{"paper_id":"095cefef-6acd-4228-bdf1-1d52885d6a48","body_text":"License and Terms: This document is copyright 2025 the Author(s); licensee Beilstein-Institut.\nThis is an open access work under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0). Please note that the reuse,\nredistribution and reproduction in particular requires that the author(s) and source are credited and that individual graphics may be subject to special legal provisions.\nThe license is subject to the Beilstein Archives terms and conditions: https://www.beilstein-archives.org/xiv/terms.\nThe definitive version of this work can be found at https://doi.org/10.3762/bxiv.2025.9.v1\nThis open access document is posted as a preprint in the Beilstein Archives at https://doi.org/10.3762/bxiv.2025.9.v1 and is\nconsidered to be an early communication for feedback before peer review. Before citing this document, please check if a final,\npeer-reviewed version has been published.\nThis document is not formatted, has not undergone copyediting or typesetting, and may contain errors, unsubstantiated scientific\nclaims or preliminary data.\nPreprint Title Synthesis of a multicomponent cellulose-based absorbent for\ntetracycline removal from aquaculture water\nAuthors Uyen B. Tran, Ngoc T. Vo-Tran, Khai T. Truong, Dat A. Nguyen,\nQuang N. Tran, Huu-Quang Nguyen, Jaebeom Lee and Hai S.\nTruong-Lam\nPublication Date 17 Feb. 2025\nArticle Type Full Research Paper\nORCID® iDs Huu-Quang Nguyen - https://orcid.org/0000-0002-8609-3038; Hai S.\nTruong-Lam - https://orcid.org/0000-0003-2435-6039\n\n1 \nSynthesis of a multicomponent cellulose-based absorbent for \ntetracycline removal from aquaculture water \nUyen Bao Tran1, 2, Vo-Tran Thanh Ngoc1, 2, Truong The Khai1, 2, Nguyen Anh Dat1, 2, Quang \nNhat Tran1, 2, Huu-Quang Nguyen3, Jaebeom Lee3, Hai Son Truong-Lam1, 2* \n1Faculty of Chemistry, University of Science, Ho Chi Minh City 70000, Vietnam  \n2Vietnam National University, Ho Chi Minh City 70000, Vietnam \n3Department of Chemistry, Chungnam National University, Daejeon 34134, Republic of Korea   \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n*Corresponding author. \nE-mail address: Hai Son Truong-Lam - tlshai@hcmus.edu.vn               \n\n2 \nAbstract \n \nExcessive use of tetracycline  (TC) antibiotics in aquaculture, particularly in Vietnam, has \ncontributed to environmental contamination and economic losses. To treat the problem, this study \ndeveloped a novel cellulose-based multicomponent adsorbent material  (PGC) synthesized from \nsodium carboxymethyl cellulose and investigated factors influencing its TC adso rption capacity. \nThe synthesis process was optimized using parameters derived from response surface \nmethodology. The surface and structural properties of PGC were characterized , and their TC \nadsorption efficiency of PGC was assessed using high-performance liquid chromatography‒mass \nspectroscopy (HPLC-MS). Elemental analysis of PGC identified four key mechanisms governing \nits endothermic TC adsorption mechanism: surface complexation, electrostatic interactions, \nhydrogen bonding, and CH–π interactions, with surface complexation between Ca2+ and TCs being \ndominant. Batch adsorption experiments conducted to examine the factors influencing adsorption \ncapacity revealed that PGC achieved up to 70% TC removal efficiency at an adsorbent dosage of \n40 mg  of the initial  TC concentration of 60 mg L –1, pH 6 –7 reaching equilibrium in 12 h. \nVerification experiments under optimal conditions confirmed that the adsorption process followed \nsecond-order kinetics and the Langmuir adsorption isotherm model. These findings indicate that \nPGC demonstrates strong potential as an effective adsorbent for the removal of TC antibiotic \nresidues, particularly oxytetracycline, chlortetracycline, TC, and doxycycline. \nKeywords \nadsorption; aquaculture water ; removal efficiency; response surface m ethodology; tetracycline \nantibiotic. \n\n3 \nIntroduction \nThe aquaculture industry plays a crucial role in the global economy , including  Vietnam’s \neconomy, particularly for coastal nations, however, its multi -billions contributions are \naccompanied by the growing problem of excess antibiotic usage , notably tetracyclines (TCs), a \nwidely used class of antibiotics in recent years [1–4]. Recent studies indicate that oxytetracycline \n(OTC), a TC derivative, is the predominant antibiotic used in Vietnam’s white leg shrimp farming \nindustry, particularly during the 10–30 day and 30–45 day rearing periods [5]. This extensive use \nof OTC is primarily attributed to its broad -spectrum activity, rendering it effective in controllin g \nvarious bacterial infections in shrimp. However, unregulated antibiotic usage poses significant \nrisks, including the presence of antibiotic residues in seafood, which threaten human health. More \nbroadly, antibiotic overuse diminishes aquatic biodiversity  and leads to substantial economic \nlosses. \nTo date, v arious methods, including adsorption, biological processing, photocatalysis, and \nelectrochemical methods , have been used to remove antibiotics from contaminated water . \nHowever, these conventional treatment methods are restricted by high costs, prolonged treatment \ndurations, and secondary pollutant formation, limiting their overall efficiency. A major drawback \nof activated carbon is its incomplete recovery after adsorption. Because adsorption primarily relies \non physical interactions such as hydrogen bonding interactions, electrostatic forces, and van der \nWaals forces, adsorbed antibiotics may de sorb and reenter aquatic environments  [6]. Moreover, \nactivated carbon exhibits low selectivity and adsorption capacity. Among novel adsorbents, metal-\norganic frameworks [7] and molecularly imprinted polymers (MIPs) [8] are particularly notable \nfor their high target specificity. Although MIPs are effective, their synthesis requires exceptional \nprecision and is time-intensive. Meanwhile, magnetic solid -phase extraction columns [9] have \n\n4 \nbeen explored for TC removal; however, they are impractical for processing large sample volumes. \nThese limitations have spurred the development of more effective and versatile adsorbents. \n \nModern adsorbents are available in diverse compositions. Moreover, they are easy to manufacture \nand generally both cost -effective and environmentally friendly . Cellulose-based adsorbents , in \nparticular, have garnered increasing attention in recent years. For instance, Yao et al. used three-\ndimensional cellulose-based materials to remove various antibiotics from water, including TC, \nexhibiting high adsorption capacity and good reusability  [10]. Moreover, three-dimensional \ncellulose-based aerogels, which feature high porosity and a large specific surface area, have \ndemonstrated adsorption efficiency across a wide pH range [11].  \n \nAlthough previous studies have offered valuable insights , further research is needed to optimize \nthe structura l and compositional properties of materials to improve their performance . For \ninstance, c arboxymethyl cellulose (CMC), an anionic derivative of cellulose, is a linear \npolysaccharide consisting of anhydroglucose units linked by β -1,4-glycosidic bonds . The k ey \ndistinction between CMC and cellulose is that some hydroxyl groups in cellulose are replaced by \ncarboxymethyl (‒CH2COOH) groups. The introduction of carboxymethyl groups greatly enhances \nthe water solubility of CMC relative to  that of cellulose. CMC, recognized as one of the most \npromising cellulose derivatives, was first synthesized in 1918 [12]. Owing to its unique surface \nproperties, high mechanical strength, abundance of raw materials, and cost -effective synthesis, \nCMC is now widely used in food, textile, pharmaceutical, and wastewater treatment industries.  \n \n\n5 \nThis study aims to synthesize a cellulose-based multicomponent adsorbent material (PGC), using \ncommercial sodium CMC, cross -linked with glutaraldehyde (GA) and polyvinyl alcohol (PVA); \nand cationized with Ca2+ and Zn2+, for the removal of TC from aquaculture effluents. Our approach \ninvolves optimizing the material’s synthesis using the response surface methodology, and a wide \nrange of characterization methods was performed to assess the  surface characteristics and \nmorphology of the synthesized absorbent . Additionally, the study examines the adsorption \nmechanism of TC on the material’s surface and evaluates the effects of pH, adsorbent dosage, and \nmatrix composition.  \n \nAs a biodegradable and easily recoverable material derived from natural cellulose, this adsorbent \noffers a sustainable alternative to synthetic materials that pose environmental risks. In addition to \nwastewater treatment, this material could be utilized in medicine, pharmaceuticals, air purification, \nand environmental monitoring.  \n\n6 \nResults and Discussion  \nExperimental optimization \n \nFigure 1: Material characterization using response surface plot analysis \n \nConventional production and modification methods typically involve the manipulation of a single \nindependent variable while holding all other variables constant [13]. However, chemical processes \nfrequently involve a multitude of interacting factors, necessitating the simultaneous evaluation of \nthese potential interrelationships. To address this challenge, statistical experimental design \nmethodologies, notably response surface methodology (RSM), have been developed. RSM, a \nrobust integration of mathematical and statistical techniques, is extensively employed for process \noptimization and the elucidation of interactions among experimental variables, ultimately leading \nto enhanced results [14], [15] . The application of RSM enables researchers to substantially  \ndecrease the number of experiments needed while simultaneously achieving a more thorough \ncomprehension of the process under investigation and the identification of optimal operating \nparameters. \n\n\n7 \nA response surface plot (Figure 1) was used to visualize variable interactions and determine \noptimal process parameters. As depicted in Figure 1a, the TC removal efficiency of the adsorbent \ndecreases when both X1 and X2 increase simultaneously . This decline is expected, as increasing \nboth CMC and PVA concentrations results in a highly viscous and non -homogeneous mixture, \nwhich deteriorates  material quality and reduces adsorption capacity . When evaluating X2 \nindependently, the optimal PVA concentration is determined to be below 2.0 g . When the PVA \nconcentration exceeds this threshold, TC adsorption efficiency declines. This occurs because \nhigher PVA levels hinder dissolution and mixing, particularly as viscosity increases. Similarly, TC \nadsorption efficiency also declines as GA concentration increases. At high concentrations, GA can \ndissolve PVA, compromising the material's stability. This interaction significantly influences the \nmodel (p-value < 0.05), particularly through factor X3 . The interaction of X4 with other factors \nalso has a significant effect on the model, yielding an optimal value of approximately 0.1 . A \nsubstantial decrease in X4 leads to a corresponding decline in the dependent variable Y, \nparticularly in the X1 ‒X4 and X3 ‒X4 interactions. This effect arises because a reduction in X4 \ndecreases water solubility and hinders the formation of a homogeneous cellulose mixture . \nAdditionally, lower Ca2+ concentrations impede chelate formation between Ca 2+ and TC (Figure \n1b). Response surface methodology (RSM) optimization in MODDE 5.0 identified the following \noptimal values for maximizing the objective function: X1 = 1.5 g, X2 = 1.0 g, X3 = 0.01 mL, and \nX4 = 0.1 . These optimized parameters will be applied in the synthesis of an adsorbent for TC \nremoval from water. \n\n8 \nMaterial characterization \nFE–SEM and FT–IR results \n \nFigure 2: (a‒c) FE–SEM images of commercial CMC, (d‒f) FE–SEM images of PGC, and (g) FT–\nIR spectra of commercial CMC and PGC. \n \nFigure 2 presents the comparative FE–SEM images and FT–IR spectra of commercial CMC and \nPGC. Notably, the FE–SEM analysis of PGC (Figures 2d –f) reveals significant morphological \nchanges compared to pristine CMC (Figures 2a –c). Specifically, the  PGC surface exhibits \nnumerous, uniformly distributed spherical nanoparticles (~200 nm in diameter), attributed to ZnO \nnanoparticles. The initial tubular structure of CMC is converted into a film-like structure owing to \nthe lateral bonding effect of GA and PVA, as well as the dissolution of cellulose by  Zn²⁺. The \nrough, wrinkled surface and cracks are likely due to the focused high-energy electron beam during \nthe FE–SEM imaging process  [16]. Larger agglomerates, possibly ZnSO 4 residues, are also \napparent, which aligns with the subsequent EDX results. \n \nThe FT–IR spectrum (Figure 2g) of commercial CMC displays distinct absorption bands at 3,219; \n2,875; 1,424; 1,325; 1,053; 1,029  and 893 cm −1. The broad band from  3,219 to 3 ,406 cm −1 \ncorresponds to O ‒H stretching vibrations, reflecting the abundance of hydroxyl an d carboxyl \n\n\n9 \ngroups in commercial CMC. Meanwhile, the absorption band at 2,875 cm−1 represents symmetric \nstretching vibrations of the ‒CH2 group. The strong peak at 1 ,620 cm −1 likely corresponds to \nasymmetric C=O stretching vibrations in carboxyl groups such as ‒COONa. The sharp, symmetric \npeaks at 1,424 cm−1 and 1,325 cm−1 correspond to symmetric stretching vibrations of alkyl groups \nin CMC. The doublet at 1,029 cm−1 and 1,053 cm−1 represents vibrations of pyranose rings formed \nduring cellulose synthesis, as well as C‒O stretching vibrations. Meanwhile, the peak at 893 cm−1 \ncorresponds to C‒O‒C stretching vibrations, characteristic of cellulose. These results are \nconsistent with previous findings on commercial CMC [17], [18]. \n \nOwing to lateral bonding, the characteristic peaks of CMC remain observable but exhibit shifts. \nFor example, the alkyl group vibration  peak shifts to 1,424 cm −1, while the  C‒O‒C stretching \nvibration peaks shift to 883 and 1 ,105 cm −1. Meanwhile, the  hydroxyl gro up vibration  peak \nbecomes broader and less intense, shifting to the  3,240‒3,386 cm −1 region, suggesting the \ninvolvement of ‒OH groups in cross -linking. The intensity of the peak at  1,325 cm−1 decreases \nsignificantly, while the peak at  1,620 cm −1, c orresponding to carbonyl (‒C=O) stretching in \ncarboxyl groups, nearly disappears, indicating lateral bonding between PVA and GA . \nAdditionally, the appearance of the peak at 668 cm−1 indicates the presence of a Zn‒O bond, while \nthe peaks at 880 cm−1 and 3,416 cm−1 correspond to Zn‒OH vibrations, suggesting the involvement \nof Zn²⁺ in dissolving CMC. The sharp peak at 568 cm−1 corresponds to a Ca‒O bond [19]. \n\n10 \nEDX \n \nFigure 3: (a, b) EDX spectra and elemental compositions of commercial CMC and PGC, \nrespectively; (c) morphology image of CMC (d-f) elemental mapping images of commercial CMC; \n(g) morphology image of PGC  and (h–l) elemental mapping images of PGC. \nEDX analysis revealed the elemental composition of the  PGC material, as detailed in Figures 3a \nand 3b. Notably, the detection of elements, particularly Zn, in PGC confirms the role of Zn2+ ions \nin cellulose dissolution via hydrate bridge formation . Additionally, the presence of Zn enhances \nthe TC adsorption capacity of PGC through a chemical adsorption mechanism. \nAccording to our findings, Zn content increased significantly from 12.45% in pristine CMC to \n22.24% in PGC, aligning with FT –IR outcomes confirming the presence of Zn –O and Zn –OH \nbonds. Furthermore, the C a content increased from 0.03% to 2.82%, accompanied by a rise in \n\n\n11 \noxygen content. This increase suggests the involvement of GA and PVA in the cross -linking \nprocess, where the –OH groups in PVA and –CHO groups in GA contribute to the rise in oxygen \ncontent. Additionally, the detection of sulfur in PGC indicates the potential presence of residual \nZnSO4 precursor. Figures 3c –l present significant changes in the elemental distribution of O, S, \nZn, and Ca in PGC compared to pristine CMC. These elements display a  higher density on the \nsurface of PGC. \n \nInvestigation of factors influencing the maximum TC adsorption capacity of \nthe synthetic material \n \nFigure 4: (a) Effect of adsorption time and initial concentration on the adsorption capacity of PGC. \n(b) Effect of a dsorbent dosage on the adsorption capacity and adsorption efficiency of PGC. (c) \n\n\n12 \nEffect of pH on the adsorption capacity of PGC. (d) Effect of initial concentration on the adsorption \ncapacity of PGC. \nEffect of initial pH \nThe effect of pH on the TC adsorption capacity of PGC is illustrated in Figure 4c. Specifically, the \nadsorption capacity increases significantly between pH 3 and 7, peaking at pH 7. Beyond  this \npoint, it decreases rapidly, with the sharpest decline observed between pH 10 and 11. \nThis occurs because, as pH increases, particularly around pH 6.8, β -ketoenol groups serve as \npreferential sites for chelate formation between TC and Ca2+ in a 1:3 ratio of Ca2+ to TC [20]. In \nthis pH range, reduced competition between H + ions and TC for adsorption sites, along with the \nionization of hydroxyl groups and their subsequent formation of  hydrogen bonds with TC \nmolecules, results in a rapid increase in adsorption capacity . Beyond pH 7, adsorption capacity \ndecreases sharply as TC transforms into negatively charged anions, causing repulsive interactions \nwith oxygen-containing functional groups on the PGC surface . Further, at pH 7.5 and above, the \nchelate complex between Ca2+ and TC preferentially forms at a 1:1 ratio [21]. Hence, the pH range \nbetween 6 and 7 is selected as  optimal for TC adsorption and will be used in subsequent \ninvestigations.  \nEffect of initial concentration and time \nAs depicted in  Figure 4a, adsorption capacity (q e) increases with higher initial concentrations.  \nSpecifically, at  low initial concentrations, adsorption capacity is low owing to the incomplete \ndiffusion of TC molecules into the material structure. However, at higher initial concentrations, a \nlarger concentration gradient drives TC diffusion into the PGC surface, resulting in a rapid increase \nin adsorption capacity. Notably, most of the adsorption occurs within the first 12 h, during which \n89–95% of TC is adsorbed . In the first 8 h, the adsorption rate  of TC  increases rapidly at all \n\n13 \nconcentrations but decreases significantly afterward. This occurs because, during the initial stage, \nnumerous vacant adsorption sites on the surface allow for easy adsorption of TC. As TC molecules \nfill the vacant adsorption sites, the adsorption rate decreases over time until equilibrium is reached \nafter 12–16 h. \nAs depicted in Figure 4a, adsorption efficiency at 60 mg L−1 increases more rapidly in the first 12 \nh than at other concentrations. Therefore, a concentration of 60 mg L −1 was selected for further \ninvestigations. \nEffect of adsorbent dosage \nAn adsorption experiment was performed using 10 different adsorbent dosages at an initial TC \nconcentration of 60 mg L−1 and pH 6–7. Figure 4b presents the effect of adsorbent dosage on  the \nTC adsorption capacity  and efficiency of PGC. Notably, as the adsorbent dosage increases, TC \nadsorption capacity decreases, whereas adsorption efficiency improves owing to the greater \nsurface area available for TC adsorption. Adsorption efficiency increases rapidly as the adsorbent \ndosage rises from 10 to 40 mg, but beyond this point, the rate of increase becomes negligible. \nDoubling the adsorbent dosage to 80 mg results in an increase of no more than 10% in both TC \nadsorption capacity and removal efficiency. However, the amount of TC adsorbed per unit mass \nof adsorbent decreases as dosage increases . Therefore, an adsorbent dosage of 40 mg is selected \nfor subsequent studies. \n\n14 \nAdsorption isotherms \n \nFigure 5: (a) Langmuir adsorption isotherms. (b) Freundlich adsorption isotherms. (c) Variation \nof the equilibrium constant RL as a function of initial concentration. \n \nAn adsorption test was conducted at pH 6–7 using a 40 mg adsorbent dosage, with varying initial \nTC concentrations. Linear regression analysis was applied to Ce/qe and Ce for the Langmuir model \n(Figure 5a) and to lnqe and lnCe for the Freundlich model (Figure 5b). To assess whether TC \nadsorption onto PGC follows  the monolayer adsorption mechanism described by the Langmuir \nmodel, the degree of fit was evaluated using the equilibrium parameter RL. Notably, the RL values, \ncalculated and presented in Figure 5c, range from 0.167 to 0.334, indicating that TC adsorption \nonto PGC is favorable and conforms to the Langmuir isotherm model. The higher R2 value for the \nLangmuir model compared to that for the Freundlich model (Figures 5a and 5b) suggests that the \nLangmuir model better describes TC adsorption onto PGC . This finding indicates that TC \nadsorption onto PGC occurs as monolayer adsorption on a homogeneous surface.  \n  \n\n\n15 \nAdsorption kinetics \nTable 1: First-order kinetics equations and R2 values \nConcentration (mg L−1) First-order kinetics equations R2 \n40 y = −0.1850x + 3.0307 0.9206 \n60 y = −0.1651x + 3.0311 0.8987 \n80 y = −0.1951x + 3.6012 0.9514 \n100 y = −0.1746x + 4.2163 0.9840 \n120 y = −0.1285x + 3.9464 0.9242 \n \nTable 2: Second-order kinetics equations and R2 values \nConcentration (mg L−1) First-order kinetics equations R2 \n40 y = 0.0275x + 0.0303 0.9971 \n60 y = 0.0181x + 0.0113 0.9995 \n80 y = 0.0137x + 0.0103 0.9992 \n100 y = 0.0118x + 0.0245 0.9946 \n120 y = 0.0113x + 0.0212 0.9952 \n \nExperimental data derived from the analysis of the effect of contact time and initial TC \nconcentration on adsorption capacity were used to study the kinetics of TC adsorption using first-\norder and second-order kinetic models. Tables 1 and 2 present the first -order and second -order \nkinetic equations, respectively. Although the first -order kinetic model yields relatively high R 2 \nvalues (0.89–0.98), the equilibrium adsorption capacity calculated based on the model equations \ndeviates significantly from experimental values. Therefore, the first -order kinetic model is \nunsuitable for describing TC adsorption onto PGC. \n\n16 \nIn contrast, the pseudo-second-order kinetic model exhibits high  R2 values (>0.99) and excellent \nagreement between calculated and experimental equilibrium adsorption capacities, indicating that \nit better describes TC adsorption onto PGC . This suggests that the adsorption process is \npredominantly chemisorption. \nMechanism \n \nFigure 6: (a) Structure of the Ca2+‒TC complex formed at pH 6.8. (b) Adsorption mechanism of \nTC onto the PGC surface. \n \nElemental analysis of the synthesized PGC material confirmed the presence of Ca2+, indicating the \npotential formation of  Ca2+‒TC complexes. Notably, the formation of these complexes depends \n\n\n17 \non pH, as specific sites on the TC structure undergo protonation before ionic bonding with Ca2+ in \nthe PGC matrix . Among the four ionizable functional groups in TC, the primary site remains \npredominantly protonated (86%) at pH 6.8 [20], [22], [23]. However, Ca2+ coordination at this site \nis expected to shift the ionization equilibrium toward the β -ketoenolate form , leading to the \ndeprotonation of TC molecules and complex formation with  Ca2+. Experimental results indicate \nthat a 1:3 Ca2+:TC complex is favored at pH 6.8 (Figure 6a) [23]. \n \nThe adsorption mechanism of TC onto PGC is illustrated in Figure 6b. This mechanism involves \nvan der Waals forces, which primarily represent electrostatic interactions . Notably, TC is an \naromatic organic compound with an amino group that can accept protons (H +) from the \nenvironment, acquiring a positive charge . The CMC network within PGC includes oxygen-\ncontaining functional groups (‒OH, ‒C=O, and ‒COOH), which confer a negative charge, \nenabling electrostatic interactions. FT–IR spectroscopy (Figure 2g) confirms the presence of these \noxygen-containing functional groups on PGC, support ing this explanation . Thus, e lectrostatic \nattraction between the positively charged TC –N+ complex and the negatively charged PGC \nmaterial drives the adsorption process . Additionally, hydroxyl groups may facilitate hydrogen \nbond formation between PGC and TC. Furthermore, the aromatic ring of TC contains conjugated \ndouble bonds, while the hexagonal network of PGC contains ‒CH groups, enabling CH–π \ndispersion interactions [24]. \nConclusion  \nThis study developed and implemented a synthesis strategy for a cellulose -derived adsorbent \nmaterial (PGC) to remove TC antibiotics (TC, CTC, and OTC) from aquaculture water. RSM was \n\n18 \nused to determine the optimal synthesis parameters for PGA: CMC mass (1.5 g), PVA mass (1.0 \ng), GA volume (0.01 mL), and Ca2+:Zn2+ molar ratio (0.1). FT–IR, EDX, FE–SEM, and Brunauer–\nEmmett–Teller (BET) analyses were used to assess the cross-linking performance of GA and PVA \nand to elucidate the role of Zn 2+ in cellulose dissolution.  The adsorption of TC onto PGA  was \nexplained by the formation of Ca 2+–TC chelate complexes, as well as electrostatic interactions, \nCH–π interactions, and hydrogen bonding  interactions between the material surface and TC . \nAdditionally, the effects of contact time, pH, initial concentration, and adsorbent do sage on the \nTC adsorption capacity of PGC were investigated . The results indicated that equilibrium was \nreached after 12 h, with an optimal pH of 6 –7, an adsorbent dosage of 40 mg, and an initial \nconcentration of 60 mg L−1. TC adsorption onto PGA followed pseudo-second-order kinetics and \nconformed to the Langmuir isotherm model. Additionally, preliminary tests in real water samples \nrevealed that fulvic acid and humic acid in the water matrix affected the adsorption process.  Owing \nto its high effi ciency, eco -friendliness, versatility, and up to 70% removal efficiency, this \nsynthesized PGC material shows great potential for addressing environmental challenges and \npromoting sustainable development. The PGC adsorbent, with higher porosity, enhanced \nselectivity, more hydrophobicity, and simple synthesis process along with cost-efficiency and high \nadsorption capacity, holds promise as an effective adsorbent for the treatment of aquaculture \nwastewater. Overall, this study lays the groundwork for future research on synthesizing adsorbents \nfrom sustainable, cellulose-based materials derived from agricultural waste.  \n \n \n\n19 \nExperimental  \nMaterials \nTetracycline hydrochloride (97.2 %), oxytetracycline dihydrate (98 %), and chlortetracycline \nhydrochloride (94.6%), all sourced from the Institute of Drug Quality Control, Ho Chi Minh City \n(Vietnam), were used as reference antibiotics  in this study. Additional reagents included \nciprofloxacin and enrofloxacin (both from Pharmaceutical Joint Stock Company of February 3rd, \nVietnam), methanol (Merck, Germany), sodium carboxymethyl cellulose (Zhanyun, China), PVA \n(95.5–96.5% hydrolyzed, M.W. ~85,000 –124,000, Thermo Scientific Chemicals, USA), GA \n(50%) (Zhanyun, China), calcium chloride anhydrous  (Xilong, China), and zinc sulfate \nheptahydrate (Xilong, China). All reagents were of analytical grade, and deion water was used for \nall experiments. \nExperimental optimization \nMODDE 5.0 software was employed to identify key influencing factors and optimize the synthesis \nprocess using RSM. The independent variables included CMC mass (X1) [25], PVA mass (X2), \nand GA volume (X3) [26], along with the molar ratio of Ca2+ and Zn2+ (X4) [27]. \n \nPolyvinyl alcohol (PVA), characterized by a high density of hydroxyl groups attached to its \npolymer chain, is widely used as a binding agent in material synthesis. PVA promotes chemical \ncross-linking between CMC molecules by interacting with acidic and/or basic functional groups \nunder thermal conditions [28], [29]. This cross-linking occurs when the polymer’s free hydroxyl \ngroups interact with the functional groups of the cross-linking agent, reducing the polymer's water \nsolubility while increasing its stiffness and chemical stability [30], [31]. \n\n20 \n \nGlutaraldehyde (GA), a linear five-carbon dialdehyde, is regarded as a more effective cross-linking \nagent compared to monoaldehydes (e.g., formaldehyde) and other dialdehydes (C2 to C6) [32]. GA \nand PVA have been used as cross-linking agents in CMC-based materials to enhance selectivity, \nstability, and mechanical properties [33]. This method is both cost -effective and highly efficient \nin strengthening materials while improving their mechanical strength and hydrophobicity. \n \nRecent studies have revealed that inorganic salt mixtures, such as zinc chloride and calcium \nchloride, effectively dissolve cellulose, facilitating the fabrication of cellulose membranes for gas \nseparation and organic pollutant removal [33], [34] . Specifically, in a cellulose solution, Ca 2+ \ncross-linking with Zn‒cellulose chains enhances the mechanical properties of the resulting \nmembranes. These ions can be incorporated into the cellulose polymer matrix with an appropriate \nratio, forming a controlled hydrogen bonding network that strengthens connectivity in the overall \npolymer network [35]. \nPreparation of PGC \n \nFigure 7: Synthesis procedure for PGC \nAs shown in Figure 7, to prepare PGC, 1.5 g of CMC, 0.25 g of CaCl2, and 3.637 g of ZnSO4 were \nadded to a beaker containing 30 mL of distilled water, where they were completely dissolved under \n\n\n21 \nmagnetic stirring at 800 rpm for 30 min, forming solution A. Subsequently, 1.0 g of PVA and 0.1 \nmL of 1% H2SO4 were added, and the solution was stirred u ntil a homogeneous mixture was \nobtained. Next, 0.01 mL of GA  was added, and the stirring speed was increased to 1, 000 rpm, \ncontinuing for 4 h. Finally, the solution was dried at 65°C for 24 h, yielding the PGC adsorbent \nmaterial for further use. \nCharacterization of PGC \nFE–SEM and EDX \nField emission SEM analysis was performed using a Merlin Compact instrument (Carl Zeiss, Jena, \nGermany) with an SE2 detector. The sample was mounted on a clean silicon wafer and coated with \na nanoscale platinum layer using an ion sputter coater (Q150T Plus, Quorum Technologies, UK). \nEDX analysis was conducted using an Aztec Energy X -MaxN system (Oxford Instruments, UK) \nat an acceleration voltage of 5 kV and a working distance of 8.5 mm. \nFT–IR \nFT–IR analysis was performed using a Spectrum Two FT –IR spectrometer (PerkinElmer, MA, \nUSA) equipped with a LiTaO3 detector and an attenuated total reflectance sampling accessory. \nThe scanning range was 400–4,000 cm−1, with a total acquisition time of 60 s. \nBET \nA 0.2653 g PGC sample was analyzed at the Institute of Chemical Technology, Ho Chi Minh City, \nover 3 h. The specific surface area of this sample was determined using N2 adsorption‒desorption \nisotherms at 77.3 K  under controlled pressure conditions . Before analysis, the  sample was \ndegassed at 150°C for 2 h and 30 min under an N2 atmosphere. \nHigh-performance liquid chromatography-mass spectroscopy (HPLC–MS/MS) \n\n22 \nThe HPLC-MS/MS system consisted of an AB Sciex 4000 QTRAP mass spectrometer equipped \nwith a Turbo Ion Spray source that was operated in both positive mode and negative mode \n(QTRAP®4000, AB SCIEX, Framingham, MA, USA). The analyses of the tetracyclines were \nperformed using a Sunfire C18 column (150 × 2.1 mm i.d., 5.0 mm particle size) from Waters \n(Milford, MA, USA) and the mobile phase consisted of ACN and 0.1% FA, delivered at 0.25 mL \nmin−1. \nFactors influencing adsorption capacity \nExperiments were conducted to evaluate factors affecting the adsorption capacity of PGC and \ndetermine optimal conditions. The investigated factors included initial pH, initial concentration \nand time, adsorbent dosage, adsorption isotherms and adsorption kinetics.  \nAcknowledgments \nThis work was supported by the National Research Foundation of Korea (NRF), grant funded by \nthe Korea government (MSIT) number RS-2023-00219710 and RS-2024-00333541. This research \nis funded by the University of Science, VNU-HCM under grant number T2024-112. \n  \n\n23 \nReferences \n[1] Q. H. Luu, T. B. T. Nguyen, T. L. A. Nguyen, T. T. T. Do, T. H. T. Dao, and P. Padungtod, \n“Antibiotics use in fish and shrimp farms in Vietnam,” Aquac Rep, vol. 20, p. 100711, Jul. \n2021, doi: 10.1016/J.AQREP.2021.100711. \n[2] K. Holmström, S. Gräslund, A. Wahlström, S. Poungshompoo, B. E. Bengtsson, and N. \nKautsky, “Antibiotic use in shrimp farming and implications for environmental impacts and \nhuman health,” Int J Food Sci Technol , vol. 38, no. 3, pp. 255 –266, Mar . 2003, doi: \n10.1046/J.1365-2621.2003.00671.X. \n[3] M. 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