuO/reduced Graphene Oxide (rGO) monohybrids was synthesized using a modified approach based on the protocol described in the referenced literature [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In a systematic approach towards the synthesis of ZnO/CuO/reduced graphene oxide (rGO) monohybrids, 5 mg of rGO was initially dispersed in 60 mL of ethanol utilizing ultra-sonication for a duration of 2 hours. The sonication process facilitates the dispersion of rGO by disrupting agglomerated particles, thus contributing to a more homogeneous distribution within the solvent. Concurrently, a separate beaker was utilized to prepare a uniform suspension of 6.3 g of the synthesized ZnO/CuO nanocomposite in 100 mL of deionized water. The suspension was subjected to magnetic stirring at a controlled temperature of 55\u0026deg;C for 2 hours. This heating and stirring process promotes complete dissolution of the nanocomposite and enhances the dispersion stability of the resulting suspension, ensuring that the nanocomposite particles are uniformly distributed throughout the aqueous medium. Following the preparation of both the rGO and the ZnO/CuO solutions, the latter was incrementally added to the former in a dropwise fashion while maintaining continuous stirring under a nitrogen atmosphere. The nitrogen environment was employed to minimize oxidation and ensure that the reactive components remained stable throughout the synthesis process. Subsequently, the temperature of the resulting mixture was equilibrated to room temperature to facilitate the interaction between the rGO and the ZnO/CuO nanocomposite. Once the two solutions were combined, the resultant suspension underwent centrifugation to separate the monohybrids from the supernatant. This step was followed by extensive washing with deionized water and ethanol, aimed at eliminating any unreacted materials and residual impurities from the synthesis. Finally, the purified ZnO/CuO/rGO nanohybrids were subjected to a drying process at 80\u0026deg;C overnight to facilitate the removal of any solvent residues and to yield a stable monohybrid material. This rigorous synthetic protocol aimed to ensure optimal integration of rGO with the ZnO/CuO nanocomposite, potentially enhancing the material's properties for subsequent applications.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e3.4.6. Synthesis ZnO/CuO/rGO/PANINS\u003c/h2\u003e\u003cp\u003e\u003cb\u003eAs\u003c/b\u003e shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the synthesis of ZnO/CuO/rGO/PANINS was accomplished through a modified procedure adapted from the method delineated in reference. Initially, 1.0 g of a composite material comprising zinc oxide (ZnO), copper oxide (CuO), and reduced graphene oxide (rGO) was dispersed in distilled water. This mixture was subjected to magnetic stirring for a duration of 1 hour at ambient temperature to ensure the formation of a homogeneous nanosuspension. Subsequently, 1.5 mL of aniline, 5.8 mL of hydrochloric acid (HCl), and 2.76 g of sodium dodecyl sulfate (SDS) were introduced into the nanosuspension as surfactants, with the process being conducted in an ice bath to control the exothermic nature of the reaction. The stirring continued for an additional 30 minutes to facilitate proper mixing and incorporation of the surfactants into the suspension. In a separate 10-mL beaker, an aqueous solution of ammonium persulfate (APS) was prepared by dissolving 1.469 g of APS in pure water. This APS solution was then carefully added to the previously prepared mixture. Upon addition, a noticeable colour change from light blue to dark green was observed, indicative of the onset of polymerization. The dark green suspension was stirred continuously for a total of 3 hours to ensure complete reaction and interaction among the components. Following the stirring phase, the mixture was allowed to mature and polymerize for a period of 48 hours, providing sufficient time for the polymerization process to reach completion. The resultant ZnO/CuO/rGO/PANINS composite was subjected to centrifugation to separate the solid product from the liquid phase. The collected product was thoroughly washed with distilled water and ethanol to eliminate unreacted monomers and any residual surfactants. Finally, the purified composite was dried in an oven at 60\u0026deg;C to yield the final ZnO/CuO/rGO/PANINS material for subsequent characterization and application.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Materials characterization\u003c/h2\u003e\u003cp\u003eThe synthesized materials, which include (ZnO), (ZnO/CuO), and ZnO/CuO/rGO), were systematically characterized using a suite of analytical techniques to elucidate their structural, morphological, and optical properties.\u003c/p\u003e\u003cp\u003eX-ray diffraction (XRD) analysis was performed employing a Bruker D2 Phaser diffractometer, utilizing a copper Kα radiation source (λ\u0026thinsp;=\u0026thinsp;1.5405 \u0026Aring;) at an operating voltage of 30 kV and a current of 10 mA. The diffraction patterns were recorded over a 2θ range of 10\u0026deg; to 80\u0026deg;, enabling the determination of phase composition and crystallite structure. Morphological characterization was carried out using scanning electron microscopy (SEM) equipped with energy-dispersive X-ray (EDX) capabilities. The SEM analysis was performed with a JEOL JSE-6700F microscope, operating at an accelerating voltage of 15 kV, which facilitated the examination of surface topology and particle size distribution, while EDX provided elemental composition analysis. The optical properties of the synthesized materials were investigated through UV-visible spectroscopy. This technique allowed for the assessment of the materials\u0026rsquo; absorption characteristics and electronic transitions, contributing to the understanding of their potential applications in optoelectronic devices. Fourier transform infrared (FTIR) spectroscopy was also employed to further characterize the materials. FTIR absorption spectra were acquired using a Shimadzu IRTracer-100 spectrometer, covering a spectral range of 4000 to 400 cm\u003csup\u003e-1\u003c/sup\u003e. This analysis was instrumental in identifying various functional groups and chemical bonds present in the samples, as well as in revealing information on the molecular interactions within the composites.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Surface modification and electrochemical measurements\u003c/h2\u003e\u003cp\u003eSurface modification on a glass carbon electrode as a substrate following our previous work [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]: the glassy carbon electrode (GCE) was polished with 1, 0.3, and 0.05 \u0026micro;M alumina powder to clean the surface. Between each polishing step, the electrodes were rinsed with distilled water. After polishing, the electrodes were sonicated in a 1:1 mixture of nitric acid (HNO3), ethanol, and deionized water for 5 minutes and dried at room temperature. Next, an 8 \u0026micro;L suspension of ZnO/CuO/rGO/PANINS was applied on bare GCE and placed in an air oven at 35\u0026deg;C until the film was completely dry. Control modified electrodes containing ZnO/GCE, CuO/GCE, ZnO/CuO/GCE, ZnO/CuO/rGO were prepared by the same experimental procedure The following is a summary of the experimental results [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. All experiments were conducted at room temperature.\u003c/p\u003e\u003cp\u003eCyclic voltammetry (CV) and amperometric detection were performed on a three-electrode system using a BAS100B Electrochemical Bioanalyzer with Windows\u0026trade; software. The system included a platinum wire as a counter electrode, a leak-free silver/silver chloride reference electrode, and a modified GCE as the working electrode. Prior to the experiment, the solution was purged with pure N2 gas to remove dissolved oxygen. For amperometric detection of glucose, glucose was continuously added under magnetic stirring at various glucose concentrations at an applied potential of 0.6 V in an electrochemical cell containing a magnetically stirred NaOH electrolyte. Interference tests were performed under the same conditions as glucose measurements, incorporating interfering compounds. Human serum samples were analyzed using the standard addition method. Glucose concentrations in human blood samples were measured using a glucose monitoring kit. Samples were diluted to 0.1 mM (10 mL) with 0.1 M NaOH solution. Then, 0, 0.5, and 1 mM glucose solutions were added to the diluted samples and recovery was determined by CV measurement (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e\u003cp\u003eTo assess the reproducibility, repeatability, and stability of the ZnO/CuO/rGO/PANINS GCE nanocomposite-based electrode, multiple electrodes were prepared and tested under similar environmental conditions. In order to determine reproducibility, glucose detection was conducted five times using a single electrode, which was thoroughly washed with deionized water after each test. The standard deviation of the electrochemical current response was then calculated. The sensor demonstrated reproducibility, as all five electrodes yielded consistent results when tested for glucose detection. The electrochemical response of each sensor was recorded, along with its standard deviation. Additionally, the long-term stability of the sensor was assessed by monitoring the current response to glucose over a period of 10 days. The stability of the ZnO/CuO/rGO/PANINS nanocomposite-modified electrode in the presence of glucose was evaluated every 2 days for the duration of the 10-day period. The modified electrodes were stored under ambient conditions, and their current responses were recorded accordingly.\u003c/p\u003e\u003cp\u003eThe effectiveness of the proposed sensor was tested by measuring the glucose levels in human blood samples. The concentration of blood glucose was determined spectrophotometrically after conducting three measurements. Prior to electrochemical analysis, the blood samples were centrifuged at 3000 rpm for 15 minutes to eliminate any precipitated proteins or other particles. A serum sample of 0.1 ml was then mixed with a 10 ml solution of 0.1 M NaOH for dilution. Electrochemical assessments were conducted using ZnO/CuO/rGO/GCE modified electrodes at the optimal applied potential. The accuracy of the method was verified by examining the recoveries as well. All tests and experiments were conducted at room temperature. The sample recoveries were calculated using the following formula.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\%\\:Recovery=\\:\\frac{concentration\\:of\\:spiked-cocentration\\:of\\:unspiked}{concentration\\:of\\:added\\:amount\\:}\\:x\\:100\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:1$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Physical characterizations\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.1.1. XRD Analysis\u003c/h2\u003e\u003cp\u003eX-ray diffraction (XRD) is a commonly employed non-destructive analytical technique utilized to investigate crystallite size, orientation, and the average spacing of atomic layers within materials. In this study, XRD analyses were conducted to verify the formation of synthesized materials including graphene oxide (GO), reduced graphene oxide (rGO), zinc oxide/copper oxide (ZnO/CuO), zinc oxide/copper oxide/reduced graphene oxide (ZnO/CuO/rGO), and zinc oxide/copper oxide/reduced graphene oxide/panins (ZnO/CuO/rGO/PANINS).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(a) illustrates the XRD patterns for GO and rGO, exhibiting distinct Bragg peaks at a 2θ value of 10.5\u0026deg; (001), which corresponds to an interplanar spacing (d) of 0.94 nm. This finding suggests the successful presence of oxidized graphite, which is characterized by various functional groups attached to its surface. The effective reduction of GO to rGO, achieved through the application of sodium borohydride (NaBH4) as a reducing agent, is substantiated by the broad XRD signals, featuring reflection peaks at 2θ values of 25.7\u0026deg; and 45.89\u0026deg;, indicating an interplanar spacing of 0.35 nm. The observed diffraction planes (011) and (004) align closely with values reported in existing literature, thereby confirming the removal of oxygen-containing functional groups from the interstitial spaces within the graphite nanostructures [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(b) displays distinct peaks at diffraction angles of 31.7\u0026deg;, 34.4\u0026deg;, 36.4\u0026deg;, 47.6\u0026deg;, 56.7\u0026deg;, 62.9\u0026deg;, and 67.9\u0026deg;, which are indicative of the crystalline planes (100), (002), (101), (102), (110), (103), and (200) of zinc oxide (ZnO) nanoparticles. These peaks are consistent with the standard reference pattern listed in the Joint Committee on Powder Diffraction Standards (JCPDS) card number 36-1451 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The remaining peaks occur at 32.41\u0026deg;, 35.61\u0026deg;, 38.81\u0026deg;, 48.91\u0026deg;, and 61.61\u0026deg;, corresponding to the corresponding faces (110), (111), (200), (202), and (113) of the CuO nanoparticle (JCPDS card number 45\u0026ndash;0397). A peak is observed at 24.4\u0026deg; corresponding to the (001) plane of rGO, confirming that GO was successfully reduced by the tour method; the 2θ reflection peak of PANINS appears at 20.5\u0026deg; and the corresponding plane is (101) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].These results indicate that ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites were successfully formed. The crystal sizes of the nanocomposites ZnO, CuO, ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS were measured to be 20.25 nm, 17.85 nm, 16.81 nm, 16.18 nm, and 18.05 nm, respectively. ZnO/CuO/rGO nanocomposites were smaller than the average particle size of the ZnO/CuO nanocomposites; the ternary ZnO/CuO/rGO nanocomposites had the smallest particle size due to the synergistic effect of ZnO, CuO, and rGO in the composite system and thus and exhibited the highest surface area. However, the crystallite size of ZnO/CuO/rGO/PANINS increased because sodium dodecyl sulfate (SDS) reduces double distillation water, which significantly affects electrochemical and catalytic activity. ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanomaterials, the crystal sizes, d-spacing of the individual materials, and the distinct shifts are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{D}=\\frac{\\varvec{K}\\varvec{\\lambda\\:}}{\\varvec{\\beta\\:}\\mathbf{c}\\mathbf{o}\\mathbf{s}\\varvec{\\theta\\:}}\\:(1\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{d}=\\frac{\\varvec{n}\\varvec{\\lambda\\:}}{2\\varvec{s}\\varvec{i}\\varvec{n}\\varvec{\\theta\\:}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u0026lsquo;D\u0026rsquo; is the average crystallite size, \u0026lsquo;d\u0026rsquo; is interplanar spacing, \u0026lsquo;θ\u0026rsquo; is Bragg\u0026rsquo;s angle, \u0026lsquo;λ\u0026rsquo; is the wavelength of X-ray and \u0026lsquo;β\u0026rsquo; is the full width half maximum (FWHM).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCrystal parameters of GO, rGO, CuO/ZnO, ZnO/CuO/rGO and ZnO/CuO/rGO/PANINS\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2θ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFWHM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCrystal size\u003c/p\u003e\u003cp\u003e(average) nm\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAverage crystal size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ed-spacing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ehkl\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.0085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.06613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.2618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e13.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.16177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.06538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.40446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.88323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e20.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.2118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.22952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.40634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.5809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.24064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.23462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.4932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.36638\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCuO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.18391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.79085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.21678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.36375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.9438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.23605\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.32033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26.3053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e202\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.49111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.3965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.36686\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e113\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO/CuO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.53199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e16.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.21333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.59879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.9502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.23807\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.36353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.1189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.61973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.6459\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.37256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO/CuO/rGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.32729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.3111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e16.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.21835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.5434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.42671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34436\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.4663\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.94772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.52601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.36593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO/CuO/rGO/PANINS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.0193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e18.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.21835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.04889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.98281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.24335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.454409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.93283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.66126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.36373\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.1.2. Surface morphology analysis\u003c/h2\u003e\u003cp\u003eThe as-synthesized ZnO nanoparticles, ZnO/CuO nanocomposites, and ZnO/CuO/rGO nanohybrid' surface morphology were studied using SEM at various magnifications, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a, b) and 3(c, d) are the SEM images of ZnO and CuO/ZnO samples. When minor ZnO nanoparticles are present, the surface morphology of the CuO nanoplatelets changes, suggesting that the ZnO nanoparticles are uniformly dispersed on the CuO nanoplatelet surface. The existence of ZnO on the CuO nanostructure forms a CuO/ZnO hetero junction with a complex shape and clearly promotes dynamic adsorption of the reacting molecules. On the other hand, the SEM micrograph of the ZnO/CuO/rGO nanohybrid in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(e, f) shows that the ZnO nanoparticles and CuO plates are uniformly distributed and interconnected on the rGO sheet nanostructure.\u003c/p\u003e\u003cp\u003eFurthermore, the SEM images reveal the distinct morphological characteristics and structural evolution of the synthesized materials. The first ZnO nanoparticles, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a) and (b), display aggregated clusters with irregular shapes and sizes, exhibiting a rough, granular surface texture with significant particle agglomeration. Upon incorporation of CuO to form CuO/ZnO nanocomposites, as depicted in images c and d, a remarkable transformation in morphology is observed. The composite structure develops into a more sophisticated flower-like or hierarchical arrangement, characterized by distinctive plate-like or leaf-like projections extending from the central structures. This modification proves enhanced dispersion suggesting successful integration of the two metal oxide components.\u003c/p\u003e\u003cp\u003eThe final stage of the composite synthesis, involving the addition of reduced graphene oxide (rGO) to form CuO/ZnO/rGO (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(e) and (f)), exhibits the most complex morphological features. The resulting structure reveals an interconnected network architecture where the metal oxide components appear to be effectively anchored onto the rGO sheets. This arrangement creates a layered structure with visible porosity, showing potential enhancement in surface area compared to its precursor materials. The SEM analysis confirms the successful synthesis of the hybrid material, showing good integration between all components. The progressive evolution of morphology throughout the synthesis stages suggests that the final composite structure may offer improved performance characteristics for various applications, attributed to its hierarchical organization and enhanced structural features.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.1.3. UV-Vis Analysis\u003c/h2\u003e\u003cp\u003eUV-visible absorption spectra of ZnO NPs, ZnO/CuO NCs, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanohybrid materials were recorded at room temperature and are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a), a sharp absorption peak at 368 nm corresponding to a band gap of 3.1 eV indicates the presence of ZnO nanostructures, and the ZnO [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(b) shows the formation of ZnO/CuO binary nanocomposites with an absorption peak at 372 nm and a reduced band gap of 2.75 eV. This represents a decrease in the band gap from 3.1 eV for ZnO nanoparticles to 2.75 eV for the ZnO/CuO binary nanocomposite. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(c), the absorption peak at 374 nm indicates the presence of ZnO/CuO/rGO ternary nanocomposites, and the band gap is further reduced to 2.68 eV. Both the ZnO/CuO binary nanocomposite and the ZnO/CuO/rGO ternary nanocomposite show enhanced in the visible light region with an enhanced absorbance in the visible region [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The spectra of the ternary nanocomposites showed a broad elevated background in the visible region, mainly due to the presence of rGO. In particular, the absorbance of the ZnO/CuO/rGO nanocomposite is increased compared to that of the ZnO nanoparticles and the ZnO/CuO binary nanocomposite. Furthermore, it is observed that the band gap of ZnO decreases when coupled with ZnO, CuO, and rGO. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(d), the spectrum of ZnO/CuO/rGO/PANINS shows a broad absorption peak at 438 nm attributed to the formation of ZnO/CuO/rGO/PANINS and also a characteristic PANINS peak around 280 nm associated with the benzenoid π-π* transition [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. These two peaks are related to the π-π* transition of the conjugated polymer and the highest occupied energy level of the benzenoid ring to the lowest occupied energy level of the quinoid ring due to charge transfer excitation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The formation of ZnO/CuO/rGO/PANINS in acidic media shifts the absorption band of the benzenoid ring to the quinoid ring.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The spectra of the quaternary nanocomposites showed a broad elevated background in the visible region, mainly due to the presence of PANINS; increased absorbance of ZnO/CuO/rGO/PANINS nanocomposites compared to ZnO, ZnO/CuO, and ZnO/CuO/rGO was observed. The optical band gap energy of each synthesized material is Tauc.\u003c/p\u003e\u003cp\u003eαhυ\u0026thinsp;=\u0026thinsp;A(hυ - Eg)^(1/2) (1)\u003c/p\u003e\u003cp\u003ewhere α is the absorption coefficient, hυ is the photon energy, A is a proportionality constant that varies with the material, and n is the optical transition index of the semiconductor, where n is 1/2 for direct band gap semiconductors and 2 for indirect band gap semiconductors. Thus, the estimated band gaps of ZnO NPs, ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites are 3.1 eV, 2.75 eV, 2.68 eV, etc., respectively. It was also observed that the band gap of ZnO decreases when coupled with CuO, rGO, and PANINS.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.1.4. FTIR analysis\u003c/h2\u003e\u003cp\u003eFTIR spectra are used to identify the presence of functional groups and types of bonding in the synthesized samples. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the FTIR spectra of pure ZnO NPs, ZnO/CuO NCs, and ZnO/CuO/rGO nanocomposites in the range of 400-4,000 cm-\u0026sup1; The broad band observed between 3,400 and 3,500 cm-\u0026sup1; is due to stretching vibrations of O-H bonds on the sample surface The peak at 3,233 cm-\u0026sup1; indicates the presence of N-H stretching vibrations, and the band around 1,650 cm-\u0026sup1; is related to the O-H bending mode of adsorbed water molecules. Furthermore, the sharp FTIR band at 442 cm-\u0026sup1; corresponds to Zn-O bond vibrations, confirming the formation of ZnO nanoparticles (Tan et al.) In the case of ZnO/CuO nanocomposites, the bands at 488 cm-\u0026sup1; and 444 cm-\u0026sup1; correspond to Cu-O and Zn-O stretching vibration modes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The peak position of ZnO/CuO nanocomposite shifted between 700 and 400 cm-\u0026sup1; compared to the pure material, indicating the interaction between Zn and Cu ions, confirming the formation of metal oxide nanocomposites. FTIR of ZnO/CuO/rGO nanohybrid spectrum, a peak at 435 cm-\u0026sup1; was observed, indicating metal oxide bonding in the ZnO/CuO nanocomposite, with a decrease in the intensity of oxygenated groups and a blue shift compared to ZnO/CuO, confirming that the nanomaterial is strongly bonded to rGO. ([\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]).The peak of rGO at 1,635 cm⁻\u0026sup1; corresponds to the sp\u0026sup2; hybridization of carbons.\u003c/p\u003e\u003cp\u003eTo confirm the quality of ZnO/CuO/rGO/PANNS, the strong peak at 3440 cm-1 is attributed to N-H stretching; the prominent peaks observed at 1350, 1486, and 1580 cm-1 are due to C-N stretching vibrations, -C\u0026thinsp;=\u0026thinsp;C stretching vibrations in the benzenoid ring, and -C\u0026thinsp;=\u0026thinsp;C stretching vibrations in the quinoid ring, respectively corresponds to In addition, the peak at 796 cm-1 is attributed to C-Cl stretching, indicating the presence of emeraldine salts; the rGO peak at 1635 cm-1 corresponds to sp2 hybridization of carbon, which shifts to 433 cm-1, indicating the formation of metal oxide nanocomposites and incorporation of CuO within ZnO nanoparticles. For ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANNS nanocomposites, peaks around 440 cm-1, 435 cm-1, and 433 cm-1 were observed, respectively. These shifts are due to the insertion of CuO, rGO, and PANNS. The slight changes in the FTIR band shifts observed in each spectrum are due to differences in the composition of the synthesized nanocomposites [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Electrochemical Characterization\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1. Electrochemical Oxidation of Glucose on Modified Electrode\u003c/h2\u003e\u003cp\u003eGlucose is the most common electro active bio compound and is readily oxidized, making it the basis for electrochemical measurements. In this study, cyclic voltammetry was used to electrochemically oxidize 2 mM glucose on ZnO/CuO/rGO/PANINS/GCE. In addition, the oxidation of glucose on GCE modified with ZnO/CuO, ZnO/CuO/rGO, and ZnO/CuO/rGO/PANINS nanocomposites was investigated in 0.1 M NaOH solution, both in the absence and in presence of glucose. This was accomplished by cyclic voltammetry at a scan rate of 50 mV/sec within a potential window of 0.4 V to 1 V. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows cyclic voltammograms of glucose on modified GCE with and without 2 mM glucose in 0.1 M NaOH solution. The voltammogram Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea obtained on bare GCE shows no significant redox behaviour in the absence or presence of glucose, which indicates the lack of electro catalytic activity of bare GCE. However, electrodes modified with ZnO/CuO/GCE, ZnO/CuO/rGO/GCE, and ZnO/CuO/rGO/PANINS/GCE (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea-d) showed high peak currents at potentials of +\u0026thinsp;0.8 V, +\u0026thinsp;0.67 V, and +\u0026thinsp;0.6 V, respectively [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. ZnO/CuO/rGO/GCE exhibited a larger peak current than ZnO/CuO-modified GCE at the same scan rate. This is due to the larger specific surface area, faster electron transfer rate, and lower charge transfer resistance of rGO. rGO facilitates the glucose oxidation process by providing uniformly distributed catalytic sites that accelerate the electro catalytic activity of the ZnO/CuO metal oxide nanocomposite [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. ZnO is one of the most attractive functional semiconductor materials that can be used as an effective mechanical support and electron conduction pathway due to its strong electron transfer capability and mechanical flexibility [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. ZnO acts as a good mechanical support and enhances the intrinsic properties of p-type CuO. P-n junction formation in the ZnO-CuO heterostructure provides fast electron transfer capability and causes increased sensitivity. In addition, cationic polymers increase the electrostatic interaction between the heterostructure and the CuO surface, facilitating the attraction of glucose molecules [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(e), the anodic peak currents of electrodes modified with ZnO/CuO/rGO/PANINS were higher than those of ZnO/CuO/rGO and ZnO/CuO modified GCE, respectively. This is because PANINS exhibit better properties that help expose more active sites, increase stability, and improve electro catalytic activity performance. Incorporation of these layers into ZnO/CuO/rGO improves catalytic activity in glucose oxidation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2. Effect of Scan Rate on the Electrochemical Oxidation of Glucose\u003c/h2\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;19, the effect of scan rate on the oxidation of glucose in 0.1 M NaOH solution containing 2 mM glucose on a ZnO/CuO/rGO/PANINS electrode was examined using cyclic voltammetry at various scan rates from 10 to 100 mV/s. The voltammogram curves show that the peak potential shifts toward more positive values as the scan rate increases. The thickness of the diffusion layer depends mainly on the scan rate; the slower the scan rate, the thicker the diffusion layer. However, as the scan rate increases, the thickness of the diffusion layer decreases and the variable flux at the electrode surface decreases significantly. Plotting peak current (ipa) against the square root of current density shows a proportional relationship with the square root of scan rate (υ^1/2). Linear correlations with regression coefficients exceeding 0.99 were obtained at the electrodes, indicating that diffusion effects primarily affect the charge transport mechanism.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3. Optimization of Experimental Conditions\u003c/h2\u003e\u003cp\u003eThe effect of NaOH concentration on amperometric readings for 2 mM glucose detection was investigated. Various concentrations of sodium hydroxide (NaOH) solutions were used to determine the optimal electrolyte concentration. Because hydroxide anion groups are involved in the catalytic process of glucose, the number of hydroxide ions in the electrolytic cell has a significant effect on the electro catalytic oxidation of glucose. In this study, the effect of NaOH concentration on the performance of electrodes designed for glucose detection was investigated through CV experiments with varying NaOH concentrations. Figure\u0026nbsp;20 shows the synthesis and characterization of ZnO/CuO/rGO/PANINS nanocomposites for non-enzymatic electrochemical glucose sensor, and shows that the peak current in the CV graph increases when the NaOH concentration is varied from 0.005 M to 0.1 M. However, further increasing the NaOH concentration decreases the peak current of the CV graph. As a result, the concentration of sodium hydroxide for glucose detection using the developed electrode is 0.1 M [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe effect of pH on the electrochemical response of ZnO/CuO/rGO/PANINS/GCE for glucose sensing was evaluated using cyclic voltammetry in the range of pH 9\u0026ndash;14, as depicted in the figure. It appears that no text has been provided to paraphrase. Please share the text! The supporting electrolyte used was a 0.1 M NaOH solution, the pH of which greatly affects the electrochemical properties of glucose. Various NaOH solutions with pH of 9, 10, 11, 12, 13, and 14 were carefully prepared. Cyclic voltammetry (CV) curves for pH 9 and 10 showed no cathodic or anodic peaks were not shown. However, the CV curve at pH 13 showed significantly higher intensity than the others due to the moderate involvement of OH ions, which promoted a faster electro oxidation process. Conversely, the peak current decreased at pH 14, possibly due to the increased involvement of OH- ions, which inhibited the electro oxidation reaction between the modified ZnO/CuO/rGO/PANINS/GCE electrode and glucose. In Fig.\u0026nbsp;21, it is clear that the peak current at pH 13 exceeds the other pH levels. Therefore, pH 13 was selected for the sodium hydroxide solution used for glucose oxidation by the electrode (Baghayeri et al.)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe amperometric response of ZnO/CuO/rGO/PANINS modified GCE was performed to evaluate the current response to glucose. In this study, the optimal potential for amperometric detection of the electrode was investigated in the potential range of 0.45 to 0.65 V. As shown in Fig.\u0026nbsp;22, the anodic current response increased rapidly from 0.45 to 0.6 V, and the amperometric current response to glucose decreased as the applied potential was increased to +\u0026thinsp;0.65 V. The highest sensitivity was observed at an operating potential of 0.6 V. Therefore, 0.6 V was chosen as the operating potential for subsequent experiments. At lower detection potentials, the effect of easily oxidized chemical species was greatly reduced (Toghill\u0026amp; Compton, 2010).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3. Glucose Detection via Amperometry\u003c/h2\u003e\u003cp\u003eElectro catalytic oxidation of glucose in ZnO/CuO/rGO/PANINS/GCE was studied using amperometry. Glucose standards were added sequentially to 10 mL of 0.1 M NaOH in a continuously stirred solution, the applied potential was set at +\u0026thinsp;0.6 V, and the glucose concentration was varied from 2 to 10 mM. Figure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA shows the amperometric response of the current over time from 2 mM to 10 mM in 0.1 M NaOH solution. After the continuous addition of glucose, modified ZnO/CuO/rGO/PANINS/GCE showed an increase in amperometric current response in relation to glucose concentration. After glucose addition, the time required to achieve 90% of steady-state current was less than 3 seconds, indicating rapid and sensitive glucose oxidation on ZnO/CuO/rGO/PANINS/GCE. The shape of the current-time step curve depends mainly on the glucose concentration in the electrolyte solution. Figure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB shows the calibration graph for ZnO/CuO/rGO/PANINS/GCE, where the slope of the calibration graph determined the glucose concentration versus current and sensitivity \u0026micro;AmM-1 cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e divided by the surface area of the working electrode along with the active surface area of the electrode (equations are given below). The graph showed improved linearity between 2 and 10 mM, with the following significant sensitivities, 5660 \u0026micro;A mM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eCm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, with a limit of detection (LOD) of 0.00054 \u0026micro;M (S/N\u0026thinsp;=\u0026thinsp;3). The minimum detection threshold for glucose, along with its sensitivity and linear range, were analyzed in relation to the current literature, as shown in Table\u0026nbsp;4 PANINS showed strong catalytic activity, and integration of these membranes into ZnO/CuO/rGO improved catalytic activity and LOD during glucose oxidation ZnO/CuO/ The extensive surface area of rGO/PANINS/GCE contributes to the formation of additional active sites for electro catalytic activity. This indicates that our ZnO/CuO/rGO/PANINS/GCE can serve as an effective and sustainable non-enzymatic glucose sensor.\u003c/p\u003e\u003cp\u003eActive surface area\u0026thinsp;=\u0026thinsp;Ip / (2.69 x 10^5 x n^ (2/3) x D^ (1/2) x ϑ^ (1/2) x C)\u003c/p\u003e\u003cp\u003ewhere Ip is the maximum current, C is the overall glucose solution concentration, n is the number of electrons transferred, D is the diffusion coefficient (1.8 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), and ϑ is the scan rate. The active surface areas of the bare electrode and ZnO/CuO/rGO/PANINS/GCE were calculated to be 0.001 cm2 and 0.199 cm\u003csup\u003e2\u003c/sup\u003e, respectively, measured at 50 mVs\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in a 0.1 M NaOH solution containing 2 mM glucose concentration.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of the analytical performance of the ZnO/CuO/rGO/PANINS sensor with other recently published non-enzymatic glucose sensors.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensing substrate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElectrode\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eE(V)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003cp\u003e\u0026micro;AmMcm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLinear range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLOD\u003c/p\u003e\u003cp\u003e(\u0026micro;M)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNiO/PANI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e606.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1-100 \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCuO/PANI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFTO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25\u0026ndash;4.6 \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNiCo\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e@PANI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.55mAmM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003ecm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.015-4.735mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePANINS@RGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3448.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u0026ndash;4000 \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNiO/CuO/rGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u0026micro;M-4.85 mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNiO/Au/PANI/RGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09\u0026ndash;6mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO\u0026thinsp;\u0026minus;\u0026thinsp;CoO/rGO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168.7\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10-11.205mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTiO\u003csub\u003e2\u003c/sub\u003e-RGO-PANI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u0026ndash;180mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCuO/rGO/Cu\u003csub\u003e2\u003c/sub\u003eO/Cu\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3401.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5\u0026ndash;8.266\u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePANI/ZnO/MWCNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.8307AmM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003ecm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1-1mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNiO-NPs @PANINS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u0026ndash;10 mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZnO/CuO/rGO/PANINS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u0026ndash;10 mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThis work\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e3.2.4. Analysis of Interference\u003c/h2\u003e\u003cp\u003eThe ability to prevent interference was extremely important for the sensor. The main problem with non-enzymatic sensors is interference from various organic compounds in the blood. These compounds have the potential to oxidize at a similar potential to glucose. Uric acid (UA), ascorbic acid (AA), maltose, sucrose, and dopamine in physiological fluids significantly interfere with the direct electrochemical oxidation of glucose on various electrodes, especially in non-enzymatic sensors. In this analysis, interference tests involving 2 mM glucose and 0.1 mM interfering substance were evaluated at a potential of 0.6 V in 0.1 M NaOH to investigate the selectivity of ZnO/CuO/rGO/PANINS/GCE electrodes. The sensor response shows no clear amperometric signal for uric acid (UA), ascorbic acid (AA), or dopamine. It showed no clear effect on glucose and great selectivity for typical interfering substances. Furthermore, the addition of maltose and sucrose caused only minor changes in the observed currents. However, when 1 mM glucose was added, the observed currents responded. The results for glucose were several times greater than those for maltose and sucrose, suggesting that the effect may not be significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e3.2.4. Stability, Reproducibility, and Repeatability of ZnO/CuO/rGO/PANINS Sensor\u003c/h2\u003e\u003cp\u003eThe stability of ZnO/CuO/rGO/PANINS-modified GCE was evaluated by monitoring the current response to 2.0 mM glucose over a 10-day period; ZnO/CuO/rGO/PANINS-modified GCE was exposed to air and its current response was evaluated every 2 days. The sensor showed strong stability, maintaining 89.5% of its original response after 10 days of storage. To verify the reproducibility of the proposed method, the relative standard deviation (RSD) of six consecutive measurements of the peak current of 2 mM glucose at the ZnO/CuO/rGO/PANINS/GCE modified electrode was 2.89%, indicating the robust reproducibility of the method. For reproducibility evaluation, the response currents of five ZnO/CuO/rGO/PANINS-modified GCEs fabricated under identical conditions were compared; the RSD of the current response to 2 mM glucose was 4.2%, indicating adequate reproducibility between electrodes. These results confirm that ZnO/CuO/rGO/PANINS-modified GCE exhibits stability, excellent reproducibility, and repeatability.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e4.2.8 Analysis of Glucose in Actual Samples\u003c/h2\u003e\u003cp\u003eTo evaluate the efficacy of the ZnO/CuO/rGO/PANINS modified electrode, it was used to measure glucose levels in human serum samples. Using a commercially available spectrophotometer, the glucose level in a diabetic blood sample was measured in triplicate to be 125 mg/dL (6.937 mM). As shown in the figure, 0.5 mL of serum sample was mixed with 10 mL of 0.1 M NaOH solution. The amperometric i-t method was performed before and after glucose was added to the blood sample at a voltage of 0.6 V to evaluate the current response using the standard addition method. Glucose measurements were made using diluted samples, and recovery tests of standard glucose solutions (2, 4, and 6 mM) were performed in parallel with diluted human blood samples within the linear operating range. Results obtained from the improved electrode were comparable to those obtained from spectrophotometry and additional values in the clinical diagnostic laboratory. The glucose levels obtained from the calibration curve using this improved electrode closely matched those obtained from spectrophotometry in the clinical diagnostic laboratory, with only a 1.7% discrepancy, as shown in Table\u0026nbsp;5 The RSD ranged from 2.62\u0026ndash;3.85%, and the recovery of glucose from the standard addition to serum samples ranged from 100.55\u0026ndash;102.65%. This indicates that the proposed modified electrode can effectively measure glucose in real samples.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWorking condition and Amperometric determination of glucose spiked in human blood samples (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConcentration of Original Blood Sample (mM)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlucose added(mM)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGlucose Detected (mM)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRSD (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRecovery (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e6.937mM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e102.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e101.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn conclusion, this study successfully developed a non-enzymatic electrochemical glucose sensor utilizing synthesized ZnO/CuO/rGO/PANINS nanocomposites. The structural and optical properties of the synthesized nanocomposites were systematically characterized using advanced techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and ultraviolet-visible spectroscopy (UV-Vis), affirming their composite nature and confirming the effective integration of materials. The cyclic voltammetry (CV) results demonstrated a significant enhancement in electrochemical activity with the incorporation of PANINS into the ZnO/CuO/rGO framework, resulting in improved electrical performance characterized by higher current responses, increased exposed surface area, and accelerated electron transfer rates. These features collectively facilitated efficient glucose oxidation during Amperometric tests. The ZnO/CuO/rGO/PANINS/glassy carbon electrode (GCE) exhibited remarkable catalytic activity, demonstrating high stability, selectivity, sensitivity, and reproducibility, thereby positioning it as a superior alternative to previously reported non-enzymatic glucose sensors. This work not only adds to the existing body of knowledge on electrochemical sensors but also presents a promising approach for the development of advanced glucose monitoring devices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval:\u003c/strong\u003e\u003cp\u003e The study received ethical approval from the Kotebe University of Education Research Ethics Review committee, in accordance with the Ethiopia National Research Ethics Review Guideline (Fifth Edition).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDeclaration of consent\u003c/strong\u003e\u003cp\u003e Written informed consent was obtained from all participants who took part in the study, after explaining the purpose and significance of the research. Data collection proceeded only after obtaining fully informed verbal consent from the participants, and confidentiality measures were implemented to protect their privacy by excluding their names and personal identification information.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003cp\u003eThe authors declare that no external funding was received for the conduct of this study.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDessalew Berihun Adam: conceptualization to final analysis\u003c/p\u003e\u003ch2\u003eData availability statement:\u003c/h2\u003e\u003cp\u003eThe Data Availability statement of this manuscript, indicating that data can be requested from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlemu, H., W. Hailu, and A. Adane, \u003cem\u003ePrevalence of chronic kidney disease and associated factors among patients with diabetes in northwest Ethiopia: a hospital-based cross-sectional study\u003c/em\u003e. Current Therapeutic Research, 2020. 92: p. 100578.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaghelani, M., et al., \u003cem\u003eNon-invasive continuous-time glucose monitoring system using a chipless printable sensor based on split ring microwave resonators\u003c/em\u003e. Scientific Reports, 2020. 10(1): p. 12980.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganization, W.H., \u003cem\u003eGlobal diffusion of eHealth: making universal health coverage achievable: report of the third global survey on eHealth\u003c/em\u003e. 2017: World Health Organization.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoy, A., et al., \u003cem\u003eElectroless deposition of Pd nanostructures for multifunctional applications as surface-enhanced Raman scattering substrates and electrochemical nonenzymatic sensors\u003c/em\u003e. ACS Applied Nano Materials, 2019. 2(4): p. 2503\u0026ndash;2514.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeymourian, H., A. Barfidokht, and J. Wang, \u003cem\u003eElectrochemical glucose sensors in diabetes management: an updated review (2010\u0026ndash;2020)\u003c/em\u003e. Chemical Society Reviews, 2020. 49(21): p. 7671\u0026ndash;7709.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, G., et al., \u003cem\u003eLow-cost voltammetric sensors for robust determination of toxic Cd (II) and Pb (II) in environment and food based on shuttle-like α-Fe2O3 nanoparticles decorated β-Bi2O3 microspheres\u003c/em\u003e. Microchemical Journal, 2022. 179: p. 107515.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKailasa, S., et al., \u003cem\u003eHigh sensitive polyaniline nanosheets (PANINS)@ rGO as non-enzymatic glucose sensor\u003c/em\u003e. Journal of Materials Science: Materials in Electronics, 2020. 31: p. 2926\u0026ndash;2937.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZimmet, P., et al., \u003cem\u003eDiabetes mellitus statistics on prevalence and mortality: facts and fallacies\u003c/em\u003e. Nature Reviews Endocrinology, 2016. 12(10): p. 616\u0026ndash;622.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMao, Q., et al., \u003cem\u003eDepositing reduced graphene oxide on ZnO nanorods to improve the performance of enzymatic glucose sensors\u003c/em\u003e. Materials Science in Semiconductor Processing, 2021. 121: p. 105391.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark, S.P., et al., \u003cem\u003eGlucose-based resistive random access memory for transient electronics\u003c/em\u003e. Journal of Information Display, 2019. 20(4): p. 231\u0026ndash;237.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeshmukh, M.A., B.-C. Kang, and T.-J. Ha, \u003cem\u003eNon-enzymatic electrochemical glucose sensors based on polyaniline/reduced-graphene-oxide nanocomposites functionalized with silver nanoparticles\u003c/em\u003e. Journal of Materials Chemistry C, 2020. 8(15): p. 5112\u0026ndash;5123.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, C., et al., \u003cem\u003eScreen-printing preparation of high-performance nonenzymatic glucose sensors based on Co3O4 nanoparticles-embedded N-doped laser-induced graphene\u003c/em\u003e. ACS Applied Nano Materials, 2022. 5(11): p. 16655\u0026ndash;16663.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, E., et al., \u003cem\u003ePorous Co3O4 hollow nanododecahedra for nonenzymatic glucose biosensor and biofuel cell\u003c/em\u003e. Biosensors and Bioelectronics, 2016. 81: p. 46\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun, K.G. and S.H. Hur, \u003cem\u003eHighly sensitive non-enzymatic glucose sensor based on Pt nanoparticle decorated graphene oxide hydrogel\u003c/em\u003e. Sensors and Actuators B: Chemical, 2015. 210: p. 618\u0026ndash;623.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, H., et al., \u003cem\u003eThree-dimensional porous NiO nanosheets vertically grown on graphite disks for enhanced performance non-enzymatic glucose sensor\u003c/em\u003e. Electrochimica Acta, 2015. 174: p. 745\u0026ndash;752.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReitz, E., et al., \u003cem\u003eCuO nanospheres based nonenzymatic glucose sensor\u003c/em\u003e. Electroanalysis: An International Journal Devoted to Fundamental and Practical Aspects of Electroanalysis, 2008. 20(22): p. 2482\u0026ndash;2486.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, G., et al., \u003cem\u003eEnzyme-free amperometric sensing of glucose using Cu-CuO nanowire composites\u003c/em\u003e. Microchimica Acta, 2010. 168: p. 87\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZheng, B., et al., \u003cem\u003eA sensitive AgNPs/CuO nanofibers non-enzymatic glucose sensor based on electrospinning technology\u003c/em\u003e. Sensors and Actuators B: Chemical, 2014. 195: p. 431\u0026ndash;438.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCai, B., et al., \u003cem\u003eSynthesis of ZnO\u0026ndash;CuO porous core\u0026ndash;shell spheres and their application for non-enzymatic glucose sensor\u003c/em\u003e. Applied physics A, 2015. 118: p. 989\u0026ndash;996.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaruppiah, C., et al., \u003cem\u003eA simple hydrothermal synthesis and fabrication of zinc oxide\u0026ndash;copper oxide heterostructure for the sensitive determination of nonenzymatic glucose biosensor\u003c/em\u003e. Sensors and Actuators B: Chemical, 2015. 221: p. 1299\u0026ndash;1306.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFang, L., et al., \u003cem\u003e3D porous structured polyaniline/reduced graphene oxide/copper oxide decorated electrode for high performance nonenzymatic glucose detection\u003c/em\u003e. Journal of Electroanalytical Chemistry, 2019. 841: p. 1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhanbari, K. and Z. Babaei, \u003cem\u003eFabrication and characterization of non-enzymatic glucose sensor based on ternary NiO/CuO/polyaniline nanocomposite\u003c/em\u003e. Analytical biochemistry, 2016. 498: p. 37\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzharudeen, A.M., et al., \u003cem\u003eFabrication, characterization of polyaniline intercalated NiO nanocomposites and application in the development of non-enzymatic glucose biosensor\u003c/em\u003e. Arabian Journal of Chemistry, 2020. 13(2): p. 4053\u0026ndash;4064.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoy, I., et al., \u003cem\u003eSynthesis and characterization of graphene from waste dry cell battery for electronic applications\u003c/em\u003e. RSC advances, 2016. 6(13): p. 10557\u0026ndash;10564.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamachandran, R., et al., \u003cem\u003eSynthesis of graphene platelets by chemical and electrochemical route\u003c/em\u003e. Materials Research Bulletin, 2013. 48(10): p. 3834\u0026ndash;3842.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalahuddin, N.A., M. El-Kemary, and E.M. Ibrahim, \u003cem\u003eSynthesis and characterization of ZnO nanoparticles via precipitation method: effect of annealing temperature on particle size\u003c/em\u003e. Nanosci. Nanotechnol, 2015. 5(4): p. 82\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShinde, R.S., et al., \u003cem\u003eSynthesis and characterization of ZnO/CuO nanocomposites as an effective photocatalyst and gas sensor for environmental remediation\u003c/em\u003e. Journal of Inorganic and Organometallic Polymers and Materials, 2022: p. 1\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYousaf, S., et al., \u003cem\u003eHierarchically porous CuO microspheres and their r-GO based nanohybrids for electrochemical supercapacitors applications\u003c/em\u003e. Journal of Materials Research and Technology, 2020. 9(6): p. 14158\u0026ndash;14167.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHussein, B.A., et al., \u003cem\u003eA sensitive non-enzymatic electrochemical glucose sensor based on a ZnO/Co 3 O 4/reduced graphene oxide nanocomposite\u003c/em\u003e. Sensors \u0026amp; Diagnostics, 2023. 2(2): p. 347\u0026ndash;360.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKailasa, S., et al., \u003cem\u003eNiO nanoparticles -decorated conductive polyaniline nanosheets for amperometric glucose biosensor\u003c/em\u003e. Materials Chemistry and Physics, 2020. 242: p. 122524.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHabte, A.T. and D.W. Ayele, \u003cem\u003eSynthesis and characterization of reduced graphene oxide (rGO) started from graphene oxide (GO) using the tour method with different parameters\u003c/em\u003e. Advances in Materials Science and Engineering, 2019. 2019(1): p. 5058163.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBasavegowda, N., et al., \u003cem\u003eBimetallic p-ZnO/n-CuO nanocomposite synthesized using Aegle marmelos leaf extract exhibits excellent visible-light-driven photocatalytic removal of 4-nitroaniline and methyl orange\u003c/em\u003e. Photochemical \u0026amp; Photobiological Sciences, 2022. 21(8): p. 1357\u0026ndash;1370.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeena, P.L., et al., \u003cem\u003eFacile synthesis of ZnO/CuO/Ag2O ternary metal oxide nanocomposite for effective photodegradation of organic water pollutants\u003c/em\u003e. Water Science and Technology, 2021. 84(9): p. 2615\u0026ndash;2634.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTantubay, K., P. Das, and M.B. Sen, \u003cem\u003eTernary reduced graphene oxide\u0026ndash;CuO/ZnO nanocomposite as a recyclable catalyst with enhanced reducing capability\u003c/em\u003e. Journal of Environmental Chemical Engineering, 2020. 8(4): p. 103818.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTovide, O., et al., \u003cem\u003eGraphenated polyaniline-doped tungsten oxide nanocomposite sensor for real time determination of phenanthrene\u003c/em\u003e. Electrochimica Acta, 2014. 128: p. 138\u0026ndash;148.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAghaei, M., S. Sajjadi, and A.H. Keihan, \u003cem\u003eSono-coprecipitation synthesis of ZnO/CuO nanophotocatalyst for removal of parathion from wastewater\u003c/em\u003e. Environmental Science and Pollution Research, 2020. 27: p. 11541\u0026ndash;11553.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnand, V.K., et al., \u003cem\u003eHighly sensitive and reusable Cu\u0026thinsp;+\u0026thinsp;2/polyaniline/reduced graphene oxide nanocomposite ink-based non-enzymatic glucose sensor\u003c/em\u003e. Applied Physics A, 2020. 126: p. 1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHassan, M.H., et al., \u003cem\u003eRecent advances in enzymatic and non-enzymatic electrochemical glucose sensing\u003c/em\u003e. Sensors, 2021. 21(14): p. 4672.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBano, S., et al., \u003cem\u003eThe non-enzymatic electrochemical detection of glucose and ammonia using ternary biopolymer based-nanocomposites\u003c/em\u003e. New Journal of Chemistry, 2021. 45(18): p. 8008\u0026ndash;8021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlizadeh, T. and S. Mirzagholipur, \u003cem\u003eA Nafion-free non-enzymatic amperometric glucose sensor based on copper oxide nanoparticles\u0026ndash;graphene nanocomposite\u003c/em\u003e. Sensors and Actuators B: Chemical, 2014. 198: p. 438\u0026ndash;447.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsmaeeli, A., et al., \u003cem\u003eCopper oxide-polyaniline nanofiber modified fluorine doped tin oxide (FTO) electrode as non-enzymatic glucose sensor\u003c/em\u003e. Sensors and Actuators B: Chemical, 2018. 266: p. 294\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu, Z., et al., \u003cem\u003eFacile synthesis of NiCo2O4@ Polyaniline core\u0026ndash;shell nanocomposite for sensitive determination of glucose\u003c/em\u003e. Biosensors and Bioelectronics, 2016. 75: p. 161\u0026ndash;165.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, S.-J., et al., \u003cem\u003eFacile synthesis of NiO/CuO/reduced graphene oxide nanocomposites for use in enzyme-free glucose sensing\u003c/em\u003e. International Journal of Electrochemical Science, 2016. 11(8): p. 6747\u0026ndash;6760.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, M., et al., \u003cem\u003eFabrication of a novel ZnO\u0026ndash;CoO/rGO nanocomposite for nonenzymatic detection of glucose and hydrogen peroxide\u003c/em\u003e. Ceramics International, 2018. 44(5): p. 5250\u0026ndash;5256.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDu, J., et al., \u003cem\u003eTitanium dioxide\u0026ndash;graphene\u0026ndash;polyaniline hybrid for nonenzymatic detection of glucose\u003c/em\u003e. Nano, 2019. 14(07): p. 1950093.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao, C., et al., \u003cem\u003eHydrothermal deposition of CuO/rGO/Cu 2 O nanocomposite on copper foil for sensitive nonenzymatic voltammetric determination of glucose and hydrogen peroxide\u003c/em\u003e. Microchimica Acta, 2017. 184: p. 2341\u0026ndash;2348.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohajeri, S., A. Dolati, and K. Yazdanbakhsh, \u003cem\u003eSynthesis and characterization of a novel non-enzymatic glucose biosensor based on polyaniline/zinc oxide/multi-walled carbon nanotube ternary nanocomposite\u003c/em\u003e. Journal of Electrochemical Science and Engineering, 2019. 9(3): p. 207\u0026ndash;222.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKailasa, S., et al., \u003cem\u003eNiO nanoparticles-decorated conductive polyaniline nanosheets for amperometric glucose biosensor\u003c/em\u003e. Materials Chemistry and Physics, 2020. 242: p. 122524.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Nanocomposite, Electrochemical glucose sensor, Sensitivity, Cyclic voltammetry, Stability, Reproducibility, Non-enzymatic detection","lastPublishedDoi":"10.21203/rs.3.rs-7148554/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7148554/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA novel Nanocomposite electrode composed of zinc oxide (ZnO), copper oxide (CuO), reduced graphene oxide (rGO), and poly(acrylonitrile-co-acrylic acid) (PANINS), denoted as ZnO/CuO/rGO/PANINS, was synthesized via a one-step in situ polymerization strategy for non-enzymatic glucose detection. The PANINS polymer was uniformly coated onto the ZnO/CuO/rGO framework, enhancing the structural integrity and conductivity of the resulting electrode. Structural and physicochemical characterizations were conducted using UV-visible spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) to evaluate the optical properties, functional groups, and crystallinity of the synthesized Nanocomposite.\u003c/p\u003e\n\u003cp\u003eElectrochemical performance was assessed using cyclic voltammetry (CV) and amperometry in 0.1 M NaOH electrolyte. The modified glassy carbon electrode (GCE) exhibited significantly enhanced current responses compared to unmodified and non-PANINS-modified counterparts, attributed to the synergistic catalytic activity of the Nanocomposite components. The active surface area increased from 0.001 cm² (bare GCE) to 0.199 cm² (ZnO/CuO/rGO/PANINS-modified GCE). The sensor demonstrated a lower onset potential and higher peak current for glucose oxidation, indicating improved electro catalytic activity.\u003c/p\u003e\n\u003cp\u003eAmperometric analysis revealed a linear detection range of 2-10 mM glucose, with a high sensitivity of 5660 μA mM\u003csup\u003e-\u003c/sup\u003e¹ cm\u003csup\u003e-\u003c/sup\u003e², a low detection limit of 0.00054 μM, and a rapid response time of 3 seconds. The sensor also exhibited excellent selectivity toward glucose in the presence of common interfering species, along with good reproducibility (RSD = 2.89 %), repeatability (RSD = 4.2 %), and long-term stability, retaining 89.5 % of its initial current response after 10 days. The sensor’s applicability was validated in real blood samples, showing strong correlation with standard spectrophotometric methods. These results suggest that the ZnO/CuO/rGO/PANINS Nanocomposite is a promising platform for the development of high-performance, non-enzymatic electrochemical glucose sensors.\u003c/p\u003e","manuscriptTitle":"Facile Fabrication of a Nanocomposite Electrode for Enhanced Electrochemical Performance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 11:03:12","doi":"10.21203/rs.3.rs-7148554/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17f7b09a-5761-4f39-9c1f-87427a85f68c","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-26T05:39:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 11:03:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7148554","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7148554","identity":"rs-7148554","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}