Evaluation of reduced graphene oxide from cotton waste as an efficient phenol adsorbent in aqueous media

Evaluation of reduced graphene oxide from cotton waste as an efficient phenol adsorbent in aqueous media | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of reduced graphene oxide from cotton waste as an efficient phenol adsorbent in aqueous media Lucas Antônio da Silva de Jesus, Rivaldo Leonn Bezerra Cabral, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4415982/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Aug, 2024 Read the published version in Environmental Science and Pollution Research → Version 1 posted 6 You are reading this latest preprint version Abstract The elimination of organic substances, as well as phenol, in conventional and biological process, has been considered a challenge for the petroleum industry due to the significant oxygen demand in the receiving bodies of water and its toxicity to aquatic life. In this work, reduced graphene oxide (rGO), obtained from cellulosic biomass (CB-rGO), as cotton waste, was employed as a phenol adsorbent in an aqueous solution simulating refinery effluent. The CB-rGO was characterized using HRTEM, RAMAN, XRD, FTIR, BET and Zeta analysis. The behavior of variables such as pH, contact time, temperature, CB-rGO mass and adsorbate concentration on the characteristics of the adsorption process were continuously investigated. These parameters of the adsorption process were evaluated across a range of adsorbent concentrations from 100–300 mg.L − 1 , pH in the range of 2–11, contact time of 20–60 min and temperature of 20–60°C. The adsorption isotherm data were better described by the Freundlich equation compared to the Langmuir and Sips models, despite the negligible difference in R 2 values. Additionally, the kinetics study of confirmed pseudo-second order as the most appropriate model. Mechanism diffusion was analyzed using the Boyd model and confirmed to be the rate-limiting step in the adsorption process. The endothermic nature of this CB-rGO adsorption process with phenol was confirmed by verifying the thermodynamic data. This successful removal of phenol from synthetic effluent highlights the promising potential of this emerging adsorbent compared to other materials identified to remove this contaminant. Cotton waste adsorption cellulosic biomass reduced graphene oxide phenol Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Industrial effluents serve as significant pathways for the discharge of considerable organic and inorganic wastes into water bodies, posing a serious environmental risk to plants, humans and animals (Aremu et al. 2020 ). Even at low concentrations, phenol is considered one of the most hazardous pollutants found in these effluents, due to its toxic and carcinogenic properties, and its solubility in water as well as various organic solvents (Aremu et al. 2020 ; Lütke et al. 2019 ). Its presence not only poses risks to human health, causing allergies, cardiovascular diseases and problems with vital organs such as intestine, lungs, liver and brain (Jia and Lua 2008 ), but also exacerbates environmental concerns (Zhang et al. 2019 ; Wang et al. 2019 ). Phenol concentrations in industrial waste typically range from 50-2000 mg.L − 1 (Allahkarami et al. 2023 ). In this context, a variety of biological and physicochemical methods have been utilized to eliminate phenol from effluents. These methods encompass microbial degradation, enzymatic polymerization, chemical oxidation, adsorption, solvent extraction, photocatalytic degradation, and ion exchange (Allahkarami et al. 2023 ; Beker et al. 2010 ). Of these techniques mentioned, adsorption is particularly notable for its ease of implementation and operation, high efficiency, low cost, and regenerative capability (Lütke et al. 2019 ). In this regard, a range of adsorbents, including activated carbon, minerals, and polymers, have been utilized to investigate the adsorption of phenol (Allahkarami et al. 2023 ), with a focus on employing novel adsorbents (Beker et al. 2010 ). Efforts aimed at achieving commercial viability have centered on the creation of cost-effective adsorbents utilizing industrial and agricultural residues. Various biomass, such as cotton spinning waste from the textile industry, and other organic residues, their viability as precursors to this process is constantly examined (Bhatnagar et al. 2015; Devi and Saroha 2016; Hafshejani et al. 2016 ). Nanotechnology appears to have tools that enable the growth of new green materials and processes (Gottardo et al. 2021). Furthermore, the reuse of waste materials to produce value-added goods appears to be the shortest route to achieving the goals set through nanomaterials. Recently, several studies have demonstrated the synthesis of inorganic nanomaterials derived from waste (Abdelbasir et al. 2020 ), spanning from the production of Si (Porrang et al. 2021 ), Ag (Benassai et al. 2021 ), Au (Amiripour et al. 2021 ) nanoparticles to such as graphene, carbon nanotubes and graphene quantum dots, among other carbon-based materials (CNM). CNMs exhibit several remarkable characteristics in diverse industrial sectors (Ebbesen 1996). Graphene, in particular, has attracted increasing interest in research spanning various scientific fields due to its excellent physicochemical, thermal, mechanical, and electrical properties, positioning it as one of the most studied CNMs (Bolotin et al. 2008; Inagaki & Kang 2014; Khanafer & Vafai 2017; Lee et al. 2008; Liu et al. 2019; Munz et al. 2015; Nair et al. 2008; Yu et al. 2015). In addition to graphene, other derivatives of this material can be obtained through oxidation (graphene oxide - GO) and reduction (reduced graphene oxide - rGO). One of the most significant graphene derivatives, features numerous functional groups containing oxygen within its basal plane and at the edges, manifested in the form of epoxy, hydroxyl, and carboxyl groups, as well as a high level of defects in the carbon structure. As a result, this nanomaterial exhibits distinct properties from graphene, such as insulating and hydrophilic electrical behavior, allowing it to form suspensions in aqueous media. rGO is produced through reduction reactions of GO with different reducing agents (Galvão et al. 2023 ). The resultant product from this reaction is a carbonaceous material with a low oxygen content and defects in the basal plane. Considerable efforts have been dedicated to the manufacture of graphene and its variants from a variety of sources (Yan et al. 2020 ). Notably, waste generated from the textile industry has emerged as a promising source, primarily due to its composition of ligno and cellulosic fibers. These materials consist of a biopolymer with dense carbon molecules that can form partially defective sheets resembling the structure of graphite, thus serving as a precursor to reduced graphene (Farid et al. 2022). The presence of residual oxygenated groups, electron domains, high surface area and porosity, and defect density make rGO nanosheets an excellent adsorbent for removing contaminants present in water (Gupta and Khatri 2017 ; Cetinkaya and Ozdemir 2018 ). Based on this context, the objective of this study is to evaluate viability of CB-rGO obtained from solid waste generated in the textile industry for the removal of phenol from aqueous solutions. These characteristics of the phenol adsorption process using CB-rGO as adsorbents were analyzed in different parameters such as solution pH, initial concentration, adsorbent mass, contact time and reaction temperature. The experimental data will assess the suitability of different adsorption, pseudo-first and pseudo-second order kinetic models, in addition to the Langmuir, Freundlich and Sips isotherm models, which helped to describe this adsorption process, offering insights into the mechanisms governing the interaction between phenol and the CB-rGO. Materials and methods Materials Waster from cotton sanding process was collected and donated from Vicunha têxtil S/A. The iron-base catalyst with a purity of ≥ 98.5 (Merck, Germany) and phenol crystal (Êxodo Científica, Brazil) were utilized. Synthesis of CB-rGO Cellulosic biomass graphene reduced (CB-rGO) was synthesized via the top-down method, as shown in Fig. 1 . In this process, 1g of cotton fiber powder was placed in a ceramic crucible along with a solid catalyst weighing 0.1g. After mixing the components, they were transferred to a muffle furnace and subjected to a pyrolysis process at 300°C for 30 min. Subsequently, the resulting powder underwent further processing until it reached a fine, dark consistency. Characterization The morphological characteristics of CB-rGO synthesized from cotton waste were examined using high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED) were performed with the JEM-2100 electron microscope (JEOL, Japan) operating at 200 kV, and with a resolution of 0.2 nm. The crystalline structure of the solid material was evaluated using an X-ray diffractometer (XRD) Miniflex II Rigaku (Bruker, USA) with copper (Cu) radiation, with a power of 30kV and current of 30mA, in the angular region of 10 to 90° with a step of 0.02 and a speed of 5°/min. Raman spectra were recorded from 500 to 3000 cm − 1 using a Raman micro spectrometer (Renishaw, UK) equipped with a 532 nm argon ion laser. Fourier-transform infrared spectroscopy (FTIR) data were obtained using an IR Tracer-100 FTIR spectrometer (Shimadzu, Japan) in the frequency range of 400 to 4000 cm − 1 with a resolution of 4 cm − 1 . From the data obtained from the XRD analysis, calculations of several crystallographic parameters were carried out., including the interlaminar space ( \({d}_{002}\) ) (KAUSHAL; DHAWAN; SINGH 2019), crystal stack height ( \({L}_{c}\) ), in-plane crystallite size ( \({L}_{a}\) ), and the number of graphene layers in the crystal ( \({N}_{c}\) ) (Romero et al. 2018 ), using the Eqs. ( 1 )-( 4 ). $${d}_{002}=\frac{\lambda }{2sen{\theta }_{\left(002\right)}}$$ 1 $${L}_{c}=\frac{{K}_{1}\lambda }{\beta cos{\theta }_{\left(002\right)}}$$ 2 $${L}_{a}=\frac{{K}_{2}\lambda }{\beta cos{\theta }_{\left(100\right)}}$$ 3 $${N}_{c}=\frac{Lc}{{d}_{002}}$$ 4 where \(\lambda\) is the wavelength of CuKα-radiation (0.154 nm), \(\beta\) is the width at half height of the corresponding diffraction peak, \({K}_{1}\) and \({K}_{2}\) are shape factor constants for spherical crystals (0.89) and Warren shape factor (1.84) (Warren and Bodenstein 1965 ), respectively. \({\theta }_{\left(002\right)}\) is the position of the diffraction peak (002), while \({\theta }_{\left(100\right)}\) is the position of the diffraction peak (100). The specific surface area of the synthesized material was determined using the Brunauer-Emmett-Teller (BET) method, which was applied to the N 2 adsorption isotherm data obtained at -196°C using the ASAP 2000 analyzer (Micromeritics, USA). From the same N 2 adsorption data, total pore volume and average pore diameter were also calculated, following the methodology presented in Rios et al. 2009 . The zeta potential measurement was carried out on a Malvern Zetasizer Nano ZS model equipment, and the zeta value of the CB -rGO adsorbent sample was measured in the pH range of 1–11. First, a small amount of material was dispersed in DIW by sonication for 120 min to take readings. The point where the value is zero, which is called the point of zero charge (ZPC), is determined by plotting a graph that relates the pH values to the potential measurements. Adsorption experiments To carry out the batch adsorption experiments, CB-rGO was used as an adsorbent and the contaminant used to be removed in the study was phenol present in an aqueous solution. Firstly, the phenol stock solution (1000 mg L − 1 ) was prepared by dissolving 1 g of phenol crystal in a beaker containing 1000 mL of deionized water. The standard solutions used in this study (100–500 mg L − 1 ) were then prepared by diluting the stock solution that had already been prepared. In all batch adsorption experiments, CB-rGO was used as an adsorbent and added to 120 mL conical flasks containing 50 mL of phenol solution, and placed in a shaker for shaking at a speed of 150 RPM. The experiments were systematically carried out by varying several process parameters: the pH ranged from 2.0–11.0, with adjustments made using standard solutions of acid (HCl 0.1M) and base (NaOH 0.1M); the initial concentration of the phenol solution varied between 100–500 mg L − 1 ; the adsorbent dosage varied from 5–25 mg; the temperature ranged from 20–60°C; and the contact time between the adsorbent and the solution was varied from 0-180 min. After each adsorption process step, the phenol solution containing CB-rGO was filtered and then was centrifuged at a speed of 4000 rpm for 10 min to separate the CB-rGO from the solution. A UV-3150 UV-VIS spectrophotometer (Shimadzu, Japan) was employed to measure both the initial concentration and remaining concentration of phenol at a wavelength of 292 nm. The equilibrium phenol absorption ( \({q}_{e}\) ), phenol adsorption at equilibrium time t (q t ), and the total percentage of removal (%R) were established using the following equations: $${q}_{e}=\frac{\left({C}_{0}-{C}_{e}\right)V}{{m}_{s}}$$ 5 $${q}_{t}=\frac{\left({C}_{0}-{C}_{t}\right)V}{{m}_{s}}$$ 6 $$\%R=\frac{({C}_{0}-{C}_{t})}{{C}_{0}}100$$ 7 where \({C}_{0}\) is the initial phenol concentration (mg.L − 1 ), \({C}_{e}\) is the equilibrium phenol concentration (mg.L − 1 ), \({C}_{t}\) is the phenol concentration at time t (mg.L − 1 ), \({m}_{s}\) is the mass of the adsorbent (mg), and \(V\) is the volume of the solution (ml). Isotherm study Based on the experimental phenol adsorption isotherm on CB-rGO, an evaluation of the Langmuir, Freundlich, and Sips adsorption isotherm equations was conducted to ascertain which of these equations provides the most accurate description of the adsorption behavior in this system. The applied nonlinear Langmuir isotherm equation is expressed as follows: $${q}_{e}=\frac{{q}_{m}{.K}_{L}{.C}_{e}}{1+{K}_{L}{.C}_{e}}$$ 8 where K L (L.mg − 1 ) is the Langmuir constant, which reflects the affinity between the adsorbent and the adsorbate, and \({q}_{m}\) (mg/g − 1 ) is the parameter that indicates the maximum adsorption capacity of the adsorbent in this process the monolayer. These constant values can be determined by fitting the Langmuir equation to the experimental data obtained from the adsorption isotherm. In addition to the parameters mentioned above, the Langmuir isotherm can also be defined through the dimensionless equilibrium, which is also known as separation factor (R L ), and can be expressed as: $${R}_{L}=\frac{1}{1+{K}_{L}{.C}_{0}}$$ 9 where the \({R}_{L}\) parameter expresses the viability of the Langmuir isotherm, with values \({R}_{L}\) > 1 pointing to a disadvantageous adsorption, \({R}_{L}\) = 1 indicating linear adsorption, 0 < \({R}_{L}\) < 1 suggesting a favorable adsorption, and \({R}_{L}\) = 0 denoting an irreversible adsorption. The Freundlich isotherm model is expressed through an equation suitable for multilayer adsorption, wherein interactions between the adsorbent, the surface, and the molecules take place in a heterogeneous surface area. This energy can be distributed in a non-uniform way, resulting in an initial occupation of these adsorption sites followed by a decrease in energy towards the end of the adsorption process (Kumar and Jena 2017 ). The nonlinear Freundlich equation is represented by the following expression: $${q}_{e}={K}_{F}. {{C}_{e}}^{1/nF}$$ 10 where \({K}_{F}\) ((mg.g − 1 )(L.mg − 1 ) 1/ nF ) is the Freundlich constant, and 1/ nF is the heterogeneity factor. A value of 1/ nF close to zero indicates a heterogeneous adsorption process, while 0 < 1/ nF < 1 suggests that the adsorption process is favorable under these conditions. When the value of 1/nF is close to 1, this indicates that chemisorption may occur in the process, and on the other hand, when this value is 1/nF > 1, it can then be suggested that cooperative adsorption occurs (Ibezim- ezeani and Orji 2017). The Sips isotherm model combines aspects from the application of the Langmuir and Freundlich models to estimate heterogeneous adsorption systems. At reduced concentrations of adsorbate, it behaves similarly to the Freundlich isotherm. However, at higher concentrations, it exhibits characteristics indicative of monolayer adsorption, akin to the Langmuir isotherm (Pérez-Marín 2007). The Sips isotherm equation is expressed as follows: $${q}_{e}=\frac{{q}_{m}.{K}_{S}.{{C}_{e}}^{n}}{1+{K}_{S}.{{C}_{e}}^{n}}$$ 11 where \({K}_{S}\) ((L.mg − 1 ) 1/ n ) is the equilibrium constant of the Sips equantion, and n is the parameter that reflects the heterogeneity of the adsorption surface. Kinetic study The study of adsorption kinetics is extremely important so that can understand the dynamics and how the mechanism for removing this contaminant occurs in the adsorption process, in particular it is used so that can predict the rate at which this contaminant will be removed from the aqueous solution. When applied to the phenol adsorption process by CB-rGO, it is possible not only to model, but also to design the best conditions with the ideal parameters to achieve the expected results for the desired adsorption processes (Rout, 2022 ). In the literature it is possible to find several kinetic models to help describe the adsorption processes kinetically and also to understand the behavior of this contaminant when adsorbed by the adsorbent and with this it may be possible to determine the mechanism that controls this studied process. To verify the kinetic behavior of the phenol in CB-rGO system, two kinetic models, namely pseudo-first-order and pseudo-second-order, were assessed. This assessment was performed by fitting these models to the experimental data of adsorbed quantity as a function of time. The pseudo-first-order model is often employed to represent the adsorption rate, taking into account the adsorption capacity from experimental data, the non-linear equation that exemplifies this kinetic model is described below: $${q}_{t}={q}_{e}\left(1-exp\left(-{k}_{1}t\right)\right)$$ 12 where \({k}_{1}\) is the pseudo-first order rate constant (min − 1 ). The pseudo-second order kinetic model deals with the adsorption capacity of phenol on the CB-rGO surface and its non-linear expression is described as: $${q}_{t}=\frac{{k}_{2}{q}_{e}^{2}t}{1+{k}_{2}{q}_{e}t}$$ 13 where \({k}_{2}\) is the pseudo-second order adsorption kinetic constant (g.mg − 1 min − 1 ). The intraparticle diffusion (IPD) model proposed by Weber is an important study model for understanding the diffusion mechanism that occurs in the contaminant removal process as well as the steps that control mass transfer (Arias, 2017) and its equation can be expressed as: $${q}_{t}={k}_{id}{t}^{1/2}+{C}_{i}$$ 14 where C i represents the intercept of stage i , which is associated with the thickness of the boundary layer (mg.g − 1 ), while kid is the intraparticle diffusion rate constant (mg.g − 1 min − 1 ). The Boyd kinetic model was applied to this adsorption process with the aim of identifying the limiting stage with maximum accuracy using the experimental data obtained. The expression that describes this model is given by: $$F=\frac{q}{{q}_{0}}$$ 15 $$F=1-\left(\frac{6}{{\pi }^{2}}\right)\text{exp}(-{B}_{t})$$ 16 where F indicates the fraction of phenol molecules adsorbed by CB-rGO at any time t , q 0 is the amount adsorbed at equilibrium, q represents the amount adsorbed at time, and B t is an expression that depends on F . Using the equations presented previously, it is possible to determine the mathematical expression for B t , expressed by: $${B}_{t}= -0.4977-\text{l}\text{n}(1-F)$$ 17 Through these obtained B t values it is possible to visually observe how the dynamics of the phenol adsorption process works at different concentrations with the CB-rGO adsorbent. These values were calculated and presented in the graphs as a function of time. Thermodynamics study The thermodynamic study within the adsorption process is essential to be able to evaluate some characteristics and discover certain natures of the adsorption process. In this analysis, some parameters are evaluated such as entropy change (∆S°), enthalpy change (∆H°) and Gibbs free energy (∆G°), and they are determined using the following equations: $${k}_{d}=\frac{{q}_{e}}{{C}_{e}}$$ 18 $$\text{ln}\left({k}_{d}\right)=\left(\frac{\varDelta S^\circ }{R}\right)-\left(\frac{\varDelta H^\circ }{RT}\right)$$ 19 $$\varDelta G^\circ = \varDelta H^\circ -T\varDelta S^\circ$$ 20 where k d is the adsorption coefficient (L.g − 1 ), R is the universal gas constant (8.314 J mol − 1 K − 1 ). Results and discussions Characterization of CB -rGO Analysis using X-ray diffraction (XRD), Raman spectroscopy, and high-resolution transmission electron microscopy (HRTEM) confirmed the formation of a 2D carbonaceous nanostructure resembling graphene. In Fig. 2 a, it is possible to observe the presence of a single peak in both diffractometer patterns, demonstrating that all organic material was converted into a 2D nanostructure. In relation to CB-rGO obtained from solid cellulose residue (Fig. 2 a), the presence of a diffraction peak of greater intensity at 2θ = 24.8 is evident, which is associated with the characteristic plane of graphite (002) and turbostatics structures, suggesting that the pyrolytic carbonization of organic waste generated from industry leads to graphene-like structures. Furthermore, previous studies have shown the presence of sharp diffraction peak of graphite oxide at 2θ angles below 11°, indicating the intercalation of oxygen moieties between graphene sheets in GO (Huang et al. 2018; Kaushal et al. 2019 ; Razmjooei et al. 2015). However, the absence of this peak in low-angle regions and its displacement to higher-angle regions suggest that the vaporized oxygen functionalities lead to the re-stacking of the graphene layers in CB-rGO (Razmjooei et al. 2015). This phenomenon promotes the formation of oxidized and reduced graphene nanosheets, as observed in the process described in this study. After the XRD analysis procedure, the calculated crystallographic parameters of the oxidized and reduced graphene obtained from cellulose pyrolysis are listed in Table 1 . Table 1 – Crystallographic parameters from XRD analysis of the CB-rGO. \({\varvec{L}}_{\varvec{c}}\) (nm) \({\varvec{L}}_{\varvec{a}}\) (nm) \({\varvec{d}}_{002}\) (Å) \({\varvec{N}}_{\varvec{c}}\) 8.2 17 3.58 ~ 3 Figure 2 b presents the Raman spectra of CB-rGO obtained from the pyrolysis of cellulose-based solid waste, regarding the determination of the amount of defect density. Peaks corresponding to the G and D bands are observed at 1588 cm − 1 and 1406 cm − 1 , respectively. Peak D represents the vibration mode of the aromatic rings, revealing imperfections in the sample. Thus, the intensity of peak D ( I D ) is indicative of the level of disorganization. In contrast, the G band arises from the vibration of the bonds between all pairs of sp² atoms in the structure's rings. (Alam et al. 2017 ). Additionally, the ratio of the intensities of the peaks relative to the D and G bands ( I D /I G ) indicates the presence of defects in the structure, with high I D /I G values suggesting increased disorder (Razmjooei et al. 2014). Based on the analysis of the Raman spectra in Fig. 2 b, the cellulose I D /I G ratios (0.66) indicate a low presence of graphene reduced defects in the graphitic structure of the CB-rGO obtained from the pyrolysis of the solid residue compared to similar nanomaterials (Ngidi et al. 2019; Razmjooei et al. 2015; Saini et al. 2017 ). This finding is in agreement with the results obtained from XRD analysis. In Fig. 2 c presents the results of the material synthesized and characterized by FTIR to demonstrate conclusive evidence of obtaining the CB-rGO from biomass. In the spectrum, the peaks are elongations that present several characteristics that provide information about its structure and composition. The 1600 cm − 1 peak is known as the C = C bond stretching peak in graphene structures, the 1220 cm − 1 peak is associated with the C-O bond vibration in alcohol and ether groups, the 1050 peak cm − 1 is related to the C-O-C bond vibration in ether groups, which are also found in oxygenated carbon materials. From Fig. 2 d it is possible to identify the nature of the material regarding its porosity and surface area using the N 2 adsorption-desorption analysis, a type IV isotherm with type H4 hysteresis at P/P0 varying from 0.42 to 0.90, indicating the mesoporous nature of the material. From 0.90 to 1.0, there is a notable increase in N 2 uptake, thus suggesting the presence of mesopores (Paranthaman et al. 2018). In Fig. 2 e, the distribution of BJH pores is evaluated, the specific surface area of CB-rGO is 208 m2 g − 1 , the total pore volume is 0.12 cm 3 g − 1 , and the average pore diameter is 3.16 nm and this may indicate that with the synthesis of CB-rGO a mesoporous material is obtained. So that the surface charge and electrical potential of CB-rGO can be evaluated, the Zeta potential is used, and the data obtained was plotted on the graph as shown in Fig. 2 f, which lists the zeta measurements as a function of pH of the phenol solution. It is possible to observe from the graph that as the pH of the solution increases, the value of the Zeta potential decreases, and this indicates that there is a reduction in the protonation of the functional groups. Where this value reaches 0 is called zero charge point (ZPC) and for this study with the CB-rGO adsorbent the value is 2.51, through this we can say that at pH 2.51, the surface has a negative charge. In Fig. 3 , the HRTEM images of CB-rGO obtained from the pyrolysis of cellulose-based solid waste displays the presence of nanosheets structure without the presence of wrinkling. Wrinkling is a stimulated characteristic of defects, present in the structure (Yokwana et al. 2018), demonstrating that the pyrolytic synthesis of cellulosic waste produces high quality rGO in a short process time. Through the image it was also possible to observe a good level of translucency of the material and this indicates that the level of graphitization of this solid waste used in the synthesis is quite high. The darker regions that appear in the image are the graphene layers stacked on top of each other. In addition, two diffraction rings associated with the 002 and 100 planes present in the structure were also revealed, which were recorded by the SAED standard, which is used to analyze the semicrystalline morphology of the material (Ngidi et al. 2019). Furthermore, it is known that the presence of diffracted concentric rings in the electron diffraction pattern is a property of crystalline materials (Singh et al. 2011 ), indicating that CB-rGO has a significantly ordered structure. Adsorption study Effect of pH Within the adsorption process, the pH of the solution plays a crucial factor, as changing the pH directly affects the surface properties of the adsorbents, thus directly affecting the electrostatic interactions between the phenol molecules and the CB-rGO surface (Kumar et al. 2009). the percentage of removal of this contaminant was studied in the pH range of 2–11, thus keeping other parameters of the adsorption process constant, such as the mass of adsorbent (10 mg), solution volume (50 ml), initial phenol concentration (200 mg L − 1 ), stirring speed (150 RPM), temperature (20°C) and time (180 min). In Fig. 4 a it is possible to confirm that as the pH of the solution increases and the static repulsion force decreases, the phenol adsorption performance improves. As the pH increases to 8.0, the removal percentage (% R ) increases and, from that point on, this value begins to decrease drastically, as does the adsorption capacity ( \({q}_{t}\) ), since, at basic pH, the repulsion force is much greater between the CB-rGO surface and the phenol ions, thus causing a lower removal efficiency. Therefore, for this study, the ideal pH identified is 8.0 and will be maintained for future studies. Effect of adsorbent dosage In the Fig. 4 b shows how the adsorption process behaves with the influence of the CB-rGO adsorbent mass on phenol removal (% R ) and adsorption capacity ( qt ), with the mass varying between 5–30 mg, maintaining the other constant adsorption parameters such as the initial concentration of phenol solution (200 mg L − 1 ), pH solution (8.0), the stirring speed (150 RPM), the time (180 min) and temperature (20°C). Thus, it was possible to observe that as the mass of adsorbent increases, this percentage of phenol removal gradually increases as well, where a plateau is reached at 15 mg and there is no further increase even with the amount of CB-rGO increasing. This occurs because as more material is added, the number of vacant activation sites on the surface of the adsorbent increases along with it and, as a result, a greater number of phenol molecules are adsorbed. However, as the mass continues to increase, these activation sites that were available remain unsaturated and, as agglomeration of the adsorbent particles occurs, there is no further increase in adsorption. Maximum removal in this study was achieved with 15 mg of CB-rGO. Effect of adsorption time and initial phenol concentration In Fig. 4 c the effects of the contact time between CB-rGO and phenol are shown and also related to the initial concentration of the solution, in the batch adsorption process as shown in the results. Parameters such as pH (8.0), temperature (20°C), adsorbent mass (10 mg) and stirring speed (150 RPM) were kept constant. The time ranges were varied from 0-180 min, with absorbance measured every 20 min. The initial concentration of the phenol solution was varied between 200–400 mg L − 1 . It is possible to confirm that a large amount of removal occurs in the initial stage of the process, and this adsorption gradually reaches equilibrium over time, as shown in the graph. This occurs due to the fact that at the beginning the CB-rGO surface has several active sites available for adsorption and which are quickly occupied by phenol molecules, and as time passes the rest of the available sites are gradually filled. Until there is no availability left and then equilibrium occurs in the adsorption process, which in the case of this study was recorded in 120 min. Effect of temperature Figure 4 d shows the adsorption behavior with the influence of temperature on the process ranging from 20–60°C. Keeping other parameters constants such as pH (8.0), CB-rGO dosage (10 mg), stirring speed (150 RPM), initial concentration of the phenol solution (200 mg L − 1 ) and time (120 min). The graph in Fig. 4 d shows a considerable increase in the phenol adsorption efficiency when the process temperature increases from 20–30°C, and it is also possible to observe from the graph that as this temperature increases, the efficiency continues to increase but with less intensity than before. This increase in removal efficiency, as the temperature increases, is the result of increased molecular or ionic agitation, which results in to an increase in this kinetic energy in the process (Jiang et al. 2018 ). As a result of this, there was an acceleration in the rate of movement, of phenol molecules for the sufficiency of CB-rGO thereby improving adsorption. With the results of this experiment, the temperature of 30°C was considered ideal for better adsorption efficiency, considering the economic aspect where the energy expenditure to give the process a temperature greater than 30°C will not generate a significant improvement. Adsorption isotherms The analysis of adsorption isotherms is crucial as it provides essential data to determine the maximum adsorption capacity of the adsorbent, as well as the interactions between the adsorbent and the adsorbate. In Fig. 7 a it is possible to observe the behavior of the isotherms, for the Langmuir isotherm model, it is assumed that the adsorption process takes place in a single layer, which can call a monolayer, and that it occurs on a homogeneous surface. As the adsorption area is uniform, there is no diffusion of molecules and the interaction between adsorbate molecules is minimal, so that the energy of the adsorbed species is the same anywhere on the surface, this implies energetic homogeneity on the surface. Adsorption occurs through the collision between adsorbate molecules and empty sites, where in this process only one molecule of the contaminant can fill each available site, the desorption rate depends only on the amount of material on the surface (Hill 1977 ). In Table 2 , it is possible to observe the values found by applying the Langmuir isotherm model, with an R 2 value of 0.992 demonstrating an excellent affinity with the proposed model and with maximum capacity values calculated in the monolayer ( q m ) of CB-rGO for phenol removal is around of 240.51 mg.g − 1 at 303 K, this value is higher than other adsorbent values found in the literature. The R L value for this study was 0.44, thus indicating that CB-rGO is a favorable adsorbent for phenol under the conditions used in this study. In the Fig. 7 a can analyze the values found when applying the Freundlich model calculated from the intercept slope of the non-linear graphs of the isotherm described above, and with the constant 1/nF it is possible to indicate how favorable this studied adsorption process can be. The table shows the values mentioned above and it is possible to say from the value of R 2 being 0.997, that the values fit well with the Freundlich isotherm model for phenol adsorption in CB-rGO. In Table 2 presents the values of the non-linear relationships of the models described above and through them it was possible to describe the adsorption behavior with these studied values. For the present study, both Langmuir, Freundlich and Sips models adapted well to the proposed values, with R 2 of both being almost the maximum, demonstrating good agreement with the proposed models. It is possible to observe in the table that the Freudlich model evidently has the best values of R 2 , indicating a better affinity with this model, in addition, having K F values of 385.28 mg.g − 1 , which is a higher value than those found in the literature, and from this it is possible to demonstrate that this adsorption process occurs in multilayers and through the values of the constants it indicates that the process is favorable and that there may be chemisorption during the adsorption of phenol, thus demonstrating that CB-rGO is favorable as an adsorbent in the removal of phenolic compounds. Table 2 Phenol adsorption parameters on CB-rGO, using Langmuir, Freundlich and Sips isothermal models. Isotherm models Parameters Value (Non-linear) Value (linear) Langmuir q m (mg g − 1 ) 240.26 240.51 \({K}_{L}\) (L mg − 1 ) 0.103 0.101 R 2 0.996 0.997 Freudlich \({K}_{F}\) (mg g − 1 ) 385.28 381.44 1/ nF 0.789 0.739 R 2 0.998 0.998 q m (mg g − 1 ) 239.93 240.01 Sips \({K}_{S}\) (L mg − 1 ) 0.102 0.101 n R 2 3.230 0.994 3.225 0.995 Adsorption kinetics The analysis of adsorption kinetics contributes to understanding the speed of the adsorption process, determined by the slope and intercept of the data in the nonlinear graph shown in Fig. 7 b. This speed influences the time that the adsorbent remains at the interface between solid and solution. For this work, the pseudo-first and pseudo-second order models were used to fit the experimental data on phenol in CB-rGO adsorption, using a non-linear method. To evaluate the quality of fit and adequacy of the model, the coefficient of determination ( R 2 ) was used. From the data obtained from the non-linearized graph, the aforementioned parameters are evaluated and presented in Table 3 . According to the data presented in the Table 3 , it is possible to observe that the values of the R 2 coefficient are 0.99 for the pseudo-first order model, thus it is possible to suggest that the experimental data used perfectly adjust to the proposed model. The calculated equilibrium adsorption capacity ( qe ) was 152.33 mg g − 1 , which was well compatible with the experimental value of 150.0 mg g − 1 , while the K 1 value was 0.031 min − 1 , which is the rate of kinetic speed of the reaction and is therefore better than the kinetic values found in the literature for this adsorption process. Therefore, it is possible to confirm that the adsorption of phenol on CB-rGO follows a first-order process in the kinetic model. The values of q e and k 2 were determined from the analysis of the slope and intercept of the graph data, which did not follow a linear pattern in Fig. 7 b. From the results presented in Table 3 , it is possible to observe that the value of the coefficient of determination R 2 for the second order kinetic model, being 0.98, is lower compared to the first order one, in addition, the adsorption capacity in the equilibrium being 180.53 mg/g − 1 , this result presents a large discrepancy from the experimental value of 150.0 mg/g − 1 . Therefore, it is possible to suggest that the phenol removal process with CB-rGO in the adsorption process does not fit the pseudo-second order kinetic model. Table 3 – Pseudo-frst order and pseudo-second-order kinetic model parameters for the adsorption of phenol on CB-rGO. Conc. (mg L − 1 ) Parameters qexp (mg g − 1 ) Pseudo-first order Pseudo-second order k 1 (min − 1 ) qcal (mg g − 1 ) R 2 k 1 (min − 1 ) qcal (mg g − 1 ) R 2 100 336.433 0.072 247.76 0.996 5.655 263.18 0.998 150 435.444 0.071 305.58 0.994 4.361 325.57 0.999 200 531.424 0.078 378.22 0.991 4.077 400.82 0.998 250 617.217 0.072 389.23 0.992 3.489 414.41 0.998 300 650.143 0.082 431.86 0.995 3.996 455 0.999 With these results demonstrated above, it is possible to state that for this adsorption process the pseudo-first order model is the most appropriate, due to its high value of the coefficient of determination and well-adjusted adsorption capacity values, better than those found. in the literature, in addition to a good rate of kinetic speed. Figure 5 a shows the IPD graph for concentrations of 100–300 mg L − 1 . The high value of \({C}_{i}\) confirmed that surface adsorption is highly effective in the rate-limiting step. The corresponding values can be seen in Table 4 the constants \({C}_{i}\) and \({k}_{id}\) that were evaluated from the diffusion graph. If the graphs pass through the origin and are linear, this means that the IPD is the only determining step in the adsorption rate (Rout 2022 ). In Fig. 5 a it is possible to observe that none of the graphs go through the beginning, thus confirming that in this studied adsorption process more than one limiting step is available. In Fig. 5 a, we observe the presence of three linear segments for each of the phenol concentrations investigated. The first segment refers to the initial phase of diffusion in the film, in which the phenol molecules begin to move from the aqueous solution to the available adsorption sites that are dispersed on the surface of the CB-rGO. In the second linear phase, there is a diffusion of phenol molecules present in the adsorption sites on the CB-rGO surface to the micropores, mesopores and macropores of the adsorbent. In the third and final phase, the establishment of adsorption equilibrium begins, and with this we have a decrease in intraparticle diffusion (Kumar and Jena, 2017 ). Through the kinetic model that was previously described, it is possible to confirm that both intraparticle diffusion and film diffusion occur in the adhesion process. This conclusion is illustrated in Fig. 5 b when applying Boyd's method, it was found that at all phenol concentrations tested, none of the curves pass through the origin. This indicates that external mass transfer or diffusion in the film is the rate determinant that controls phenol adsorption onto the CB-rGO adsorbent. Table 4 – Intraparticle diffusion model parameters for the adsorption of phenol on CB-rGO. C (mg L − 1 ) K1d (mg g − 1 min − 0.5 ) K2d (mg g − 1 min − 0.5 ) K3d (mg g − 1 min − 0.5 ) Ci1 (mg g − 1 ) Ci2 (mg g − 1 ) Ci3 (mg g − 1 ) 100 26.234 12.321 0.012 15.535 13.543 212.345 150 36.764 18.682 0.085 18.546 126.546 332.543 200 53.876 25.435 0.022 22.435 134.345 434.546 250 67.023 23.743 0.002 35.453 212.454 495.565 300 75.923 31.323 0.011 42.435 232.342 543.535 Thermodynamic study Figure 7 c shows the graph that relates ln ( k d ) vs 1/ T ( K ), and from the values obtained with the linearization of these experimental data it is possible to obtain the enthalpy, entropy and Gibbs free energy parameters. In Table 5 it is possible to evaluate the data on the thermodynamic parameters extracted from the graphs and describe some characteristics of the reaction. Using the Van't Hof graph, the enthalpy value ∆H° was calculated to be 84,054 kJ mol − 1 , and this positive value confirms that this reaction is endothermic in nature. Furthermore, also through Table 5 , it is possible to observe that the Gibbs free energy value ∆G° shows a decrease from − 66.81 to -79.60 kJ mol − 1 as the temperature increases from 293-333K, indicating that at high temperatures, phenol adsorption, in addition to being spontaneous, is also favorable (Côrtes et al. 2019 ). The positive value of entropy ∆S° (319.756 J mol − 1 K − 1 ) indicates that a solid/solution randomness occurs while the adsorption process occurs (Rout 2022 ). Certain important information can be obtained after obtaining data on thermodynamic parameters and with this it is possible to understand more about this adoption process. Physisorption, like van der Waals interactions, is generally less than 20 kJ/mol − 1 , and electrostatic interaction varies from 20–80 kJ mol − 1 . The binding forces by chemisorption can be from 80–450 kJ mol − 1 (Bonilla-Petriciolet 2017 ). Normally, it is possible to classify the adsorption process according to the type of interaction between the adsorbent and the adsorbate. If there is a transfer of electrons, can classify it as a chemical adsorption process or can also call it chemisorption. For this situation, this process demands high energy, with enthalpy values ranging from 40–800 KJ/mol − 1 , in addition, of course, to the transfer of electrons. As a result, desorption ends up becoming difficult, meaning this process ends up being irreversible and only a monolayer is observed (Crini and Badot 2008 ). With the values obtained in the table, with the value of ∆H° being greater than 20 kJ mol − 1 , can state that in this phenol adsorption process chemical adsorption may occur, which may lead to an irreversible reaction. Table 5 – Thermodynamic parameters for the adsorption of phenol. Temperature (K) ∆G° (kJ mol − 1 ) ∆H° (kJ mol − 1 ) ∆S° (J mol − 1 K − 1 ) 293 -66.811 303 -70.009 84.0545 319.7564 313 -73.206 323 -76.404 333 -79.601 Reuse study For an economical application, the recyclability potential is one of the extremely important factors for adsorbents, this factor can significantly reduce the cost of the adsorbent and its reuse cycle is exemplified in the scheme in Fig. 6 . In order to evaluate this CB-rGO recycle in phenol adsorption, the test was carried out under the conditions of best results with constant parameters such as pH (8.0), temperature (30°C), adsorbent dosage (10 mg), concentration initial phenol (200 mg L − 1 ), solution volume (50 ml), stirring speed (150 RPM) and equilibrium time (60 min). The CB-rGO, after the filtering process, was washed with distilled water to eliminate traces of phenol and then placed for drying in an oven with a temperature of 110°C so that the water could be evaporated and the adsorbent activated, after complete drying was reused in another solution with the same parameters as the previous one to carry out the new adsorption cycle. In Fig. 7 d, after five cycles, the removal rate begins to have an almost imperceptible drop of around 80%, and can be considered constant from the fifth to the sixth cycle, thus suggesting that CB-rGO synthesized from cellulosic biomass is an excellent candidate for repeated adsorption. Comparison between adsorbents Carrying out this type of comparison between adsorbents is very important to demonstrate the effectiveness of this adsorbent presented in this specific application. At this stage, a comparison is observed between the CB-rGO that was synthesized from a cellulosic biomass with other adsorbents that are also used to remove phenol that were found in the literature and are demonstrated in Table 6 , relating the maximum adsorption capacity, concentration initial, pH and temperature. Its maximum adsorption capacity recorded was qm = 240.1 mg g − 1 using only 10 mg of adsorbent, this value is already much higher than that of other adsorbents found in the literature and presented in this work. With this result, it is possible to affirm the great potential of CB-rGO synthesized by this biological process, which, in addition to being sustainable, can also be used to remove phenol from aqueous solutions. Table 6 – Comparison of CB-rGO with other different adsorbents for phenol removal. Adsorbent Adsorption capacity (mg g − 1 ) pH Concentration (mg mL − 1 ) Temperature (K) References Date pit AC 262.3 8 300 298 El-Naas et al. ( 2010 ) Petroleum asphalt 127.32 8 250 308 Adam et al. (2013) Lantana camara 112.5 8 250 298 Girish et al. (2014) Ziziphus leaves 15 6 200 298 Bsoul et al. (2021) CB-rGO 240.5 8 300 303 This Work Adsorption mechanism For the mechanism of phenol adsorption on materials based on reduced graphene, as well as the CB-rGO presented in this work, involves both chemical interactions and physical interactions. as the structure of reduced graphene is composed of sp 2 bonds, it thus presents a high electronic density that facilitates π-π interactions and improves adsorption (Liu et al., 2012 ). Furthermore, when present in an aqueous solution, phenol forms phenolate ions, and as it has opposite charges with reduced graphene, which has –COOH + and –OH + functional groups on its surface, this difference in charges provides a strong electrostatic interaction between the two. (Pei et al., 2010 ). Not to mention the lamellar structure that this material has, which significantly increases the surface area available for adsorption of contaminant molecules present in the solution. The presence of mesopores and micropores in the CB-rGO structure also contributes to both the trapping of these molecules and their diffusion, thus contributing to improved adsorption (Zhu et al., 2010 ). Conclusion The synthesis process, structural characterization and use as an efficient adsorbent of CB-rGO for phenol removal are reported in this work, and one of the most important advantages of this adsorbent is that its synthesis is made from solid industrial waste, very common in industry. textile, and which can be used as a high-value-added nanomaterial for phenol removal. XRD analysis confirms the highest intensity diffraction peaks of cellulose at 2θ = 24.8, which are associated with the characteristic plane of graphite and turbostatics structures, clearly suggesting that the pyrolytic carbonization of organic residue leads to formation of oxidized and reduced graphene nanosheets. The results of the Raman spectrum analysis indicate the low presence of CB-rGO defects in the graphitic structure of the CB-rGO obtained from the pyrolysis of the solid residue. Through the HRTEM images of the CB-rGO, it is possible to say that there is the presence of nanosheets of structure without the presence of wrinkles, and thus indicate that the cellulosic biomass graphene reduced has an ordered structure. From the batch study carried out in this work, it was possible to confirm the good efficiency of CB-rGO adsorbent in removing phenol from aqueous solutions, but for this to occur efficiently it depends on the adjustment of some parameters such as pH, adsorbent mass, temperature and initial concentration of the solution. The adsorption isotherm data are best fitted with the Freundlich isotherm model, confirming a multilayer adsorption and a maximum absorption capacity of 240.1 mg g − 1 . The adsorption kinetic data follows the pseudo-first order model. The thermodynamic study suggests that the phenol adsorption reaction on CB-rGO occurs in an endothermic process, and the negative Gibbs values imply that the adsorption is spontaneous and possibility of chemical adsorption occurring. The positive entropy value indicates that randomness increases at the solid/liquid interface. Declarations Ethics approval Not applicable. In this work presented here, no tests were used on humans or animals, where national or international guidelines are necessary to protect animals and preserve the well-being of human beings. Consent to participate All authors mentioned here certify that this manuscript was read and authorized by everyone and that there are no other people who meet the authorship criteria but were not properly cited. We also confirm that all the authors mentioned were approved by us Consent for publish We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that all the authors listed in the manuscript have been approved. Author contributions L.A.S. Jesus: Conceptualization, methodology, validation, formal analysis, investigation, resources, writing—original draft preparation. R.L.B. Cabral: Formal analysis, writing—original draft preparation, writing—review and editing and visualization. M.K.P. Ferreira: Validation and formal analysis. D.F.S. Souza and E.R.V.P. Galvão: Formal analysis, writing—original draft preparation and visualization. R.B. Rios: Validation, data curation and formal analysis: J.H.O. Nascimento: Conceptualization, formal analysis, resources, data curation, writing— original draft preparation, writing—review and editing, visualization, supervision and founding acquisition All authors read and approved the final manuscript. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing interest All authors mentioned here declare that they have no conflicts or interests References Abdelbasir SM, McCourt KM, Lee CM, Vanegas DC (2020) Waste-derived nanoparticles: synthesis approaches, environmental applications, and sustainability considerations. 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Chem Eng J 378:122085 Yan Y, Nashath F, Zahra (2020) Chen, Sharon, Manickam, Sivakumar, Lim, Siew Shee, Zhao, Haitao, Lester, Edward, Wu, Tao and Pang, Cheng Heng. Synthesis of graphene: Potential carbon precursors and approaches. Nanatechnol Reviews 9(1):1284–1314 Kholiswa YOKWANA et al (2018) Facile synthesis of nitrogen doped graphene oxide from graphite flakes and powders: A comparison of their surface chemistry. Journal of Nanoscience and Nanotechnology, [ s. l. ], v. 18, n. 8, pp. 5470–5484 Zhu Y et al (2010) Graphene and graphene oxide: Synthesis, properties, and applications. Adv Mater 22(35):3906–3924 Supplementary Files graphicabstractPHENOL.png Cite Share Download PDF Status: Published Journal Publication published 23 Aug, 2024 Read the published version in Environmental Science and Pollution Research → Version 1 posted Editorial decision: Major Revision 19 Jun, 2024 Reviewers agreed at journal 21 May, 2024 Reviewers invited by journal 21 May, 2024 Editor invited by journal 21 May, 2024 Editor assigned by journal 17 May, 2024 First submitted to journal 15 May, 2024 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. 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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-4415982","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":305203752,"identity":"5b7aca0c-6584-49b9-a696-04d5c3ece167","order_by":0,"name":"Lucas Antônio da Silva de Jesus","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACPgSTsQFEyoGIAw/waGGD0hIwLcZgLQnEaYGARLBGvFokkh9+/FFzp45furnxAUOFdfr8sMMPgbbYyek24NKSZizNc+yZhOScg80GDGfSczfeTjMAakk2NjuAS0sOgzQD22EJgxuJbRKMbYdzN85OAGk5kLgNtxbmnz/+wbT8O5xuODv9AyEtbBK8bTAtDYcT5KVzCNjC88zMmrfvsOTMGYnNBgnH0g03SOcUHEgwwO0Xfvbkxzd/fDvMzy+R/vDBhxprefnZ6Zs/fKiwk8OlBRUkMDAzGIBVGhCjHAKYGeQbiFc9CkbBKBgFIwMAAEetXXwGzwVyAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0003-9306-4635","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":true,"prefix":"","firstName":"Lucas","middleName":"Antônio da Silva","lastName":"de Jesus","suffix":""},{"id":305203753,"identity":"cb3385a1-e5d2-40a8-97ff-3f75f57d0fec","order_by":1,"name":"Rivaldo Leonn Bezerra Cabral","email":"","orcid":"","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"Rivaldo","middleName":"Leonn Bezerra","lastName":"Cabral","suffix":""},{"id":305203754,"identity":"e6729535-5107-4339-9401-f35b674f8dc0","order_by":2,"name":"Myllena Kely Pereira Ferreira","email":"","orcid":"","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"Myllena","middleName":"Kely Pereira","lastName":"Ferreira","suffix":""},{"id":305203755,"identity":"b9a24fd2-e0ae-447c-b66b-20bf2a919922","order_by":3,"name":"Domingos Fabiano de Santana Souza","email":"","orcid":"","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"Domingos","middleName":"Fabiano de Santana","lastName":"Souza","suffix":""},{"id":305203756,"identity":"8293bc7a-5fef-4b43-b482-36662d56e1c6","order_by":4,"name":"Edney Rafael Viana Pinheiro Galvão","email":"","orcid":"","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"Edney","middleName":"Rafael Viana Pinheiro","lastName":"Galvão","suffix":""},{"id":305203757,"identity":"4fd553fd-9bdd-4ad6-883b-a0eb2a460842","order_by":5,"name":"Rafael Barbosa Rios","email":"","orcid":"","institution":"UFERSA: Universidade Federal Rural do Semi-Arido","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"Barbosa","lastName":"Rios","suffix":""},{"id":305203758,"identity":"1a8e689e-e3b2-43e3-a146-fc8e876d4905","order_by":6,"name":"José Heriberto Oliveira do Nascimento","email":"","orcid":"","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Heriberto Oliveira do","lastName":"Nascimento","suffix":""}],"badges":[],"createdAt":"2024-05-14 02:43:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4415982/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4415982/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11356-024-34708-6","type":"published","date":"2024-08-23T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57592252,"identity":"8bd05485-403c-47b1-a1bf-21069a30c79c","added_by":"auto","created_at":"2024-06-03 05:46:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2520510,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the synthesis procedure for CB-rGO.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/376ff8c62adb5efe47b1084d.png"},{"id":57592953,"identity":"9f4d1131-5080-4e3b-974d-0d9d5b7f580c","added_by":"auto","created_at":"2024-06-03 06:02:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":577519,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) X-ray diffraction investigation, (\u003cstrong\u003eb\u003c/strong\u003e) Raman spectroscopy analysis, (\u003cstrong\u003ec\u003c/strong\u003e) Fourier transform infrared spectroscopy (FTIR), (\u003cstrong\u003ed\u003c/strong\u003e) evaluation of the nitrogen adsorption-desorption isotherm, (\u003cstrong\u003ee\u003c/strong\u003e) determination of pore size distribution by the BJH method and (\u003cstrong\u003ef\u003c/strong\u003e) zeta potential plot\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/ea01c34d791be6f9f94a7a3a.png"},{"id":57592610,"identity":"2d59b5c8-f9f4-4217-bf50-4eac249f97b5","added_by":"auto","created_at":"2024-06-03 05:54:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":169477,"visible":true,"origin":"","legend":"\u003cp\u003eHRTEM and SAED patterns (in the insets) of the solid waste CB-rGO nanosheets of cellulose as precursors.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/56a31d850f87dc53e33b12b5.png"},{"id":57592611,"identity":"3c99cda4-ed8e-4caf-bf24-032b2588e46d","added_by":"auto","created_at":"2024-06-03 05:54:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28874,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) The impact of the pH level, (\u003cstrong\u003eb\u003c/strong\u003e) The impact of the amount of adsorbent used, (\u003cstrong\u003ec\u003c/strong\u003e) The impact of the initial phenol concentration, (\u003cstrong\u003ed\u003c/strong\u003e) The impact of temperature.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/c14be056a4cee1627f15b254.png"},{"id":57592236,"identity":"28b3016b-0e65-45b7-b779-958eda9b508e","added_by":"auto","created_at":"2024-06-03 05:46:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":18506,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Intraparticle diffusion (IPD) and\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eb\u003c/strong\u003e) Boyd kinetic plots\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/bd59b9ff4a645530e384c6ac.png"},{"id":57592238,"identity":"7196291f-b078-488f-9bfc-62f72cad2ecd","added_by":"auto","created_at":"2024-06-03 05:46:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":179414,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the reuse study of adsorption with phenol and CB-rGO.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/b11e910c444efe8caaf7492a.png"},{"id":57592242,"identity":"435111d4-c3bf-4806-bb3a-ee209b974bca","added_by":"auto","created_at":"2024-06-03 05:46:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":37013,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Adsorption isotherm plots, (\u003cstrong\u003eb\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eKinetics plots, (\u003cstrong\u003ec\u003c/strong\u003e) Thermodynamic study, and (\u003cstrong\u003ed\u003c/strong\u003e) regeneration performance of CB-rGO.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/8e65cd39aec6a8c395935eff.png"},{"id":63300716,"identity":"88f154ef-bebe-409c-9ad0-589a289fc4d8","added_by":"auto","created_at":"2024-08-26 16:16:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4884131,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/394159ea-c55a-450e-97c8-318b9f39be57.pdf"},{"id":57592241,"identity":"68701fde-5152-4229-9b90-d7cb5339e35a","added_by":"auto","created_at":"2024-06-03 05:46:31","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":554251,"visible":true,"origin":"","legend":"","description":"","filename":"graphicabstractPHENOL.png","url":"https://assets-eu.researchsquare.com/files/rs-4415982/v1/ea9ee6718ffc931625be9f59.png"}],"financialInterests":"","formattedTitle":"Evaluation of reduced graphene oxide from cotton waste as an efficient phenol adsorbent in aqueous media","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIndustrial effluents serve as significant pathways for the discharge of considerable organic and inorganic wastes into water bodies, posing a serious environmental risk to plants, humans and animals (Aremu et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Even at low concentrations, phenol is considered one of the most hazardous pollutants found in these effluents, due to its toxic and carcinogenic properties, and its solubility in water as well as various organic solvents (Aremu et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; L\u0026uuml;tke et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Its presence not only poses risks to human health, causing allergies, cardiovascular diseases and problems with vital organs such as intestine, lungs, liver and brain (Jia and Lua \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), but also exacerbates environmental concerns (Zhang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Phenol concentrations in industrial waste typically range from 50-2000 mg.L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Allahkarami et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, a variety of biological and physicochemical methods have been utilized to eliminate phenol from effluents. These methods encompass microbial degradation, enzymatic polymerization, chemical oxidation, adsorption, solvent extraction, photocatalytic degradation, and ion exchange (Allahkarami et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Beker et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Of these techniques mentioned, adsorption is particularly notable for its ease of implementation and operation, high efficiency, low cost, and regenerative capability (L\u0026uuml;tke et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this regard, a range of adsorbents, including activated carbon, minerals, and polymers, have been utilized to investigate the adsorption of phenol (Allahkarami et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), with a focus on employing novel adsorbents (Beker et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Efforts aimed at achieving commercial viability have centered on the creation of cost-effective adsorbents utilizing industrial and agricultural residues. Various biomass, such as cotton spinning waste from the textile industry, and other organic residues, their viability as precursors to this process is constantly examined (Bhatnagar et al. 2015; Devi and Saroha 2016; Hafshejani et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Nanotechnology appears to have tools that enable the growth of new green materials and processes (Gottardo et al. 2021). Furthermore, the reuse of waste materials to produce value-added goods appears to be the shortest route to achieving the goals set through nanomaterials.\u003c/p\u003e \u003cp\u003eRecently, several studies have demonstrated the synthesis of inorganic nanomaterials derived from waste (Abdelbasir et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), spanning from the production of Si (Porrang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Ag (Benassai et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Au (Amiripour et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) nanoparticles to such as graphene, carbon nanotubes and graphene quantum dots, among other carbon-based materials (CNM). CNMs exhibit several remarkable characteristics in diverse industrial sectors (Ebbesen 1996). Graphene, in particular, has attracted increasing interest in research spanning various scientific fields due to its excellent physicochemical, thermal, mechanical, and electrical properties, positioning it as one of the most studied CNMs (Bolotin et al. 2008; Inagaki \u0026amp; Kang 2014; Khanafer \u0026amp; Vafai 2017; Lee et al. 2008; Liu et al. 2019; Munz et al. 2015; Nair et al. 2008; Yu et al. 2015).\u003c/p\u003e \u003cp\u003eIn addition to graphene, other derivatives of this material can be obtained through oxidation (graphene oxide - GO) and reduction (reduced graphene oxide - rGO). One of the most significant graphene derivatives, features numerous functional groups containing oxygen within its basal plane and at the edges, manifested in the form of epoxy, hydroxyl, and carboxyl groups, as well as a high level of defects in the carbon structure. As a result, this nanomaterial exhibits distinct properties from graphene, such as insulating and hydrophilic electrical behavior, allowing it to form suspensions in aqueous media. rGO is produced through reduction reactions of GO with different reducing agents (Galv\u0026atilde;o et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The resultant product from this reaction is a carbonaceous material with a low oxygen content and defects in the basal plane.\u003c/p\u003e \u003cp\u003eConsiderable efforts have been dedicated to the manufacture of graphene and its variants from a variety of sources (Yan et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, waste generated from the textile industry has emerged as a promising source, primarily due to its composition of ligno and cellulosic fibers. These materials consist of a biopolymer with dense carbon molecules that can form partially defective sheets resembling the structure of graphite, thus serving as a precursor to reduced graphene (Farid et al. 2022). The presence of residual oxygenated groups, electron domains, high surface area and porosity, and defect density make rGO nanosheets an excellent adsorbent for removing contaminants present in water (Gupta and Khatri \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cetinkaya and Ozdemir \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on this context, the objective of this study is to evaluate viability of CB-rGO obtained from solid waste generated in the textile industry for the removal of phenol from aqueous solutions. These characteristics of the phenol adsorption process using CB-rGO as adsorbents were analyzed in different parameters such as solution pH, initial concentration, adsorbent mass, contact time and reaction temperature. The experimental data will assess the suitability of different adsorption, pseudo-first and pseudo-second order kinetic models, in addition to the Langmuir, Freundlich and Sips isotherm models, which helped to describe this adsorption process, offering insights into the mechanisms governing the interaction between phenol and the CB-rGO.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eWaster from cotton sanding process was collected and donated from Vicunha t\u0026ecirc;xtil S/A. The iron-base catalyst with a purity of \u0026ge;\u0026thinsp;98.5 (Merck, Germany) and phenol crystal (\u0026Ecirc;xodo Cient\u0026iacute;fica, Brazil) were utilized.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of CB-rGO\u003c/h2\u003e \u003cp\u003eCellulosic biomass graphene reduced (CB-rGO) was synthesized via the top-down method, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In this process, 1g of cotton fiber powder was placed in a ceramic crucible along with a solid catalyst weighing 0.1g. After mixing the components, they were transferred to a muffle furnace and subjected to a pyrolysis process at 300\u0026deg;C for 30 min. Subsequently, the resulting powder underwent further processing until it reached a fine, dark consistency.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCharacterization\u003c/h2\u003e \u003cp\u003eThe morphological characteristics of CB-rGO synthesized from cotton waste were examined using high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED) were performed with the JEM-2100 electron microscope (JEOL, Japan) operating at 200 kV, and with a resolution of 0.2 nm. The crystalline structure of the solid material was evaluated using an X-ray diffractometer (XRD) Miniflex II Rigaku (Bruker, USA) with copper (Cu) radiation, with a power of 30kV and current of 30mA, in the angular region of 10 to 90\u0026deg; with a step of 0.02 and a speed of 5\u0026deg;/min. Raman spectra were recorded from 500 to 3000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using a Raman micro spectrometer (Renishaw, UK) equipped with a 532 nm argon ion laser. Fourier-transform infrared spectroscopy (FTIR) data were obtained using an IR Tracer-100 FTIR spectrometer (Shimadzu, Japan) in the frequency range of 400 to 4000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with a resolution of 4 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFrom the data obtained from the XRD analysis, calculations of several crystallographic parameters were carried out., including the interlaminar space (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({d}_{002}\\)\u003c/span\u003e\u003c/span\u003e) (KAUSHAL; DHAWAN; SINGH 2019), crystal stack height (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({L}_{c}\\)\u003c/span\u003e\u003c/span\u003e), in-plane crystallite size (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({L}_{a}\\)\u003c/span\u003e\u003c/span\u003e), and the number of graphene layers in the crystal (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({N}_{c}\\)\u003c/span\u003e\u003c/span\u003e) (Romero et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), using the Eqs.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)-(\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$${d}_{002}=\\frac{\\lambda }{2sen{\\theta }_{\\left(002\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${L}_{c}=\\frac{{K}_{1}\\lambda }{\\beta cos{\\theta }_{\\left(002\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$${L}_{a}=\\frac{{K}_{2}\\lambda }{\\beta cos{\\theta }_{\\left(100\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$${N}_{c}=\\frac{Lc}{{d}_{002}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\lambda\\)\u003c/span\u003e\u003c/span\u003e is the wavelength of CuKα-radiation (0.154 nm), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e is the width at half height of the corresponding diffraction peak, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{1}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{2}\\)\u003c/span\u003e\u003c/span\u003e are shape factor constants for spherical crystals (0.89) and Warren shape factor (1.84) (Warren and Bodenstein \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e1965\u003c/span\u003e), respectively. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta }_{\\left(002\\right)}\\)\u003c/span\u003e\u003c/span\u003e is the position of the diffraction peak (002), while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta }_{\\left(100\\right)}\\)\u003c/span\u003e\u003c/span\u003e is the position of the diffraction peak (100).\u003c/p\u003e \u003cp\u003eThe specific surface area of the synthesized material was determined using the Brunauer-Emmett-Teller (BET) method, which was applied to the N\u003csub\u003e2\u003c/sub\u003e adsorption isotherm data obtained at -196\u0026deg;C using the ASAP 2000 analyzer (Micromeritics, USA). From the same N\u003csub\u003e2\u003c/sub\u003e adsorption data, total pore volume and average pore diameter were also calculated, following the methodology presented in Rios et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2009\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe zeta potential measurement was carried out on a Malvern Zetasizer Nano ZS model equipment, and the zeta value of the CB -rGO adsorbent sample was measured in the pH range of 1\u0026ndash;11. First, a small amount of material was dispersed in DIW by sonication for 120 min to take readings. The point where the value is zero, which is called the point of zero charge (ZPC), is determined by plotting a graph that relates the pH values to the potential measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAdsorption experiments\u003c/h2\u003e \u003cp\u003eTo carry out the batch adsorption experiments, CB-rGO was used as an adsorbent and the contaminant used to be removed in the study was phenol present in an aqueous solution. Firstly, the phenol stock solution (1000 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was prepared by dissolving 1 g of phenol crystal in a beaker containing 1000 mL of deionized water. The standard solutions used in this study (100\u0026ndash;500 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were then prepared by diluting the stock solution that had already been prepared. In all batch adsorption experiments, CB-rGO was used as an adsorbent and added to 120 mL conical flasks containing 50 mL of phenol solution, and placed in a shaker for shaking at a speed of 150 RPM. The experiments were systematically carried out by varying several process parameters: the pH ranged from 2.0\u0026ndash;11.0, with adjustments made using standard solutions of acid (HCl 0.1M) and base (NaOH 0.1M); the initial concentration of the phenol solution varied between 100\u0026ndash;500 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; the adsorbent dosage varied from 5\u0026ndash;25 mg; the temperature ranged from 20\u0026ndash;60\u0026deg;C; and the contact time between the adsorbent and the solution was varied from 0-180 min. After each adsorption process step, the phenol solution containing CB-rGO was filtered and then was centrifuged at a speed of 4000 rpm for 10 min to separate the CB-rGO from the solution. A UV-3150 UV-VIS spectrophotometer (Shimadzu, Japan) was employed to measure both the initial concentration and remaining concentration of phenol at a wavelength of 292 nm. The equilibrium phenol absorption (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({q}_{e}\\)\u003c/span\u003e\u003c/span\u003e), phenol adsorption at equilibrium time t (q\u003csub\u003et\u003c/sub\u003e), and the total percentage of removal (%R) were established using the following equations:\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$${q}_{e}=\\frac{\\left({C}_{0}-{C}_{e}\\right)V}{{m}_{s}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$${q}_{t}=\\frac{\\left({C}_{0}-{C}_{t}\\right)V}{{m}_{s}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\%R=\\frac{({C}_{0}-{C}_{t})}{{C}_{0}}100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the initial phenol concentration (mg.L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{e}\\)\u003c/span\u003e\u003c/span\u003e is the equilibrium phenol concentration (mg.L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{t}\\)\u003c/span\u003e\u003c/span\u003e is the phenol concentration at time \u003cem\u003et\u003c/em\u003e (mg.L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({m}_{s}\\)\u003c/span\u003e\u003c/span\u003e is the mass of the adsorbent (mg), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(V\\)\u003c/span\u003e\u003c/span\u003e is the volume of the solution (ml).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eIsotherm study\u003c/h2\u003e \u003cp\u003eBased on the experimental phenol adsorption isotherm on CB-rGO, an evaluation of the Langmuir, Freundlich, and Sips adsorption isotherm equations was conducted to ascertain which of these equations provides the most accurate description of the adsorption behavior in this system. The applied nonlinear Langmuir isotherm equation is expressed as follows:\u003cdiv id=\"Equ8\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ8\" name=\"EquationSource\"\u003e\n$${q}_{e}=\\frac{{q}_{m}{.K}_{L}{.C}_{e}}{1+{K}_{L}{.C}_{e}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e (L.mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is the Langmuir constant, which reflects the affinity between the adsorbent and the adsorbate, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({q}_{m}\\)\u003c/span\u003e\u003c/span\u003e (mg/g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is the parameter that indicates the maximum adsorption capacity of the adsorbent in this process the monolayer. These constant values can be determined by fitting the Langmuir equation to the experimental data obtained from the adsorption isotherm.\u003c/p\u003e \u003cp\u003eIn addition to the parameters mentioned above, the Langmuir isotherm can also be defined through the dimensionless equilibrium, which is also known as separation factor (R\u003csub\u003eL\u003c/sub\u003e), and can be expressed as:\u003cdiv id=\"Equ9\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ9\" name=\"EquationSource\"\u003e\n$${R}_{L}=\\frac{1}{1+{K}_{L}{.C}_{0}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{L}\\)\u003c/span\u003e\u003c/span\u003e parameter expresses the viability of the Langmuir isotherm, with values \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{L}\\)\u003c/span\u003e\u003c/span\u003e \u0026gt; 1 pointing to a disadvantageous adsorption, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{L}\\)\u003c/span\u003e\u003c/span\u003e = 1 indicating linear adsorption, 0 \u0026lt; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{L}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt; 1 suggesting a favorable adsorption, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{L}\\)\u003c/span\u003e\u003c/span\u003e = 0 denoting an irreversible adsorption.\u003c/p\u003e \u003cp\u003eThe Freundlich isotherm model is expressed through an equation suitable for multilayer adsorption, wherein interactions between the adsorbent, the surface, and the molecules take place in a heterogeneous surface area. This energy can be distributed in a non-uniform way, resulting in an initial occupation of these adsorption sites followed by a decrease in energy towards the end of the adsorption process (Kumar and Jena \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The nonlinear Freundlich equation is represented by the following expression:\u003cdiv id=\"Equ10\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ10\" name=\"EquationSource\"\u003e\n$${q}_{e}={K}_{F}. {{C}_{e}}^{1/nF}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{F}\\)\u003c/span\u003e\u003c/span\u003e ((mg.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)(L.mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003csup\u003e1/\u003cem\u003enF\u003c/em\u003e\u003c/sup\u003e) is the Freundlich constant, and 1/\u003cem\u003enF\u003c/em\u003e is the heterogeneity factor. A value of 1/\u003cem\u003enF\u003c/em\u003e close to zero indicates a heterogeneous adsorption process, while 0\u0026thinsp;\u0026lt;\u0026thinsp;1/\u003cem\u003enF\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1 suggests that the adsorption process is favorable under these conditions. When the value of \u003cem\u003e1/nF\u003c/em\u003e is close to 1, this indicates that chemisorption may occur in the process, and on the other hand, when this value is \u003cem\u003e1/nF\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;1, it can then be suggested that cooperative adsorption occurs (Ibezim- ezeani and Orji 2017).\u003c/p\u003e \u003cp\u003eThe Sips isotherm model combines aspects from the application of the Langmuir and Freundlich models to estimate heterogeneous adsorption systems. At reduced concentrations of adsorbate, it behaves similarly to the Freundlich isotherm. However, at higher concentrations, it exhibits characteristics indicative of monolayer adsorption, akin to the Langmuir isotherm (P\u0026eacute;rez-Mar\u0026iacute;n 2007). The Sips isotherm equation is expressed as follows:\u003cdiv id=\"Equ11\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ11\" name=\"EquationSource\"\u003e\n$${q}_{e}=\\frac{{q}_{m}.{K}_{S}.{{C}_{e}}^{n}}{1+{K}_{S}.{{C}_{e}}^{n}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{S}\\)\u003c/span\u003e\u003c/span\u003e ((L.mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003csup\u003e1/\u003cem\u003en\u003c/em\u003e\u003c/sup\u003e) is the equilibrium constant of the Sips equantion, and \u003cem\u003en\u003c/em\u003e is the parameter that reflects the heterogeneity of the adsorption surface.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eKinetic study\u003c/h2\u003e \u003cp\u003eThe study of adsorption kinetics is extremely important so that can understand the dynamics and how the mechanism for removing this contaminant occurs in the adsorption process, in particular it is used so that can predict the rate at which this contaminant will be removed from the aqueous solution. When applied to the phenol adsorption process by CB-rGO, it is possible not only to model, but also to design the best conditions with the ideal parameters to achieve the expected results for the desired adsorption processes (Rout, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the literature it is possible to find several kinetic models to help describe the adsorption processes kinetically and also to understand the behavior of this contaminant when adsorbed by the adsorbent and with this it may be possible to determine the mechanism that controls this studied process.\u003c/p\u003e \u003cp\u003eTo verify the kinetic behavior of the phenol in CB-rGO system, two kinetic models, namely pseudo-first-order and pseudo-second-order, were assessed. This assessment was performed by fitting these models to the experimental data of adsorbed quantity as a function of time.\u003c/p\u003e \u003cp\u003eThe pseudo-first-order model is often employed to represent the adsorption rate, taking into account the adsorption capacity from experimental data, the non-linear equation that exemplifies this kinetic model is described below:\u003cdiv id=\"Equ12\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ12\" name=\"EquationSource\"\u003e\n$${q}_{t}={q}_{e}\\left(1-exp\\left(-{k}_{1}t\\right)\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e12\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({k}_{1}\\)\u003c/span\u003e\u003c/span\u003e is the pseudo-first order rate constant (min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe pseudo-second order kinetic model deals with the adsorption capacity of phenol on the CB-rGO surface and its non-linear expression is described as:\u003cdiv id=\"Equ13\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ13\" name=\"EquationSource\"\u003e\n$${q}_{t}=\\frac{{k}_{2}{q}_{e}^{2}t}{1+{k}_{2}{q}_{e}t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e13\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({k}_{2}\\)\u003c/span\u003e\u003c/span\u003eis the pseudo-second order adsorption kinetic constant (g.mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe intraparticle diffusion (IPD) model proposed by Weber is an important study model for understanding the diffusion mechanism that occurs in the contaminant removal process as well as the steps that control mass transfer (Arias, 2017) and its equation can be expressed as:\u003cdiv id=\"Equ14\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ14\" name=\"EquationSource\"\u003e\n$${q}_{t}={k}_{id}{t}^{1/2}+{C}_{i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e14\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e represents the intercept of stage \u003cem\u003ei\u003c/em\u003e, which is associated with the thickness of the boundary layer (mg.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), while kid is the intraparticle diffusion rate constant (mg.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe Boyd kinetic model was applied to this adsorption process with the aim of identifying the limiting stage with maximum accuracy using the experimental data obtained. The expression that describes this model is given by:\u003cdiv id=\"Equ15\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ15\" name=\"EquationSource\"\u003e\n$$F=\\frac{q}{{q}_{0}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e15\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ16\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ16\" name=\"EquationSource\"\u003e\n$$F=1-\\left(\\frac{6}{{\\pi }^{2}}\\right)\\text{exp}(-{B}_{t})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e16\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eF\u003c/em\u003e indicates the fraction of phenol molecules adsorbed by CB-rGO at any time \u003cem\u003et\u003c/em\u003e, \u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e is the amount adsorbed at equilibrium, q represents the amount adsorbed at time, and \u003cem\u003eB\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e is an expression that depends on \u003cem\u003eF\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eUsing the equations presented previously, it is possible to determine the mathematical expression for \u003cem\u003eB\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e, expressed by:\u003cdiv id=\"Equ17\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ17\" name=\"EquationSource\"\u003e\n$${B}_{t}= -0.4977-\\text{l}\\text{n}(1-F)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e17\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThrough these obtained \u003cem\u003eB\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e values it is possible to visually observe how the dynamics of the phenol adsorption process works at different concentrations with the CB-rGO adsorbent. These values were calculated and presented in the graphs as a function of time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eThermodynamics study\u003c/h2\u003e \u003cp\u003eThe thermodynamic study within the adsorption process is essential to be able to evaluate some characteristics and discover certain natures of the adsorption process. In this analysis, some parameters are evaluated such as entropy change (∆S\u0026deg;), enthalpy change (∆H\u0026deg;) and Gibbs free energy (∆G\u0026deg;), and they are determined using the following equations:\u003cdiv id=\"Equ18\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ18\" name=\"EquationSource\"\u003e\n$${k}_{d}=\\frac{{q}_{e}}{{C}_{e}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e18\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ19\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ19\" name=\"EquationSource\"\u003e\n$$\\text{ln}\\left({k}_{d}\\right)=\\left(\\frac{\\varDelta S^\\circ }{R}\\right)-\\left(\\frac{\\varDelta H^\\circ }{RT}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e19\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ20\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ20\" name=\"EquationSource\"\u003e\n$$\\varDelta G^\\circ = \\varDelta H^\\circ -T\\varDelta S^\\circ$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e20\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sub\u003e is the adsorption coefficient (L.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u003cem\u003eR\u003c/em\u003e is the universal gas constant (8.314 J mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussions","content":"\u003cp\u003e \u003cb\u003eCharacterization of\u003c/b\u003e CB\u003cb\u003e-rGO\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnalysis using X-ray diffraction (XRD), Raman spectroscopy, and high-resolution transmission electron microscopy (HRTEM) confirmed the formation of a 2D carbonaceous nanostructure resembling graphene. In Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, it is possible to observe the presence of a single peak in both diffractometer patterns, demonstrating that all organic material was converted into a 2D nanostructure. In relation to CB-rGO obtained from solid cellulose residue (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), the presence of a diffraction peak of greater intensity at 2θ\u0026thinsp;=\u0026thinsp;24.8 is evident, which is associated with the characteristic plane of graphite (002) and turbostatics structures, suggesting that the pyrolytic carbonization of organic waste generated from industry leads to graphene-like structures. Furthermore, previous studies have shown the presence of sharp diffraction peak of graphite oxide at 2θ angles below 11\u0026deg;, indicating the intercalation of oxygen moieties between graphene sheets in GO (Huang et al. 2018; Kaushal et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Razmjooei et al. 2015). However, the absence of this peak in low-angle regions and its displacement to higher-angle regions suggest that the vaporized oxygen functionalities lead to the re-stacking of the graphene layers in CB-rGO (Razmjooei et al. 2015). This phenomenon promotes the formation of oxidized and reduced graphene nanosheets, as observed in the process described in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the XRD analysis procedure, the calculated crystallographic parameters of the oxidized and reduced graphene obtained from cellulose pyrolysis are listed in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Crystallographic parameters from XRD analysis of the CB-rGO.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{L}}_{\\varvec{c}}\\)\u003c/span\u003e\u003c/span\u003e (nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{L}}_{\\varvec{a}}\\)\u003c/span\u003e\u003c/span\u003e (nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{d}}_{002}\\)\u003c/span\u003e\u003c/span\u003e (\u0026Aring;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{N}}_{\\varvec{c}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e~\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb presents the Raman spectra of CB-rGO obtained from the pyrolysis of cellulose-based solid waste, regarding the determination of the amount of defect density. Peaks corresponding to the \u003cem\u003eG\u003c/em\u003e and \u003cem\u003eD\u003c/em\u003e bands are observed at 1588 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1406 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively. Peak D represents the vibration mode of the aromatic rings, revealing imperfections in the sample. Thus, the intensity of peak D (\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e) is indicative of the level of disorganization. In contrast, the G band arises from the vibration of the bonds between all pairs of sp\u0026sup2; atoms in the structure's rings. (Alam et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the ratio of the intensities of the peaks relative to the \u003cem\u003eD\u003c/em\u003e and \u003cem\u003eG\u003c/em\u003e bands (\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e/I\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e) indicates the presence of defects in the structure, with high \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e/I\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e values suggesting increased disorder (Razmjooei et al. 2014). Based on the analysis of the Raman spectra in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, the cellulose I\u003csub\u003eD\u003c/sub\u003e/I\u003csub\u003eG\u003c/sub\u003e ratios (0.66) indicate a low presence of graphene reduced defects in the graphitic structure of the CB-rGO obtained from the pyrolysis of the solid residue compared to similar nanomaterials (Ngidi et al. 2019; Razmjooei et al. 2015; Saini et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This finding is in agreement with the results obtained from XRD analysis. In Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec presents the results of the material synthesized and characterized by FTIR to demonstrate conclusive evidence of obtaining the CB-rGO from biomass. In the spectrum, the peaks are elongations that present several characteristics that provide information about its structure and composition. The 1600 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e peak is known as the C\u0026thinsp;=\u0026thinsp;C bond stretching peak in graphene structures, the 1220 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e peak is associated with the C-O bond vibration in alcohol and ether groups, the 1050 peak cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is related to the C-O-C bond vibration in ether groups, which are also found in oxygenated carbon materials.\u003c/p\u003e \u003cp\u003eFrom Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed it is possible to identify the nature of the material regarding its porosity and surface area using the N\u003csub\u003e2\u003c/sub\u003e adsorption-desorption analysis, a type IV isotherm with type H4 hysteresis at \u003cem\u003eP/P0\u003c/em\u003e varying from 0.42 to 0.90, indicating the mesoporous nature of the material. From 0.90 to 1.0, there is a notable increase in N\u003csub\u003e2\u003c/sub\u003e uptake, thus suggesting the presence of mesopores (Paranthaman et al. 2018). In Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, the distribution of BJH pores is evaluated, the specific surface area of CB-rGO is 208 m2 g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, the total pore volume is 0.12 cm\u003csup\u003e3\u003c/sup\u003e g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and the average pore diameter is 3.16 nm and this may indicate that with the synthesis of CB-rGO a mesoporous material is obtained.\u003c/p\u003e \u003cp\u003eSo that the surface charge and electrical potential of CB-rGO can be evaluated, the Zeta potential is used, and the data obtained was plotted on the graph as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef, which lists the zeta measurements as a function of pH of the phenol solution. It is possible to observe from the graph that as the pH of the solution increases, the value of the Zeta potential decreases, and this indicates that there is a reduction in the protonation of the functional groups. Where this value reaches 0 is called zero charge point (ZPC) and for this study with the CB-rGO adsorbent the value is 2.51, through this we can say that at pH\u0026thinsp;\u0026lt;\u0026thinsp;2.51, the surface of the CB-rGO is positively charged, while at pH\u0026thinsp;\u0026gt;\u0026thinsp;2.51, the surface has a negative charge.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the HRTEM images of CB-rGO obtained from the pyrolysis of cellulose-based solid waste displays the presence of nanosheets structure without the presence of wrinkling. Wrinkling is a stimulated characteristic of defects, present in the structure (Yokwana et al. 2018), demonstrating that the pyrolytic synthesis of cellulosic waste produces high quality rGO in a short process time. Through the image it was also possible to observe a good level of translucency of the material and this indicates that the level of graphitization of this solid waste used in the synthesis is quite high. The darker regions that appear in the image are the graphene layers stacked on top of each other. In addition, two diffraction rings associated with the 002 and 100 planes present in the structure were also revealed, which were recorded by the SAED standard, which is used to analyze the semicrystalline morphology of the material (Ngidi et al. 2019). Furthermore, it is known that the presence of diffracted concentric rings in the electron diffraction pattern is a property of crystalline materials (Singh et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), indicating that CB-rGO has a significantly ordered structure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAdsorption study\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eEffect of pH\u003c/h2\u003e \u003cp\u003eWithin the adsorption process, the pH of the solution plays a crucial factor, as changing the pH directly affects the surface properties of the adsorbents, thus directly affecting the electrostatic interactions between the phenol molecules and the CB-rGO surface (Kumar et al. 2009). the percentage of removal of this contaminant was studied in the pH range of 2\u0026ndash;11, thus keeping other parameters of the adsorption process constant, such as the mass of adsorbent (10 mg), solution volume (50 ml), initial phenol concentration (200 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), stirring speed (150 RPM), temperature (20\u0026deg;C) and time (180 min). In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea it is possible to confirm that as the pH of the solution increases and the static repulsion force decreases, the phenol adsorption performance improves. As the pH increases to 8.0, the removal percentage (%\u003cem\u003eR\u003c/em\u003e) increases and, from that point on, this value begins to decrease drastically, as does the adsorption capacity (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({q}_{t}\\)\u003c/span\u003e\u003c/span\u003e), since, at basic pH, the repulsion force is much greater between the CB-rGO surface and the phenol ions, thus causing a lower removal efficiency. Therefore, for this study, the ideal pH identified is 8.0 and will be maintained for future studies.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffect of adsorbent dosage\u003c/h2\u003e \u003cp\u003eIn the Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb shows how the adsorption process behaves with the influence of the CB-rGO adsorbent mass on phenol removal (%\u003cem\u003eR\u003c/em\u003e) and adsorption capacity (\u003cem\u003eqt\u003c/em\u003e), with the mass varying between 5\u0026ndash;30 mg, maintaining the other constant adsorption parameters such as the initial concentration of phenol solution (200 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), pH solution (8.0), the stirring speed (150 RPM), the time (180 min) and temperature (20\u0026deg;C). Thus, it was possible to observe that as the mass of adsorbent increases, this percentage of phenol removal gradually increases as well, where a plateau is reached at 15 mg and there is no further increase even with the amount of CB-rGO increasing. This occurs because as more material is added, the number of vacant activation sites on the surface of the adsorbent increases along with it and, as a result, a greater number of phenol molecules are adsorbed. However, as the mass continues to increase, these activation sites that were available remain unsaturated and, as agglomeration of the adsorbent particles occurs, there is no further increase in adsorption. Maximum removal in this study was achieved with 15 mg of CB-rGO.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffect of adsorption time and initial phenol concentration\u003c/h2\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec the effects of the contact time between CB-rGO and phenol are shown and also related to the initial concentration of the solution, in the batch adsorption process as shown in the results. Parameters such as pH (8.0), temperature (20\u0026deg;C), adsorbent mass (10 mg) and stirring speed (150 RPM) were kept constant. The time ranges were varied from 0-180 min, with absorbance measured every 20 min. The initial concentration of the phenol solution was varied between 200\u0026ndash;400 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. It is possible to confirm that a large amount of removal occurs in the initial stage of the process, and this adsorption gradually reaches equilibrium over time, as shown in the graph. This occurs due to the fact that at the beginning the CB-rGO surface has several active sites available for adsorption and which are quickly occupied by phenol molecules, and as time passes the rest of the available sites are gradually filled. Until there is no availability left and then equilibrium occurs in the adsorption process, which in the case of this study was recorded in 120 min.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffect of temperature\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed shows the adsorption behavior with the influence of temperature on the process ranging from 20\u0026ndash;60\u0026deg;C. Keeping other parameters constants such as pH (8.0), CB-rGO dosage (10 mg), stirring speed (150 RPM), initial concentration of the phenol solution (200 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and time (120 min). The graph in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed shows a considerable increase in the phenol adsorption efficiency when the process temperature increases from 20\u0026ndash;30\u0026deg;C, and it is also possible to observe from the graph that as this temperature increases, the efficiency continues to increase but with less intensity than before. This increase in removal efficiency, as the temperature increases, is the result of increased molecular or ionic agitation, which results in to an increase in this kinetic energy in the process (Jiang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result of this, there was an acceleration in the rate of movement, of phenol molecules for the sufficiency of CB-rGO thereby improving adsorption. With the results of this experiment, the temperature of 30\u0026deg;C was considered ideal for better adsorption efficiency, considering the economic aspect where the energy expenditure to give the process a temperature greater than 30\u0026deg;C will not generate a significant improvement.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAdsorption isotherms\u003c/h2\u003e \u003cp\u003eThe analysis of adsorption isotherms is crucial as it provides essential data to determine the maximum adsorption capacity of the adsorbent, as well as the interactions between the adsorbent and the adsorbate. In Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea it is possible to observe the behavior of the isotherms, for the Langmuir isotherm model, it is assumed that the adsorption process takes place in a single layer, which can call a monolayer, and that it occurs on a homogeneous surface. As the adsorption area is uniform, there is no diffusion of molecules and the interaction between adsorbate molecules is minimal, so that the energy of the adsorbed species is the same anywhere on the surface, this implies energetic homogeneity on the surface. Adsorption occurs through the collision between adsorbate molecules and empty sites, where in this process only one molecule of the contaminant can fill each available site, the desorption rate depends only on the amount of material on the surface (Hill \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). In Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, it is possible to observe the values found by applying the Langmuir isotherm model, with an \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e value of 0.992 demonstrating an excellent affinity with the proposed model and with maximum capacity values calculated in the monolayer (\u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e) of CB-rGO for phenol removal is around of 240.51 mg.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 303 K, this value is higher than other adsorbent values found in the literature. The \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e value for this study was 0.44, thus indicating that CB-rGO is a favorable adsorbent for phenol under the conditions used in this study. In the Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea can analyze the values found when applying the Freundlich model calculated from the intercept slope of the non-linear graphs of the isotherm described above, and with the constant \u003cem\u003e1/nF\u003c/em\u003e it is possible to indicate how favorable this studied adsorption process can be. The table shows the values mentioned above and it is possible to say from the value of \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e being 0.997, that the values fit well with the Freundlich isotherm model for phenol adsorption in CB-rGO.\u003c/p\u003e \u003cp\u003eIn Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the values of the non-linear relationships of the models described above and through them it was possible to describe the adsorption behavior with these studied values. For the present study, both Langmuir, Freundlich and Sips models adapted well to the proposed values, with \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e of both being almost the maximum, demonstrating good agreement with the proposed models. It is possible to observe in the table that the Freudlich model evidently has the best values of \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, indicating a better affinity with this model, in addition, having \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eF\u003c/em\u003e\u003c/sub\u003e values of 385.28 mg.g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which is a higher value than those found in the literature, and from this it is possible to demonstrate that this adsorption process occurs in multilayers and through the values of the constants it indicates that the process is favorable and that there may be chemisorption during the adsorption of phenol, thus demonstrating that CB-rGO is favorable as an adsorbent in the removal of phenolic compounds.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhenol adsorption parameters on CB-rGO, using Langmuir, Freundlich and Sips isothermal models.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsotherm models\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003cp\u003e(Non-linear)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValue (linear)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLangmuir\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eq\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e240.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e240.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{L}\\)\u003c/span\u003e\u003c/span\u003e (L mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eFreudlich\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{F}\\)\u003c/span\u003e\u003c/span\u003e (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e385.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e381.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/\u003cem\u003enF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eq\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e239.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e240.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSips\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{S}\\)\u003c/span\u003e\u003c/span\u003e (L mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.230\u003c/p\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.225\u003c/p\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAdsorption kinetics\u003c/h2\u003e \u003cp\u003eThe analysis of adsorption kinetics contributes to understanding the speed of the adsorption process, determined by the slope and intercept of the data in the nonlinear graph shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb. This speed influences the time that the adsorbent remains at the interface between solid and solution. For this work, the pseudo-first and pseudo-second order models were used to fit the experimental data on phenol in CB-rGO adsorption, using a non-linear method. To evaluate the quality of fit and adequacy of the model, the coefficient of determination (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) was used. From the data obtained from the non-linearized graph, the aforementioned parameters are evaluated and presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. According to the data presented in the Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, it is possible to observe that the values of the \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e coefficient are 0.99 for the pseudo-first order model, thus it is possible to suggest that the experimental data used perfectly adjust to the proposed model. The calculated equilibrium adsorption capacity (\u003cem\u003eqe\u003c/em\u003e) was 152.33 mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which was well compatible with the experimental value of 150.0 mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while the \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e value was 0.031 min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which is the rate of kinetic speed of the reaction and is therefore better than the kinetic values found in the literature for this adsorption process. Therefore, it is possible to confirm that the adsorption of phenol on CB-rGO follows a first-order process in the kinetic model.\u003c/p\u003e \u003cp\u003eThe values of \u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e were determined from the analysis of the slope and intercept of the graph data, which did not follow a linear pattern in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb. From the results presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, it is possible to observe that the value of the coefficient of determination \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e for the second order kinetic model, being 0.98, is lower compared to the first order one, in addition, the adsorption capacity in the equilibrium being 180.53 mg/g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, this result presents a large discrepancy from the experimental value of 150.0 mg/g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Therefore, it is possible to suggest that the phenol removal process with CB-rGO in the adsorption process does not fit the pseudo-second order kinetic model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Pseudo-frst order and pseudo-second-order kinetic model parameters for the adsorption of phenol on CB-rGO.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eConc. (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eqexp (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ePseudo-first order\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePseudo-second order\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ek\u003csub\u003e1\u003c/sub\u003e (min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eqcal (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ek\u003csub\u003e1\u003c/sub\u003e (min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eqcal (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e336.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e247.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e263.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e435.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e305.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e325.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e200\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e531.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e378.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e400.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e250\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e617.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e389.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e414.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e650.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e431.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWith these results demonstrated above, it is possible to state that for this adsorption process the pseudo-first order model is the most appropriate, due to its high value of the coefficient of determination and well-adjusted adsorption capacity values, better than those found. in the literature, in addition to a good rate of kinetic speed.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea shows the IPD graph for concentrations of 100\u0026ndash;300 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The high value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{i}\\)\u003c/span\u003e\u003c/span\u003e confirmed that surface adsorption is highly effective in the rate-limiting step. The corresponding values can be seen in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e the constants \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{i}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({k}_{id}\\)\u003c/span\u003e\u003c/span\u003e that were evaluated from the diffusion graph. If the graphs pass through the origin and are linear, this means that the IPD is the only determining step in the adsorption rate (Rout \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea it is possible to observe that none of the graphs go through the beginning, thus confirming that in this studied adsorption process more than one limiting step is available.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, we observe the presence of three linear segments for each of the phenol concentrations investigated. The first segment refers to the initial phase of diffusion in the film, in which the phenol molecules begin to move from the aqueous solution to the available adsorption sites that are dispersed on the surface of the CB-rGO. In the second linear phase, there is a diffusion of phenol molecules present in the adsorption sites on the CB-rGO surface to the micropores, mesopores and macropores of the adsorbent. In the third and final phase, the establishment of adsorption equilibrium begins, and with this we have a decrease in intraparticle diffusion (Kumar and Jena, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThrough the kinetic model that was previously described, it is possible to confirm that both intraparticle diffusion and film diffusion occur in the adhesion process. This conclusion is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb when applying Boyd's method, it was found that at all phenol concentrations tested, none of the curves pass through the origin. This indicates that external mass transfer or diffusion in the film is the rate determinant that controls phenol adsorption onto the CB-rGO adsorbent.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Intraparticle diffusion model parameters for the adsorption of phenol on CB-rGO.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003cp\u003e(mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eK1d\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;0.5\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK2d\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;0.5\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK3d\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;0.5\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCi1\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCi2\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCi3\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e212.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e126.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e332.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e200\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e134.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e434.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e250\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e212.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e495.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e232.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e543.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eThermodynamic study\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec shows the graph that relates ln (\u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sub\u003e) vs 1/\u003cem\u003eT\u003c/em\u003e(\u003cem\u003eK\u003c/em\u003e), and from the values obtained with the linearization of these experimental data it is possible to obtain the enthalpy, entropy and Gibbs free energy parameters. In Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e it is possible to evaluate the data on the thermodynamic parameters extracted from the graphs and describe some characteristics of the reaction. Using the Van't Hof graph, the enthalpy value ∆H\u0026deg; was calculated to be 84,054 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and this positive value confirms that this reaction is endothermic in nature. Furthermore, also through Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, it is possible to observe that the Gibbs free energy value ∆G\u0026deg; shows a decrease from \u0026minus;\u0026thinsp;66.81 to -79.60 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as the temperature increases from 293-333K, indicating that at high temperatures, phenol adsorption, in addition to being spontaneous, is also favorable (C\u0026ocirc;rtes et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The positive value of entropy ∆S\u0026deg; (319.756 J mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) indicates that a solid/solution randomness occurs while the adsorption process occurs (Rout \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCertain important information can be obtained after obtaining data on thermodynamic parameters and with this it is possible to understand more about this adoption process. Physisorption, like van der Waals interactions, is generally less than 20 kJ/mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and electrostatic interaction varies from 20\u0026ndash;80 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The binding forces by chemisorption can be from 80\u0026ndash;450 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Bonilla-Petriciolet \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Normally, it is possible to classify the adsorption process according to the type of interaction between the adsorbent and the adsorbate. If there is a transfer of electrons, can classify it as a chemical adsorption process or can also call it chemisorption. For this situation, this process demands high energy, with enthalpy values ranging from 40\u0026ndash;800 KJ/mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, in addition, of course, to the transfer of electrons. As a result, desorption ends up becoming difficult, meaning this process ends up being irreversible and only a monolayer is observed (Crini and Badot \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). With the values obtained in the table, with the value of ∆H\u0026deg; being greater than 20 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, can state that in this phenol adsorption process chemical adsorption may occur, which may lead to an irreversible reaction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Thermodynamic parameters for the adsorption of phenol.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e∆G\u0026deg; (kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆H\u0026deg; (kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e∆S\u0026deg; (J mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-66.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-70.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.0545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e319.7564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-73.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-76.404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-79.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eReuse study\u003c/h2\u003e \u003cp\u003eFor an economical application, the recyclability potential is one of the extremely important factors for adsorbents, this factor can significantly reduce the cost of the adsorbent and its reuse cycle is exemplified in the scheme in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. In order to evaluate this CB-rGO recycle in phenol adsorption, the test was carried out under the conditions of best results with constant parameters such as pH (8.0), temperature (30\u0026deg;C), adsorbent dosage (10 mg), concentration initial phenol (200 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), solution volume (50 ml), stirring speed (150 RPM) and equilibrium time (60 min). The CB-rGO, after the filtering process, was washed with distilled water to eliminate traces of phenol and then placed for drying in an oven with a temperature of 110\u0026deg;C so that the water could be evaporated and the adsorbent activated, after complete drying was reused in another solution with the same parameters as the previous one to carry out the new adsorption cycle. In Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed, after five cycles, the removal rate begins to have an almost imperceptible drop of around 80%, and can be considered constant from the fifth to the sixth cycle, thus suggesting that CB-rGO synthesized from cellulosic biomass is an excellent candidate for repeated adsorption.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eComparison between adsorbents\u003c/h2\u003e \u003cp\u003eCarrying out this type of comparison between adsorbents is very important to demonstrate the effectiveness of this adsorbent presented in this specific application. At this stage, a comparison is observed between the CB-rGO that was synthesized from a cellulosic biomass with other adsorbents that are also used to remove phenol that were found in the literature and are demonstrated in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, relating the maximum adsorption capacity, concentration initial, pH and temperature. Its maximum adsorption capacity recorded was \u003cem\u003eqm\u003c/em\u003e\u0026thinsp;=\u0026thinsp;240.1 mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using only 10 mg of adsorbent, this value is already much higher than that of other adsorbents found in the literature and presented in this work. With this result, it is possible to affirm the great potential of CB-rGO synthesized by this biological process, which, in addition to being sustainable, can also be used to remove phenol from aqueous solutions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Comparison of CB-rGO with other different adsorbents for phenol removal.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdsorbent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdsorption capacity\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConcentration\u003c/p\u003e \u003cp\u003e(mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003cp\u003e(K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDate pit AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEl-Naas et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePetroleum asphalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdam et\u0026nbsp;al. (2013)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLantana camara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGirish et\u0026nbsp;al. (2014)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZiziphus leaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBsoul et\u0026nbsp;al. (2021)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCB-rGO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e240.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e303\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eThis Work\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAdsorption mechanism\u003c/h2\u003e \u003cp\u003eFor the mechanism of phenol adsorption on materials based on reduced graphene, as well as the CB-rGO presented in this work, involves both chemical interactions and physical interactions. as the structure of reduced graphene is composed of sp\u003csup\u003e2\u003c/sup\u003e bonds, it thus presents a high electronic density that facilitates π-π interactions and improves adsorption (Liu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, when present in an aqueous solution, phenol forms phenolate ions, and as it has opposite charges with reduced graphene, which has \u0026ndash;COOH\u0026thinsp;+\u0026thinsp;and \u0026ndash;OH\u0026thinsp;+\u0026thinsp;functional groups on its surface, this difference in charges provides a strong electrostatic interaction between the two. (Pei et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNot to mention the lamellar structure that this material has, which significantly increases the surface area available for adsorption of contaminant molecules present in the solution. The presence of mesopores and micropores in the CB-rGO structure also contributes to both the trapping of these molecules and their diffusion, thus contributing to improved adsorption (Zhu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe synthesis process, structural characterization and use as an efficient adsorbent of CB-rGO for phenol removal are reported in this work, and one of the most important advantages of this adsorbent is that its synthesis is made from solid industrial waste, very common in industry. textile, and which can be used as a high-value-added nanomaterial for phenol removal.\u003c/p\u003e \u003cp\u003eXRD analysis confirms the highest intensity diffraction peaks of cellulose at 2θ\u0026thinsp;=\u0026thinsp;24.8, which are associated with the characteristic plane of graphite and turbostatics structures, clearly suggesting that the pyrolytic carbonization of organic residue leads to formation of oxidized and reduced graphene nanosheets. The results of the Raman spectrum analysis indicate the low presence of CB-rGO defects in the graphitic structure of the CB-rGO obtained from the pyrolysis of the solid residue. Through the HRTEM images of the CB-rGO, it is possible to say that there is the presence of nanosheets of structure without the presence of wrinkles, and thus indicate that the cellulosic biomass graphene reduced has an ordered structure.\u003c/p\u003e \u003cp\u003eFrom the batch study carried out in this work, it was possible to confirm the good efficiency of CB-rGO adsorbent in removing phenol from aqueous solutions, but for this to occur efficiently it depends on the adjustment of some parameters such as pH, adsorbent mass, temperature and initial concentration of the solution. The adsorption isotherm data are best fitted with the Freundlich isotherm model, confirming a multilayer adsorption and a maximum absorption capacity of 240.1 mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The adsorption kinetic data follows the pseudo-first order model. The thermodynamic study suggests that the phenol adsorption reaction on CB-rGO occurs in an endothermic process, and the negative Gibbs values imply that the adsorption is spontaneous and possibility of chemical adsorption occurring. The positive entropy value indicates that randomness increases at the solid/liquid interface.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eIn this work presented here, no tests were used on humans or animals, where national or international guidelines are necessary to protect animals and preserve the well-being of human beings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003eAll authors mentioned here certify that this manuscript was read and authorized by everyone and that there are no other people who meet the authorship criteria but were not properly cited. We also confirm that all the authors mentioned were approved by us\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publish\u0026nbsp;\u003c/strong\u003eWe confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that all the authors listed in the manuscript have been approved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eL.A.S. Jesus: Conceptualization, methodology, validation, formal analysis, investigation, resources, writing\u0026mdash;original draft preparation. R.L.B. Cabral: Formal analysis, writing\u0026mdash;original draft preparation, writing\u0026mdash;review and editing and visualization. M.K.P. Ferreira: Validation and formal analysis. D.F.S. Souza and E.R.V.P. Galv\u0026atilde;o: Formal analysis, writing\u0026mdash;original draft preparation and visualization. R.B. Rios: Validation, data curation and formal analysis: J.H.O. Nascimento: Conceptualization, formal analysis, resources, data curation, writing\u0026mdash; original draft preparation, writing\u0026mdash;review and editing, visualization, supervision and founding acquisition All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u0026nbsp;\u003c/strong\u003eAll authors mentioned here declare that they have no conflicts or interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdelbasir SM, McCourt KM, Lee CM, Vanegas DC (2020) Waste-derived nanoparticles: synthesis approaches, environmental applications, and sustainability considerations. 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Adv Mater 22(35):3906\u0026ndash;3924\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cotton waste, adsorption, cellulosic biomass, reduced graphene oxide, phenol","lastPublishedDoi":"10.21203/rs.3.rs-4415982/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4415982/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe elimination of organic substances, as well as phenol, in conventional and biological process, has been considered a challenge for the petroleum industry due to the significant oxygen demand in the receiving bodies of water and its toxicity to aquatic life. In this work, reduced graphene oxide (rGO), obtained from cellulosic biomass (CB-rGO), as cotton waste, was employed as a phenol adsorbent in an aqueous solution simulating refinery effluent. The CB-rGO was characterized using HRTEM, RAMAN, XRD, FTIR, BET and Zeta analysis. The behavior of variables such as pH, contact time, temperature, CB-rGO mass and adsorbate concentration on the characteristics of the adsorption process were continuously investigated. These parameters of the adsorption process were evaluated across a range of adsorbent concentrations from 100\u0026ndash;300 mg.L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, pH in the range of 2\u0026ndash;11, contact time of 20\u0026ndash;60 min and temperature of 20\u0026ndash;60\u0026deg;C. The adsorption isotherm data were better described by the Freundlich equation compared to the Langmuir and Sips models, despite the negligible difference in \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e values. Additionally, the kinetics study of confirmed pseudo-second order as the most appropriate model. Mechanism diffusion was analyzed using the Boyd model and confirmed to be the rate-limiting step in the adsorption process. The endothermic nature of this CB-rGO adsorption process with phenol was confirmed by verifying the thermodynamic data. This successful removal of phenol from synthetic effluent highlights the promising potential of this emerging adsorbent compared to other materials identified to remove this contaminant.\u003c/p\u003e","manuscriptTitle":"Evaluation of reduced graphene oxide from cotton waste as an efficient phenol adsorbent in aqueous media","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 05:38:26","doi":"10.21203/rs.3.rs-4415982/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2024-06-19T09:39:29+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-05-21T21:53:56+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-21T21:31:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2024-05-21T14:13:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-17T04:34:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2024-05-15T22:12:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0408531b-0340-4d43-a7f7-821451b5e6fa","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T16:10:08+00:00","versionOfRecord":{"articleIdentity":"rs-4415982","link":"https://doi.org/10.1007/s11356-024-34708-6","journal":{"identity":"environmental-science-and-pollution-research","isVorOnly":false,"title":"Environmental Science and Pollution Research"},"publishedOn":"2024-08-23 15:58:01","publishedOnDateReadable":"August 23rd, 2024"},"versionCreatedAt":"2024-06-03 05:38:26","video":"","vorDoi":"10.1007/s11356-024-34708-6","vorDoiUrl":"https://doi.org/10.1007/s11356-024-34708-6","workflowStages":[]},"version":"v1","identity":"rs-4415982","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4415982","identity":"rs-4415982","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}