Electrochemical Glucose Detection Using Ag@MoS₂/Graphene Oxide Aerogel Nanocomposite: A Study on Sensitivity, Stability, and Selectivity

Electrochemical Glucose Detection Using Ag@MoS₂/Graphene Oxide Aerogel Nanocomposite: A Study on Sensitivity, Stability, and Selectivity | 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 Article Electrochemical Glucose Detection Using Ag@MoS₂/Graphene Oxide Aerogel Nanocomposite: A Study on Sensitivity, Stability, and Selectivity Haniyeh Shahba, Fatemeh Davar, Navid Nejatbakhsh, Esmaeil Heydari-Bafrooei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6292994/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract In this study, a Ag@MoS₂/graphene oxide aerogel (GOA) nanocomposite was synthesized and used to fabricate a non-enzymatic glucose sensor. The sensor exhibited a wide linear range (1.0 to 10.0 mM), high sensitivity (546.37 nA mM⁻¹ cm⁻²), and a low detection limit (53.29 µM). The sensor's performance was significantly enhanced in an alkaline environment due to the presence of hydroxide ions, which facilitated glucose oxidation. The sensor also demonstrated excellent selectivity against common interferents and maintained high stability over 30 days. The synergistic effects of AgNPs, MoS₂ nanosheets, and GOA contributed to the sensor's superior electrochemical performance, making it a promising candidate for glucose sensing applications. Physical sciences/Chemistry/Biochemistry Physical sciences/Chemistry/Inorganic chemistry Electrochemical detection Molybdenum disulfide Graphene oxide aerogel glucose Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction The majority of bodily tissues rely on glucose (C 6 H 12 O 6 ), a significant monosaccharide, as their primary energy source. The efficient distribution of glucose in the human body depends on the requirements of specific organs [ 1 – 3 ]. Although sugars are the primary source of energy for humans, excessive consumption can lead to various ailments, which represent significant global health concerns [ 4 – 6 ]. According to research, the normal range for blood glucose levels in non-diabetic individuals is between 4.90 and 6.90 mM [ 7 , 8 ]. A person is diagnosed with diabetes when their blood glucose concentration rises above normal levels [ 9 , 10 ]. The increasing global prevalence of diabetes, which poses serious health risks and financial burdens, has significantly increased the demand for precise and effective glucose sensing in recent years [ 11 – 13 ]. For diabetes monitoring, particularly in critical contexts such as dietary intake and fermentation processes, glucose detection is crucial. Despite numerous advancements in this field, glucose detection technology continues to evolve. The pioneering research by Clark and Lyon in 1962 led to the invention of the first glucose sensor. These electrochemical sensors are known as the first generation of blood glucose sensors [ 14 , 15 ]. Electrochemical blood glucose detection sensors are primarily divided into two categories: enzymatic glucose detection sensors and non-enzymatic glucose detection sensors. Additionally, they are categorized into generations: first (the most common), second, third, and fourth-generation electrochemical glucose sensors. In the electrochemical glucose detection process, the catalyst plays a critical role. In the first to third generations, the enzyme glucose oxidase serves this function, thus classifying them as enzymatic electrocatalytic sensors. However, in the fourth generation, other catalysts are utilized [ 15 – 18 ]. Recent advances in electrochemical sensing have focused on developing a new generation of glucose sensors that completely eliminate the use of glucose oxidases and instead utilize various advanced catalysts for the direct electrochemical oxidation of glucose as biomimetic materials, including precious metal nanoparticles, metal sulfides/oxides, novel carbon-based materials, and inorganic-organic composites [ 13 , 19 – 24 ]. A non-enzymatic glucose sensor was developed by Yuan et al. using Cu 2 O/NiOx/spherical graphene oxide as matrix materials. By increasing the electrochemical active area through Cu 2 O and NiOx, the electrocatalytic activity is enhanced, demonstrating selectivity for glucose over other coexisting substances in human serum [ 25 ]. Molybdenum disulfide (MoS 2 ) typically has a band gap of 1.8 eV and offers a suitable surface area, low coefficient of friction, and superior physicochemical and catalytic characteristics [ 26 – 28 ]. Non-enzymatic biosensors utilizing MoS 2 nanosheets have been created; however, due to their low electrocatalytic activity toward glucose, such sensors perform inadequately. Therefore, efforts must focus on enhancing their biosensing performance [ 29 ]. Researchers have aimed to improve catalytic properties by focusing on the functional groups of the MoS 2 surface and combining it with polymers, carbonaceous materials, metal nanoparticles, as well as metal sulfides and oxides [ 30 – 33 ]. In this context, a non-enzymatic sensor based on CuS/MoS 2 bimetallic composites was prepared using a one-step hydrothermal process [ 34 ]. MoS2 nanosheets may be combined with noble metal nanoparticles such as Pt, Ag, Au, Ni, and Cu because noble metals exhibit greater electrocatalytic activity for glucose detection and oxidation [ 35 , 36 ]. Furthermore, rapid, heterogeneous electron transfer—which significantly boosts electrical conductivity—may result from the interaction between metal nanoparticles and MoS₂ [ 37 ]. Silver nanoparticles have been widely utilized for non-enzymatic detection of blood glucose due to their large surface area and excellent electrocatalytic activity [ 38 – 40 ]. For instance, Mehdi et al. used carbon nanotubes (CNT) and Ag NPs to create a non-enzymatic glucose sensor [ 41 ]. They demonstrated that the combination of Ag nanoparticles (NPs) and CNT increased the sensor’s long-term stability, sensitivity, and electrode conductivity. Another study investigated non-enzymatic glucose detection using AgNPs/MoS₂, fabricated via a hydrothermal process [ 29 ]. Graphene, graphene oxide, activated carbon, and carbon nanotubes are examples of carbon-based compounds that have garnered significant interest in recent scientific research. Carbon-based materials are excellent candidates for electrode modification due to their high electron transport, large electrochemical range, high specific surface area, and good chemical stability, making them useful for glucose sensing [ 42 , 43 ]. The highly porous structure of graphene oxide aerogel (GOA), composed of interconnected three-dimensional graphene oxide sheets (rich in oxygen-containing functional groups), has drawn interest due to its improved electrical conductivity, large specific surface area, and excellent mechanical strength. Its large pore volume facilitates rapid mass transfer of redox species, and its large specific surface area can provide numerous active sites for the sensor’s catalytic process [ 44 – 47 ]. Graphene possesses a sp 2 -conjugated structure, and the presence of oxygen-containing functional groups disrupts this structure, reducing the electrical conductivity of the material, thereby significantly hindering charge transfer [ 48 – 50 ]. These features make them a potentially broad and suitable platform for effective nanoparticle placement [ 51 ]. This study synthesized a ternary composite of silver nanoparticles, molybdenum disulfide nanosheets, and graphene oxide aerogel using a one-step hydrothermal method to serve as a non-enzymatic glucose sensing electrode. This non-enzymatic sensor, which exhibits catalytic properties and a large active surface area, demonstrated high performance in detecting glucose concentrations and shows potential for further development [ 29 ]. 2. Experimental 2.1. Chemical Reagents Silver nanopowder (Ag > 99.5%) from TitraChem, molybdenum disulfide nanopowder (MoS 2 > 99%) from 3302 Twig Leaf Lane, Houston, TX 77084, and glucose were purchased from Merck. Sodium hydroxide (NaOH) was obtained from Mojallali Company, pyrrole (Py) from Merck, and phosphate-buffered saline (PBS) was prepared by mixing stock solutions of NaCl, KCl, KH₂PO₄, and Na₂HPO₄, all of which were purchased from Mojallali Company. 2.2. Preparation of MoS₂ Suspensions 160 mg of MoS₂ nanopowder was dispersed in distilled water to achieve an initial mass concentration of 8 mg·mL⁻¹. The mixture was stirred at 80°C for 2 h. Afterward, the dispersion was placed in a water bath and sonicated for 4 h using an ultrasonic processor with a maximum power of 500 W and an amplitude of 20%. The sonication cycle consisted of 6-second “on” and 6-second “off” intervals. The temperature was maintained between 30°C and 50°C throughout the sonication process. A second method involved the use of a bath sonicator under similar conditions, with the temperature being controlled between 40°C and 50°C. Both methods were compared, and the results showed that both achieved acceptable efficacy. 2.3. Synthesis of AgNPs@MoS2/GOA The synthesis of Ag@MoS2/GOA was carried out by mixing 40 mL of MoS₂NSs suspension (2 mg/mL), AgNPs (8 mg/mL), and GO NSs (3.125 mg/mL). The mixture was sonicated for 1 hour. The resulting stable suspension was then transferred to a Teflon-lined autoclave and hydrothermally treated at 150°C for 5 h. The product was subsequently freeze-dried for 24 hours to obtain the final material. (See Scheme 1) 2.4. Preparation of the Ag@MoS 2 /GOA-Modified Electrode To prepare the Ag@MoS 2 /GOA-modified electrode, 10 mg of the prepared composite (1 mg/mL) was mixed with 80.1 mg of poly(styrene sulfonate) (PSS) and 70 µL of pyrrole (Py) in 10 mL of PBS. The mixture was sonicated for 1 hour to ensure the uniform distribution of the components within the solution. Pyrrole polymerization was carried out electrochemically, and a 5-µm thick composite layer was deposited onto tantalum (110 µm) and platinum (10 µm) electrodes. 2.5. Electrochemical Measurements of Ag@MoS 2 /GOA/W-AuE Electrochemical characterization was performed using cyclic voltammetry (CV) with Ag@MoS 2 /GOA/W-AuE as the working electrode, a platinum wire as the counter electrode, and an Ag/AgCl electrode as the reference electrode. Amperometric measurements were also conducted using a two-electrode system (working electrode and Ag/AgCl as the reference electrode). Glucose concentration detection was carried out by scanning the potential between − 0.4 V and 0.65 V at a scanning rate of 100 mV·s⁻¹, and amperometric measurements were performed at 500 mV in NaOH solution. 3. Results and discussion 3.1. Characterization of Ag@MoS 2 /GOA) nanocomposite 3.1.1. SEM, TEM, EDS and mapping characterization Figures 1a to 1f illustrate the morphology of AgNPs, GO, GOA, MoS₂/GOA, and Ag@MoS 2 /GOA), respectively, as characterized by field emission scanning electron microscopy (FE-SEM). Graphene oxide sheets (Figure 1a) were stacked and connected to create a three-dimensional aerogel structure (Figures 1b and 1c), as illustrated in Scheme 1. The Ag@MoS 2 /GOA) nanocomposite was also prepared through in situ hydrothermal synthesis. The TEM image in Figure 2 displays graphene oxide aerogel, MoS₂ nanosheets, and Ag nanoparticles. Figure 3 presents the elemental mapping and EDS analysis of the Ag@MoS 2 /GOA) nanocomposite. Figure 4a and 4b show images of the electrode wire before and after deposition, as well as FE-SEM images of the electrode surface. Additionally, Figure 4c–e shows the FE-SEM image of the electrode surface after deposition using the polymerization method. The composition of Ag@MoS 2 /GOA) was analyzed using energy-dispersive X-ray spectroscopy (EDS), which revealed that the atomic percentages of carbon, oxygen, molybdenum, and silver were 32.90%, 13.89%, 43.82%, and 10.60%, respectively. The percentage of sulfur is expected to be approximately twice that of molybdenum; however, since its peak overlaps with that of molybdenum, there is an error in the measurement. The results of the EDS mapping confirmed that AgNPs were embedded within the MoS 2 NSs and that the MoS₂NSs were distributed within the cavities of the GOA (Figure 3). The particle size of the silver nanoparticles was measured to be 70.41 nm. 3.1.2. X-ray diffraction characterization, FT-IR and Raman Figure 5a shows the XRD patterns of the samples. In this image, the orange curve corresponds to graphene oxide and exhibits a peak at 12.5°, originating from the (001) plane. The blue curve displays a broad peak at 2ϴ = 24°, which clearly indicates the formation of graphene oxide aerogel. The green curve shows the peaks for molybdenum disulfide nanosheets at angles of 58.5° and 33°, which are assigned to the (110) and (100) crystal planes, respectively. It also exhibits peaks at angles of 73°, 60.5°, 50°, 39°, 36°, 33.5°, and 14.5°, which correspond to the (203), (008), (105), (103), (102), (101), and (002) planes, respectively. These peaks are in good agreement with the hexagonal structure predicted by the JCPDS#01-073-1508 card [52]. The curve for the Ag@MoS 2 /GOA) composite also shows new peaks at angles of 77.5°, 64.5°, 44.5°, and 38°, in addition to the peaks related to GOA and MoS₂. These new peaks are attributed to the crystalline structure of silver nanoparticles, confirming the face-centered cubic (fcc) structure of silver nanoparticles (JCPDS#01-087-0720) [53]. As shown in Figure 5b, the orange, blue, green, purple, and pink curves correspond to the FT-IR spectra of graphene oxide (GO), graphene oxide aerogel (GOA), molybdenum disulfide (MoS₂) nanostructures, graphene oxide aerogel composited with MoS₂, and the Ag@MoS 2 /GOA) nanocomposite, respectively. For the nanocomposite spectrum, the intense peak located at 660 cm⁻¹ can be attributed to the Mo–S stretching vibration, while the band around 500 cm⁻¹ may be due to the S–S bond. The composite also exhibits a strong and broad O–H stretching vibration band at 3450 cm⁻¹, a carboxyl or carbonyl C=O stretching band at 1639 cm⁻¹, and an alkoxy O–C–O stretching vibration at 1105 cm⁻¹. The prominent peak at 1581 cm⁻¹ can be assigned to the carbon double bond [43, 54, 55]. Raman spectroscopy was used to study the carbon nanostructure. The Raman spectrum in Figure 5c clearly demonstrates the formation of graphene oxide aerogel and the presence of MoS₂ nanostructures in the pink curve, which corresponds to the Ag@MoS 2 NSs/GOA nanocomposite. The orange Raman spectrum represents graphene oxide, which has a D-to-G ratio of 0.84. This ratio increases to 1.004 for GOA in the blue, violet, and pink Raman spectra. In general, the I _D /I _G ratio quantifies the defects in the lattice and the disruption of conjugation. Similar to previous studies [56], the disorder and conjugation disruption increase with the formation of the aerogel. 3.2. Electrochemical characterization for non-enzymatic glucose detector 3.2.1. Cyclovoltammetry analysis Figure 6 presents a comparative analysis of the cyclic voltammetry (CV) curves for the base electrode and modified electrodes in the presence of glucose. The base electrode (W/Au) demonstrates the lowest current response, reflecting minimal electrochemical activity. This suggests a limited number of catalytic sites, making it an appropriate reference for evaluating subsequent modifications. The enhanced current response observed in the MoS₂-modified electrode can be attributed to its large surface area and electroactive properties. MoS₂ facilitates charge transport and promotes redox reactions, thereby improving glucose oxidation. In the MoS₂ + Ag-modified electrode, the further increase in current response indicates improved electrical conductivity and enhanced electrocatalytic activity toward glucose oxidation. Silver nanoparticles contribute to faster electron transfer kinetics due to their high electrical conductivity and intrinsic catalytic properties, providing additional active sites for glucose detection. The appearance of new peaks may correspond to silver oxidation/reduction processes involved in glucose electrooxidation. While MoS₂ enhances catalytic activity through its layered structure and active edges, silver nanoparticles serve as catalytic centers, further improving electron transfer and glucose sensitivity. The combination of MoS₂ and Ag exhibits a synergistic effect, maximizing the electrochemical response in the presence of glucose. The observed peak shifts and intensifications indicate enhanced electron transfer and improved glucose oxidation efficiency, confirming that each modification progressively enhances the electrode's performance for glucose sensing. Electrochemical analysis of Ag@MoS 2 /GOA/W-AuE was conducted to evaluate its electrocatalytic performance for glucose oxidation using cyclic voltammetry (CV) (Figure 7) and chronoamperometry (Figure 8). The results indicate excellent catalytic activity of the Ag@MoS 2 /GOA)/W-Au electrode. Comparing the CV results in PBS solution (pH 7.0) with those in a 1.0 M NaOH aqueous electrolyte solution shows that the current increase in NaOH solution is significantly greater than that in PBS solution. Therefore, electrochemical detection of glucose using a non-enzymatic method requires alkaline conditions, which were used for subsequent electrochemical measurements. It is expected that in non-enzymatic sensors, where glucose oxidase enzyme is absent, inorganic catalysts require hydroxide ions to detect glucose. As a result, the biosensor exhibits higher sensitivity in NaOH solution. In PBS solution, the hydroxide ions resulting from water dissociation are less abundant and do not contribute significantly to increasing sensitivity. The CV analysis of the Ag@MoS2/GOA/W-Au electrode was conducted to study the effect of increasing glucose concentration, as shown in Figures 6a and 6c for neutral and alkaline environments, respectively. The electrode was placed in a 1.0 M NaOH stock solution at a potential of 0.5 V, and the glucose concentration was gradually increased. The selection of the -0.04 V peak as the quantitative glucose detection signal, which is based on increasing glucose concentrations, was made possible by the positive scan. This scan revealed a significantly higher current at the -0.04 V peak compared to the 0.275 V peak (Figure 7c). As the analyte concentration increases, the number of species that lose electrons increases, leading to more electrons circulating in the circuit and a corresponding increase in the measured current [57]. Based on the results from Figure 7c, Figure 7d shows the calibration curve of the MoS₂ /Ag@GOA/Ta-Pt electrode for glucose detection. The sensitivity of the sensor was 2.1 × 10⁻³ nA mM⁻¹ cm⁻² (r² = 0.990) for glucose concentrations ranging from 0.0 to 30.0 mM (equivalent to 0 to 540 mg/dL), and the detection limit was 5.32 µM. Figure 7e shows the CV analysis results of the AgNPs@MoS 2 /GOA)/W-Au electrode at scan rates of 40–220 mV/s. As evident from Figure 7f, the peak current increases as the electrode scan rate increases. It is likely that silver nanoparticles are initially oxidized to AgOH and AgO species in the presence of hydroxide ions. This process creates favorable conditions for the oxidation of glucose, during which glucose releases electrons, resulting in current generation. Silver-based electrocatalysts exhibit a distinct mechanism in glucose oxidation compared to transition metals like Ni, Cu, and Co. Unlike these metals, which directly participate in glucose oxidation via the formation of stable metal-glucose complexes, silver acts primarily as an electron mediator rather than a direct catalytic site. The electrochemical oxidation of silver in an alkaline medium leads to the formation of AgO, which serves as an electron acceptor in the oxidation of glucose. This process differs fundamentally from Ni, Cu, and Co, where metal oxyhydroxides (e.g., NiOOH, CuOOH) directly oxidize glucose through redox cycling. The absence of strong metal-glucose interactions in silver-based systems reduces unwanted side reactions, contributing to higher stability and selectivity in non-enzymatic glucose sensing applications. This distinction makes silver a promising candidate for long-term electrochemical sensing, particularly in implantable and continuous monitoring devices [56, 57]. A) In PBS (without OH⁻): • Glucose oxidation (weaker): C 6 H 12 O 6 → C 6 H 12 O 7 + 2e− • Water hydrolysis: 2H 2 O → 2H 2 + O 2 • Silver-assisted electron transfer (same): Ag + e− → Ag+ B) In Alkaline Environment (OH⁻ present): • Glucose oxidation with OH⁻: C 6 H 12 O 6 + 2OH− → C 6 H 12 O 7 + 2e− + H 2 O • Silver-assisted electron transfer: Ag + e− → Ag+ Increased Electron Transfer in Alkaline Medium: In an alkaline medium, the presence of hydroxide ions (OH⁻) facilitates a more efficient oxidation of glucose. The oxidation reaction of glucose in an alkaline medium involves the direct interaction of glucose with OH⁻ ions, which significantly increases the rate of the reaction. As a result, more electrons are released during the glucose oxidation process, leading to a higher current. Role of Hydroxide Ions (OH ⁻ ): In alkaline solutions, OH⁻ ions play a critical role in enhancing the rate of glucose oxidation by providing additional reaction sites on the electrode and facilitating the oxidation process. This leads to more electrons being transferred to the electrode, which directly correlates with an increase in the peak current observed in the cyclic voltammetry measurements. Additionally, OH⁻ ions might help prevent the passivation of the electrode surface, which can sometimes occur in neutral or acidic conditions, reducing the efficiency of electron transfer. Therefore, in alkaline conditions, the overall reaction proceeds more efficiently, yielding higher current. More Peaks in the CV Plot: The additional peaks in the cyclic voltammetry plot in an alkaline medium are likely due to multiple electrochemical reactions occurring simultaneously at different potential windows, which is typical in complex systems with multiple active species or reaction pathways. These peaks may represent: Glucose oxidation and reduction at different electrode potentials, with oxidation occurring at one potential and reduction occurring at another. Side reactions , such as the formation and reduction of intermediate species (like glucose oxidation products), which may have their own characteristic redox potentials. Hydroxide ion interactions , where OH⁻ may participate in various electrochemical reactions alongside glucose oxidation. The multiple peaks indicate that various electrochemical processes are taking place , a nd these are more likely to occur in an alkaline medium because of the increased number of possible redox reactions between glucose, the electrode surface, and hydroxide ions. Higher Sensitivity and Resolution: In alkaline solutions, the higher concentration of OH⁻ ions and the more efficient electrochemical processes contribute to an overall increase in the current and a more detailed electrochemical response. This causes in better resolution of peaks in the CV plot, allowing for the detection of multiple reaction steps that may not be as distinguishable in PBS or neutral solutions. It is probable that silver nanoparticles are first oxidized to AgOH and AgO species in an environment containing hydroxide ions, and then oxidize glucose, converting it to gluconolactone, which is itself reduced. The enhanced performance of the Ag@MoS₂/GOA sensor in an alkaline medium can be attributed to the increased availability of hydroxide ions (OH⁻), which facilitate the oxidation of glucose. In alkaline conditions, the silver nanoparticles are oxidized to AgOH and AgO species, which act as active sites for glucose oxidation. This process not only increases the rate of electron transfer but also prevents the passivation of the electrode surface, which is a common issue in neutral or acidic environments. The presence of OH⁻ ions also stabilizes the intermediate species formed during glucose oxidation, leading to a more efficient and stable electrochemical response. 3.2.2. Chronoamperometry Analysis Figure 8a shows the chronoamperometric spectrum of the platinum electrode in a basic alkaline solution (0.1 M NaOH). As evident, the gradual addition of glucose to the solution causes an increase in the current. The stepwise increase in current density corresponds to the increase in glucose concentration every 60 seconds, and the trend of increasing current density maintains a broad linear relationship in the glucose concentration range of 0.005–22.0 mM. In fact, the detection limit represents the lowest concentration of a solute that an analytical system can reliably discriminate. Additionally, the sensitivity of the sensor is determined by the slope (m) of the calibration equation [58]. The electrode shows a linear response between 1.0 and 10.0 mM (equivalent to 18 to 180 mg/dL). The calculated sensitivity for this electrode is 546.37 nA mM⁻¹ cm⁻², and the limit of detection (LOD) is 53.29 μM. For concentrations between 10.0 and 22.0 mM (equivalent to 180 to 440 mg/dL), the sensitivity is 22.18 nA mM⁻¹ cm⁻². For glucose concentrations ranging from 5.0 to 1000.0 μM, the sensitivity was calculated to be 0.24 nA mM⁻¹ cm⁻². Sensitivity is defined as the slope of the curve generated when the measurement results are plotted against the determined concentrations. This definition of sensitivity corresponds to the slope of the analytical calibration curve. The lower limit of detection is defined as the level below which detection is impossible with a certain degree of certainty [59-68]. The linear range, detection limit, and sensitivity of comparable materials that have been developed and reported elsewhere are contrasted in Table 1. 3.3. Stability and reproducibility of AgNPs@MoS 2 /GOA/W-AuE Another crucial factor in assessing the lifespan and effectiveness of a glucose biosensor is its stability. The stability of the AgNPs@MoS2/GOA/W-AuE biosensor was investigated over a period of 30 days, as shown in Figure 8, with a stability of 86% observed for the sensor. It exhibited significantly higher stability for glucose detection compared to other non-enzymatic sensors. To evaluate the repeatability of the Ag@MoS 2 /GOA)/W-AuE sensor, the response of six distinct electrodes to a solution with a constant glucose concentration of 5.0 mM was measured. The relative standard deviation (RSD) of 2.20%, as shown in Figure 9, indicates that the reproducibility of the Ag@(MoS 2 /GOA)/W-AuE biosensor is excellent. 3.4. Selectivity of Ag@MoS 2 /GOA/W-AuE The selectivity parameter for a sensor refers to its ability to distinguish a specific analyte from other analytes in a sample containing potential contaminants. The non-enzymatic glucose detection method has the capacity to oxidize species such as citric acid, ascorbic acid, fructose, and sucrose, which are present in human blood alongside glucose. Human blood glucose levels typically range from 4.0 to 7.0 mM (70 to 130 mg/dL) [2, 34], which exceeds the levels of ascorbic acid (0.125 mM), fructose (0.36–0.75 mM) [64], and sucrose (3.9–5.6 mM) [35]. In this work, the selectivity of the Ag@MoS2/GOA/W-AuE biosensor was comprehensively investigated by detecting glucose at a concentration of 6.0 mM in a stock solution of 1 mM NaOH containing interfering agents at ratios of 1:50 (citric acid to glucose), 1:10 (fructose), 1:10 (ascorbic acid), and 1:10 (sucrose). As shown in Figure 10, the responses of the AgNPs@MoS2/GOA/W-AuE biosensor to other interferents were minimal, while the biosensor exhibited a significant response to glucose. The results demonstrate that the AgNPs@(MoS2/GOA)/W-AuE biosensor is highly selective for non-enzymatic glucose detection. The long-term stability of the Ag@MoS₂/GOA sensor, retaining 86% of its initial response after 30 days, is a significant improvement over many existing non-enzymatic glucose sensors. This high stability can be attributed to the robust structure of the graphene oxide aerogel, which prevents the aggregation of AgNPs and MoS₂ nanosheets, thereby maintaining the active surface area over time. Additionally, the sensor's excellent selectivity against common interferents such as ascorbic acid, fructose, and citric acid is due to the specific catalytic properties of AgNPs and the unique electronic structure of MoS₂, which preferentially catalyze glucose oxidation over other species. 3.5. Special Characteristics and Performance of the Prepared Electrode The electrochemical performance of the Ag@MoS2/GOA/W-AuE-based glucose sensor was compared with several previously reported non-enzymatic glucose sensors in terms of key performance metrics, including material composition, sensitivity, detection limit, linear range, stability, reproducibility, and potential applications. As shown in Table 2 , the proposed sensor demonstrates exceptional performance across all these parameters. The Ag@MoS2/GOA/W-AuE sensor developed in this study exhibits excellent stability, retaining 86% of its initial response after 30 days, along with high reproducibility ( 2.20% RSD ). Additionally, its compact design enhances its suitability for implantable biomedical applications. These characteristics make it a strong candidate for long-term, non-enzymatic glucose detection in medical and implantable settings. Compared to other non-enzymatic glucose sensors reported in the literature, the Ag@MoS₂/GOA sensor demonstrates superior performance in terms of sensitivity, detection limit, and linear range. For instance, sensors based on CuO or NiO nanostructures often suffer from limited stability and selectivity, whereas the incorporation of AgNPs and MoS₂ in our design significantly enhances both stability and selectivity. The unique three-dimensional structure of the graphene oxide aerogel (GOA) further contributes to the high surface area and efficient mass transfer, which are critical for achieving high sensitivity and low detection limits. These advantages make the Ag@MoS₂/GOA sensor a promising candidate for practical applications in continuous glucose monitoring The mechanism of glucose detection in non-enzymatic sensors relies on the direct electrochemical oxidation of glucose on the surface of the electrode. In the case of the Ag@MoS₂/GOA nanocomposite, the presence of silver nanoparticles (AgNPs) plays a crucial role in facilitating electron transfer due to their high electrical conductivity and catalytic activity. The MoS₂ nanosheets provide a large surface area and active sites for glucose adsorption, while the graphene oxide aerogel (GOA) enhances the overall conductivity and stability of the electrode. The synergistic effect of these components results in a highly efficient glucose oxidation process, which is further amplified in alkaline conditions due to the presence of hydroxide ions (OH⁻) that promote the oxidation reaction . 4. Conclusions A one-step hydrothermal synthesis approach was used to successfully create a highly sensitive non-enzymatic biosensor for glucose detection based on the Ag@MoS2/GOA nanocomposite. The morphological structure of Ag@MoS2/GOA provides a significant number of active sites for glucose electrooxidation. The nanocomposite was deposited by polymerization onto a 1 cm layer at the beginning of the W/Au electrode wire. The AgNPs@MoS2/GOA/W-AuE biosensor responds well to glucose concentrations ranging from 1.0 to 10.0 mM, with sensitivity and limit of detection (LOD) values of 546.37 nA mM⁻¹ cm⁻² and 53.29 µM, respectively. The AgNPs@MoS2/GOA-based glucose sensor exhibits exceptional selectivity against interfering species, acceptable repeatability, a wide linear range, and stability, indicating its potential as a non-enzymatic electrochemical glucose sensor. Silver nanoparticles are oxidized in the presence of the supporting electrolyte NaOH (0.1 M), promoting glucose redox reactions. The biosensor can be used in two environments: its performance is highly favorable in an alkaline environment but can be further improved in a PBS environment. Outlook The Ag@MoS₂/GOA sensor developed in this study holds great promise for various applications, including continuous glucose monitoring in diabetic patients and glucose detection in fermentation processes. The sensor's high sensitivity, wide linear range, and excellent stability make it suitable for integration into wearable devices or implantable sensors. Future research could focus on further optimizing the sensor's performance by exploring different ratios of AgNPs, MoS₂, and GOA, as well as investigating the sensor's behavior in real biological samples such as blood or interstitial fluid. Declarations Acknowledgment This work was funded by Behyaar sanaat Sepahan Company. This work was done under support of Iran national science foundation (Grant no. 4039256). Conflict of Interest The authors declare that they have no conflict of interest with any individual, company, or organization concerning this research. Data availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Author statement: All authors contributed in analysis, wrting and editing manuscript. References Y. Hu, X. Wang, W. Li, Y. Lai, Y. Chen, Z. Wei and H. Yang,“in Metal-organic frameworks and related materials for nonenzymatic electrochemical glucose sensorsˮ, International Journal of Electrochemical Science 100466, 2024. A. Chadt and H. Al-Hasani,“in Glucose transporters in adipose tissue, liver, and skeletal muscle in metabolic health and diseaseˮ, Pflügers Archiv-European Journal of Physiology 472, 1273-1298, 2020. H.-S. Han, G. Kang, J. S. Kim, B. H. Choi and S.-H. Koo,“in Regulation of glucose metabolism from a liver-centric perspectiveˮ, Experimental & molecular medicine 48, e218-e218, 2016. P. Preechakasedkit, N. Nawaukkaratharnant, K. Teekayupak, A. Lomae and N. Ruecha,“in Single-preparation rGO/Cu–Cu2O nanocomposite-modified electrode integrating NaOH immobilized polymer blend film for one-step nonenzymatic glucose detectionˮ, Journal of Science: Advanced Materials and Devices 8, 100535, 2023. P. Punnoy, P. Preechakasedkit, C. Aumnate, N. Rodthongkum, P. Potiyaraj and N. Ruecha,“in Polyvinyl alcohol/starch modified cotton thread surface as a novel colorimetric glucose sensorˮ, Materials Letters 299, 130076, 2021. Z. Li, Y. Zhu, W. Zhang, C. Xu, Y. Pan and Y. Zhao,“in A low-cost and high sensitive paper-based microfluidic device for rapid detection of glucose in fruitˮ, Food analytical methods 10, 666-674, 2017. D. Bruen, C. Delaney, L. Florea and D. Diamond,“in Glucose sensing for diabetes monitoring: recent developmentsˮ, Sensors 17, 1866, 2017. C. E. F. Do Amaral and B. Wolf,“in Current development in non-invasive glucose monitoringˮ, Medical engineering & physics 30, 541-549, 2008. R. Badugu, J. R. Lakowicz and C. D. Geddes ˮin Ophthalmic glucose monitoring using disposable contact lensesˮ, Springer, pp. 363-397, 2005. R. Badugu, J. R. Lakowicz and C. D. Geddes,“in Fluorescence sensors for monosaccharides based on the 6-methylquinolinium nucleus and boronic acid moiety: potential application to ophthalmic diagnosticsˮ, Talanta 65, 762-768, 2005. H. Sun, P. Saeedi, S. Karuranga, M. Pinkepank, K. Ogurtsova, B. B. Duncan, C. Stein, A. Basit, J. C. Chan and J. C. Mbanya,“in IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045ˮ, Diabetes research and clinical practice 183, 109119, 2022. P. Lu, Y. Lei, S. Lu, Q. Wang and Q. Liu,“in Three-dimensional roselike α-Ni (OH) 2 assembled from nanosheet building blocks for non-enzymatic glucose detectionˮ, Analytica chimica acta 880, 42-51, 2015. S. Bakhshi, M. Rahmanipour, A. R. Amirsoleimani, M. Rezazadeh, H. Siampour and A. Moshaii,“in Nanopyramid copper structures on screen-printed carbon electrode for high-performance non-enzymatic glucose sensing: A cost-effective and scalable approachˮ, Sensing and Bio-Sensing Research 46, 100706, 2024. M. Adeel, M. M. Rahman, I. Caligiuri, V. Canzonieri, F. Rizzolio and S. Daniele,“in Recent advances of electrochemical and optical enzyme-free glucose sensors operating at physiological conditionsˮ, Biosensors and Bioelectronics 165, 112331, 2020. L. C. Clark Jr and C. Lyons,“in Electrode systems for continuous monitoring in cardiovascular surgeryˮ, Annals of the New York Academy of sciences 102, 29-45, 1962. S. J. Updike and G. P. Hicks,“in The enzyme electrodeˮ, Nature 214, 986-988, 1967. G. Guilbault and G. Lubrano,“in An enzyme electrode for the amperometric determination of glucoseˮ, Analytica chimica acta 64, 439-455, 1973. C. Chen, Q. Xie, D. Yang, H. Xiao, Y. Fu, Y. Tan and S. Yao,“in Recent advances in electrochemical glucose biosensors: a reviewˮ, Rsc Advances 3, 4473-4491, 2013. S.-C. Hung,“in Highly Sensitive Non-Enzymatic Glucose Sensing Using Ni Nanowires and Graphene Thin Film on the Gate Area of Extended Gate Electric Double-Layer Field-Effect Transistorˮ, Heliyon 2025. A. Aygun, E. Ozveren, E. Halvaci, D. Ikballi, R. N. E. Tiri, C. Catal, M. Bekmezci, A. Ozengul, I. Kaynak and F. Sen,“in The performance of a very sensitive glucose sensor developed with copper nanostructure-supported nitrogen-doped carbon quantum dotsˮ, RSC advances 14, 34964-34970, 2024. J. Yang, J. Yin and L. Xu,“in Electrochemical non-enzymatic glucose sensors based on CuO nanostructuresˮ, Journal of Alloys and Compounds 177796, 2024. V. Sabaghi, P. Rashidi-Ranjbar, F. Davar and E. Sharif-Paghaleh,“in Development of multifunctional MnO2-based nanoplatforms for hypoxia modulation/T1-weighted MRI/optical biosensing and targeted drug deliveryˮ, Journal of Drug Delivery Science and Technology 91, 105190, 2024. M. Adeel, K. Asif, M. M. Rahman, S. Daniele, V. Canzonieri and F. Rizzolio,“in Glucose detection devices and methods based on metal–organic frameworks and related materialsˮ, Advanced Functional Materials 31, 2106023, 2021. H. Shahba and M. Sabet,“in Two-step and green synthesis of highly fluorescent carbon quantum dots and carbon nanofibers from pine fruitˮ, Journal of Fluorescence 30, 927-938, 2020. B. Yuan, C. Xu, L. Liu, Q. Zhang, S. Ji, L. Pi, D. Zhang and Q. Huo,“in Cu2O/NiOx/graphene oxide modified glassy carbon electrode for the enhanced electrochemical oxidation of reduced glutathione and nonenzyme glucose sensorˮ, Electrochimica Acta 104, 78-83, 2013. X. Li and H. Zhu,“in Two-dimensional MoS2: Properties, preparation, and applicationsˮ, Journal of Materiomics 1, 33-44, 2015. J. A. Wilson and A. Yoffe,“in The transition metal dichalcogenides discussion and interpretation of the observed optical, electrical and structural propertiesˮ, Advances in Physics 18, 193-335, 1969. I. A. Rahman and A. Purqon, Journal of Physics: Conference Series p. 012026, 2017. T. D. Van, N. D. T. Thuy, T. D. V. Phuong, N. N. Thi, T. N. Thi, T. N. Phuong, T. V. Van, H. Vuong-Pham and T. P. Dinh,“in High-performance nonenzymatic electrochemical glucose biosensor based on AgNP-decorated MoS2 microflowersˮ, Current Applied Physics 43, 116-123, 2022. F. Xu, M. Wu, G. Ma, H. Xu and W. Shang,“in Copper-molybdenum sulfide/reduced graphene oxide hybrid with three-dimensional wrinkles and pores for enhanced amperometric detection of glucoseˮ, Microchemical Journal 159, 105432, 2020. X. Sui, L. Zhang, J. Li, K. Doyle‐Davis, R. Li, Z. Wang and X. Sun,“in Advanced support materials and interactions for atomically dispersed noble‐metal catalysts: from support effects to design strategiesˮ, Advanced Energy Materials 12, 2102556, 2022. F. Guo, H. Yang, L. Liu, Y. Han, A. M. Al-Enizi, A. Nafady, P. E. Kruger, S. G. Telfer and S. Ma,“in Hollow capsules of doped carbon incorporating metal@ metal sulfide and metal@ metal oxide core–shell nanoparticles derived from metal–organic framework composites for efficient oxygen electrocatalysisˮ, Journal of Materials Chemistry A 7, 3624-3631, 2019. H. Zengin and G. Kalaycı,“in Synthesis and characterization of polyaniline/activated carbon composites and preparation of conductive filmsˮ, Materials Chemistry and Physics 120, 46-53, 2010. K. P. Sharma, M. Shin, G. P. Awasthi, S. Cho and C. Yu,“in One-step hydrothermal synthesis of CuS/MoS2 composite for use as an electrochemical non-enzymatic glucose sensorˮ, Heliyon 10, 2024. L. Fang, F. Wang, Z. Chen, Y. Qiu, T. Zhai, M. Hu, C. Zhang and K. Huang,“in Flower-like MoS2 decorated with Cu2O nanoparticles for non-enzymatic amperometric sensing of glucoseˮ, Talanta 167, 593-599, 2017. X. Lin, Y. Ni and S. Kokot,“in Electrochemical and bio-sensing platform based on a novel 3D Cu nano-flowers/layered MoS2 compositeˮ, Biosensors and Bioelectronics 79, 685-692, 2016. Y. Jiang, Y. Li, Y. Li and S. Li,“in A sensitive enzyme-free hydrogen peroxide sensor based on a chitosan–graphene quantum dot/silver nanocube nanocomposite modified electrodeˮ, Analytical Methods 8, 2448-2455, 2016. Z. Zhao, J. Liu, W. Wang, J. Zhang, G. Li, J. Liu, K. Lian, J. Hu and S. Zhuiykov,“in Ag functionalized molybdenum disulfide hybrid nanostructures for selective and sensitive amperometric hydrogen peroxide detectionˮ, International Journal of Electrochemical Science 12, 8761-8776, 2017. W. Yu, X. Bai, G. Tian, J. Deng, Z. Zhang, Q. Ke, S. Liu and C. Huang,“in Robust bonding of Ag nanoparticles on bicomponent fibers enabled highly reliable, multi-functional piezoresistive sensingˮ, Chemical Engineering Journal 503, 158414, 2025. M. Baghayeri, A. Amiri and S. Farhadi,“in Development of non-enzymatic glucose sensor based on efficient loading Ag nanoparticles on functionalized carbon nanotubesˮ, Sensors and Actuators B: Chemical 225, 354-362, 2016. J. Li, H. Hu, H. Li and C. Yao,“in Recent developments in electrochemical sensors based on nanomaterials for determining glucose and its byproduct H 2 O 2ˮ, Journal of Materials Science 52, 10455-10469, 2017. B. Fall, D. D. Sall, M. Hémadi, A. K. D. Diaw, M. Fall, H. Randriamahazaka and S. Thomas,“in Highly efficient non-enzymatic electrochemical glucose sensor based on carbon nanotubes functionalized by molybdenum disulfide and decorated with nickel nanoparticles (GCE/CNT/MoS2/NiNPs)ˮ, Sensors and Actuators Reports 5, 100136, 2023. L. Zhao, X.-L. Sui, J.-L. Li, J.-J. Zhang, L.-M. Zhang and Z.-B. Wang,“in Ultra-fine Pt nanoparticles supported on 3D porous N-doped graphene aerogel as a promising electro-catalyst for methanol electrooxidationˮ, Catalysis Communications 86, 46-50, 2016. L. Ruiyi, Z. Juanjuan, W. Zhouping, L. Zaijun, L. Junkang, G. Zhiguo and W. Guangli,“in Novel graphene-gold nanohybrid with excellent electrocatalytic performance for the electrochemical detection of glucoseˮ, Sensors and Actuators B: Chemical 208, 421-428, 2015. M. B. Lim, M. Hu, S. Manandhar, A. Sakshaug, A. Strong, L. Riley and P. J. Pauzauskie,“in Ultrafast sol–gel synthesis of graphene aerogel materialsˮ, Carbon 95, 616-624, 2015. R. Li, T. Yang, Z. Li, Z. Gu, G. Wang and J. Liu,“in Synthesis of palladium@ gold nanoalloys/nitrogen and sulphur-functionalized multiple graphene aerogel for electrochemical detection of dopamineˮ, Analytica Chimica Acta 954, 43-51, 2017. H.-P. Cong, J.-F. Chen and S.-H. Yu,“in Graphene-based macroscopic assemblies and architectures: an emerging material systemˮ, Chemical Society Reviews 43, 7295-7325, 2014. Y. Jiang, H. Shao, C. Li, T. Xu, Y. Zhao, G. Shi, L. Jiang and L. Qu,“in Versatile Graphene Oxide Putty-Like Materialˮ, Advanced Materials (Deerfield Beach, Fla.) 28, 10287-10292, 2016. W. Liu, Z. Wang, W. Yan, Z. Zhao, L. Shi, L. Huang, Y. Liu, X. He and S. Cui,“in Construction of ultra-sensitive surface-enhanced Raman scattering substrates based on 3D graphene oxide aerogelsˮ, Carbon 202, 389-397, 2023. M. Mazloum-Ardakani, N. Shaker-Ardakani and F. Farbod,“in Highly efficient enzyme less glucose sensor based on cross-linked nitrogen-doped graphene aerogel incorporated with ytterbium oxide and decorated with nickel nitride nanoparticlesˮ, Sensors International 5, 100290, 2024. J. Yang, C. Zhang, Y. Niu, J. Huang, X. Qian and K.-Y. Wong,“in N-doped C-CoS2@ CoS2/MoS2 nano polyhedrons with hierarchical yolk-shelled structures as bifunctional catalysts for enhanced photovoltaics and hydrogen evolutionˮ, Chemical Engineering Journal 409, 128293, 2021. A. K. Alzubaidi, W. J. Al-Kaabi, A. A. Ali, S. Albukhaty, H. Al-Karagoly, G. M. Sulaiman, M. Asiri and Y. Khane,“in Green synthesis and characterization of silver nanoparticles using flaxseed extract and evaluation of their antibacterial and antioxidant activitiesˮ, Applied Sciences 13, 2182, 2023. Z. Çiplak, N. Yildiz and A. Çalimli,“in Investigation of Graphene/Ag Nanocomposites Synthesis Parameters for Two Different Synthesis Methodsˮ, Fullerenes, Nanotubes and Carbon Nanostructures 23, 361-370, 2015. W. Gul and H. Alrobei,“in Effect of graphene oxide nanoparticles on the physical and mechanical properties of medium density fiberboardˮ, Polymers 13, 1818, 2021. Q. Tang, S. Luo, H. Gao, Y. Fan, W. Bao, Y. Gao, Y. Sun and C. Yang,“in N-doped graphene aerogel cathode with internal aeration for enhanced degradation of p-nitrophenol by electro-Fenton processˮ, Environmental Science and Pollution Research 30, 23481-23493, 2023. F. J. Rahmania, T. Imae and J. P. Chu,“in Electrochemical nonenzymatic glucose sensors catalyzed by Au nanoclusters on metallic nanotube arrays and polypyrrole nanowiresˮ, Journal of Colloid and Interface Science 657, 567-579, 2024. Y. Wang, Q. Wang, G. Chai, W. Fan, Q. Shi, W. Zhang, J. Mao, J. Xie, R. Wei and Q. Zhang,“in A flexible electrochemical glucose sensing platform based on an electrospun PVA mat covered with in situ grown silver nanoparticles and a mixed self-assembled monolayer of glucose oxidase and ferroceneˮ, Analyst 148, 3724-3729, 2023. S. Y. Ejeta and T. Imae,“in Selective colorimetric and electrochemical detections of Cr (III) pollutant in water on 3-mercaptopropionic acid-functionalized gold plasmon nanoparticlesˮ, Analytica Chimica Acta 1152, 338272, 2021. ˮin Chapter 7 - Sensitivity and Limit of Detectionˮ, Vol. 2 Eds.: D.L. Massart, B.G.M. Vandeginste, S.N. Deming, Y. Michotte and L. Kaufman), Elsevier, pp. 107-114, 2003. M. A. Deshmukh, B.-C. Kang and T.-J. Ha,“in Non-enzymatic electrochemical glucose sensors based on polyaniline/reduced-graphene-oxide nanocomposites functionalized with silver nanoparticlesˮ, Journal of Materials Chemistry C 8, 5112-5123, 2020. M. S. Gijare, S. R. Chaudhari, S. Ekar, S. F. Shaikh, A. M. Al-Enizi, B. Pandit and A. D. Garje,“in Green synthesis of reduced graphene oxide (rGO) and its applications in non-enzymatic electrochemical glucose sensorsˮ, Journal of Photochemistry and Photobiology A: Chemistry 450, 115434, 2024. S. Phetsang, P. Kidkhunthod, N. Chanlek, J. Jakmunee, P. Mungkornasawakul and K. Ounnunkad,“in Copper/reduced graphene oxide film modified electrode for non-enzymatic glucose sensing applicationˮ, Scientific reports 11, 9302, 2021. K. P. Sharma, M. Shin, K. Kim, K. Woo, G. P. Awasthi and C. Yu,“in Copper nanoparticles/polyaniline/molybdenum disulfide composite as a nonenzymatic electrochemical glucose sensorˮ, Heliyon 9, 2023. T. Kawasaki, H. Akanuma and T. Yamanouchi,“in Increased fructose concentrations in blood and urine in patients with diabetesˮ, Diabetes care 25, 353-357, 2002. K. Anderson, B. Poulter, J. Dudgeon, S.-E. Li and X. Ma,“in A highly sensitive nonenzymatic glucose biosensor based on the regulatory effect of glucose on electrochemical behaviors of colloidal silver nanoparticles on MoS2ˮ, Sensors 17, 1807, 2017. G. Jeevanandham, R. Jerome, N. Murugan, M. Preethika, K. Vediappan and A. K. Sundramoorthy,“in Nickel oxide decorated MoS 2 nanosheet-based non-enzymatic sensor for the selective detection of glucoseˮ, RSC advances 10, 643-654, 2020. L.-Y. Xiong, Y.-J. Kim, W.-C. Seo, H.-K. Lee, W.-C. Yang and W.-F. Xie,“in High-performance non-enzymatic glucose sensor based on Co3O4/rGO nanohybridˮ, Rare Metals 42, 3046-3053, 2023. T. Sridara, J. Upan, G. Saianand, A. Tuantranont, C. Karuwan and J. Jakmunee,“in Non-enzymatic amperometric glucose sensor based on carbon nanodots and copper oxide nanocomposites electrodeˮ, Sensors 20, 808, 2020. Tables Table 1 performance comparison between the created non-enzyme glucose biosensor AgNPs@(MoS₂NSs/GOA)/W-AuE and other non-enzyme glucose biosensors. Modified Electrodes Method Linear range Sensitivity Detection Limit Ref. Ag–PANI/rGO CV 0.1 – 50 μM - 0.79 (µM) [1] AuNC(c10)/PPyNW CV 0.05 – 10 mM 14.5 (µA mM -1 cm -2 ) 48.2 (µM) [2] AgNPs/MoS 2 CV 1.0 – 15 mM 46.5 (µA mM -1 cm -2 ) 1.0 (µM) [3] rGO CV 0.2 – 10 mM 19.17 (µA mM -1 cm -2 ) 1.901 (µM) [4] Cu (II)/rGO/SPCE CV Amperometry 0.1–12.5 mM 171.95 (µA mM -1 cm -2 ) 65 (µM) [5] CuS/MoS 2 CV Amperometry 0.1–11 mM 252.71 (µA mM -1 cm -2 ) 1.52 (µM) [6] Cu/Pani/MoS 2 CV Amperometry 0.1–11 mM 69.82 (µA mM -1 cm -2 ) 1.78 (μM) [7] AgNPs@(MoS₂NSs/GOA) CV Amperometry 0.005 – 1mM 1 – 10 mM 10 – 22 mM 0.24 (nA mM -1 cm -2 ) 546.37 (nA mM -1 cm -2 ) 22.18 (nA mM -1 cm -2 ) 121 (mM) 53.29 (µM) 1.32 (mM) This work Table 2 Comparison Table of the Proposed Glucose Sensor with Other Similar Sensors: Sensor Composition Sensitivity (µA·mM⁻¹·cm⁻²) Detection Limit (µM) Linear Range (mM) Performance Stability (30 days) Reproducibility (RSD) Structural Stability Specific Applications Reference AgNPs@(MoS₂NSs/GOA) nanocoposite 546.37 53.29 0.005–1, 1–10, 10–22 86% retention 2.20% High Implantable biomedical applications This work Colloidal AgNPs on MoS₂ 9044.6 0.03 0.1–1 80% retention 3.10% Moderate Point-of-care diagnostics [8] NiO-decorated MoS₂ nanosheets 2310 0.1 0.001–5 78% retention 4.50% High Wearable sensors [9] Co₃O₄/reduced graphene oxide (rGO) nanohybrid 839.3 0.5 0.001–2 75% retention 5.00% Moderate Non-invasive glucose monitoring [10] Carbon nanodots (C-dots)/CuO nanocomposites 5300 0.5 0.001–1.1 82% retention 3.80% High Continuous glucose monitoring (CGM) [11] Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Jul, 2025 Reviews received at journal 09 Jul, 2025 Reviewers agreed at journal 02 Jul, 2025 Reviews received at journal 02 May, 2025 Reviewers agreed at journal 23 Apr, 2025 Reviewers agreed at journal 23 Apr, 2025 Reviewers invited by journal 10 Apr, 2025 Editor assigned by journal 10 Apr, 2025 Editor invited by journal 10 Apr, 2025 Submission checks completed at journal 07 Apr, 2025 First submitted to journal 24 Mar, 2025 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-6292994","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442656260,"identity":"1d2fb80e-e171-4f5c-b08c-c26624202923","order_by":0,"name":"Haniyeh Shahba","email":"","orcid":"","institution":"Isfahan university of technology","correspondingAuthor":false,"prefix":"","firstName":"Haniyeh","middleName":"","lastName":"Shahba","suffix":""},{"id":442656263,"identity":"ada7e9dc-b1fc-4571-8048-16892b32d0e8","order_by":1,"name":"Fatemeh Davar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArElEQVRIiWNgGAWjYDCCAyCiQgLKMyBayxkJBh7StDC2MUC1EAP4jp8x/Fw5zyJxPwPzww8MBfcIa5E8k2MseXabRGIPA5uxBINBMWEtBgfSEiQbwVoYzIDcBCK0nH+W/LNxDkgL+zcitdxIPibZ2ADSwkOkLZI3Hh+zbDgmYdxzmKdYIoEYLXznE5tvNtTUyba3t2/88OEPEVoQgBmISdIwCkbBKBgFowA3AAAmOTRWGhYjWgAAAABJRU5ErkJggg==","orcid":"","institution":"Isfahan university of technology","correspondingAuthor":true,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Davar","suffix":""},{"id":442656264,"identity":"79116061-4cf3-4969-89b1-2f2813152ea6","order_by":2,"name":"Navid Nejatbakhsh","email":"","orcid":"","institution":"Isfahan university of technology","correspondingAuthor":false,"prefix":"","firstName":"Navid","middleName":"","lastName":"Nejatbakhsh","suffix":""},{"id":442656265,"identity":"ee01d928-311c-415f-9d62-b88ca2ff46ee","order_by":3,"name":"Esmaeil Heydari-Bafrooei","email":"","orcid":"","institution":"Isfahan university of technology","correspondingAuthor":false,"prefix":"","firstName":"Esmaeil","middleName":"","lastName":"Heydari-Bafrooei","suffix":""}],"badges":[],"createdAt":"2025-03-24 08:08:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6292994/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6292994/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-25570-8","type":"published","date":"2025-12-01T15:58:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80636985,"identity":"cf3a4400-e890-49d9-a064-326e8bfa3de0","added_by":"auto","created_at":"2025-04-15 12:36:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":927155,"visible":true,"origin":"","legend":"\u003cp\u003eFE-SEM images at (a) Ag NPs, (b) GO, (c, d) GOA, (e) MoS\u003csub\u003e2\u003c/sub\u003eNSs/GOA, and (f) AgNPs@(MoS₂NSs/GOA).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/059ab37b548b366c1baf5abc.png"},{"id":80635183,"identity":"3bb3464f-6deb-487e-9cc7-f7663c7ba979","added_by":"auto","created_at":"2025-04-15 12:20:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":777061,"visible":true,"origin":"","legend":"\u003cp\u003eTEM images of AgNPs@(MoS₂NSs/GOA) nanocomposite\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/be9d4d2e8af9577607f2342b.png"},{"id":80635185,"identity":"9e95c73c-7a0f-46e3-b7a3-886b05d5972d","added_by":"auto","created_at":"2025-04-15 12:20:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":834291,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Mapping images and (b) EDS spectrum of Ag@(MoS\u003csub\u003e2\u003c/sub\u003e/GOA) nanocomposite\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/a0bc1518a86b72c96c0ed24c.png"},{"id":80636395,"identity":"0780740e-27e5-4ee2-bd33-1662fdafc62e","added_by":"auto","created_at":"2025-04-15 12:28:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":655223,"visible":true,"origin":"","legend":"\u003cp\u003e(a,b) Electrode wire\u003cstrong\u003e \u003c/strong\u003ebefore and after deposition nanocomposite and (c-f)\u003cstrong\u003e \u003c/strong\u003eFE-SEM images at of AgNPs@(MoS₂NSs/GOA)/W-Auelectrode surface.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/ccaf48dfd99e5a9a9dbd57d1.png"},{"id":80636393,"identity":"067a4065-8b5a-4c97-9ae3-4aec9d59e001","added_by":"auto","created_at":"2025-04-15 12:28:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":167183,"visible":true,"origin":"","legend":"\u003cp\u003e(a) XRD patterns of GO, GOA, MoS\u003csub\u003e2 \u003c/sub\u003eand MoS\u003csub\u003e2\u003c/sub\u003e/Ag@GOA (b) FTIR spectra from bottom to top correspond to GO, GOA, MoS\u003csub\u003e2 \u003c/sub\u003eand MoS\u003csub\u003e2\u003c/sub\u003e/Ag@GOA respectively, and (c) Raman spectra of GO, GOA, MoS\u003csub\u003e2\u003c/sub\u003e, MoS\u003csub\u003e2\u003c/sub\u003e/GOA and Ag@(MoS\u003csub\u003e2\u003c/sub\u003e/GOA).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/cb2b4d1e9d049ccf735c6815.png"},{"id":80637692,"identity":"2e91506e-46b6-4460-8c07-f169f76a7c33","added_by":"auto","created_at":"2025-04-15 12:44:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61246,"visible":true,"origin":"","legend":"\u003cp\u003eCV curves of the base electrode (blue curve), MoS₂-modified electrode (red curve), and MoS₂ + Ag -modified electrode (green curve) in the presence of glucose.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/5b02c865178945a65cfb5882.png"},{"id":80636993,"identity":"e9948c90-a5c3-4f47-a956-4d9feaa34856","added_by":"auto","created_at":"2025-04-15 12:36:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":141446,"visible":true,"origin":"","legend":"\u003cp\u003eCV curves of AgNPs@(MoS₂NSs/GOA)/W−AuE in response to varying glucose concentrations using applied potentials ranging from -0.40 to 0.65 V and a scan rate of 100 mVs⁻¹ in (a) PBS solution, (c) 1.0 M NaOH solution. Plot of calibration for the relationship between glucose concentration and peak current in (b) PBS solution, (d) 1.0 M NaOH solution. (e) \u0026nbsp;AgNPs@(MoS₂NSs/GOA)/W−AuE at various scan rates in NaOH solution. (f) The square root of the scan rate has a linear relationship with the oxidation peak current of 0.275 V.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/b4f9125a7411239f18e3d698.png"},{"id":80636987,"identity":"54ba56e7-e74f-4867-a7f4-e2536519c175","added_by":"auto","created_at":"2025-04-15 12:36:57","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":84736,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Steps of chronoamperometric analysis of the AgNPs@(MoS₂NSs/GOA)/W-AuE biosensor in response to increasing glucose concentration from 5 μM to 10 mM in a 0.1 M NaOH stock solution with a 60 s time interval and an applied potential of 0.6 V. (b) Plot of the catalytic current density vs. glucose concentration.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/016e28e3908c472de4db8176.png"},{"id":80635187,"identity":"91549e22-9d6d-4265-8116-64e18a6eb737","added_by":"auto","created_at":"2025-04-15 12:20:57","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":101737,"visible":true,"origin":"","legend":"\u003cp\u003e(a) AgNPs@(MoS₂NSs/GOA)/W-AuE stability for glucose sensing. (b) AgNPs@(MoS₂NSs/GOA)/W-AuE reproducibility in a NaOH solution with 5.0 mM glucose.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/4133e935d2acae4221d8f1c2.png"},{"id":80638215,"identity":"230b9e99-add7-49e8-86f3-b020f52d89ea","added_by":"auto","created_at":"2025-04-15 12:52:57","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":21550,"visible":true,"origin":"","legend":"\u003cp\u003eStudy of biosensor selectivity for glucose, in the presence of fructose, sucrose, citric acid, and ascorbic acid.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/415f0c423c78aca15af46b7b.png"},{"id":97723942,"identity":"9588e267-cb13-4e30-9e80-299b8b18da78","added_by":"auto","created_at":"2025-12-08 16:10:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5138916,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6292994/v1/db4b2515-0717-4e3c-86d7-6d32e7294232.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electrochemical Glucose Detection Using Ag@MoS₂/Graphene Oxide Aerogel Nanocomposite: A Study on Sensitivity, Stability, and Selectivity","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe majority of bodily tissues rely on glucose (C\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e), a significant monosaccharide, as their primary energy source. The efficient distribution of glucose in the human body depends on the requirements of specific organs [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although sugars are the primary source of energy for humans, excessive consumption can lead to various ailments, which represent significant global health concerns [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. According to research, the normal range for blood glucose levels in non-diabetic individuals is between 4.90 and 6.90 mM [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A person is diagnosed with diabetes when their blood glucose concentration rises above normal levels [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The increasing global prevalence of diabetes, which poses serious health risks and financial burdens, has significantly increased the demand for precise and effective glucose sensing in recent years [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor diabetes monitoring, particularly in critical contexts such as dietary intake and fermentation processes, glucose detection is crucial. Despite numerous advancements in this field, glucose detection technology continues to evolve. The pioneering research by Clark and Lyon in 1962 led to the invention of the first glucose sensor. These electrochemical sensors are known as the first generation of blood glucose sensors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Electrochemical blood glucose detection sensors are primarily divided into two categories: enzymatic glucose detection sensors and non-enzymatic glucose detection sensors. Additionally, they are categorized into generations: first (the most common), second, third, and fourth-generation electrochemical glucose sensors. In the electrochemical glucose detection process, the catalyst plays a critical role. In the first to third generations, the enzyme glucose oxidase serves this function, thus classifying them as enzymatic electrocatalytic sensors. However, in the fourth generation, other catalysts are utilized [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Recent advances in electrochemical sensing have focused on developing a new generation of glucose sensors that completely eliminate the use of glucose oxidases and instead utilize various advanced catalysts for the direct electrochemical oxidation of glucose as biomimetic materials, including precious metal nanoparticles, metal sulfides/oxides, novel carbon-based materials, and inorganic-organic composites [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA non-enzymatic glucose sensor was developed by Yuan et al. using Cu\u003csub\u003e2\u003c/sub\u003eO/NiOx/spherical graphene oxide as matrix materials. By increasing the electrochemical active area through Cu\u003csub\u003e2\u003c/sub\u003eO and NiOx, the electrocatalytic activity is enhanced, demonstrating selectivity for glucose over other coexisting substances in human serum [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Molybdenum disulfide (MoS\u003csub\u003e2\u003c/sub\u003e) typically has a band gap of 1.8 eV and offers a suitable surface area, low coefficient of friction, and superior physicochemical and catalytic characteristics [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Non-enzymatic biosensors utilizing MoS\u003csub\u003e2\u003c/sub\u003e nanosheets have been created; however, due to their low electrocatalytic activity toward glucose, such sensors perform inadequately. Therefore, efforts must focus on enhancing their biosensing performance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Researchers have aimed to improve catalytic properties by focusing on the functional groups of the MoS\u003csub\u003e2\u003c/sub\u003e surface and combining it with polymers, carbonaceous materials, metal nanoparticles, as well as metal sulfides and oxides [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this context, a non-enzymatic sensor based on CuS/MoS\u003csub\u003e2\u003c/sub\u003e bimetallic composites was prepared using a one-step hydrothermal process [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. MoS2 nanosheets may be combined with noble metal nanoparticles such as Pt, Ag, Au, Ni, and Cu because noble metals exhibit greater electrocatalytic activity for glucose detection and oxidation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Furthermore, rapid, heterogeneous electron transfer\u0026mdash;which significantly boosts electrical conductivity\u0026mdash;may result from the interaction between metal nanoparticles and MoS₂ [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSilver nanoparticles have been widely utilized for non-enzymatic detection of blood glucose due to their large surface area and excellent electrocatalytic activity [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. For instance, Mehdi et al. used carbon nanotubes (CNT) and Ag NPs to create a non-enzymatic glucose sensor [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. They demonstrated that the combination of Ag nanoparticles (NPs) and CNT increased the sensor\u0026rsquo;s long-term stability, sensitivity, and electrode conductivity. Another study investigated non-enzymatic glucose detection using AgNPs/MoS₂, fabricated via a hydrothermal process [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGraphene, graphene oxide, activated carbon, and carbon nanotubes are examples of carbon-based compounds that have garnered significant interest in recent scientific research. Carbon-based materials are excellent candidates for electrode modification due to their high electron transport, large electrochemical range, high specific surface area, and good chemical stability, making them useful for glucose sensing [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe highly porous structure of graphene oxide aerogel (GOA), composed of interconnected three-dimensional graphene oxide sheets (rich in oxygen-containing functional groups), has drawn interest due to its improved electrical conductivity, large specific surface area, and excellent mechanical strength. Its large pore volume facilitates rapid mass transfer of redox species, and its large specific surface area can provide numerous active sites for the sensor\u0026rsquo;s catalytic process [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Graphene possesses a sp\u003csup\u003e2\u003c/sup\u003e-conjugated structure, and the presence of oxygen-containing functional groups disrupts this structure, reducing the electrical conductivity of the material, thereby significantly hindering charge transfer [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These features make them a potentially broad and suitable platform for effective nanoparticle placement [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study synthesized a ternary composite of silver nanoparticles, molybdenum disulfide nanosheets, and graphene oxide aerogel using a one-step hydrothermal method to serve as a non-enzymatic glucose sensing electrode. This non-enzymatic sensor, which exhibits catalytic properties and a large active surface area, demonstrated high performance in detecting glucose concentrations and shows potential for further development [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemical Reagents\u003c/h2\u003e \u003cp\u003eSilver nanopowder (Ag\u0026thinsp;\u0026gt;\u0026thinsp;99.5%) from TitraChem, molybdenum disulfide nanopowder (MoS\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;99%) from 3302 Twig Leaf Lane, Houston, TX 77084, and glucose were purchased from Merck. Sodium hydroxide (NaOH) was obtained from Mojallali Company, pyrrole (Py) from Merck, and phosphate-buffered saline (PBS) was prepared by mixing stock solutions of NaCl, KCl, KH₂PO₄, and Na₂HPO₄, all of which were purchased from Mojallali Company.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Preparation of MoS₂ Suspensions\u003c/h2\u003e \u003cp\u003e160 mg of MoS₂ nanopowder was dispersed in distilled water to achieve an initial mass concentration of 8 mg\u0026middot;mL⁻\u0026sup1;. The mixture was stirred at 80\u0026deg;C for 2 h. Afterward, the dispersion was placed in a water bath and sonicated for 4 h using an ultrasonic processor with a maximum power of 500 W and an amplitude of 20%. The sonication cycle consisted of 6-second \u0026ldquo;on\u0026rdquo; and 6-second \u0026ldquo;off\u0026rdquo; intervals. The temperature was maintained between 30\u0026deg;C and 50\u0026deg;C throughout the sonication process. A second method involved the use of a bath sonicator under similar conditions, with the temperature being controlled between 40\u0026deg;C and 50\u0026deg;C. Both methods were compared, and the results showed that both achieved acceptable efficacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Synthesis of AgNPs@MoS2/GOA\u003c/h2\u003e \u003cp\u003eThe synthesis of Ag@MoS2/GOA was carried out by mixing 40 mL of MoS₂NSs suspension (2 mg/mL), AgNPs (8 mg/mL), and GO NSs (3.125 mg/mL). The mixture was sonicated for 1 hour. The resulting stable suspension was then transferred to a Teflon-lined autoclave and hydrothermally treated at 150\u0026deg;C for 5 h. The product was subsequently freeze-dried for 24 hours to obtain the final material. (See Scheme 1)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Preparation of the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA-Modified Electrode\u003c/h2\u003e \u003cp\u003eTo prepare the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA-modified electrode, 10 mg of the prepared composite (1 mg/mL) was mixed with 80.1 mg of poly(styrene sulfonate) (PSS) and 70 \u0026micro;L of pyrrole (Py) in 10 mL of PBS. The mixture was sonicated for 1 hour to ensure the uniform distribution of the components within the solution. Pyrrole polymerization was carried out electrochemically, and a 5-\u0026micro;m thick composite layer was deposited onto tantalum (110 \u0026micro;m) and platinum (10 \u0026micro;m) electrodes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Electrochemical Measurements of Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA/W-AuE\u003c/h2\u003e \u003cp\u003eElectrochemical characterization was performed using cyclic voltammetry (CV) with Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA/W-AuE as the working electrode, a platinum wire as the counter electrode, and an Ag/AgCl electrode as the reference electrode. Amperometric measurements were also conducted using a two-electrode system (working electrode and Ag/AgCl as the reference electrode). Glucose concentration detection was carried out by scanning the potential between \u0026minus;\u0026thinsp;0.4 V and 0.65 V at a scanning rate of 100 mV\u0026middot;s⁻\u0026sup1;, and amperometric measurements were performed at 500 mV in NaOH \u003cem\u003esolution.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cp\u003e\u003cstrong\u003e3.1. Characterization of Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) nanocomposite\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.1. SEM, TEM, EDS and mapping characterization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigures\u0026nbsp;1a to 1f illustrate the morphology of AgNPs, GO, GOA, MoS₂/GOA, and Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA), respectively, as characterized by field emission scanning electron microscopy (FE-SEM). Graphene oxide sheets (Figure 1a) were stacked and connected to create a three-dimensional aerogel structure (Figures 1b and 1c), as illustrated in Scheme 1. The Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) nanocomposite was also prepared through in situ hydrothermal synthesis. The TEM image in Figure 2 displays graphene oxide aerogel, MoS₂\u0026nbsp;nanosheets, and Ag nanoparticles. Figure 3 presents the elemental mapping and EDS analysis of the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) nanocomposite. Figure 4a and 4b show images of the electrode wire before and after deposition, as well as FE-SEM images of the electrode surface. Additionally, Figure 4c\u0026ndash;e shows the FE-SEM image of the electrode surface after deposition using the polymerization method.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe composition of Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) was analyzed using energy-dispersive X-ray spectroscopy (EDS), which revealed that the atomic percentages of carbon, oxygen, molybdenum, and silver were 32.90%, 13.89%, 43.82%, and 10.60%, respectively. The percentage of sulfur is expected to be approximately twice that of molybdenum; however, since its peak overlaps with that of molybdenum, there is an error in the measurement. The results of the EDS mapping confirmed that AgNPs were embedded within the MoS\u003csub\u003e2\u003c/sub\u003eNSs and that the MoS₂NSs were distributed within the cavities of the GOA (Figure 3). The particle size of the silver nanoparticles was measured to be 70.41 nm.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eX-ray diffraction characterization, FT-IR and Raman\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;5a shows the XRD patterns of the samples. In this image, the orange curve corresponds to graphene oxide and exhibits a peak at 12.5\u0026deg;, originating from the (001) plane. The blue curve displays a broad peak at 2ϴ = 24\u0026deg;, which clearly indicates the formation of graphene oxide aerogel. The green curve shows the peaks for molybdenum disulfide nanosheets at angles of 58.5\u0026deg; and 33\u0026deg;, which are assigned to the (110) and (100) crystal planes, respectively. It also exhibits peaks at angles of 73\u0026deg;, 60.5\u0026deg;, 50\u0026deg;, 39\u0026deg;, 36\u0026deg;, 33.5\u0026deg;, and 14.5\u0026deg;, which correspond to the (203), (008), (105), (103), (102), (101), and (002) planes, respectively. These peaks are in good agreement with the hexagonal structure predicted by the JCPDS#01-073-1508 card [52]. The curve for the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) composite also shows new peaks at angles of 77.5\u0026deg;, 64.5\u0026deg;, 44.5\u0026deg;, and 38\u0026deg;, in addition to the peaks related to GOA and MoS₂. These new peaks are attributed to the crystalline structure of silver nanoparticles, confirming the face-centered cubic (fcc) structure of silver nanoparticles (JCPDS#01-087-0720) [53].\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 5b, the orange, blue, green, purple, and pink curves correspond to the FT-IR spectra of graphene oxide (GO), graphene oxide aerogel (GOA), molybdenum disulfide (MoS₂) nanostructures, graphene oxide aerogel composited with MoS₂, and the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA) nanocomposite, respectively. For the nanocomposite spectrum, the intense peak located at 660 cm⁻\u0026sup1; can be attributed to the Mo\u0026ndash;S stretching vibration, while the band around 500 cm⁻\u0026sup1;\u0026nbsp;may be due to the S\u0026ndash;S bond. The composite also exhibits a strong and broad O\u0026ndash;H stretching vibration band at 3450 cm⁻\u0026sup1;, a carboxyl or carbonyl C=O stretching band at 1639 cm⁻\u0026sup1;, and an alkoxy O\u0026ndash;C\u0026ndash;O stretching vibration at 1105 cm⁻\u0026sup1;. The prominent peak at 1581 cm⁻\u0026sup1;\u0026nbsp;can be assigned to the carbon double bond [43, 54, 55].\u003c/p\u003e\n\u003cp\u003eRaman spectroscopy was used to study the carbon nanostructure. The Raman spectrum in Figure 5c clearly demonstrates the formation of graphene oxide aerogel and the presence of MoS₂\u0026nbsp;nanostructures in the pink curve, which corresponds to the Ag@MoS\u003csub\u003e2\u003c/sub\u003eNSs/GOA nanocomposite. The orange Raman spectrum represents graphene oxide, which has a D-to-G ratio of 0.84. This ratio increases to 1.004 for GOA in the blue, violet, and pink Raman spectra. In general, the I\u003csub\u003e_D\u003c/sub\u003e/I\u003csub\u003e_G\u003c/sub\u003e ratio quantifies the defects in the lattice and the disruption of conjugation. Similar to previous studies [56], the disorder and conjugation disruption increase with the formation of the aerogel.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Electrochemical characterization for non-enzymatic glucose detector\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.1. Cyclovoltammetry analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;6\u0026nbsp;presents a comparative analysis of the cyclic voltammetry (CV) curves for the base electrode and modified electrodes in the presence of glucose. The base electrode (W/Au) demonstrates the lowest current response, reflecting minimal electrochemical activity. This suggests a limited number of catalytic sites, making it an appropriate reference for evaluating subsequent modifications. The enhanced current response observed in the MoS₂-modified electrode can be attributed to its large surface area and electroactive properties. MoS₂\u0026nbsp;facilitates charge transport and promotes redox reactions, thereby improving glucose oxidation.\u003c/p\u003e\n\u003cp\u003eIn the MoS₂\u0026nbsp;+ Ag-modified electrode, the further increase in current response indicates improved electrical conductivity and enhanced electrocatalytic activity toward glucose oxidation. Silver nanoparticles contribute to faster electron transfer kinetics due to their high electrical conductivity and intrinsic catalytic properties, providing additional active sites for glucose detection. The appearance of new peaks may correspond to silver oxidation/reduction processes involved in glucose electrooxidation. While MoS₂\u0026nbsp;enhances catalytic activity through its layered structure and active edges, silver nanoparticles serve as catalytic centers, further improving electron transfer and glucose sensitivity.\u003c/p\u003e\n\u003cp\u003eThe combination of MoS₂\u0026nbsp;and Ag exhibits a synergistic effect, maximizing the electrochemical response in the presence of glucose. The observed peak shifts and intensifications indicate enhanced electron transfer and improved glucose oxidation efficiency, confirming that each modification progressively enhances the electrode\u0026apos;s performance for glucose sensing.\u003c/p\u003e\n\u003cp\u003eElectrochemical analysis of Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA/W-AuE was conducted to evaluate its electrocatalytic performance for glucose oxidation using cyclic voltammetry (CV) (Figure\u0026nbsp;7) and chronoamperometry (Figure\u0026nbsp;8). The results indicate excellent catalytic activity of the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA)/W-Au electrode. Comparing the CV results in PBS solution (pH 7.0) with those in a 1.0 M NaOH aqueous electrolyte solution shows that the current increase in NaOH solution is significantly greater than that in PBS solution. Therefore, electrochemical detection of glucose using a non-enzymatic method requires alkaline conditions, which were used for subsequent electrochemical measurements. It is expected that in non-enzymatic sensors, where glucose oxidase enzyme is absent, inorganic catalysts require hydroxide ions to detect glucose. As a result, the biosensor exhibits higher sensitivity in NaOH solution. In PBS solution, the hydroxide ions resulting from water dissociation are less abundant and do not contribute significantly to increasing sensitivity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe CV analysis of the Ag@MoS2/GOA/W-Au electrode was conducted to study the effect of increasing glucose concentration, as shown in Figures 6a and 6c for neutral and alkaline environments, respectively. The electrode was placed in a 1.0 M NaOH stock solution at a potential of 0.5 V, and the glucose concentration was gradually increased. The selection of the -0.04 V peak as the quantitative glucose detection signal, which is based on increasing glucose concentrations, was made possible by the positive scan. This scan revealed a significantly higher current at the -0.04 V peak compared to the 0.275 V peak (Figure\u0026nbsp;7c). As the analyte concentration increases, the number of species that lose electrons increases, leading to more electrons circulating in the circuit and a corresponding increase in the measured current [57]. Based on the results from Figure 7c, Figure 7d shows the calibration curve of the MoS₂\u0026nbsp;/Ag@GOA/Ta-Pt electrode for glucose detection. The sensitivity of the sensor was 2.1\u0026nbsp;\u0026times;\u0026nbsp;10⁻\u0026sup3;\u0026nbsp;nA mM⁻\u0026sup1;\u0026nbsp;cm⁻\u0026sup2;\u0026nbsp;(r\u0026sup2;\u0026nbsp;= 0.990) for glucose concentrations ranging from 0.0 to 30.0 mM (equivalent to 0 to 540 mg/dL), and the detection limit was 5.32 \u0026micro;M. Figure 7e shows the CV analysis results of the AgNPs@MoS\u003csub\u003e2\u003c/sub\u003e/GOA)/W-Au electrode at scan rates of 40\u0026ndash;220 mV/s. As evident from Figure 7f, the peak current increases as the electrode scan rate increases.\u003c/p\u003e\n\u003cp\u003eIt is likely that silver nanoparticles are initially oxidized to AgOH and AgO species in the presence of hydroxide ions. This process creates favorable conditions for the oxidation of glucose, during which glucose releases electrons, resulting in current generation.\u003c/p\u003e\n\u003cp\u003eSilver-based electrocatalysts exhibit a distinct mechanism in glucose oxidation compared to transition metals like Ni, Cu, and Co. Unlike these metals, which directly participate in glucose oxidation via the formation of stable metal-glucose complexes, silver acts primarily as an electron mediator rather than a direct catalytic site. The electrochemical oxidation of silver in an alkaline medium leads to the formation of AgO, which serves as an electron acceptor in the oxidation of glucose. This process differs fundamentally from Ni, Cu, and Co, where metal oxyhydroxides (e.g., NiOOH, CuOOH) directly oxidize glucose through redox cycling. The absence of strong metal-glucose interactions in silver-based systems reduces unwanted side reactions, contributing to higher stability and selectivity in non-enzymatic glucose sensing applications. This distinction makes silver a promising candidate for long-term electrochemical sensing, particularly in implantable and continuous monitoring devices [56, 57].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;In PBS (without OH⁻):\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Glucose oxidation (weaker): C\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e \u0026rarr; C\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e + 2e\u0026minus;\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Water hydrolysis: 2H\u003csub\u003e2\u003c/sub\u003eO \u0026rarr; 2H\u003csub\u003e2\u003c/sub\u003e + O\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Silver-assisted electron transfer (same): Ag + e\u0026minus; \u0026rarr; Ag+\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eB)\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In Alkaline Environment (OH⁻ present):\u003c/p\u003e\n\u003cp\u003e\u0026bull; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Glucose oxidation with OH⁻: C\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e + 2OH\u0026minus; \u0026rarr; C\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e + 2e\u0026minus; + H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n\u003cp\u003e\u0026bull; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Silver-assisted electron transfer: Ag + e\u0026minus; \u0026rarr; Ag+ \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncreased Electron Transfer in Alkaline Medium:\u0026nbsp;\u003c/strong\u003eIn an alkaline medium, the presence of hydroxide ions (OH⁻)\u0026nbsp;facilitates\u0026nbsp;a more efficient oxidation of glucose. The oxidation reaction of glucose in an alkaline medium\u0026nbsp;involves\u0026nbsp;the direct interaction of glucose with OH⁻\u0026nbsp;ions, which significantly\u0026nbsp;increases\u0026nbsp;the rate of the reaction. As a result, more electrons\u0026nbsp;are released\u0026nbsp;during the glucose oxidation process, leading to a higher current.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of Hydroxide Ions (OH\u003c/strong\u003e\u003cstrong\u003e⁻\u003c/strong\u003e\u003cstrong\u003e):\u003c/strong\u003eIn alkaline solutions, OH⁻\u0026nbsp;ions play a critical role in enhancing the rate of glucose oxidation by providing additional reaction sites on the electrode and facilitating the oxidation process. This leads to more electrons being transferred to the electrode, which directly correlates with an increase in the peak current observed in the cyclic voltammetry measurements. Additionally, OH⁻\u0026nbsp;ions\u0026nbsp;might help prevent\u0026nbsp;the passivation of the electrode surface, which\u0026nbsp;can sometimes occur\u0026nbsp;in neutral or acidic conditions,\u0026nbsp;reducing\u0026nbsp;the efficiency of electron transfer. Therefore, in alkaline conditions, the overall reaction\u0026nbsp;proceeds\u0026nbsp;more efficiently,\u0026nbsp;yielding\u0026nbsp;higher current.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMore Peaks in the CV Plot:\u003c/strong\u003eThe additional peaks in the cyclic voltammetry plot in an alkaline medium\u0026nbsp;are likely due to\u0026nbsp;multiple electrochemical reactions\u0026nbsp;occurring\u0026nbsp;simultaneously at different potential windows, which\u0026nbsp;is typical\u0026nbsp;in complex systems with multiple active species or reaction pathways. These peaks\u0026nbsp;may represent:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eGlucose oxidation and reduction\u003c/strong\u003e at different electrode potentials, with oxidation \u003cstrong\u003eoccurring\u003c/strong\u003e at one potential and reduction occurring at another.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSide reactions\u003c/strong\u003e, such as the formation and reduction of intermediate species (like glucose oxidation products), which\u0026nbsp;may have\u0026nbsp;their own characteristic redox potentials.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHydroxide ion interactions\u003c/strong\u003e, where OH⁻\u0026nbsp;may participate in various electrochemical reactions alongside glucose oxidation.\u003c/li\u003e\n \u003cli\u003eThe multiple peaks\u0026nbsp;indicate\u0026nbsp;that various electrochemical processes\u0026nbsp;are taking place\u003cstrong\u003e, a\u003c/strong\u003end these \u003cstrong\u003eare\u0026nbsp;\u003c/strong\u003emore likely to occur\u0026nbsp;in an alkaline medium because of the increased number of possible redox reactions between glucose, the electrode surface, and hydroxide ions.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHigher Sensitivity and Resolution:\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003eIn alkaline solutions, the higher concentration of OH⁻\u0026nbsp;ions and the more efficient electrochemical processes contribute to an overall increase in the current and a more detailed electrochemical response. This causes in better resolution of peaks in the CV plot, allowing for the detection of multiple reaction steps that may not be as distinguishable in PBS or neutral solutions. It is probable that silver nanoparticles are first oxidized to AgOH and AgO species in an environment containing hydroxide ions, and then oxidize glucose, converting it to gluconolactone, which is itself reduced.\u003c/p\u003e\n\u003cp\u003eThe enhanced performance of the Ag@MoS₂/GOA sensor in an alkaline medium can be attributed to the increased availability of hydroxide ions (OH⁻), which facilitate the oxidation of glucose. In alkaline conditions, the silver nanoparticles are oxidized to AgOH and AgO species, which act as active sites for glucose oxidation. This process not only increases the rate of electron transfer but also prevents the passivation of the electrode surface, which is a common issue in neutral or acidic environments. The presence of OH⁻\u0026nbsp;ions also stabilizes the intermediate species formed during glucose oxidation, leading to a more efficient and stable electrochemical response.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2. Chronoamperometry Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;8a shows the chronoamperometric spectrum of the platinum electrode in a basic alkaline solution (0.1 M NaOH). As evident, the gradual addition of glucose to the solution causes an increase in the current. The stepwise increase in current density corresponds to the increase in glucose concentration every 60 seconds, and the trend of increasing current density maintains a broad linear relationship in the glucose concentration range of 0.005\u0026ndash;22.0 mM. In fact, the detection limit represents the lowest concentration of a solute that an analytical system can reliably discriminate. Additionally, the sensitivity of the sensor is determined by the slope (m) of the calibration equation [58].\u003c/p\u003e\n\u003cp\u003eThe electrode shows a linear response between 1.0 and 10.0 mM (equivalent to 18 to 180 mg/dL). The calculated sensitivity for this electrode is 546.37 nA mM⁻\u0026sup1; cm⁻\u0026sup2;, and the limit of detection (LOD) is 53.29\u0026nbsp;\u0026mu;M. For concentrations between 10.0 and 22.0 mM (equivalent to 180 to 440 mg/dL), the sensitivity is 22.18 nA mM⁻\u0026sup1;\u0026nbsp;cm⁻\u0026sup2;. For glucose concentrations ranging from 5.0 to 1000.0 \u0026mu;M, the sensitivity was calculated to be 0.24 nA mM⁻\u0026sup1;\u0026nbsp;cm⁻\u0026sup2;. Sensitivity is defined as the slope of the curve generated when the measurement results are plotted against the determined concentrations. This definition of sensitivity corresponds to the slope of the analytical calibration curve. The lower limit of detection is defined as the level below which detection is impossible with a certain degree of certainty [59-68].\u003c/p\u003e\n\u003cp\u003eThe linear range, detection limit, and sensitivity of comparable materials that have been developed and reported elsewhere are contrasted in Table 1.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Stability and reproducibility of AgNPs@MoS\u003csub\u003e2\u003c/sub\u003e/GOA/W-AuE\u003c/strong\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eAnother crucial factor in assessing the lifespan and effectiveness of a glucose biosensor is its stability. The stability of the AgNPs@MoS2/GOA/W-AuE biosensor was investigated over a period of 30 days, as shown in Figure\u0026nbsp;8, with a stability of 86% observed for the sensor. It exhibited significantly higher stability for glucose detection compared to other non-enzymatic sensors. To evaluate the repeatability of the Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA)/W-AuE sensor, the response of six distinct electrodes to a solution with a constant glucose concentration of 5.0 mM was measured. The relative standard deviation (RSD) of 2.20%, as shown in Figure\u0026nbsp;9, indicates that the reproducibility of the Ag@(MoS\u003csub\u003e2\u003c/sub\u003e/GOA)/W-AuE biosensor is excellent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Selectivity of Ag@MoS\u003csub\u003e2\u003c/sub\u003e/GOA/W-AuE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe selectivity parameter for a sensor refers to its ability to distinguish a specific analyte from other analytes in a sample containing potential contaminants. The non-enzymatic glucose detection method has the capacity to oxidize species such as citric acid, ascorbic acid, fructose, and sucrose, which are present in human blood alongside glucose. Human blood glucose levels typically range from 4.0 to 7.0 mM (70 to 130 mg/dL) [2, 34], which exceeds the levels of ascorbic acid (0.125 mM), fructose (0.36\u0026ndash;0.75 mM) [64], and sucrose (3.9\u0026ndash;5.6 mM) [35]. In this work, the selectivity of the Ag@MoS2/GOA/W-AuE \u003cem\u003ebiosensor\u0026nbsp;was comprehensively investigated by detecting glucose at a concentration of\u0026nbsp;6.0 mM\u0026nbsp;in a stock\u003c/em\u003e solution of 1 mM NaOH containing interfering agents at ratios of 1:50 (citric acid to glucose), 1:10 (fructose), 1:10 (ascorbic acid), and 1:10 (sucrose). As shown in Figure 10, the responses of the AgNPs@MoS2/GOA/W-AuE biosensor to other interferents were minimal, while the biosensor exhibited a significant response to glucose. The results demonstrate that the AgNPs@(MoS2/GOA)/W-AuE biosensor is highly selective for non-enzymatic glucose detection.\u003c/p\u003e\n\u003cp\u003eThe long-term stability of the Ag@MoS₂/GOA sensor, retaining 86% of its initial response after 30 days, is a significant improvement over many existing non-enzymatic glucose sensors. This high stability can be attributed to the robust structure of the graphene oxide aerogel, which prevents the aggregation of AgNPs and MoS₂ nanosheets, thereby maintaining the active surface area over time. Additionally, the sensor\u0026apos;s excellent selectivity against common interferents such as ascorbic acid, fructose, and citric acid is due to the specific catalytic properties of AgNPs and the unique electronic structure of MoS₂, which preferentially catalyze glucose oxidation over other species.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Special Characteristics and Performance of the Prepared Electrode\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe electrochemical performance of the Ag@MoS2/GOA/W-AuE-based glucose sensor was compared with several previously reported non-enzymatic glucose sensors in terms of key performance metrics, including material composition, sensitivity, detection limit, linear range, stability, reproducibility, and potential applications. As shown in \u003cstrong\u003eTable 2\u003c/strong\u003e, the proposed sensor demonstrates exceptional performance across all these parameters.\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003eAg@MoS2/GOA/W-AuE\u003c/strong\u003e sensor developed in this study exhibits excellent stability, retaining 86% of its initial response after 30 days, along with high reproducibility (\u003cstrong\u003e2.20% RSD\u003c/strong\u003e). Additionally, its compact design enhances its suitability for implantable biomedical applications. These characteristics make it a strong candidate for long-term, non-enzymatic glucose detection in medical and implantable settings.\u003c/p\u003e\n\u003cp\u003eCompared to other non-enzymatic glucose sensors reported in the literature, the Ag@MoS₂/GOA sensor demonstrates superior performance in terms of sensitivity, detection limit, and linear range. For instance, sensors based on CuO or NiO nanostructures often suffer from limited stability and selectivity, whereas the incorporation of AgNPs and MoS₂\u0026nbsp;in our design significantly enhances both stability and selectivity. The unique three-dimensional structure of the graphene oxide aerogel (GOA) further contributes to the high surface area and efficient mass transfer, which are critical for achieving high sensitivity and low detection limits. These advantages make the Ag@MoS₂/GOA sensor a promising candidate for practical applications in continuous glucose monitoring\u003c/p\u003e\n\u003cp\u003eThe mechanism of glucose detection in non-enzymatic sensors relies on the direct electrochemical oxidation of glucose on the surface of the electrode. In the case of the Ag@MoS₂/GOA nanocomposite, the presence of silver nanoparticles (AgNPs) plays a crucial role in facilitating electron transfer due to their high electrical conductivity and catalytic activity. The MoS₂\u0026nbsp;nanosheets provide a large surface area and active sites for glucose adsorption, while the graphene oxide aerogel (GOA) enhances the overall conductivity and stability of the electrode. The synergistic effect of these components results in a highly efficient glucose oxidation process, which is further amplified in alkaline conditions due to the presence of hydroxide ions (OH⁻) that promote the oxidation reaction\u003cspan dir=\"RTL\"\u003e.\u003c/span\u003e\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eA one-step hydrothermal synthesis approach was used to successfully create a highly sensitive non-enzymatic biosensor for glucose detection based on the Ag@MoS2/GOA nanocomposite. The morphological structure of Ag@MoS2/GOA provides a significant number of active sites for glucose electrooxidation. The nanocomposite was deposited by polymerization onto a 1 cm layer at the beginning of the W/Au electrode wire. The AgNPs@MoS2/GOA/W-AuE biosensor responds well to glucose concentrations ranging from 1.0 to 10.0 mM, with sensitivity and limit of detection (LOD) values of 546.37 nA mM⁻\u0026sup1; cm⁻\u0026sup2; and 53.29 \u0026micro;M, respectively. The AgNPs@MoS2/GOA-based glucose sensor exhibits exceptional selectivity against interfering species, acceptable repeatability, a wide linear range, and stability, indicating its potential as a non-enzymatic electrochemical glucose sensor. Silver nanoparticles are oxidized in the presence of the supporting electrolyte NaOH (0.1 M), promoting glucose redox reactions. The biosensor can be used in two environments: its performance is highly favorable in an alkaline environment but can be further improved in a PBS environment.\u003c/p\u003e \u003cp\u003e \u003cb\u003eOutlook\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Ag@MoS₂/GOA sensor developed in this study holds great promise for various applications, including continuous glucose monitoring in diabetic patients and glucose detection in fermentation processes. The sensor's high sensitivity, wide linear range, and excellent stability make it suitable for integration into wearable devices or implantable sensors. Future research could focus on further optimizing the sensor's performance by exploring different ratios of AgNPs, MoS₂, and GOA, as well as investigating the sensor's behavior in real biological samples such as blood or interstitial fluid.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by Behyaar sanaat Sepahan Company.\u003c/p\u003e\n\u003cp\u003eThis work was done under support of Iran national science foundation (Grant no. 4039256).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have\u0026nbsp;no conflict of interest\u0026nbsp;with any individual, company, or organization concerning this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All authors contributed in analysis, wrting and editing manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eY. Hu, X. Wang, W. Li, Y. Lai, Y. Chen, Z. Wei and H. Yang,\u0026ldquo;in Metal-organic frameworks and related materials for nonenzymatic electrochemical glucose sensorsˮ, International Journal of Electrochemical Science 100466, 2024.\u003c/li\u003e\n\u003cli\u003eA. Chadt and H. Al-Hasani,\u0026ldquo;in Glucose transporters in adipose tissue, liver, and skeletal muscle in metabolic health and diseaseˮ, Pfl\u0026uuml;gers Archiv-European Journal of Physiology 472, 1273-1298, 2020.\u003c/li\u003e\n\u003cli\u003eH.-S. Han, G. Kang, J. S. Kim, B. H. Choi and S.-H. Koo,\u0026ldquo;in Regulation of glucose metabolism from a liver-centric perspectiveˮ, Experimental \u0026amp; molecular medicine 48, e218-e218, 2016.\u003c/li\u003e\n\u003cli\u003eP. Preechakasedkit, N. Nawaukkaratharnant, K. Teekayupak, A. Lomae and N. Ruecha,\u0026ldquo;in Single-preparation rGO/Cu\u0026ndash;Cu2O nanocomposite-modified electrode integrating NaOH immobilized polymer blend film for one-step nonenzymatic glucose detectionˮ, Journal of Science: Advanced Materials and Devices 8, 100535, 2023.\u003c/li\u003e\n\u003cli\u003eP. Punnoy, P. Preechakasedkit, C. Aumnate, N. Rodthongkum, P. Potiyaraj and N. Ruecha,\u0026ldquo;in Polyvinyl alcohol/starch modified cotton thread surface as a novel colorimetric glucose sensorˮ, Materials Letters 299, 130076, 2021.\u003c/li\u003e\n\u003cli\u003eZ. Li, Y. Zhu, W. Zhang, C. Xu, Y. Pan and Y. Zhao,\u0026ldquo;in A low-cost and high sensitive paper-based microfluidic device for rapid detection of glucose in fruitˮ, Food analytical methods 10, 666-674, 2017.\u003c/li\u003e\n\u003cli\u003eD. Bruen, C. Delaney, L. Florea and D. Diamond,\u0026ldquo;in Glucose sensing for diabetes monitoring: recent developmentsˮ, Sensors 17, 1866, 2017.\u003c/li\u003e\n\u003cli\u003eC. E. F. Do Amaral and B. Wolf,\u0026ldquo;in Current development in non-invasive glucose monitoringˮ, Medical engineering \u0026amp; physics 30, 541-549, 2008.\u003c/li\u003e\n\u003cli\u003eR. Badugu, J. R. Lakowicz and C. D. Geddes ˮin Ophthalmic glucose monitoring using disposable contact lensesˮ, Springer, pp. 363-397, 2005.\u003c/li\u003e\n\u003cli\u003eR. Badugu, J. R. Lakowicz and C. D. Geddes,\u0026ldquo;in Fluorescence sensors for monosaccharides based on the 6-methylquinolinium nucleus and boronic acid moiety: potential application to ophthalmic diagnosticsˮ, Talanta 65, 762-768, 2005.\u003c/li\u003e\n\u003cli\u003eH. Sun, P. Saeedi, S. Karuranga, M. Pinkepank, K. Ogurtsova, B. B. Duncan, C. Stein, A. Basit, J. C. Chan and J. C. Mbanya,\u0026ldquo;in IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045ˮ, Diabetes research and clinical practice 183, 109119, 2022.\u003c/li\u003e\n\u003cli\u003eP. Lu, Y. Lei, S. Lu, Q. Wang and Q. Liu,\u0026ldquo;in Three-dimensional roselike \u0026alpha;-Ni (OH) 2 assembled from nanosheet building blocks for non-enzymatic glucose detectionˮ, Analytica chimica acta 880, 42-51, 2015.\u003c/li\u003e\n\u003cli\u003eS. Bakhshi, M. Rahmanipour, A. R. Amirsoleimani, M. Rezazadeh, H. Siampour and A. Moshaii,\u0026ldquo;in Nanopyramid copper structures on screen-printed carbon electrode for high-performance non-enzymatic glucose sensing: A cost-effective and scalable approachˮ, Sensing and Bio-Sensing Research 46, 100706, 2024.\u003c/li\u003e\n\u003cli\u003eM. Adeel, M. M. Rahman, I. Caligiuri, V. Canzonieri, F. Rizzolio and S. Daniele,\u0026ldquo;in Recent advances of electrochemical and optical enzyme-free glucose sensors operating at physiological conditionsˮ, Biosensors and Bioelectronics 165, 112331, 2020.\u003c/li\u003e\n\u003cli\u003eL. C. Clark Jr and C. Lyons,\u0026ldquo;in Electrode systems for continuous monitoring in cardiovascular surgeryˮ, Annals of the New York Academy of sciences 102, 29-45, 1962.\u003c/li\u003e\n\u003cli\u003eS. J. Updike and G. P. Hicks,\u0026ldquo;in The enzyme electrodeˮ, Nature 214, 986-988, 1967.\u003c/li\u003e\n\u003cli\u003eG. Guilbault and G. Lubrano,\u0026ldquo;in An enzyme electrode for the amperometric determination of glucoseˮ, Analytica chimica acta 64, 439-455, 1973.\u003c/li\u003e\n\u003cli\u003eC. Chen, Q. Xie, D. Yang, H. Xiao, Y. Fu, Y. Tan and S. Yao,\u0026ldquo;in Recent advances in electrochemical glucose biosensors: a reviewˮ, Rsc Advances 3, 4473-4491, 2013.\u003c/li\u003e\n\u003cli\u003eS.-C. Hung,\u0026ldquo;in Highly Sensitive Non-Enzymatic Glucose Sensing Using Ni Nanowires and Graphene Thin Film on the Gate Area of Extended Gate Electric Double-Layer Field-Effect Transistorˮ, Heliyon 2025.\u003c/li\u003e\n\u003cli\u003eA. Aygun, E. Ozveren, E. Halvaci, D. Ikballi, R. N. E. Tiri, C. Catal, M. Bekmezci, A. Ozengul, I. Kaynak and F. Sen,\u0026ldquo;in The performance of a very sensitive glucose sensor developed with copper nanostructure-supported nitrogen-doped carbon quantum dotsˮ, RSC advances 14, 34964-34970, 2024.\u003c/li\u003e\n\u003cli\u003eJ. Yang, J. Yin and L. Xu,\u0026ldquo;in Electrochemical non-enzymatic glucose sensors based on CuO nanostructuresˮ, Journal of Alloys and Compounds 177796, 2024.\u003c/li\u003e\n\u003cli\u003eV. Sabaghi, P. Rashidi-Ranjbar, F. Davar and E. Sharif-Paghaleh,\u0026ldquo;in Development of multifunctional MnO2-based nanoplatforms for hypoxia modulation/T1-weighted MRI/optical biosensing and targeted drug deliveryˮ, Journal of Drug Delivery Science and Technology 91, 105190, 2024.\u003c/li\u003e\n\u003cli\u003eM. Adeel, K. Asif, M. M. Rahman, S. Daniele, V. Canzonieri and F. Rizzolio,\u0026ldquo;in Glucose detection devices and methods based on metal\u0026ndash;organic frameworks and related materialsˮ, Advanced Functional Materials 31, 2106023, 2021.\u003c/li\u003e\n\u003cli\u003eH. Shahba and M. Sabet,\u0026ldquo;in Two-step and green synthesis of highly fluorescent carbon quantum dots and carbon nanofibers from pine fruitˮ, Journal of Fluorescence 30, 927-938, 2020.\u003c/li\u003e\n\u003cli\u003eB. Yuan, C. Xu, L. Liu, Q. Zhang, S. Ji, L. Pi, D. Zhang and Q. Huo,\u0026ldquo;in Cu2O/NiOx/graphene oxide modified glassy carbon electrode for the enhanced electrochemical oxidation of reduced glutathione and nonenzyme glucose sensorˮ, Electrochimica Acta 104, 78-83, 2013.\u003c/li\u003e\n\u003cli\u003eX. Li and H. Zhu,\u0026ldquo;in Two-dimensional MoS2: Properties, preparation, and applicationsˮ, Journal of Materiomics 1, 33-44, 2015.\u003c/li\u003e\n\u003cli\u003eJ. A. Wilson and A. Yoffe,\u0026ldquo;in The transition metal dichalcogenides discussion and interpretation of the observed optical, electrical and structural propertiesˮ, Advances in Physics 18, 193-335, 1969.\u003c/li\u003e\n\u003cli\u003eI. A. Rahman and A. Purqon, Journal of Physics: Conference Series p. 012026, 2017.\u003c/li\u003e\n\u003cli\u003eT. D. Van, N. D. T. Thuy, T. D. V. Phuong, N. N. Thi, T. N. Thi, T. N. Phuong, T. V. Van, H. Vuong-Pham and T. P. Dinh,\u0026ldquo;in High-performance nonenzymatic electrochemical glucose biosensor based on AgNP-decorated MoS2 microflowersˮ, Current Applied Physics 43, 116-123, 2022.\u003c/li\u003e\n\u003cli\u003eF. Xu, M. Wu, G. Ma, H. Xu and W. Shang,\u0026ldquo;in Copper-molybdenum sulfide/reduced graphene oxide hybrid with three-dimensional wrinkles and pores for enhanced amperometric detection of glucoseˮ, Microchemical Journal 159, 105432, 2020.\u003c/li\u003e\n\u003cli\u003eX. Sui, L. Zhang, J. Li, K. Doyle‐Davis, R. Li, Z. Wang and X. Sun,\u0026ldquo;in Advanced support materials and interactions for atomically dispersed noble‐metal catalysts: from support effects to design strategiesˮ, Advanced Energy Materials 12, 2102556, 2022.\u003c/li\u003e\n\u003cli\u003eF. Guo, H. Yang, L. Liu, Y. Han, A. M. Al-Enizi, A. Nafady, P. E. Kruger, S. G. Telfer and S. Ma,\u0026ldquo;in Hollow capsules of doped carbon incorporating metal@ metal sulfide and metal@ metal oxide core\u0026ndash;shell nanoparticles derived from metal\u0026ndash;organic framework composites for efficient oxygen electrocatalysisˮ, Journal of Materials Chemistry A 7, 3624-3631, 2019.\u003c/li\u003e\n\u003cli\u003eH. Zengin and G. Kalaycı,\u0026ldquo;in Synthesis and characterization of polyaniline/activated carbon composites and preparation of conductive filmsˮ, Materials Chemistry and Physics 120, 46-53, 2010.\u003c/li\u003e\n\u003cli\u003eK. P. Sharma, M. Shin, G. P. Awasthi, S. Cho and C. Yu,\u0026ldquo;in One-step hydrothermal synthesis of CuS/MoS2 composite for use as an electrochemical non-enzymatic glucose sensorˮ, Heliyon 10, 2024.\u003c/li\u003e\n\u003cli\u003eL. Fang, F. Wang, Z. Chen, Y. Qiu, T. Zhai, M. Hu, C. Zhang and K. Huang,\u0026ldquo;in Flower-like MoS2 decorated with Cu2O nanoparticles for non-enzymatic amperometric sensing of glucoseˮ, Talanta 167, 593-599, 2017.\u003c/li\u003e\n\u003cli\u003eX. Lin, Y. Ni and S. Kokot,\u0026ldquo;in Electrochemical and bio-sensing platform based on a novel 3D Cu nano-flowers/layered MoS2 compositeˮ, Biosensors and Bioelectronics 79, 685-692, 2016.\u003c/li\u003e\n\u003cli\u003eY. Jiang, Y. Li, Y. Li and S. Li,\u0026ldquo;in A sensitive enzyme-free hydrogen peroxide sensor based on a chitosan\u0026ndash;graphene quantum dot/silver nanocube nanocomposite modified electrodeˮ, Analytical Methods 8, 2448-2455, 2016.\u003c/li\u003e\n\u003cli\u003eZ. Zhao, J. Liu, W. Wang, J. Zhang, G. Li, J. Liu, K. Lian, J. Hu and S. Zhuiykov,\u0026ldquo;in Ag functionalized molybdenum disulfide hybrid nanostructures for selective and sensitive amperometric hydrogen peroxide detectionˮ, International Journal of Electrochemical Science 12, 8761-8776, 2017.\u003c/li\u003e\n\u003cli\u003eW. Yu, X. Bai, G. Tian, J. Deng, Z. Zhang, Q. Ke, S. Liu and C. Huang,\u0026ldquo;in Robust bonding of Ag nanoparticles on bicomponent fibers enabled highly reliable, multi-functional piezoresistive sensingˮ, Chemical Engineering Journal 503, 158414, 2025.\u003c/li\u003e\n\u003cli\u003eM. Baghayeri, A. Amiri and S. Farhadi,\u0026ldquo;in Development of non-enzymatic glucose sensor based on efficient loading Ag nanoparticles on functionalized carbon nanotubesˮ, Sensors and Actuators B: Chemical 225, 354-362, 2016.\u003c/li\u003e\n\u003cli\u003eJ. Li, H. Hu, H. Li and C. Yao,\u0026ldquo;in Recent developments in electrochemical sensors based on nanomaterials for determining glucose and its byproduct H 2 O 2ˮ, Journal of Materials Science 52, 10455-10469, 2017.\u003c/li\u003e\n\u003cli\u003eB. Fall, D. D. Sall, M. H\u0026eacute;madi, A. K. D. Diaw, M. Fall, H. Randriamahazaka and S. Thomas,\u0026ldquo;in Highly efficient non-enzymatic electrochemical glucose sensor based on carbon nanotubes functionalized by molybdenum disulfide and decorated with nickel nanoparticles (GCE/CNT/MoS2/NiNPs)ˮ, Sensors and Actuators Reports 5, 100136, 2023.\u003c/li\u003e\n\u003cli\u003eL. Zhao, X.-L. Sui, J.-L. Li, J.-J. Zhang, L.-M. Zhang and Z.-B. Wang,\u0026ldquo;in Ultra-fine Pt nanoparticles supported on 3D porous N-doped graphene aerogel as a promising electro-catalyst for methanol electrooxidationˮ, Catalysis Communications 86, 46-50, 2016.\u003c/li\u003e\n\u003cli\u003eL. Ruiyi, Z. Juanjuan, W. Zhouping, L. Zaijun, L. Junkang, G. Zhiguo and W. Guangli,\u0026ldquo;in Novel graphene-gold nanohybrid with excellent electrocatalytic performance for the electrochemical detection of glucoseˮ, Sensors and Actuators B: Chemical 208, 421-428, 2015.\u003c/li\u003e\n\u003cli\u003eM. B. Lim, M. Hu, S. Manandhar, A. Sakshaug, A. Strong, L. Riley and P. J. Pauzauskie,\u0026ldquo;in Ultrafast sol\u0026ndash;gel synthesis of graphene aerogel materialsˮ, Carbon 95, 616-624, 2015.\u003c/li\u003e\n\u003cli\u003eR. Li, T. Yang, Z. Li, Z. Gu, G. Wang and J. Liu,\u0026ldquo;in Synthesis of palladium@ gold nanoalloys/nitrogen and sulphur-functionalized multiple graphene aerogel for electrochemical detection of dopamineˮ, Analytica Chimica Acta 954, 43-51, 2017.\u003c/li\u003e\n\u003cli\u003eH.-P. Cong, J.-F. Chen and S.-H. Yu,\u0026ldquo;in Graphene-based macroscopic assemblies and architectures: an emerging material systemˮ, Chemical Society Reviews 43, 7295-7325, 2014.\u003c/li\u003e\n\u003cli\u003eY. Jiang, H. Shao, C. Li, T. Xu, Y. Zhao, G. Shi, L. Jiang and L. Qu,\u0026ldquo;in Versatile Graphene Oxide Putty-Like Materialˮ, Advanced Materials (Deerfield Beach, Fla.) 28, 10287-10292, 2016.\u003c/li\u003e\n\u003cli\u003eW. Liu, Z. Wang, W. Yan, Z. Zhao, L. Shi, L. Huang, Y. Liu, X. He and S. Cui,\u0026ldquo;in Construction of ultra-sensitive surface-enhanced Raman scattering substrates based on 3D graphene oxide aerogelsˮ, Carbon 202, 389-397, 2023.\u003c/li\u003e\n\u003cli\u003eM. Mazloum-Ardakani, N. Shaker-Ardakani and F. Farbod,\u0026ldquo;in Highly efficient enzyme less glucose sensor based on cross-linked nitrogen-doped graphene aerogel incorporated with ytterbium oxide and decorated with nickel nitride nanoparticlesˮ, Sensors International 5, 100290, 2024.\u003c/li\u003e\n\u003cli\u003eJ. Yang, C. Zhang, Y. Niu, J. Huang, X. Qian and K.-Y. Wong,\u0026ldquo;in N-doped C-CoS2@ CoS2/MoS2 nano polyhedrons with hierarchical yolk-shelled structures as bifunctional catalysts for enhanced photovoltaics and hydrogen evolutionˮ, Chemical Engineering Journal 409, 128293, 2021.\u003c/li\u003e\n\u003cli\u003eA. K. Alzubaidi, W. J. Al-Kaabi, A. A. Ali, S. Albukhaty, H. Al-Karagoly, G. M. Sulaiman, M. Asiri and Y. Khane,\u0026ldquo;in Green synthesis and characterization of silver nanoparticles using flaxseed extract and evaluation of their antibacterial and antioxidant activitiesˮ, Applied Sciences 13, 2182, 2023.\u003c/li\u003e\n\u003cli\u003eZ. \u0026Ccedil;iplak, N. Yildiz and A. \u0026Ccedil;alimli,\u0026ldquo;in Investigation of Graphene/Ag Nanocomposites Synthesis Parameters for Two Different Synthesis Methodsˮ, Fullerenes, Nanotubes and Carbon Nanostructures 23, 361-370, 2015.\u003c/li\u003e\n\u003cli\u003eW. Gul and H. Alrobei,\u0026ldquo;in Effect of graphene oxide nanoparticles on the physical and mechanical properties of medium density fiberboardˮ, Polymers 13, 1818, 2021.\u003c/li\u003e\n\u003cli\u003eQ. Tang, S. Luo, H. Gao, Y. Fan, W. Bao, Y. Gao, Y. Sun and C. Yang,\u0026ldquo;in N-doped graphene aerogel cathode with internal aeration for enhanced degradation of p-nitrophenol by electro-Fenton processˮ, Environmental Science and Pollution Research 30, 23481-23493, 2023.\u003c/li\u003e\n\u003cli\u003eF. J. Rahmania, T. Imae and J. P. Chu,\u0026ldquo;in Electrochemical nonenzymatic glucose sensors catalyzed by Au nanoclusters on metallic nanotube arrays and polypyrrole nanowiresˮ, Journal of Colloid and Interface Science 657, 567-579, 2024.\u003c/li\u003e\n\u003cli\u003eY. Wang, Q. Wang, G. Chai, W. Fan, Q. Shi, W. Zhang, J. Mao, J. Xie, R. Wei and Q. Zhang,\u0026ldquo;in A flexible electrochemical glucose sensing platform based on an electrospun PVA mat covered with in situ grown silver nanoparticles and a mixed self-assembled monolayer of glucose oxidase and ferroceneˮ, Analyst 148, 3724-3729, 2023.\u003c/li\u003e\n\u003cli\u003eS. Y. Ejeta and T. Imae,\u0026ldquo;in Selective colorimetric and electrochemical detections of Cr (III) pollutant in water on 3-mercaptopropionic acid-functionalized gold plasmon nanoparticlesˮ, Analytica Chimica Acta 1152, 338272, 2021.\u003c/li\u003e\n\u003cli\u003eˮin Chapter 7 - Sensitivity and Limit of Detectionˮ, Vol. 2 Eds.: D.L. Massart, B.G.M. Vandeginste, S.N. Deming, Y. Michotte and L. Kaufman), Elsevier, pp. 107-114, 2003.\u003c/li\u003e\n\u003cli\u003eM. A. Deshmukh, B.-C. Kang and T.-J. Ha,\u0026ldquo;in Non-enzymatic electrochemical glucose sensors based on polyaniline/reduced-graphene-oxide nanocomposites functionalized with silver nanoparticlesˮ, Journal of Materials Chemistry C 8, 5112-5123, 2020.\u003c/li\u003e\n\u003cli\u003eM. S. Gijare, S. R. Chaudhari, S. Ekar, S. F. Shaikh, A. M. Al-Enizi, B. Pandit and A. D. Garje,\u0026ldquo;in Green synthesis of reduced graphene oxide (rGO) and its applications in non-enzymatic electrochemical glucose sensorsˮ, Journal of Photochemistry and Photobiology A: Chemistry 450, 115434, 2024.\u003c/li\u003e\n\u003cli\u003eS. Phetsang, P. Kidkhunthod, N. Chanlek, J. Jakmunee, P. Mungkornasawakul and K. Ounnunkad,\u0026ldquo;in Copper/reduced graphene oxide film modified electrode for non-enzymatic glucose sensing applicationˮ, Scientific reports 11, 9302, 2021.\u003c/li\u003e\n\u003cli\u003eK. P. Sharma, M. Shin, K. Kim, K. Woo, G. P. Awasthi and C. Yu,\u0026ldquo;in Copper nanoparticles/polyaniline/molybdenum disulfide composite as a nonenzymatic electrochemical glucose sensorˮ, Heliyon 9, 2023.\u003c/li\u003e\n\u003cli\u003eT. Kawasaki, H. Akanuma and T. Yamanouchi,\u0026ldquo;in Increased fructose concentrations in blood and urine in patients with diabetesˮ, Diabetes care 25, 353-357, 2002.\u003c/li\u003e\n\u003cli\u003eK. Anderson, B. Poulter, J. Dudgeon, S.-E. Li and X. Ma,\u0026ldquo;in A highly sensitive nonenzymatic glucose biosensor based on the regulatory effect of glucose on electrochemical behaviors of colloidal silver nanoparticles on MoS2ˮ, Sensors 17, 1807, 2017.\u003c/li\u003e\n\u003cli\u003eG. Jeevanandham, R. Jerome, N. Murugan, M. Preethika, K. Vediappan and A. K. Sundramoorthy,\u0026ldquo;in Nickel oxide decorated MoS 2 nanosheet-based non-enzymatic sensor for the selective detection of glucoseˮ, RSC advances 10, 643-654, 2020.\u003c/li\u003e\n\u003cli\u003eL.-Y. Xiong, Y.-J. Kim, W.-C. Seo, H.-K. Lee, W.-C. Yang and W.-F. Xie,\u0026ldquo;in High-performance non-enzymatic glucose sensor based on Co3O4/rGO nanohybridˮ, Rare Metals 42, 3046-3053, 2023.\u003c/li\u003e\n\u003cli\u003eT. Sridara, J. Upan, G. Saianand, A. Tuantranont, C. Karuwan and J. Jakmunee,\u0026ldquo;in Non-enzymatic amperometric glucose sensor based on carbon nanodots and copper oxide nanocomposites electrodeˮ, Sensors 20, 808, 2020.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eperformance comparison between the created non-enzyme glucose biosensor AgNPs@(MoS₂NSs/GOA)/W-AuE and other non-enzyme glucose biosensors.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eModified Electrodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eMethod\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eLinear range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eDetection Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eAg\u0026ndash;PANI/rGO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.1 \u0026ndash; 50 \u0026mu;M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.79 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eAuNC(c10)/PPyNW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.05 \u0026ndash; 10 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e14.5 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e48.2 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eAgNPs/MoS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.0 \u0026ndash; 15 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e46.5 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.0 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003erGO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.2 \u0026ndash; 10 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e19.17 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.901 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eCu (II)/rGO/SPCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003cp\u003eAmperometry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.1\u0026ndash;12.5 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e171.95 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e65 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[5]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eCuS/MoS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003cp\u003eAmperometry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.1\u0026ndash;11 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e252.71 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.52 (\u0026micro;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eCu/Pani/MoS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003cp\u003eAmperometry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.1\u0026ndash;11 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e69.82 (\u0026micro;A mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.78 (\u0026mu;M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e[7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eAgNPs@(MoS₂NSs/GOA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003cp\u003eAmperometry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.005 \u0026ndash; 1mM\u003c/p\u003e\n \u003cp\u003e1 \u0026ndash; 10 mM\u003c/p\u003e\n \u003cp\u003e10 \u0026ndash; 22 mM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0.24 (nA mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003e546.37 (nA mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003e22.18 (nA mM\u003csup\u003e-1\u003c/sup\u003e cm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e121 (mM)\u003c/p\u003e\n \u003cp\u003e53.29\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(\u0026micro;M)\u003c/p\u003e\n \u003cp\u003e1.32 (mM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eThis work\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eComparison Table of the Proposed Glucose Sensor with Other Similar Sensors:\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensor Composition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (\u0026micro;A\u0026middot;mM⁻\u0026sup1;\u0026middot;cm⁻\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDetection Limit (\u0026micro;M)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLinear Range (mM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerformance Stability (30 days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReproducibility (RSD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStructural Stability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecific Applications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.2129%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgNPs@(MoS₂NSs/GOA) nanocoposite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e546.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e53.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e0.005\u0026ndash;1, 1\u0026ndash;10, 10\u0026ndash;22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e86% retention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e2.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.4032%;\"\u003e\n \u003cp\u003eImplantable biomedical applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eThis work\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eColloidal AgNPs on MoS₂\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e9044.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e0.1\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e80% retention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e3.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePoint-of-care diagnostics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.2129%;\"\u003e\n \u003cp\u003e[8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNiO-decorated MoS₂ nanosheets\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e2310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e0.001\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e78% retention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e4.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eWearable sensors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.2129%;\"\u003e\n \u003cp\u003e[9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo₃O₄/reduced graphene oxide (rGO) nanohybrid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e839.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e0.001\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e75% retention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e5.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNon-invasive glucose monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.2129%;\"\u003e\n \u003cp\u003e[10]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1869%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarbon nanodots (C-dots)/CuO nanocomposites\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.212%;\"\u003e\n \u003cp\u003e5300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8558%;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.6655%;\"\u003e\n \u003cp\u003e0.001\u0026ndash;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7125%;\"\u003e\n \u003cp\u003e82% retention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.855%;\"\u003e\n \u003cp\u003e3.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.57%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eContinuous glucose monitoring (CGM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.2129%;\"\u003e\n \u003cp\u003e[11]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electrochemical detection, Molybdenum disulfide, Graphene oxide aerogel, glucose","lastPublishedDoi":"10.21203/rs.3.rs-6292994/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6292994/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, a Ag@MoS₂/graphene oxide aerogel (GOA) nanocomposite was synthesized and used to fabricate a non-enzymatic glucose sensor. The sensor exhibited a wide linear range (1.0 to 10.0 mM), high sensitivity (546.37 nA mM⁻\u0026sup1; cm⁻\u0026sup2;), and a low detection limit (53.29 \u0026micro;M). The sensor's performance was significantly enhanced in an alkaline environment due to the presence of hydroxide ions, which facilitated glucose oxidation. The sensor also demonstrated excellent selectivity against common interferents and maintained high stability over 30 days. The synergistic effects of AgNPs, MoS₂ nanosheets, and GOA contributed to the sensor's superior electrochemical performance, making it a promising candidate for glucose sensing applications.\u003c/p\u003e","manuscriptTitle":"Electrochemical Glucose Detection Using Ag@MoS₂/Graphene Oxide Aerogel Nanocomposite: A Study on Sensitivity, Stability, and Selectivity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 12:20:52","doi":"10.21203/rs.3.rs-6292994/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-17T05:33:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-10T02:01:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65670614689387285435504729012517100427","date":"2025-07-02T18:19:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-02T06:19:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51177103263028990018965181245714187683","date":"2025-04-23T14:13:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"307226207774454778397452037541430547819","date":"2025-04-23T13:36:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-10T09:28:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-10T08:51:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-10T05:24:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-07T12:17:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-24T08:05:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e63a73a0-f81d-46fe-a5c9-6340c9fdcdf7","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47124087,"name":"Physical sciences/Chemistry/Biochemistry"},{"id":47124088,"name":"Physical sciences/Chemistry/Inorganic chemistry"}],"tags":[],"updatedAt":"2025-12-08T16:03:23+00:00","versionOfRecord":{"articleIdentity":"rs-6292994","link":"https://doi.org/10.1038/s41598-025-25570-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-01 15:58:13","publishedOnDateReadable":"December 1st, 2025"},"versionCreatedAt":"2025-04-15 12:20:52","video":"","vorDoi":"10.1038/s41598-025-25570-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-25570-8","workflowStages":[]},"version":"v1","identity":"rs-6292994","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6292994","identity":"rs-6292994","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}