Development of Chitosan–Sulfonated Polystyrene–Sulfonated Nanosilica Nanocomposite Proton Exchange Membranes for Direct Methanol Fuel Cells

Development of Chitosan–Sulfonated Polystyrene–Sulfonated Nanosilica Nanocomposite Proton Exchange Membranes for Direct Methanol Fuel Cells | 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 Development of Chitosan–Sulfonated Polystyrene–Sulfonated Nanosilica Nanocomposite Proton Exchange Membranes for Direct Methanol Fuel Cells Shayan Navabi, Mahdi Tohidian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9426945/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract In this study, proton exchange membranes (PEMs) based on chitosan, sulfonated polystyrene (SPS), and pristine or modified nanosilica were fabricated for direct methanol fuel cell (DMFC) applications. Membranes containing different SPS contents were prepared, and polystyrene was sulfonated to an optimal degree of sulfonation determined by evaluating its hydrolytic stability. Proton conductivity and methanol permeability were measured to determine the membrane selectivity parameter, defined as the ratio of proton conductivity to methanol permeability. Among the prepared membranes, the membrane containing 40 wt.% SPS exhibited the highest selectivity parameter (39,908 S. s. cm − 3 ) and was therefore identified as the optimal composition. To improve membrane performance, nanocomposite membranes containing 2 wt.% silica nanoparticles (SiO 2 ) or sulfonated silica nanoparticles (S-SiO 2 ) were separately prepared using the optimal chitosan/SPS blend. The incorporation of SPS increased the glass transition temperature and decreased the crystallinity of the chitosan matrix due to electrostatic interactions between the –SO 3 H groups of SPS and the –NH 2 groups of chitosan. Furthermore, the nanocomposite membranes exhibited higher proton conductivity and lower methanol permeability compared with the optimal blend membrane. The membrane containing S-SiO 2 nanoparticles showed the highest selectivity (54,010 S. s. cm − 3 ), indicating its strong potential as an alternative proton exchange membrane for DMFC applications. Direct methanol fuel cell Proton conductivity Methanol permeability Sulfonated polymers Acid–base membranes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 1. Introduction Direct methanol fuel cells (DMFCs) continue to garner significant research interest as a leading candidate for clean and sustainable energy conversion technologies, primarily owing to their favorable characteristics such as high energy density, ambient operating temperatures, and negligible environmental impact [1,2]. Central to DMFC performance is the proton exchange membrane (PEM), tasked with orchestrating efficient proton transport across the electrochemical cell while simultaneously mitigating detrimental methanol crossover [3]. While perfluorosulfonic acid (PFSA) membranes, exemplified by Nafion®, have historically dominated this field due to their excellent proton conductivity and robust electrochemical stability [4,5], their inherent drawbacks—including prohibitive cost, limited thermal stability, susceptibility to dehydration, and significant methanol permeability—have spurred an intensive global quest for cost-effective and high-performance alternatives [6]. The exploration of polymer electrolyte membranes derived from renewable feedstocks has gained considerable traction, offering a compelling blend of sustainability, biodegradability, and economic viability. Among these, chitosan (CS), a naturally abundant polysaccharide, presents a unique profile of desirable attributes for PEM applications: inherent hydrophilicity, excellent film-forming characteristics, low intrinsic methanol permeability, commendable thermal stability, and biocompatibility [7–9]. However, the intrinsic proton conductivity of pristine chitosan remains suboptimal, largely attributable to its high degree of crystallinity and the absence of readily mobile proton carriers [10]. Consequently, a diverse array of strategies has been rigorously investigated to enhance the performance metrics of CS-based membranes. These encompass chemical modifications (e.g., sulfonation, crosslinking), polymer blending with proton-donating moieties, incorporation of strong protonic acids, and the development of sophisticated nanocomposite architectures utilizing functionalized nanofillers [11,12]. A particularly promising avenue lies in the strategic design of acid–base pair systems within the polymer matrix. This approach leverages the synergistic interactions between acidic functional groups (e.g., –SO 3 H) and basic functional groups (e.g., –NH 2 ) to facilitate rapid proton hopping mechanisms, thereby establishing low-energy proton transport pathways. Concurrently, strong electrostatic interactions arising from these acid–base pairings contribute to enhanced water management, improved dimensional stability, and superior mechanical robustness [13–15]. Blending basic polymers such as CS or polybenzimidazole (PBI) with acidic polymers like sulfonated poly(ether ether ketone) (SPEEK) or sulfonated polyethersulfone (SPES) represents a well-established method for creating these advantageous acid–base environments [13,16]. Sulfonation is widely recognized as an effective chemical modification strategy for improving the proton conductivity of proton exchange membranes (PEMs). The incorporation of sulfonic acid groups (–SO 3 H) into the polymer backbone introduces proton-conducting sites, thereby increasing the membrane’s hydrophilicity and ion-exchange capacity, which in turn facilitates proton transport throughout the polymer matrix. Nevertheless, although a higher degree of sulfonation generally leads to enhanced proton conductivity, excessive functionalization may adversely affect the membrane by reducing mechanical stability and promoting methanol permeability. Consequently, careful control and optimization of the degree of sulfonation are essential to maintain an appropriate balance between proton conductivity, dimensional stability, and resistance to methanol crossover, all of which critically influence the membrane’s overall performance in DMFC systems. In this context, sulfonated polystyrene (SPS) represents a cost-effective and readily synthesizable aromatic polymer that provides abundant sulfonic acid groups capable of forming effective acid–base interactions [17,18]. Concurrently, the integration of organic–inorganic nanocomposites has emerged as a powerful paradigm for simultaneously improving the mechanical integrity, thermal endurance, and ionic transport properties of polymer membranes. Hybrid systems leveraging the flexibility and processability of organic polymer matrices with the inherent rigidity and thermal resistance of inorganic nanoparticles, such as silica, offer a pathway to achieving a well-balanced property profile [19]. Silica nanoparticles, in particular, are widely employed to enhance thermal stability, mechanical modulus, water retention, and proton conductivity. However, challenges related to nanoparticle aggregation and potential blockage of ionic pathways necessitate surface modification strategies. Functionalization of nanofillers with acidic or basic groups not only promotes uniform dispersion within the polymer matrix but also strengthens interfacial interactions, thereby facilitating the formation of interconnected proton-conductive channels, particularly through acid–base pair mechanisms within the composite [20–22]. Notably, Wang et al. [23] demonstrated substantial improvements in DMFC performance by incorporating carboxylated silica into CS membranes, achieving a 63% decrease in methanol permeability and a 40% increase in proton conductivity compared to the unmodified CS membrane. Despite these advancements, a critical research gap persists in the systematic exploration and optimization of hybrid chitosan-based nanocomposite membranes that synergistically integrate both an acidic polymer (SPS) and functionalized inorganic nanofillers (silica/sulfonated silica). Specifically, there is a paucity of studies that comprehensively address the rational design and characterization of CS/SPS acid–base blend membranes, the optimization of the blend composition to maximize proton selectivity, and the evaluation of the synergistic effects derived from incorporating silica and sulfonated silica nanoparticles on enhancing proton conductivity while simultaneously suppressing methanol crossover. This knowledge deficit underscores the need for a holistic investigation into developing advanced CS-based PEMs that leverage multi-component interactions for superior DMFC performance. Building upon our prior investigation [12], which demonstrated the efficacy of CS/Nafion blends in enhancing proton transfer through interfacial interactions, the present research embarks on an extended exploration. We systematically investigate the impact of introducing sulfonated polystyrene (SPS) and silica-based nanofillers on the performance characteristics of chitosan membranes tailored for DMFC applications. The SPS component was chemically functionalized with sulfonic acid (–SO 3 H) groups to imbue proton-conducting capabilities, while the inherent basic amine (–NH 2 ) groups of chitosan were strategically utilized to establish robust acid–base interactions and hydrogen-bonding networks, thereby creating efficient proton transport conduits. A series of CS/SPS blend membranes with systematically varied weight ratios was fabricated, and their optimal composition was rigorously determined based on the proton selectivity parameter (defined as the ratio of proton conductivity to methanol permeability, σ/P). Subsequently, the optimized blend was modified by incorporating silica and sulfonated silica nanoparticles to investigate their synergistic role in enhancing proton conductivity while reducing methanol permeability. The membranes were systematically evaluated in terms of thermal and chemical stability, proton conductivity, and methanol permeability. The results indicate that the combined effect of acid–base interactions between CS and SPS together with functionalized silica nanoparticles forms efficient proton transport pathways, improves physicochemical stability, and significantly suppresses methanol crossover, making these membranes promising alternatives to commercial Nafion membranes. 2. Materials and Methods 2.1. Materials Polystyrene (grade 1028, Mw ≈ 30,000 g. mol − 1 ) was supplied by Petropak Mashregh Zamin Co. (Iran). Chitosan with a medium molecular weight and a degree of deacetylation of approximately 80% was purchased from Sigma-Aldrich (USA). Methanol, dichloromethane, and sulfuric acid were obtained from Dr. Mojalli Co. (Iran), whereas acetic anhydride was provided by Pars Chemical Co. (Iran). Acetic acid, dimethylformamide (DMF), sodium hydroxide, and hydrochloric acid were purchased from Merck (USA). Nanosilica (SiO 2 ) with a specific surface area of 250 ± 30 m 2 . g − 1 and approximately 2.2 silanol groups per nm 2 was supplied by Evonik (Germany). 2.2. Sulfonation of polystyrene Polystyrene was sulfonated (SPS) according to the method described in our earlier study [24]. In brief, acetyl sulfate—the sulfonating reagent—was prepared by mixing 50 mL of dichloromethane, 13.7 mL of acetic anhydride, and 9.25 mL of sulfuric acid under continuous stirring for 40 minutes. Owing to the strongly exothermic nature of the reaction, the mixture was maintained in an ice bath throughout this step. Subsequently, to obtain the SPS with the optimum degree of sulfonation (18.26%), 5 g of polystyrene was introduced into the acetyl sulfate solution and allowed to react at 25°C to achieve an optimal degree of sulfonation. The reaction was continued for an additional 120 minutes until a uniform mixture was obtained. Upon completion, SPS was precipitated by adding deionized water, and the resulting white solid was thoroughly washed multiple times with deionized water to eliminate any remaining acidic by-products or unreacted reagents. 2.3. Sulfonation of SiO 2 The SiO 2 nanoparticles were sulfonated using sulfuric acid following the procedure reported by Wang et al. [25]. A predetermined amount of SiO 2 nanoparticles was dispersed in 35 mL of a methanolic solution containing 15 mL of 0.5 M sulfuric acid. The resulting mixture was ultrasonicated for 1 h to facilitate surface functionalization. Subsequently, the product was washed with deionized water through six successive centrifugation–redispersion cycles to remove residual acid and impurities. Finally, the obtained white powder was dried at 100°C for 24 h to yield sulfonated silica nanoparticles (S-SiO 2 ). 2.4. Preparation of the blend membranes The blend membranes were prepared using the solution-casting method. First, dried chitosan powder was dissolved in a pre-prepared aqueous acetic acid solution (2% v/v) to obtain a 2 wt.% chitosan solution. Meanwhile, SPS was dissolved in dimethylformamide (DMF) at 25°C for 2 h. The SPS solution was then slowly added to the chitosan solution under continuous stirring, and the mixture was stirred at room temperature for 24 h to obtain homogeneous CS/SPS blend solutions. The weight ratios of chitosan to SPS were adjusted to 100:0, 90:10, 80:20, 70:30, and 60:40, and the resulting membranes were denoted as CS, CSSPS10, CSSPS20, CSSPS30, and CSSPS40, respectively. The prepared CS/SPS solutions were cast onto glass Petri dishes and dried at 40°C for 48 h to form the membranes. To neutralize the chitosan-based membranes, the dried films were immersed in a 1 N sodium hydroxide solution and subsequently washed several times with deionized water. To induce ionic crosslinking between chitosan chains, the membranes were then immersed in a 1 M sulfuric acid solution for 24 h. After crosslinking, the membranes were thoroughly washed with deionized water to remove excess sulfuric acid and finally dried at room temperature for 24 h. A crosslinked chitosan membrane (CS) was also prepared using the same procedure without the addition of SPS. 2.5. Preparation of the blend nanocomposite membranes To fabricate the blend nanocomposite membranes, the CSSPS40 blend solution was initially prepared. Then, 2 wt.% of SiO 2 and S-SiO 2 nanoparticles were separately added to the solutions and stirred with a magnetic stirrer for 24 h. In the next step, the mixtures were ultrasonicated for 1 h, poured into a glass Petri dish, and dried at 40°C for 48 h. Finally, as described previously, the dried membranes were neutralized and then cross-linked. The blend nanocomposite membranes prepared with nanosilica and sulfonated nanosilica were designated as CSSPS40/SiO 2 and CSSPS40/S-SiO 2 , respectively. 2.6. Characterization techniques Fourier Transform Infrared Spectroscopy (FTIR) Fourier transform infrared spectroscopy (FTIR) was employed to confirm the sulfonation of SiO 2 . The spectra were recorded using an FTIR spectrometer (Equinox 55, Bruker, Latvia) in the wavenumber range of 4000–400 cm − 1 with a resolution of 2 cm − 1 . Zeta potential Zeta potential measurements were performed using a Zetasizer (Version 7.11, Malvern Instruments Ltd., UK) to evaluate the surface charge characteristics of pristine SiO 2 and sulfonated SiO 2 (S-SiO 2 ) nanoparticles. Ion Exchange Capacity (IEC) The ion exchange capacity (IEC), which represents the number of available proton-exchangeable sites per unit mass of the membrane, was determined by an acid–base titration method. In this procedure, the dried membranes were first accurately weighed and then immersed in 0.01 N NaOH solution for 24 h to completely exchange the H + ions in the membranes with Na + ions. The IEC value was calculated using Eq. ( 1 ): $$\:\text{I}\text{E}\text{C}=\frac{\left({\text{V}}_{\text{N}\text{a}\text{O}\text{H}}-{\text{V}}_{\text{H}\text{C}\text{l}}\right)\times\:\text{M}}{{\text{W}}_{\text{d}\text{r}\text{y}}}$$ 1 where V NaOH and V HCl are the volumes of NaOH and HCl solutions (mL) used in titration, M is the concentration of solutions (0.01 N), and W dry is the weight of dry membrane (g). Water uptake Water molecules play a crucial role in facilitating proton transport within polymer electrolyte membranes. Therefore, evaluating the water uptake behavior of the membranes is essential for understanding their proton conduction performance. For water uptake measurements, the membranes were first thoroughly dried in a vacuum oven and accurately weighed. The samples were then immersed in deionized water at ambient temperature. After reaching swelling equilibrium, the excess surface water was gently removed using filter paper, and the membranes were immediately reweighed. This procedure was repeated until a constant weight was obtained. The following Eq. ( 2 ) was used to determine the water uptake of the samples: $$\:\text{W}\text{U}\:\left(\text{%}\right)=\frac{{\text{W}}_{\text{w}\text{e}\text{t}}-{\text{W}}_{\text{d}\text{r}\text{y}}}{{\text{W}}_{\text{d}\text{r}\text{y}}}\:\times\:\:100$$ 2 where W wet is the weight of the fully hydrated membrane, and W dry is the weight of the completely dried membrane, respectively. Additionally, the average number of absorbed water molecules per ion-conducting group (λ) was determined using Eq. ( 3 ). $$\:{\lambda\:}=\frac{\text{W}\text{U}}{\text{I}\text{E}\text{C}\:\times\:\:{\text{M}}_{\text{w}}}$$ 3 where M w is the molecular weight of water (18 g. mol − 1 ). Atomic Force Microscopy (AFM) A tapping mode AFM (model: Universal SPM, Ambios Technology, USA) with a micro-fabricated cantilever was employed to explore the surface topography and roughness of the membranes in the ambient atmosphere at a frequency of 180 kHz. Surface roughness parameters such as average roughness (R a ) and root mean square roughness (R q ) were obtained from the 5 µm × 5 µm scan. Contact angle measurement Static contact angle measurements were conducted using a contact angle goniometer (Jikan CAG-20, Iran) to assess the surface wettability and hydrophilicity of the prepared membranes. A droplet of deionized water was gently placed on the membrane surface, and the contact angle was determined using the Smart Drop software based on the Bashforth–Adams fitting method. Each reported contact angle value represents the average of at least three independent measurements. Thermogravimetric Analysis (TGA) TGA was performed using an SDT Q600 V20.9 Build 20 analyzer (TA Instruments, USA) to assess the thermal stability of the prepared membranes. Approximately 10 mg of thoroughly dried membrane samples were used for each test. The measurements were conducted under a nitrogen atmosphere at a heating rate of 10°C min − 1 , from room temperature up to 800°C. Differential Scanning Calorimetry (DSC) Differential scanning calorimetry (DSC) was carried out using a DSC1 Star System (Mettler Toledo, USA) to examine the thermal characteristics of the membranes. The glass transition temperature (T g ) of the PEMs was determined by heating the samples from 25 to 250°C at a rate of 10°C min − 1 under a nitrogen atmosphere. DSC analysis was also employed to quantify the amounts of free water and bound water within the membranes. For this purpose, fully hydrated membranes were weighed and sealed in DSC pans. The samples were first cooled to − 40°C to freeze the free water molecules and subsequently heated to 40°C at a rate of 5°C min − 1 . An endothermic melting peak appeared near 0°C, and the corresponding peak area was used to calculate the amount of freezable (free) water in the membrane. The weight fraction of free water (W f ) was then determined using Eq. ( 4 ). $$\:{\text{W}}_{\text{f}}=\frac{{\Delta\:}{\text{H}}_{\text{m}}}{{\text{Q}}_{\text{m}\text{e}\text{l}\text{t}\text{i}\text{n}\text{g}}}=\frac{\int\:{\Delta\:}{\text{C}}_{\text{P}}d\text{t}}{{\text{Q}}_{\text{m}\text{e}\text{l}\text{t}\text{i}\text{n}\text{g}}}$$ 4 where ΔH m is the total melting enthalpy, Qmelting is the heat of fusion of bulk ice (334 J. g − 1 ), and ΔCp is the transition heat capacity. The bound water content, which plays a crucial role in proton conduction, was calculated by subtracting the free water content from the total water uptake. Finally, the bound water degree (χ), which is defined as the ratio of bound water content to free water content, was calculated for each membrane. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX) Scanning electron microscopy (SEM) (Seron Technology, South Korea) was employed to examine the cross-sectional morphology and thickness of the prepared membranes. The membranes were fractured in liquid nitrogen to obtain clean cross-sections and then sputter-coated with a thin layer of gold prior to imaging. The micrographs were recorded under high-vacuum conditions. In addition, field emission scanning electron microscopy (FE-SEM) (TESCAN MIRA3) equipped with energy-dispersive X-ray spectroscopy (EDX) was used to investigate the surface morphology and elemental composition of the silica nanoparticles. The FE-SEM/EDX system was also utilized to perform elemental mapping of the cross-sections of the composite membranes. All images were obtained under high-vacuum conditions. X-ray diffraction (XRD) X-ray diffraction (XRD) analysis was performed using a QUINOX3000 diffractometer (Thermo Scientific, USA) to investigate the crystalline structure of the prepared membranes. The diffraction patterns were recorded in the 2θ range of 10°–80° at a scanning rate of 2° min − 1 using Cu Kα radiation as the X-ray source. Oxidative stability The oxidative stability of the membranes was evaluated using Fenton’s reagent, which simulates the oxidative conditions present in fuel cells. In this test, the membranes were fully immersed in the Fenton solution and the weight change was monitored after a specified period. The Fenton solution consisted of 3 wt.% hydrogen peroxide containing 4 ppm Fe 2+ ions, which can readily generate oxidative species capable of degrading the membrane without requiring elevated temperature or pressure. Prior to the test, the membranes were thoroughly dried and accurately weighed. The samples were then immersed in 50 mL of the prepared solution at room temperature for 24 h. After the treatment, the membranes were removed, dried, and reweighed to determine the extent of weight loss [12]. Proton conductivity For proton conductivity measurements, electrochemical impedance spectroscopy (EIS) was carried out using an MCTS 94A analyzer (Ahnsco, Iran). The measurements were performed in the through‑plane configuration using fully hydrated membrane samples under saturated humidity conditions (≈ 100% RH). The impedance spectra were collected over a frequency range from 1 MHz to 1 Hz with an AC perturbation amplitude of 10 mV under open‑circuit conditions. The membrane resistance was obtained from the high‑frequency intercept of the Nyquist plot. Each experiment was repeated at least three times, and the reported conductivity values represent the average along with the corresponding standard deviation. The proton conductivity was calculated using Eq. ( 5 ). $$\:{\sigma\:}=\frac{\text{L}}{\text{R}\times\:\text{A}}$$ 5 where σ is the proton conductivity (S. cm − 1 ), L is the membrane thickness (cm), R is the membrane resistance (Ω), and A is the cross-sectional surface area of the membrane (cm 2 ). Methanol permeability The methanol permeability of the membranes was measured using a laboratory diffusion cell, wherein the membrane was positioned between two distinct chambers (A and B). Chamber A was filled with a 5 M methanol solution, while Chamber B was filled with deionized water. To maintain homogeneity, a mechanical stirrer was used to stir the solutions. The concentration of methanol in chamber B was measured using gas chromatography analysis (Agilent 6890 N) at specified time intervals. The following Eq. ( 6 ) was used to determine the methanol permeability at room temperature: $$\:\text{P}=\frac{1}{{\text{C}}_{\text{A}}}\times\:\frac{{\Delta\:}{\text{C}}_{\text{B}}\left(\text{t}\right)}{{\Delta\:}\text{t}}\times\:\frac{{\text{V}}_{\text{B}}\times\:\text{L}}{\text{A}}$$ 6 In this equation, C A is the methanol concentration in chamber A (mol. L − 1 ), and ΔC B (t)/Δt is the slope of methanol concentration variation over time in chamber B; L, A, V B , and P are the membrane thickness (cm), membrane surface area (cm 2 ), water volume in chamber B (cm 3 ), and methanol permeability (cm 2 . s − 1 ), respectively. 3. Results and discussion FTIR analysis was performed to confirm the successful sulfonation of silica nanoparticles, and the spectra of pristine SiO 2 , and S-SiO 2 are presented in Fig. 1 . In the spectrum of pristine SiO 2 , the strong absorption band at 1,101 cm − 1 is attributed to the asymmetric stretching vibration of Si–O–Si bonds, while the band observed at 960 cm − 1 corresponds to the stretching vibration of surface silanol (Si–OH) groups. After sulfonation, the spectrum of S-SiO 2 exhibits additional characteristic bands at 1,171 cm − 1 and 1,286 cm − 1 , which are assigned to the asymmetric and symmetric stretching vibrations of the sulfonic acid (–SO 3 H) groups. The appearance of these bands provides clear evidence for the successful introduction of sulfonic acid functionalities onto the surface of the silica nanoparticles. In addition, the broad absorption band centered around 3400 cm − 1 is associated with the stretching vibration of hydroxyl groups and adsorbed water molecules on the surface of both SiO 2 and S-SiO 2 nanoparticles, reflecting the hydrophilic nature of the silica surface. The band observed around 1,640 cm − 1 is attributed to the bending vibration of molecularly adsorbed water (H–O–H), which is associated with the hydrophilic silanol groups present on the silica surface [26,27]. The zeta potential measurements were carried out to investigate the surface charge characteristics of SiO 2 and sulfonated silica (S-SiO 2 ) nanoparticles and to confirm the successful surface modification. The variation of zeta potential as a function of pH is presented in Fig. 2 . For pristine SiO 2 , the zeta potential exhibits a positive value at strongly acidic conditions (pH = 2, + 3.2 mV) and gradually shifts toward negative values with increasing pH, reaching − 28 mV at pH 12. This behavior is attributed to the acid–base properties of surface silanol groups (Si–OH). At low pH, these groups remain protonated, resulting in a slightly positive surface charge. As the pH increases, progressive deprotonation of silanol groups occurs, forming negatively charged siloxide groups (Si–O − ), which leads to increasingly negative zeta potential values. In contrast, S-SiO 2 nanoparticles exhibit significantly more negative zeta potential values over the entire pH range. For instance, the zeta potential changes from − 1.4 mV at pH 2 to − 38 mV at pH 12. The consistently more negative surface charge of S-SiO 2 compared with pristine SiO 2 can be attributed to the presence of sulfonic acid (–SO 3 H) groups introduced during the sulfonation process. These groups readily dissociate in aqueous media to form negatively charged sulfonate species (–SO 3 − ), thereby increasing the surface charge density. The noticeable shift toward more negative zeta potential values after sulfonation clearly indicates the successful functionalization of the silica surface with sulfonic acid groups [20]. The FE-SEM micrographs of pristine SiO 2 and S-SiO 2 nanoparticles are presented in Fig. 3 . The pristine SiO 2 nanoparticles exhibit a relatively uniform and well-defined spherical morphology with a narrow particle size distribution, indicating a homogeneous particle formation. After the sulfonation treatment, the FE-SEM image of S-SiO 2 reveals that the nanoparticles largely retain their original spherical morphology and size, with no noticeable structural deformation. This observation indicates that the sulfonation process primarily occurs at the surface of the silica nanoparticles and does not significantly affect their morphological structure. Therefore, the chemical functionalization with sulfonic acid groups successfully modifies the surface properties of SiO 2 while preserving the intrinsic morphology of the nanoparticles [28]. The elemental composition of S-SiO 2 nanoparticles was analyzed using EDX, and the corresponding spectrum is presented in Fig. 4 . The spectrum exhibits the characteristic peaks of Si and O associated with the silica framework, along with a distinct sulfur peak, confirming the successful incorporation of sulfur-containing functional groups onto the silica surface. Quantitative analysis indicates that the sulfur content in S-SiO 2 is approximately 3.6 wt.%. Considering the stoichiometry of the sulfonic acid group (–SO 3 H), this sulfur content corresponds to about 9.1 wt.% of sulfonic acid functionalities grafted onto the silica surface (112.5 mmol of –SO 3 H groups per 100 g of S-SiO 2 ). The appearance of sulfur, which is absent in pristine SiO 2 , provides clear evidence for the successful sulfonation of the nanoparticles. These results confirm that the sulfonation process effectively introduces sulfonic acid groups onto the surface of SiO 2 nanoparticles [28,29]. Figures 5 a–d illustrate the cross-sectional SEM micrographs of the CS, SPS, CSSPS40, and CSSPS40/S-SiO 2 membranes. All membranes exhibit a dense, compact, and defect-free morphology throughout the thickness, with no observable voids, cracks, or pinholes. This compact structure is crucial for suppressing methanol crossover and maintaining the mechanical integrity required for DMFC applications. The CSSPS40 blend membrane (Fig. 5 c) shows no signs of macrophase separation, indicating good miscibility and interfacial compatibility between chitosan and SPS. Such compatibility is expected to result from hydrogen bonding and electrostatic interactions between the hydrophilic CS chains and the sulfonated aromatic segments of SPS [30]. In the CSSPS40/S-SiO 2 composite membrane (Fig. 5 d), the SEM micrograph reveals that the functionalized silica nanoparticles are well dispersed within the polymer matrix without forming visible aggregates. The bright nano-sized spots correspond to S-SiO 2 particles and confirm their successful incorporation. Homogeneous dispersion of these nanoparticles suggests strong interactions—likely hydrogen bonding—between the surface –SO 3 H groups of S-SiO 2 and the functional groups of the polymer matrix (–NH 2 and –OH of chitosan, and –SO 3 H of SPS). This uniform distribution plays a key role in creating a more tortuous pathway for methanol molecules, thereby decreasing methanol permeability and enhancing membrane selectivity. To further verify nanoparticle dispersion and evaluate the distribution of functional groups, EDX elemental mapping of the composite membrane was conducted (Figs. 5 e–g). The silicon map (Fig. 5 e) shows a uniform and continuous distribution of Si signals across the cross-section, confirming that S-SiO 2 particles are homogenously embedded within the membrane structure. The nitrogen map (Fig. 5 f), which corresponds to the –NH 2 groups of chitosan, shows an even distribution throughout the matrix, indicating the absence of polymer phase segregation. The sulfur map (Fig. 5 g) exhibits a uniform distribution of –SO 3 H groups originating from both SPS and S-SiO 2 . The co-localization of N and S signals demonstrates that proton-conducting sites are evenly dispersed across the membrane, which is essential for forming efficient proton-transfer pathways [31,32]. Overall, the combination of dense morphology, absence of defects, strong polymer–filler interactions, and uniform distribution of proton-conducting functional groups suggests that the CSSPS40/S-SiO 2 membrane possesses the structural features necessary for improved proton conductivity, reduced methanol crossover, and enhanced mechanical stability. These morphological characteristics support its potential as a promising proton exchange membrane for DMFC applications. Figure 6 shows XRD patterns of the pristine CS membrane and the CSSPS40 blend membrane, providing insight into the structural modifications occurring in the polymer matrix after the incorporation of SPS. The CS membrane exhibits two characteristic diffraction peaks at approximately 2θ = 12° and 23°, which are typical of the semi-crystalline structure of chitosan. The diffraction peak at around 12° is attributed to the ordered crystalline domains arising from strong intermolecular hydrogen bonding between chitosan chains, while the broad peak near 23° corresponds to the amorphous regions of the polymer structure [10,33]. Upon blending with SPS, noticeable changes appear in the XRD profile of the CSSPS40 membrane. Specifically, the intensity of the crystalline peak decreases and becomes broader compared to that of the pristine CS membrane, indicating a partial disruption of the ordered chitosan structure. This reduction in crystallinity can be attributed to the strong electrostatic interactions between the protonated amino groups (–NH 3 + ) of chitosan and the sulfonic acid groups (–SO 3 H) of SPS. These interactions disturb the regular packing between chitosan chains, resulting in a less ordered polymer arrangement [34]. The decrease in crystallinity consequently increases the fraction of amorphous regions within the membrane matrix. Such an increase in amorphous domains enhances polymer chain mobility and may facilitate the formation of interconnected proton-transport pathways. These structural features are beneficial for proton conduction, as the amorphous phase provides more accessible sites for proton hopping and water-assisted proton transport mechanisms. Therefore, the observed structural modification in the CSSPS40 membrane is expected to contribute positively to the proton conductivity and overall electrochemical performance of the membrane in proton exchange membrane fuel cell applications [35]. The thermal stability of proton exchange membranes (PEMs) is a crucial factor determining their durability and performance under fuel cell operating conditions. Therefore, the thermal behavior of the prepared membranes was investigated using TGA, and the results are displayed in Fig. 7 . The TGA curve of the pristine CS membrane exhibits three main stages of thermal decomposition under a nitrogen atmosphere. The first weight loss, occurring between 50°C and 200°C, corresponds to the evaporation of physically adsorbed and bound water molecules due to dehydration. The second stage, observed between 200°C and 300°C, is attributed to the degradation of chitosan side-chain functional groups, including amino (–NH 2 ) and hydroxyl groups, as well as partial desulfonation of any residual acid functionalities. The third degradation phase initiates at approximately 300°C and extends to higher temperatures, representing the decomposition of the chitosan backbone structure, which leads to complete thermal decomposition of the polymer matrix [12,36,37]. The SPS membrane also exhibits a three-step thermal degradation profile. The first step, between 50°C and 200°C, is associated with the release of absorbed water interacting with the hydrophilic –SO 3 H groups. The second stage, spanning 200–360°C, corresponds to the decomposition of sulfonic acid groups and fragmentation of the aromatic polymer framework. The final step involves the complete breakdown of the polymer chains at higher temperatures [38]. The TGA curves of the CSSPS40 and CSSPS40/S-SiO 2 composite membranes show similar overall decomposition patterns, with improved thermal stability compared to the pristine CS membrane. The lower weight loss observed at corresponding temperature intervals suggests that blending chitosan with SPS and incorporating S-SiO 2 nanoparticles strengthens the polymer matrix and enhances its resistance to thermal degradation. This improvement is likely due to strong interfacial interactions—including hydrogen bonding and electrostatic attractions—between the functional groups of the polymer chains and the surface of S-SiO 2 nanoparticles, which restrict polymer chain mobility and delay decomposition. Consequently, the CSSPS40/S-SiO 2 membrane demonstrates superior thermal endurance. The thermal behavior of the prepared membranes was further examined using differential scanning calorimetry (DSC), and the results are presented in Fig. 8 . All membranes exhibit an endothermic peak within the temperature range of 200–240°C, which is associated with the thermal decomposition of the chitosan chains, which is consistent with the TGA results. In addition, the acid–base interactions between chitosan and sulfonated polystyrene not only lead to an increase in the thermal decomposition temperature of the membranes but also result in an enhancement of the glass transition temperature (T g ). Specifically, the protonated amino groups (–NH 3 + ) of chitosan interact electrostatically with the sulfonic acid groups (–SO 3 H/–SO 3 − ) of SPS, forming ionic pairs within the polymer network. These interactions act as physical cross-linking points that restrict the segmental mobility of polymer chains and increase the rigidity of the polymer matrix. Consequently, greater thermal energy is required to initiate chain motion, leading to an increase in the T g of the blended membranes compared with the pristine chitosan membrane. Moreover, the formation of these strong intermolecular interactions also influence the free volume of the membrane and the transport phenomena within it, stabilize the polymer structure and delay the onset of thermal degradation, which contributes to the improved thermal stability observed for the composite membranes [39–41]. IEC is one of the most important parameters of PEMs, as it reflects the density of proton-conducting sites within the membrane structure and is closely related to water uptake and electrochemical performance [31]. The IEC values of the prepared membranes are shown in Fig. 9 . As can be observed, the CS membrane exhibits a lower IEC compared with the blend membranes. This behavior might be attributed to the relatively high crystallinity of chitosan, which restricts the accessibility of ion-exchangeable functional groups. With increasing SPS content in the chitosan matrix, the IEC of the blend membranes increases noticeably. This improvement can be attributed to higher IEC of SPS which stems from the sulfonic acid groups (–SO 3 H) present in its structure, serving as additional proton-conducting sites, in addition to the reduction in crystallinity of the blend system relative to the CS membrane, leading to the formation of more amorphous regions that facilitate the accessibility of functional groups responsible for ion transport [12]. The incorporation of SiO 2 results in a marginal increase in IEC, whereas the addition of S-SiO 2 leads to a more pronounced enhancement. This improvement is primarily attributed to the sulfonic acid (–SO 3 H) moieties present on the surface of S-SiO 2 nanoparticles, which introduce additional proton-conducting sites. Furthermore, the hydroxyl groups on the surface of pristine nanosilica also participate in proton exchange through hydrogen-bonding interactions, contributing to the overall increase in IEC within the membrane structure [27]. Water uptake is one of the most important parameters of proton exchange membranes. The presence of water facilitates proton transport within the membrane; however, excessive water absorption can negatively affect membrane performance by reducing dimensional stability, increasing the swelling ratio, and deteriorating mechanical properties [42]. Therefore, controlling the water uptake of PEMs is essential to achieve an appropriate balance between proton conductivity and structural stability. The water uptake values of the prepared membranes are presented in Fig. 9 . The pristine CS membrane exhibited the highest water uptake due to the inherently hydrophilic nature of chitosan [43]. With increasing SPS content in the CS matrix, the water uptake of the blend membranes gradually decreased. This behavior can be attributed to the relatively lower water affinity of SPS compared with chitosan, as well as the electrostatic interactions between the amino groups of chitosan and the sulfonic acid groups of SPS, which reduce the free volume within the membrane structure [16,44]. The CSSPS40/SiO 2 membrane shows slightly higher water uptake than CSSPS40, owing to the hydrophilic nature of SiO 2 and the presence of hydroxyl groups on its surface. Moreover, the CSSPS40/S-SiO 2 membrane exhibits higher water uptake than CSSPS40/SiO 2 , which is mainly attributed to the sulfonic acid groups on the surface of the functionalized nanoparticles that can form hydrogen bonds with water molecules, thereby enhancing the membrane hydrophilicity [28]. Besides the total water uptake, the state of water molecules within the fabricated membranes is also an important factor to consider. Generally, the water absorbed by hydrophilic groups can be classified into two categories: bound water and free water. Bound water refers to water molecules that surround ionic groups and form hydrogen bonds within ionic domains, thereby facilitating various transport mechanisms and enhancing proton transport across the membrane. In contrast, free water consists of water molecules that occupy the free volume within the membrane structure [45]. The amounts of bound and free water in the fabricated membranes are presented in Table 1 . The incorporation of SPS into the CS matrix in the CSSPS40 membrane, as well as the addition of S-SiO 2 , increases the proportion of bound water relative to free water, which is beneficial for proton conduction. This behavior can be attributed to the presence of sulfonic acid (–SO 3 H) groups in SPS and S-SiO 2 , which promote the formation and stabilization of bound water molecules within the membrane through hydrogen-bonding interactions [46]. Table 1 The water state values, and surface roughness of the prepared membranes. Sample SPS CS CSSPS40 CSSPS40/S-SiO 2 IEC (meq. g − 1 ) 1.54 0.18 0.69 0.91 Water uptake (%) 24 110 66 71 Mean roughness (nm) 0.8 12.3 22.1 23.3 Rms roughness (nm) 1.3 16.5 28.1 29.7 λ 8.76 342.53 53.14 43.34 λ f 5.41 267.89 32.35 23.59 λ b 3.35 74.64 20.79 19.75 Bound water (%) 38.24 21.79 39.14 45.57 χ 0.62 0.27 0.64 0.83 Note : λ: the total number of water molecules per proton-conducting group. λ b : the number of bound water molecules per a proton-conducting group. λ f : the number of free water molecules per a proton-conducting group. χ: the ratio of bound water to free water content. AFM was employed to investigate the surface morphology of chitosan-based membranes incorporating SPS and S-SiO 2 , with the corresponding roughness data summarized in Table 1 and Fig. 10 . The pristine CS membrane exhibited a relatively uniform and homogeneous surface, although its roughness was higher than that of SPS. Upon the incorporation of SPS (CSSPS40), the surface roughness (S q ) increased markedly from 16.5 nm to 28.1 nm, which can be attributed to the formation of heterogeneous microdomains arising from electrostatic interactions between the amino groups of CS and the sulfonic acid groups of SPS, as well as the partial disruption of polymer crystallinity leading to a more amorphous surface structure. This morphological evolution is in agreement with the observed trend in water uptake [7]. The CSSPS40/S-SiO 2 membrane exhibited only a slight further increase in surface roughness compared to CSSPS40, suggesting improved interfacial compatibility and uniform dispersion of S-SiO 2 nanoparticles within the matrix [15]. The surface hydrophilicity of the membranes was evaluated by contact angle measurements, and the corresponding results are presented in Fig. 11 . As compared to the pristine CS membrane, the CSSPS40 membrane exhibited a higher contact angle, indicating a moderate reduction in surface hydrophilicity upon the incorporation of SPS. This behavior can be attributed to the combined effects of altered surface morphology and microphase separation within the blended matrix, as evidenced by the increased surface roughness observed in AFM analysis [31]. The CSSPS40/S-SiO 2 membrane exhibited a lower contact angle compared to the CSSPS40 membrane, indicating an increase in surface hydrophilicity after the incorporation of S-SiO 2 nanoparticles. This behavior can be attributed to the presence of hydrophilic functional groups, particularly sulfonic acid and hydroxyl groups, on the surface of S-SiO 2 nanoparticles, which enhance the affinity of the membrane surface toward water molecules. The improved hydrophilicity is consistent with the observed increase in water uptake for the CSSPS40/S-SiO 2 membrane. The presence of these polar functional groups promotes stronger hydrogen-bonding interactions with water and facilitates the formation of hydrophilic domains within the polymer matrix, thereby enabling greater water absorption. Consequently, the reduced contact angle and increased water uptake collectively confirm that the incorporation of S-SiO 2 enhances the overall hydrophilic character of the membrane, which is beneficial for proton transport in proton exchange membrane applications [47]. In a fuel cell environment, the electrochemical reactions occurring at the anode and cathode generate highly reactive oxygen species, including hydroperoxyl (HOO˙) and hydroxyl (HO˙) radicals, which can attack polymer backbones and functional groups, ultimately leading to membrane degradation and performance loss [48]. Therefore, ensuring adequate oxidative stability is essential for the long-term durability of proton exchange membranes. The oxidative stability of the prepared membranes was assessed through weight-loss measurements after exposure to Fenton’s reagent, and the corresponding results are shown in Fig. 12 . The pristine SPS membrane exhibited moderate stability, with a weight loss of 5.0 wt.%. The CSSPS40 membrane demonstrated a significantly lower weight loss (12.4 wt.%) compared to the pristine CS membrane (20 wt.%), indicating improved resistance to oxidative attack. This enhancement is attributed to the protective effect of SPS, where the –SO 3 H groups interact with chitosan’s –NH 2 groups through ionic cross-linking and hydrogen bonding, thereby reducing the susceptibility of the polymer chains to radical-induced degradation [49]. Furthermore, the incorporation of S-SiO 2 nanoparticles further improved the membrane’s oxidation resistance, with the CSSPS40/S-SiO 2 sample exhibiting a reduced weight loss of 11.3 wt.%. This improvement arises from strong interfacial interactions between the nanoparticles and the polymer matrix, which help stabilize the membrane structure and hinder radical penetration [50]. Overall, the results confirm that the synthesized membranes possess good oxidative stability, making them suitable candidates for DMFC applications. Low methanol permeability is a critical requirement for improving the efficiency of DMFCs. In PEMs, methanol crossover predominantly occurs due to the combined effects of concentration gradient–driven diffusion and electro-osmotic drag between the anode and cathode compartments [51]. The diffusion of methanol is governed by several physicochemical parameters, including the free void volume within the membrane, the molecular dimensions of the penetrant, and the segmental mobility of the polymer chains [52]. As shown in Table 2 , the incorporation of SPS into the chitosan matrix and the subsequent increase in SPS content led to a substantial reduction in methanol permeability. This decrease can be attributed to electrostatic interactions between chitosan and SPS, which constrain polymer chain mobility, diminish free volume, and thereby reduce the effective channels available for methanol transport [16,52,53]. Further decreases in permeability were observed upon embedding SiO 2 and S-SiO 2 nanoparticles, as the presence of these inorganic fillers introduced tortuous diffusion pathways that hinder methanol permeation [54]. Interestingly, nanocomposite membranes containing S-SiO 2 exhibited slightly higher methanol crossover than their SiO 2 -based counterparts, a phenomenon associated with the increased water uptake of S-SiO 2 -modified membranes that facilitates methanol diffusion through hydrated domains. Overall, the results confirm that the incorporation of SPS and inorganic nanoparticles into the chitosan matrix effectively suppresses methanol crossover while maintaining desirable electrochemical properties, demonstrating excellent potential for high-performance DMFC applications. High proton conduction is also essential for ensuring high performance of a PEM in a DMFC structure. On the molecular level, proton transition in hydrated conditions can be defined by two main mechanisms: the vehicle mechanism and the proton hopping mechanism, which is generally known as the Grotthuss mechanism [55,56]. In the Grotthuss mechanism, protons jump from one proton conducting site, such as –NH 3 + , H 3 O + or –SO 3 − , to another site across the membrane by forming and breaking hydrogen bonds. In contrast, in the vehicle mechanism, due to electrochemical differences, protons attach to the vehicle sites, such as water molecules, and diffuse through the aqueous or other liquid media [57]. The proton conductivity of the prepared membranes at 25°C is summarized in Table 2 . The pristine CS membrane exhibits a proton conductivity of 0.008 S. cm − 1 , which is mainly associated with proton transport through hydrogen-bonded networks formed by the hydrophilic –NH 2 and –OH groups of chitosan. With the incorporation of SPS into the chitosan matrix, the conductivity gradually increases and reaches 0.0089 S. cm − 1 for the CSSPS30 membrane. This improvement is attributed to the strong electrostatic interactions and hydrogen bonding between the –SO 3 H groups of SPS, the adsorbed sulfuric acid molecules acting as crosslinking agents, and the –NH 2 groups of chitosan, which contribute to the formation of interconnected hydrogen-bond networks that facilitate proton hopping along continuous conduction pathways [58]. However, when the SPS content is increased to 40 wt.% (CSSPS40), the proton conductivity slightly decreases to 0.0087 S. cm − 1 . The excessive SPS incorporation may disturb the optimal microstructural organization of the polymer network and reduce the connectivity of proton-conducting domains. As a result, the continuity of proton transport pathways becomes partially limited, restricting proton mobility. In addition, the lower proton conductivity of SPS, as well as the relatively lower water uptake observed for the CSSPS40 membrane may further hinder the formation of extended hydrogen-bonded networks required for efficient proton transfer through the Grotthuss mechanism. The incorporation of inorganic nanoparticles further enhances the proton conductivity of the membranes. The CSSPS40/SiO 2 membrane exhibits higher conductivity due to the hydrophilic nature of silica nanoparticles, which improve water retention and increase the IEC, thereby facilitating the formation of more continuous hydrated pathways for proton transport. The CSSPS40/S-SiO 2 membrane shows the highest conductivity among all samples (0.0101 S. cm − 1 ). This superior performance is attributed to the presence of sulfonic acid groups grafted onto the surface of S-SiO 2 nanoparticles, which provide additional proton-conducting sites and promote stronger hydrogen-bond networks within the membrane. Consequently, these functionalized nanoparticles shorten the proton hopping distance and enhance proton migration mainly through the Grotthuss mechanism [59]. Table 2 The electrochemical characteristics of the prepared membranes at 25°C. Sample Proton conductivity (×10 − 3 S. cm − 1 ) Methanol permeability (×10 − 7 cm 2 . s − 1 ) Selectivity (S. s. cm − 3 ) SPS 0.7 ± 0.1 1.17 ± 0.05 5,982 CS 8.0 ± 0.1 3.25 ± 0.03 24,615 CSSPS10 8.3 ± 0.1 3.07 ± 0.05 27,035 CSSPS20 8.6 ± 0.1 2.84 ± 0.05 30,281 CSSPS30 8.9 ± 0.1 2.55 ± 0.04 34,901 CSSPS40 8.7 ± 0.1 2.18 ± 0.06 39,908 CSSPS40/SiO 2 9.3 ± 0.1 1.76 ± 0.05 52,840 CSSPS40/S-SiO 2 10.1 ± 0.1 1.87 ± 0.04 54,010 Figure 13 illustrates the discussed proton transport mechanism in the CSSPS40/S-SiO 2 nanocomposite membrane. Proton conduction is facilitated by the cooperative interactions between chitosan, SPS, and S-SiO 2 . Acid–base interactions between the –NH 2 groups of chitosan and the –SO 3 H groups of SPS and S-SiO 2 lead to the formation of ionic pairs (–NH 3 + /–SO 3 − ), generating interconnected ionic domains within the membrane. The hydrophilic –SO 3 H and –OH groups enhance water retention and promote the formation of hydrogen-bonded networks, enabling proton transport through both the vehicle (H 3 O + diffusion) and Grotthuss (proton hopping) mechanisms. An ideal proton exchange membrane (PEM) should simultaneously exhibit high proton conductivity and low methanol permeability; therefore, membrane selectivity is a key parameter for evaluating PEM performance in DMFCs. Because proton conductivity and methanol permeability directly reflect the transport behavior of protons and fuel molecules, their ratio provides a reliable indicator of the membrane’s practical applicability. Accordingly, a high selectivity value is essential for PEMs intended for DMFC operation [60]. The selectivity values of the prepared membranes at 25°C are summarized in Table 2 . Among the blend membranes with different SPS contents, the CSSPS40 membrane shows the highest selectivity (39,908 S. s. cm − 3 ), indicating that 40 wt.% SPS represents the optimal composition for achieving a balanced combination of proton transport and methanol barrier properties. Moreover, the incorporation of inorganic fillers further enhances membrane selectivity. In particular, the CSSPS40/S-SiO 2 membrane exhibits the highest selectivity of all investigated samples (54,010 S. s. cm − 3 ), which is more than twice that of the pristine CS membrane (24,615 S. s. cm − 3 ). Table 3 compares the proton conductivity, methanol permeability, and membrane selectivity parameters of several previously reported chitosan-based PEMs with those of the studied polyelectrolyte membrane (CSSPS40/S-SiO 2 ) and recast Nafion. As shown in Table 3 , the CSSPS40/S-SiO 2 membrane exhibits a selectivity value higher than that of recast Nafion, indicating its strong potential as a promising PEM candidate for DMFC applications. Table 3 Characteristics of chitosan-based PEMs reported for DMFC applications. Membrane Components Proton conductivity (S. cm − 1 ) Methanol permeability (cm 2 . s − 1 ) Selectivity (S. s. cm − 3 ) Reference CSSPS40/S-SiO 2 10.1 × 10 − 3 at 25°C 1.87 × 10 − 7 at 25°C 54,010 This study Pure chitosan 0.38×10 − 2 at 20°C 1.0×10 − 6 at 20°C 3,800 [61] Sulfonated chitosan 1.45×10 − 2 at 20°C 4.7×10 − 7 at 20°C 30,851 [61] Chitosan/sulfonated polyvinylidene fluoride 8.12 × 10 − 3 at 30°C 4.8 × 10 − 7 at 30°C 16,900 [16] Chitosan/sulfonated chitosan/sulfonated graphene oxide 7.2 × 10 − 3 at 25°C 4.75 × 10 − 8 at 25°C 151,500 [40] Chitosan/polyvinyl alcohol/organophosphorus acids 3.5 × 10 − 2 at 20°C 3×10 − 7 at 20°C 116,666 [62] Chitosan/phosphotungstic acid 3 × 10 − 2 at 25°C 3.1×10 − 7 at 25°C 96,774 [63] Chitosan/Nafion 6.01 × 10 − 2 at 25°C 1.60 × 10 − 6 at 25°C 37,569 [12] Chitosan/phosphomolybdic acid 1.5×10 − 2 at 25°C 2.7×10 − 7 at 25°C 55,555 [64] Recast Nafion 8.1 × 10 − 2 at 25°C 2 × 10 − 6 at 25°C 40,500 [65] Conclusion In this work, chitosan-based blend membranes containing different amounts of SPS (acid–base blend) were fabricated using the solution-casting technique. Among the prepared membranes, the CSSPS40 membrane exhibited the highest selectivity parameter and was therefore identified as the optimal composition. Blending chitosan with SPS reduced the methanol permeability of the membranes, while the presence of sulfonic acid groups facilitated proton transport through the Grotthuss mechanism via acid–base interactions between chitosan and SPS. Furthermore, the incorporation of SiO 2 and sulfonated SiO 2 (S-SiO 2 ) nanoparticles into the optimal blend membrane effectively reduced methanol crossover and enhanced proton conductivity. The blend nanocomposite membrane, CSSPS40/S-SiO 2 , exhibited a proton conductivity of 10.1 × 10 − 3 S. cm − 1 and a methanol permeability of 1.87 × 10 − 7 cm 2 . S − 1 , resulting in a selectivity of approximately 54,010 S. s. cm − 3 , which is the highest among all the prepared membranes. In addition to its improved electrochemical performance, the selected membrane can also be considered an economically attractive option due to the use of abundant and relatively low-cost materials such as chitosan, SPS and silica nanoparticles. Therefore, the developed membrane shows strong potential as a promising and cost-effective candidate for future direct methanol fuel cell (DMFC) applications. Declarations Author Contribution Mahdi Tohidian: Supervisor, Revising the manuscriptShayan Navabi:Experiments, Data generation, writing the manuscript Acknowledgment This research was financially supported by Amirkabir University of Technology, Tehran, Iran. References Wu J, Wang F, Fan X, Chu J, Cheng F, Hu F, et al. Phosphoric acid-doped Gemini quaternary ammonium-grafted SPEEK membranes with superhigh proton conductivity and mechanical strength for direct methanol fuel cells. J Memb Sci 2023;672:121431. https://doi.org/https://doi.org/10.1016/j.memsci.2023.121431. 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J Ind Eng Chem 2015;21:36–52. https://doi.org/https://doi.org/10.1016/j.jiec.2014.04.030. Sinirlioglu D, Muftuoglu AE, Golcuk K, Bozkurt A. Investigation of proton conductivity of anhydrous proton exchange membranes prepared via grafting vinyltriazole onto alkaline-treated PVDF. J Polym Sci Part A Polym Chem 2014;52:1885–97. https://doi.org/https://doi.org/10.1002/pola.27197. Modau LE, Mashola T, Sigwadi RA, Mokrani T, Nemavhola F. Nano-Silica-Modified Chitosan-Based Membranes for Application in Direct Methanol Fuel Cells. Polymers (Basel) 2025;17:3281. https://doi.org/10.3390/polym17243281. Muhmed SA, Jaafar J, Daud SS, Hanifah MFR, Purwanto M, Othman MHD, et al. Improvement in properties of nanocrystalline cellulose/poly (vinylidene fluoride) nanocomposite membrane for direct methanol fuel cell application. J Environ Chem Eng 2021;9:105577. https://doi.org/https://doi.org/10.1016/j.jece.2021.105577. Xiang Y, Yang M, Guo Z, Cui Z. Alternatively chitosan sulfate blending membrane as methanol-blocking polymer electrolyte membrane for direct methanol fuel cell. J Memb Sci 2009;337:318–23. https://doi.org/10.1016/j.memsci.2009.04.006. Jiang Z, Zheng X, Wu H, Pan F. Proton conducting membranes prepared by incorporation of organophosphorus acids into alcohol barrier polymers for direct methanol fuel cells. J Power Sources 2008;185:85–94. https://doi.org/10.1016/j.jpowsour.2008.06.086. Shakeri SE, Ghaffarian SR, Tohidian M, Bahlakeh G, Taranejoo S. Polyelectrolyte Nanocomposite Membranes, Based on Chitosan-phosphotungstic Acid Complex and Montmorillonite for Fuel Cells Applications. J Macromol Sci Part B 2013;52:1226–41. https://doi.org/10.1080/00222348.2013.763565. Cui Z, Xing W, Liu C, Liao J, Zhang H. Chitosan/heteropolyacid composite membranes for direct methanol fuel cell. J Power Sources 2009;188:24–9. https://doi.org/10.1016/j.jpowsour.2008.11.108. Hasani-Sadrabadi MM, Dashtimoghadam E, Majedi F. Investigation of a Double Layer Membrane for Direct Methanol Fuel Cell Applications. ECS Meet Abstr 2009;MA2009-02:1094. https://doi.org/10.1149/MA2009-02/10/1094. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 04 May, 2026 Reviews received at journal 29 Apr, 2026 Reviews received at journal 29 Apr, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 18 Apr, 2026 Submission checks completed at journal 18 Apr, 2026 First submitted to journal 15 Apr, 2026 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. 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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-9426945","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630897909,"identity":"f090ecf9-4655-4824-a417-709422e106f6","order_by":0,"name":"Shayan Navabi","email":"","orcid":"","institution":"Amirkabir University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Shayan","middleName":"","lastName":"Navabi","suffix":""},{"id":630897910,"identity":"ad12d013-08cc-4544-ac10-60a328883580","order_by":1,"name":"Mahdi Tohidian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFACHgaJBCBlwMxgcICBwQYmLEFIiwFMSxoDAxsxWhhAWkAEA8NhmBbcQLf97MEbDxj+yJmzM2888HPHeXmD+w2MH34wWOTj0mJ2Ji/ZAugwY8tmtoKDvWduG244xsAs2cMgYdmAS8uBHDOQXxI3HOYxOMDbdpsRqIVBGugXA5y2nH+D0HLwb9s5e5Atv/FquYFky2HetgOJQC1s+G258cbYIsHA2NjgMFvBYdm25OSZxxLbLHsM8Dksx/Dmjwo5OYPzhzd/fNtmZ9t3+PDhGz8q6nBqgQBUacYGdJFRMApGwSgYBSQCAFaZVAtcPh9oAAAAAElFTkSuQmCC","orcid":"","institution":"Amirkabir University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Mahdi","middleName":"","lastName":"Tohidian","suffix":""}],"badges":[],"createdAt":"2026-04-15 12:24:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9426945/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9426945/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108491177,"identity":"660f9e84-5a00-4fe4-bc7c-782c3545e00a","added_by":"auto","created_at":"2026-05-05 09:52:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":165175,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR spectra of SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/9e8fdce7bf19005aa9e6e1f7.png"},{"id":108185551,"identity":"e026438b-fabd-42ab-a74b-1b0370b449ec","added_by":"auto","created_at":"2026-04-30 09:07:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83873,"visible":true,"origin":"","legend":"\u003cp\u003eZeta potential analysis of SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/0f252c3e3f09912d52782cf4.png"},{"id":108804105,"identity":"529db5b2-108e-40ae-b866-af28b51ff13a","added_by":"auto","created_at":"2026-05-08 15:15:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":868047,"visible":true,"origin":"","legend":"\u003cp\u003eFE-SEM images of (a) SiO\u003csub\u003e2\u003c/sub\u003e and (b) S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/91a706dd622950c295cb3411.png"},{"id":108185552,"identity":"ab933337-a335-4ea4-b653-1185463c064d","added_by":"auto","created_at":"2026-04-30 09:07:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":123046,"visible":true,"origin":"","legend":"\u003cp\u003eEDX elemental analysis spectrum of sulfonated SiO\u003csub\u003e2\u003c/sub\u003e and S‑SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/a0f4e293735d441ccf88ee50.png"},{"id":108803815,"identity":"6431dbe6-e7e7-49c2-aaff-3df4c51a5f8e","added_by":"auto","created_at":"2026-05-08 15:08:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6628030,"visible":true,"origin":"","legend":"\u003cp\u003eCross-sectional scanning electron microscopy images of (a) CS, (b) SPS, (c) CSSPS40, and (d) CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membranes. Elemental mapping images of the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e composite membrane showing the distribution of (e) silicon (Si), (f) nitrogen (N), and (g) sulfur (S).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/b95bb430a38c7b46c87abebc.png"},{"id":108185554,"identity":"32427bce-cbdf-47cb-82db-257e9118f6b7","added_by":"auto","created_at":"2026-04-30 09:07:06","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":156944,"visible":true,"origin":"","legend":"\u003cp\u003eThe XRD patterns of CS and CSSPS40 membranes.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/16dab5c7ce4cfe24896ada43.png"},{"id":108976640,"identity":"e5a8a7c1-9341-4f0d-adb9-b060313f77af","added_by":"auto","created_at":"2026-05-11 11:27:04","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":175684,"visible":true,"origin":"","legend":"\u003cp\u003eThermal decomposition behavior of CS, SPS, CSSPS40, and CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membranes.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/0cd6d0728c7c78415a158c3c.png"},{"id":109204423,"identity":"dcc8b566-83a9-4d66-ae7b-603ff2c05ef9","added_by":"auto","created_at":"2026-05-13 14:59:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":140347,"visible":true,"origin":"","legend":"\u003cp\u003eDSC curves of CS, SPS, CSSPS40, and CSSPS40/S‑SiO\u003csub\u003e2\u003c/sub\u003e membranes, illustrating their thermal transition behavior.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/805cf4e9190807bb82d4344f.png"},{"id":109204402,"identity":"77aa23a3-b238-41c8-8b5a-95f2714b565b","added_by":"auto","created_at":"2026-05-13 14:59:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":161359,"visible":true,"origin":"","legend":"\u003cp\u003eThe IEC and water uptake values of the prepared membranes.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/801f5dd7c3f2f275910e47c6.png"},{"id":108185558,"identity":"dfbf56db-404f-4450-b6be-e12b353565e3","added_by":"auto","created_at":"2026-04-30 09:07:06","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":6880124,"visible":true,"origin":"","legend":"\u003cp\u003eThe atomic force microscopy images of (a) SPS, (b) CS, (c) CSSPS40, and (d) CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membranes.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/2125bda8cbd249d3a6f4ec76.png"},{"id":108803513,"identity":"52d9702e-5b0c-40ec-a473-a2822e612937","added_by":"auto","created_at":"2026-05-08 14:57:44","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1612262,"visible":true,"origin":"","legend":"\u003cp\u003eThe contact angle images of (a) CS, (b) SPS, (c) CSSPS40, and (d) CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membranes.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/484984a7e2c929336ddf88cb.png"},{"id":108491113,"identity":"1b2b8eea-5048-427e-911d-48cca7ef1c31","added_by":"auto","created_at":"2026-05-05 09:52:21","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":112842,"visible":true,"origin":"","legend":"\u003cp\u003eOxidative stability test results of CS, CSSPS40, CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e, and SPS membranes.\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/2f2343571ac47c5eeefde828.png"},{"id":108491133,"identity":"0090ee66-f061-4f9d-a4ed-1b47ef88974c","added_by":"auto","created_at":"2026-05-05 09:52:27","extension":"jpeg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":576614,"visible":true,"origin":"","legend":"\u003cp\u003eThe presumptive illustration of proton-conducting pathways in CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane.\u003c/p\u003e","description":"","filename":"floatimage13.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/6a4574486ce9ae12f24ae94f.jpeg"},{"id":109207914,"identity":"70de50a3-7e6c-42bd-882d-56a9c3987932","added_by":"auto","created_at":"2026-05-13 15:22:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16888392,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9426945/v1/7e8d6d81-0896-47c6-8ad3-229ea93dbeb7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of Chitosan–Sulfonated Polystyrene–Sulfonated Nanosilica Nanocomposite Proton Exchange Membranes for Direct Methanol Fuel Cells","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDirect methanol fuel cells (DMFCs) continue to garner significant research interest as a leading candidate for clean and sustainable energy conversion technologies, primarily owing to their favorable characteristics such as high energy density, ambient operating temperatures, and negligible environmental impact [1,2]. Central to DMFC performance is the proton exchange membrane (PEM), tasked with orchestrating efficient proton transport across the electrochemical cell while simultaneously mitigating detrimental methanol crossover [3]. While perfluorosulfonic acid (PFSA) membranes, exemplified by Nafion\u0026reg;, have historically dominated this field due to their excellent proton conductivity and robust electrochemical stability [4,5], their inherent drawbacks\u0026mdash;including prohibitive cost, limited thermal stability, susceptibility to dehydration, and significant methanol permeability\u0026mdash;have spurred an intensive global quest for cost-effective and high-performance alternatives [6].\u003c/p\u003e \u003cp\u003eThe exploration of polymer electrolyte membranes derived from renewable feedstocks has gained considerable traction, offering a compelling blend of sustainability, biodegradability, and economic viability. Among these, chitosan (CS), a naturally abundant polysaccharide, presents a unique profile of desirable attributes for PEM applications: inherent hydrophilicity, excellent film-forming characteristics, low intrinsic methanol permeability, commendable thermal stability, and biocompatibility [7\u0026ndash;9]. However, the intrinsic proton conductivity of pristine chitosan remains suboptimal, largely attributable to its high degree of crystallinity and the absence of readily mobile proton carriers [10]. Consequently, a diverse array of strategies has been rigorously investigated to enhance the performance metrics of CS-based membranes. These encompass chemical modifications (e.g., sulfonation, crosslinking), polymer blending with proton-donating moieties, incorporation of strong protonic acids, and the development of sophisticated nanocomposite architectures utilizing functionalized nanofillers [11,12].\u003c/p\u003e \u003cp\u003eA particularly promising avenue lies in the strategic design of acid\u0026ndash;base pair systems within the polymer matrix. This approach leverages the synergistic interactions between acidic functional groups (e.g., \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) and basic functional groups (e.g., \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e) to facilitate rapid proton hopping mechanisms, thereby establishing low-energy proton transport pathways. Concurrently, strong electrostatic interactions arising from these acid\u0026ndash;base pairings contribute to enhanced water management, improved dimensional stability, and superior mechanical robustness [13\u0026ndash;15]. Blending basic polymers such as CS or polybenzimidazole (PBI) with acidic polymers like sulfonated poly(ether ether ketone) (SPEEK) or sulfonated polyethersulfone (SPES) represents a well-established method for creating these advantageous acid\u0026ndash;base environments [13,16]. Sulfonation is widely recognized as an effective chemical modification strategy for improving the proton conductivity of proton exchange membranes (PEMs). The incorporation of sulfonic acid groups (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) into the polymer backbone introduces proton-conducting sites, thereby increasing the membrane\u0026rsquo;s hydrophilicity and ion-exchange capacity, which in turn facilitates proton transport throughout the polymer matrix. Nevertheless, although a higher degree of sulfonation generally leads to enhanced proton conductivity, excessive functionalization may adversely affect the membrane by reducing mechanical stability and promoting methanol permeability. Consequently, careful control and optimization of the degree of sulfonation are essential to maintain an appropriate balance between proton conductivity, dimensional stability, and resistance to methanol crossover, all of which critically influence the membrane\u0026rsquo;s overall performance in DMFC systems. In this context, sulfonated polystyrene (SPS) represents a cost-effective and readily synthesizable aromatic polymer that provides abundant sulfonic acid groups capable of forming effective acid\u0026ndash;base interactions [17,18].\u003c/p\u003e \u003cp\u003eConcurrently, the integration of organic\u0026ndash;inorganic nanocomposites has emerged as a powerful paradigm for simultaneously improving the mechanical integrity, thermal endurance, and ionic transport properties of polymer membranes. Hybrid systems leveraging the flexibility and processability of organic polymer matrices with the inherent rigidity and thermal resistance of inorganic nanoparticles, such as silica, offer a pathway to achieving a well-balanced property profile [19]. Silica nanoparticles, in particular, are widely employed to enhance thermal stability, mechanical modulus, water retention, and proton conductivity. However, challenges related to nanoparticle aggregation and potential blockage of ionic pathways necessitate surface modification strategies. Functionalization of nanofillers with acidic or basic groups not only promotes uniform dispersion within the polymer matrix but also strengthens interfacial interactions, thereby facilitating the formation of interconnected proton-conductive channels, particularly through acid\u0026ndash;base pair mechanisms within the composite [20\u0026ndash;22]. Notably, Wang et al. [23] demonstrated substantial improvements in DMFC performance by incorporating carboxylated silica into CS membranes, achieving a 63% decrease in methanol permeability and a 40% increase in proton conductivity compared to the unmodified CS membrane.\u003c/p\u003e \u003cp\u003eDespite these advancements, a critical research gap persists in the systematic exploration and optimization of hybrid chitosan-based nanocomposite membranes that synergistically integrate both an acidic polymer (SPS) and functionalized inorganic nanofillers (silica/sulfonated silica). Specifically, there is a paucity of studies that comprehensively address the rational design and characterization of CS/SPS acid\u0026ndash;base blend membranes, the optimization of the blend composition to maximize proton selectivity, and the evaluation of the synergistic effects derived from incorporating silica and sulfonated silica nanoparticles on enhancing proton conductivity while simultaneously suppressing methanol crossover. This knowledge deficit underscores the need for a holistic investigation into developing advanced CS-based PEMs that leverage multi-component interactions for superior DMFC performance. Building upon our prior investigation [12], which demonstrated the efficacy of CS/Nafion blends in enhancing proton transfer through interfacial interactions, the present research embarks on an extended exploration. We systematically investigate the impact of introducing sulfonated polystyrene (SPS) and silica-based nanofillers on the performance characteristics of chitosan membranes tailored for DMFC applications. The SPS component was chemically functionalized with sulfonic acid (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) groups to imbue proton-conducting capabilities, while the inherent basic amine (\u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e) groups of chitosan were strategically utilized to establish robust acid\u0026ndash;base interactions and hydrogen-bonding networks, thereby creating efficient proton transport conduits. A series of CS/SPS blend membranes with systematically varied weight ratios was fabricated, and their optimal composition was rigorously determined based on the proton selectivity parameter (defined as the ratio of proton conductivity to methanol permeability, σ/P). Subsequently, the optimized blend was modified by incorporating silica and sulfonated silica nanoparticles to investigate their synergistic role in enhancing proton conductivity while reducing methanol permeability. The membranes were systematically evaluated in terms of thermal and chemical stability, proton conductivity, and methanol permeability. The results indicate that the combined effect of acid\u0026ndash;base interactions between CS and SPS together with functionalized silica nanoparticles forms efficient proton transport pathways, improves physicochemical stability, and significantly suppresses methanol crossover, making these membranes promising alternatives to commercial Nafion membranes.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Materials\u003c/h2\u003e \u003cp\u003ePolystyrene (grade 1028, Mw\u0026thinsp;\u0026asymp;\u0026thinsp;30,000 g. mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was supplied by Petropak Mashregh Zamin Co. (Iran). Chitosan with a medium molecular weight and a degree of deacetylation of approximately 80% was purchased from Sigma-Aldrich (USA). Methanol, dichloromethane, and sulfuric acid were obtained from Dr. Mojalli Co. (Iran), whereas acetic anhydride was provided by Pars Chemical Co. (Iran). Acetic acid, dimethylformamide (DMF), sodium hydroxide, and hydrochloric acid were purchased from Merck (USA). Nanosilica (SiO\u003csub\u003e2\u003c/sub\u003e) with a specific surface area of 250\u0026thinsp;\u0026plusmn;\u0026thinsp;30 m\u003csup\u003e2\u003c/sup\u003e. g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and approximately 2.2 silanol groups per nm\u003csup\u003e2\u003c/sup\u003e was supplied by Evonik (Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sulfonation of polystyrene\u003c/h2\u003e \u003cp\u003ePolystyrene was sulfonated (SPS) according to the method described in our earlier study [24]. In brief, acetyl sulfate\u0026mdash;the sulfonating reagent\u0026mdash;was prepared by mixing 50 mL of dichloromethane, 13.7 mL of acetic anhydride, and 9.25 mL of sulfuric acid under continuous stirring for 40 minutes. Owing to the strongly exothermic nature of the reaction, the mixture was maintained in an ice bath throughout this step. Subsequently, to obtain the SPS with the optimum degree of sulfonation (18.26%), 5 g of polystyrene was introduced into the acetyl sulfate solution and allowed to react at 25\u0026deg;C to achieve an optimal degree of sulfonation. The reaction was continued for an additional 120 minutes until a uniform mixture was obtained. Upon completion, SPS was precipitated by adding deionized water, and the resulting white solid was thoroughly washed multiple times with deionized water to eliminate any remaining acidic by-products or unreacted reagents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Sulfonation of SiO\u003csub\u003e2\u003c/sub\u003e\u003c/h2\u003e \u003cp\u003eThe SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles were sulfonated using sulfuric acid following the procedure reported by Wang et al. [25]. A predetermined amount of SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles was dispersed in 35 mL of a methanolic solution containing 15 mL of 0.5 M sulfuric acid. The resulting mixture was ultrasonicated for 1 h to facilitate surface functionalization. Subsequently, the product was washed with deionized water through six successive centrifugation\u0026ndash;redispersion cycles to remove residual acid and impurities. Finally, the obtained white powder was dried at 100\u0026deg;C for 24 h to yield sulfonated silica nanoparticles (S-SiO\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Preparation of the blend membranes\u003c/h2\u003e \u003cp\u003eThe blend membranes were prepared using the solution-casting method. First, dried chitosan powder was dissolved in a pre-prepared aqueous acetic acid solution (2% v/v) to obtain a 2 wt.% chitosan solution. Meanwhile, SPS was dissolved in dimethylformamide (DMF) at 25\u0026deg;C for 2 h. The SPS solution was then slowly added to the chitosan solution under continuous stirring, and the mixture was stirred at room temperature for 24 h to obtain homogeneous CS/SPS blend solutions.\u003c/p\u003e \u003cp\u003eThe weight ratios of chitosan to SPS were adjusted to 100:0, 90:10, 80:20, 70:30, and 60:40, and the resulting membranes were denoted as CS, CSSPS10, CSSPS20, CSSPS30, and CSSPS40, respectively. The prepared CS/SPS solutions were cast onto glass Petri dishes and dried at 40\u0026deg;C for 48 h to form the membranes.\u003c/p\u003e \u003cp\u003eTo neutralize the chitosan-based membranes, the dried films were immersed in a 1 N sodium hydroxide solution and subsequently washed several times with deionized water. To induce ionic crosslinking between chitosan chains, the membranes were then immersed in a 1 M sulfuric acid solution for 24 h. After crosslinking, the membranes were thoroughly washed with deionized water to remove excess sulfuric acid and finally dried at room temperature for 24 h. A crosslinked chitosan membrane (CS) was also prepared using the same procedure without the addition of SPS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Preparation of the blend nanocomposite membranes\u003c/h2\u003e \u003cp\u003eTo fabricate the blend nanocomposite membranes, the CSSPS40 blend solution was initially prepared. Then, 2 wt.% of SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles were separately added to the solutions and stirred with a magnetic stirrer for 24 h. In the next step, the mixtures were ultrasonicated for 1 h, poured into a glass Petri dish, and dried at 40\u0026deg;C for 48 h. Finally, as described previously, the dried membranes were neutralized and then cross-linked. The blend nanocomposite membranes prepared with nanosilica and sulfonated nanosilica were designated as CSSPS40/SiO\u003csub\u003e2\u003c/sub\u003e and CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Characterization techniques\u003c/h2\u003e \u003cp\u003eFourier Transform Infrared Spectroscopy (FTIR)\u003c/p\u003e \u003cp\u003eFourier transform infrared spectroscopy (FTIR) was employed to confirm the sulfonation of SiO\u003csub\u003e2\u003c/sub\u003e. The spectra were recorded using an FTIR spectrometer (Equinox 55, Bruker, Latvia) in the wavenumber range of 4000\u0026ndash;400 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with a resolution of 2 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eZeta potential\u003c/p\u003e \u003cp\u003eZeta potential measurements were performed using a Zetasizer (Version 7.11, Malvern Instruments Ltd., UK) to evaluate the surface charge characteristics of pristine SiO\u003csub\u003e2\u003c/sub\u003e and sulfonated SiO\u003csub\u003e2\u003c/sub\u003e (S-SiO\u003csub\u003e2\u003c/sub\u003e) nanoparticles.\u003c/p\u003e \u003cp\u003eIon Exchange Capacity (IEC)\u003c/p\u003e \u003cp\u003eThe ion exchange capacity (IEC), which represents the number of available proton-exchangeable sites per unit mass of the membrane, was determined by an acid\u0026ndash;base titration method. In this procedure, the dried membranes were first accurately weighed and then immersed in 0.01 N NaOH solution for 24 h to completely exchange the H\u003csup\u003e+\u003c/sup\u003e ions in the membranes with Na\u003csup\u003e+\u003c/sup\u003e ions. The IEC value was calculated using Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{I}\\text{E}\\text{C}=\\frac{\\left({\\text{V}}_{\\text{N}\\text{a}\\text{O}\\text{H}}-{\\text{V}}_{\\text{H}\\text{C}\\text{l}}\\right)\\times\\:\\text{M}}{{\\text{W}}_{\\text{d}\\text{r}\\text{y}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere V\u003csub\u003eNaOH\u003c/sub\u003e and V\u003csub\u003eHCl\u003c/sub\u003e are the volumes of NaOH and HCl solutions (mL) used in titration, M is the concentration of solutions (0.01 N), and W\u003csub\u003edry\u003c/sub\u003e is the weight of dry membrane (g).\u003c/p\u003e \u003cp\u003eWater uptake\u003c/p\u003e \u003cp\u003eWater molecules play a crucial role in facilitating proton transport within polymer electrolyte membranes. Therefore, evaluating the water uptake behavior of the membranes is essential for understanding their proton conduction performance.\u003c/p\u003e \u003cp\u003eFor water uptake measurements, the membranes were first thoroughly dried in a vacuum oven and accurately weighed. The samples were then immersed in deionized water at ambient temperature. After reaching swelling equilibrium, the excess surface water was gently removed using filter paper, and the membranes were immediately reweighed. This procedure was repeated until a constant weight was obtained. The following Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) was used to determine the water uptake of the samples:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{W}\\text{U}\\:\\left(\\text{%}\\right)=\\frac{{\\text{W}}_{\\text{w}\\text{e}\\text{t}}-{\\text{W}}_{\\text{d}\\text{r}\\text{y}}}{{\\text{W}}_{\\text{d}\\text{r}\\text{y}}}\\:\\times\\:\\:100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere W\u003csub\u003ewet\u003c/sub\u003e is the weight of the fully hydrated membrane, and W\u003csub\u003edry\u003c/sub\u003e is the weight of the completely dried membrane, respectively.\u003c/p\u003e \u003cp\u003eAdditionally, the average number of absorbed water molecules per ion-conducting group (λ) was determined using Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{\\lambda\\:}=\\frac{\\text{W}\\text{U}}{\\text{I}\\text{E}\\text{C}\\:\\times\\:\\:{\\text{M}}_{\\text{w}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere M\u003csub\u003ew\u003c/sub\u003e is the molecular weight of water (18 g. mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eAtomic Force Microscopy (AFM)\u003c/p\u003e \u003cp\u003eA tapping mode AFM (model: Universal SPM, Ambios Technology, USA) with a micro-fabricated cantilever was employed to explore the surface topography and roughness of the membranes in the ambient atmosphere at a frequency of 180 kHz. Surface roughness parameters such as average roughness (R\u003csub\u003ea\u003c/sub\u003e) and root mean square roughness (R\u003csub\u003eq\u003c/sub\u003e) were obtained from the 5 \u0026micro;m \u0026times; 5 \u0026micro;m scan.\u003c/p\u003e \u003cp\u003eContact angle measurement\u003c/p\u003e \u003cp\u003eStatic contact angle measurements were conducted using a contact angle goniometer (Jikan CAG-20, Iran) to assess the surface wettability and hydrophilicity of the prepared membranes. A droplet of deionized water was gently placed on the membrane surface, and the contact angle was determined using the Smart Drop software based on the Bashforth\u0026ndash;Adams fitting method. Each reported contact angle value represents the average of at least three independent measurements.\u003c/p\u003e \u003cp\u003eThermogravimetric Analysis (TGA)\u003c/p\u003e \u003cp\u003eTGA was performed using an SDT Q600 V20.9 Build 20 analyzer (TA Instruments, USA) to assess the thermal stability of the prepared membranes. Approximately 10 mg of thoroughly dried membrane samples were used for each test. The measurements were conducted under a nitrogen atmosphere at a heating rate of 10\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, from room temperature up to 800\u0026deg;C.\u003c/p\u003e \u003cp\u003eDifferential Scanning Calorimetry (DSC)\u003c/p\u003e \u003cp\u003eDifferential scanning calorimetry (DSC) was carried out using a DSC1 Star System (Mettler Toledo, USA) to examine the thermal characteristics of the membranes. The glass transition temperature (T\u003csub\u003eg\u003c/sub\u003e) of the PEMs was determined by heating the samples from 25 to 250\u0026deg;C at a rate of 10\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e under a nitrogen atmosphere.\u003c/p\u003e \u003cp\u003eDSC analysis was also employed to quantify the amounts of free water and bound water within the membranes. For this purpose, fully hydrated membranes were weighed and sealed in DSC pans. The samples were first cooled to \u0026minus;\u0026thinsp;40\u0026deg;C to freeze the free water molecules and subsequently heated to 40\u0026deg;C at a rate of 5\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. An endothermic melting peak appeared near 0\u0026deg;C, and the corresponding peak area was used to calculate the amount of freezable (free) water in the membrane. The weight fraction of free water (W\u003csub\u003ef\u003c/sub\u003e) was then determined using Eq.\u0026nbsp;(\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{\\text{W}}_{\\text{f}}=\\frac{{\\Delta\\:}{\\text{H}}_{\\text{m}}}{{\\text{Q}}_{\\text{m}\\text{e}\\text{l}\\text{t}\\text{i}\\text{n}\\text{g}}}=\\frac{\\int\\:{\\Delta\\:}{\\text{C}}_{\\text{P}}d\\text{t}}{{\\text{Q}}_{\\text{m}\\text{e}\\text{l}\\text{t}\\text{i}\\text{n}\\text{g}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere ΔH\u003csub\u003em\u003c/sub\u003e is the total melting enthalpy, Qmelting is the heat of fusion of bulk ice (334 J. g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e ), and ΔCp is the transition heat capacity. The bound water content, which plays a crucial role in proton conduction, was calculated by subtracting the free water content from the total water uptake. Finally, the bound water degree (χ), which is defined as the ratio of bound water content to free water content, was calculated for each membrane.\u003c/p\u003e \u003cp\u003eScanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX)\u003c/p\u003e \u003cp\u003eScanning electron microscopy (SEM) (Seron Technology, South Korea) was employed to examine the cross-sectional morphology and thickness of the prepared membranes. The membranes were fractured in liquid nitrogen to obtain clean cross-sections and then sputter-coated with a thin layer of gold prior to imaging. The micrographs were recorded under high-vacuum conditions.\u003c/p\u003e \u003cp\u003eIn addition, field emission scanning electron microscopy (FE-SEM) (TESCAN MIRA3) equipped with energy-dispersive X-ray spectroscopy (EDX) was used to investigate the surface morphology and elemental composition of the silica nanoparticles. The FE-SEM/EDX system was also utilized to perform elemental mapping of the cross-sections of the composite membranes. All images were obtained under high-vacuum conditions.\u003c/p\u003e \u003cp\u003eX-ray diffraction (XRD)\u003c/p\u003e \u003cp\u003eX-ray diffraction (XRD) analysis was performed using a QUINOX3000 diffractometer (Thermo Scientific, USA) to investigate the crystalline structure of the prepared membranes. The diffraction patterns were recorded in the 2θ range of 10\u0026deg;\u0026ndash;80\u0026deg; at a scanning rate of 2\u0026deg; min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using Cu Kα radiation as the X-ray source.\u003c/p\u003e \u003cp\u003eOxidative stability\u003c/p\u003e \u003cp\u003eThe oxidative stability of the membranes was evaluated using Fenton\u0026rsquo;s reagent, which simulates the oxidative conditions present in fuel cells. In this test, the membranes were fully immersed in the Fenton solution and the weight change was monitored after a specified period.\u003c/p\u003e \u003cp\u003eThe Fenton solution consisted of 3 wt.% hydrogen peroxide containing 4 ppm Fe\u003csup\u003e2+\u003c/sup\u003e ions, which can readily generate oxidative species capable of degrading the membrane without requiring elevated temperature or pressure. Prior to the test, the membranes were thoroughly dried and accurately weighed. The samples were then immersed in 50 mL of the prepared solution at room temperature for 24 h. After the treatment, the membranes were removed, dried, and reweighed to determine the extent of weight loss [12].\u003c/p\u003e \u003cp\u003eProton conductivity\u003c/p\u003e \u003cp\u003eFor proton conductivity measurements, electrochemical impedance spectroscopy (EIS) was carried out using an MCTS 94A analyzer (Ahnsco, Iran). The measurements were performed in the through‑plane configuration using fully hydrated membrane samples under saturated humidity conditions (\u0026asymp;\u0026thinsp;100% RH). The impedance spectra were collected over a frequency range from 1 MHz to 1 Hz with an AC perturbation amplitude of 10 mV under open‑circuit conditions. The membrane resistance was obtained from the high‑frequency intercept of the Nyquist plot. Each experiment was repeated at least three times, and the reported conductivity values represent the average along with the corresponding standard deviation. The proton conductivity was calculated using Eq.\u0026nbsp;(\u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:{\\sigma\\:}=\\frac{\\text{L}}{\\text{R}\\times\\:\\text{A}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere σ is the proton conductivity (S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), L is the membrane thickness (cm), R is the membrane resistance (Ω), and A is the cross-sectional surface area of the membrane (cm\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eMethanol permeability\u003c/p\u003e \u003cp\u003eThe methanol permeability of the membranes was measured using a laboratory diffusion cell, wherein the membrane was positioned between two distinct chambers (A and B). Chamber A was filled with a 5 M methanol solution, while Chamber B was filled with deionized water. To maintain homogeneity, a mechanical stirrer was used to stir the solutions. The concentration of methanol in chamber B was measured using gas chromatography analysis (Agilent 6890 N) at specified time intervals. The following Eq.\u0026nbsp;(\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) was used to determine the methanol permeability at room temperature:\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:\\text{P}=\\frac{1}{{\\text{C}}_{\\text{A}}}\\times\\:\\frac{{\\Delta\\:}{\\text{C}}_{\\text{B}}\\left(\\text{t}\\right)}{{\\Delta\\:}\\text{t}}\\times\\:\\frac{{\\text{V}}_{\\text{B}}\\times\\:\\text{L}}{\\text{A}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this equation, C\u003csub\u003eA\u003c/sub\u003e is the methanol concentration in chamber A (mol. L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and ΔC\u003csub\u003eB\u003c/sub\u003e(t)/Δt is the slope of methanol concentration variation over time in chamber B; L, A, V\u003csub\u003eB\u003c/sub\u003e, and P are the membrane thickness (cm), membrane surface area (cm\u003csup\u003e2\u003c/sup\u003e), water volume in chamber B (cm\u003csup\u003e3\u003c/sup\u003e), and methanol permeability (cm\u003csup\u003e2\u003c/sup\u003e. s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cp\u003eFTIR analysis was performed to confirm the successful sulfonation of silica nanoparticles, and the spectra of pristine SiO\u003csub\u003e2\u003c/sub\u003e, and S-SiO\u003csub\u003e2\u003c/sub\u003e are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the spectrum of pristine SiO\u003csub\u003e2\u003c/sub\u003e, the strong absorption band at 1,101 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is attributed to the asymmetric stretching vibration of Si\u0026ndash;O\u0026ndash;Si bonds, while the band observed at 960 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e corresponds to the stretching vibration of surface silanol (Si\u0026ndash;OH) groups. After sulfonation, the spectrum of S-SiO\u003csub\u003e2\u003c/sub\u003e exhibits additional characteristic bands at 1,171 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1,286 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which are assigned to the asymmetric and symmetric stretching vibrations of the sulfonic acid (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) groups. The appearance of these bands provides clear evidence for the successful introduction of sulfonic acid functionalities onto the surface of the silica nanoparticles. In addition, the broad absorption band centered around 3400 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is associated with the stretching vibration of hydroxyl groups and adsorbed water molecules on the surface of both SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, reflecting the hydrophilic nature of the silica surface. The band observed around 1,640 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is attributed to the bending vibration of molecularly adsorbed water (H\u0026ndash;O\u0026ndash;H), which is associated with the hydrophilic silanol groups present on the silica surface [26,27].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe zeta potential measurements were carried out to investigate the surface charge characteristics of SiO\u003csub\u003e2\u003c/sub\u003e and sulfonated silica (S-SiO\u003csub\u003e2\u003c/sub\u003e) nanoparticles and to confirm the successful surface modification. The variation of zeta potential as a function of pH is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFor pristine SiO\u003csub\u003e2\u003c/sub\u003e, the zeta potential exhibits a positive value at strongly acidic conditions (pH\u0026thinsp;=\u0026thinsp;2, +\u0026thinsp;3.2 mV) and gradually shifts toward negative values with increasing pH, reaching\u0026thinsp;\u0026minus;\u0026thinsp;28 mV at pH 12. This behavior is attributed to the acid\u0026ndash;base properties of surface silanol groups (Si\u0026ndash;OH). At low pH, these groups remain protonated, resulting in a slightly positive surface charge. As the pH increases, progressive deprotonation of silanol groups occurs, forming negatively charged siloxide groups (Si\u0026ndash;O\u003csup\u003e\u0026minus;\u003c/sup\u003e), which leads to increasingly negative zeta potential values.\u003c/p\u003e \u003cp\u003eIn contrast, S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles exhibit significantly more negative zeta potential values over the entire pH range. For instance, the zeta potential changes from \u0026minus;\u0026thinsp;1.4 mV at pH 2 to \u0026minus;\u0026thinsp;38 mV at pH 12. The consistently more negative surface charge of S-SiO\u003csub\u003e2\u003c/sub\u003e compared with pristine SiO\u003csub\u003e2\u003c/sub\u003e can be attributed to the presence of sulfonic acid (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) groups introduced during the sulfonation process. These groups readily dissociate in aqueous media to form negatively charged sulfonate species (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e), thereby increasing the surface charge density. The noticeable shift toward more negative zeta potential values after sulfonation clearly indicates the successful functionalization of the silica surface with sulfonic acid groups [20].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe FE-SEM micrographs of pristine SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The pristine SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles exhibit a relatively uniform and well-defined spherical morphology with a narrow particle size distribution, indicating a homogeneous particle formation. After the sulfonation treatment, the FE-SEM image of S-SiO\u003csub\u003e2\u003c/sub\u003e reveals that the nanoparticles largely retain their original spherical morphology and size, with no noticeable structural deformation. This observation indicates that the sulfonation process primarily occurs at the surface of the silica nanoparticles and does not significantly affect their morphological structure. Therefore, the chemical functionalization with sulfonic acid groups successfully modifies the surface properties of SiO\u003csub\u003e2\u003c/sub\u003e while preserving the intrinsic morphology of the nanoparticles [28].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe elemental composition of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles was analyzed using EDX, and the corresponding spectrum is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The spectrum exhibits the characteristic peaks of Si and O associated with the silica framework, along with a distinct sulfur peak, confirming the successful incorporation of sulfur-containing functional groups onto the silica surface. Quantitative analysis indicates that the sulfur content in S-SiO\u003csub\u003e2\u003c/sub\u003e is approximately 3.6 wt.%. Considering the stoichiometry of the sulfonic acid group (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH), this sulfur content corresponds to about 9.1 wt.% of sulfonic acid functionalities grafted onto the silica surface (112.5 mmol of \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups per 100 g of S-SiO\u003csub\u003e2\u003c/sub\u003e). The appearance of sulfur, which is absent in pristine SiO\u003csub\u003e2\u003c/sub\u003e, provides clear evidence for the successful sulfonation of the nanoparticles. These results confirm that the sulfonation process effectively introduces sulfonic acid groups onto the surface of SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles [28,29].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigures\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea\u0026ndash;d illustrate the cross-sectional SEM micrographs of the CS, SPS, CSSPS40, and CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membranes. All membranes exhibit a dense, compact, and defect-free morphology throughout the thickness, with no observable voids, cracks, or pinholes. This compact structure is crucial for suppressing methanol crossover and maintaining the mechanical integrity required for DMFC applications. The CSSPS40 blend membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) shows no signs of macrophase separation, indicating good miscibility and interfacial compatibility between chitosan and SPS. Such compatibility is expected to result from hydrogen bonding and electrostatic interactions between the hydrophilic CS chains and the sulfonated aromatic segments of SPS [30].\u003c/p\u003e \u003cp\u003eIn the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e composite membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed), the SEM micrograph reveals that the functionalized silica nanoparticles are well dispersed within the polymer matrix without forming visible aggregates. The bright nano-sized spots correspond to S-SiO\u003csub\u003e2\u003c/sub\u003e particles and confirm their successful incorporation. Homogeneous dispersion of these nanoparticles suggests strong interactions\u0026mdash;likely hydrogen bonding\u0026mdash;between the surface \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups of S-SiO\u003csub\u003e2\u003c/sub\u003e and the functional groups of the polymer matrix (\u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e and \u0026ndash;OH of chitosan, and \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH of SPS). This uniform distribution plays a key role in creating a more tortuous pathway for methanol molecules, thereby decreasing methanol permeability and enhancing membrane selectivity.\u003c/p\u003e \u003cp\u003eTo further verify nanoparticle dispersion and evaluate the distribution of functional groups, EDX elemental mapping of the composite membrane was conducted (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee\u0026ndash;g). The silicon map (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee) shows a uniform and continuous distribution of Si signals across the cross-section, confirming that S-SiO\u003csub\u003e2\u003c/sub\u003e particles are homogenously embedded within the membrane structure. The nitrogen map (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef), which corresponds to the \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e groups of chitosan, shows an even distribution throughout the matrix, indicating the absence of polymer phase segregation. The sulfur map (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg) exhibits a uniform distribution of \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups originating from both SPS and S-SiO\u003csub\u003e2\u003c/sub\u003e. The co-localization of N and S signals demonstrates that proton-conducting sites are evenly dispersed across the membrane, which is essential for forming efficient proton-transfer pathways [31,32].\u003c/p\u003e \u003cp\u003eOverall, the combination of dense morphology, absence of defects, strong polymer\u0026ndash;filler interactions, and uniform distribution of proton-conducting functional groups suggests that the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane possesses the structural features necessary for improved proton conductivity, reduced methanol crossover, and enhanced mechanical stability. These morphological characteristics support its potential as a promising proton exchange membrane for DMFC applications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows XRD patterns of the pristine CS membrane and the CSSPS40 blend membrane, providing insight into the structural modifications occurring in the polymer matrix after the incorporation of SPS. The CS membrane exhibits two characteristic diffraction peaks at approximately 2θ\u0026thinsp;=\u0026thinsp;12\u0026deg; and 23\u0026deg;, which are typical of the semi-crystalline structure of chitosan. The diffraction peak at around 12\u0026deg; is attributed to the ordered crystalline domains arising from strong intermolecular hydrogen bonding between chitosan chains, while the broad peak near 23\u0026deg; corresponds to the amorphous regions of the polymer structure [10,33].\u003c/p\u003e \u003cp\u003eUpon blending with SPS, noticeable changes appear in the XRD profile of the CSSPS40 membrane. Specifically, the intensity of the crystalline peak decreases and becomes broader compared to that of the pristine CS membrane, indicating a partial disruption of the ordered chitosan structure. This reduction in crystallinity can be attributed to the strong electrostatic interactions between the protonated amino groups (\u0026ndash;NH\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) of chitosan and the sulfonic acid groups (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) of SPS. These interactions disturb the regular packing between chitosan chains, resulting in a less ordered polymer arrangement [34].\u003c/p\u003e \u003cp\u003eThe decrease in crystallinity consequently increases the fraction of amorphous regions within the membrane matrix. Such an increase in amorphous domains enhances polymer chain mobility and may facilitate the formation of interconnected proton-transport pathways. These structural features are beneficial for proton conduction, as the amorphous phase provides more accessible sites for proton hopping and water-assisted proton transport mechanisms. Therefore, the observed structural modification in the CSSPS40 membrane is expected to contribute positively to the proton conductivity and overall electrochemical performance of the membrane in proton exchange membrane fuel cell applications [35].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe thermal stability of proton exchange membranes (PEMs) is a crucial factor determining their durability and performance under fuel cell operating conditions. Therefore, the thermal behavior of the prepared membranes was investigated using TGA, and the results are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe TGA curve of the pristine CS membrane exhibits three main stages of thermal decomposition under a nitrogen atmosphere. The first weight loss, occurring between 50\u0026deg;C and 200\u0026deg;C, corresponds to the evaporation of physically adsorbed and bound water molecules due to dehydration. The second stage, observed between 200\u0026deg;C and 300\u0026deg;C, is attributed to the degradation of chitosan side-chain functional groups, including amino (\u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e) and hydroxyl groups, as well as partial desulfonation of any residual acid functionalities. The third degradation phase initiates at approximately 300\u0026deg;C and extends to higher temperatures, representing the decomposition of the chitosan backbone structure, which leads to complete thermal decomposition of the polymer matrix [12,36,37].\u003c/p\u003e \u003cp\u003eThe SPS membrane also exhibits a three-step thermal degradation profile. The first step, between 50\u0026deg;C and 200\u0026deg;C, is associated with the release of absorbed water interacting with the hydrophilic \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups. The second stage, spanning 200\u0026ndash;360\u0026deg;C, corresponds to the decomposition of sulfonic acid groups and fragmentation of the aromatic polymer framework. The final step involves the complete breakdown of the polymer chains at higher temperatures [38].\u003c/p\u003e \u003cp\u003eThe TGA curves of the CSSPS40 and CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e composite membranes show similar overall decomposition patterns, with improved thermal stability compared to the pristine CS membrane. The lower weight loss observed at corresponding temperature intervals suggests that blending chitosan with SPS and incorporating S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles strengthens the polymer matrix and enhances its resistance to thermal degradation. This improvement is likely due to strong interfacial interactions\u0026mdash;including hydrogen bonding and electrostatic attractions\u0026mdash;between the functional groups of the polymer chains and the surface of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, which restrict polymer chain mobility and delay decomposition. Consequently, the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane demonstrates superior thermal endurance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe thermal behavior of the prepared membranes was further examined using differential scanning calorimetry (DSC), and the results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. All membranes exhibit an endothermic peak within the temperature range of 200\u0026ndash;240\u0026deg;C, which is associated with the thermal decomposition of the chitosan chains, which is consistent with the TGA results. In addition, the acid\u0026ndash;base interactions between chitosan and sulfonated polystyrene not only lead to an increase in the thermal decomposition temperature of the membranes but also result in an enhancement of the glass transition temperature (T\u003csub\u003eg\u003c/sub\u003e). Specifically, the protonated amino groups (\u0026ndash;NH\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) of chitosan interact electrostatically with the sulfonic acid groups (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH/\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) of SPS, forming ionic pairs within the polymer network. These interactions act as physical cross-linking points that restrict the segmental mobility of polymer chains and increase the rigidity of the polymer matrix. Consequently, greater thermal energy is required to initiate chain motion, leading to an increase in the T\u003csub\u003eg\u003c/sub\u003e of the blended membranes compared with the pristine chitosan membrane. Moreover, the formation of these strong intermolecular interactions also influence the free volume of the membrane and the transport phenomena within it, stabilize the polymer structure and delay the onset of thermal degradation, which contributes to the improved thermal stability observed for the composite membranes [39\u0026ndash;41].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIEC is one of the most important parameters of PEMs, as it reflects the density of proton-conducting sites within the membrane structure and is closely related to water uptake and electrochemical performance [31]. The IEC values of the prepared membranes are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. As can be observed, the CS membrane exhibits a lower IEC compared with the blend membranes. This behavior might be attributed to the relatively high crystallinity of chitosan, which restricts the accessibility of ion-exchangeable functional groups. With increasing SPS content in the chitosan matrix, the IEC of the blend membranes increases noticeably. This improvement can be attributed to higher IEC of SPS which stems from the sulfonic acid groups (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) present in its structure, serving as additional proton-conducting sites, in addition to the reduction in crystallinity of the blend system relative to the CS membrane, leading to the formation of more amorphous regions that facilitate the accessibility of functional groups responsible for ion transport [12].\u003c/p\u003e \u003cp\u003eThe incorporation of SiO\u003csub\u003e2\u003c/sub\u003e results in a marginal increase in IEC, whereas the addition of S-SiO\u003csub\u003e2\u003c/sub\u003e leads to a more pronounced enhancement. This improvement is primarily attributed to the sulfonic acid (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) moieties present on the surface of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, which introduce additional proton-conducting sites. Furthermore, the hydroxyl groups on the surface of pristine nanosilica also participate in proton exchange through hydrogen-bonding interactions, contributing to the overall increase in IEC within the membrane structure [27].\u003c/p\u003e \u003cp\u003eWater uptake is one of the most important parameters of proton exchange membranes. The presence of water facilitates proton transport within the membrane; however, excessive water absorption can negatively affect membrane performance by reducing dimensional stability, increasing the swelling ratio, and deteriorating mechanical properties [42]. Therefore, controlling the water uptake of PEMs is essential to achieve an appropriate balance between proton conductivity and structural stability. The water uptake values of the prepared membranes are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The pristine CS membrane exhibited the highest water uptake due to the inherently hydrophilic nature of chitosan [43]. With increasing SPS content in the CS matrix, the water uptake of the blend membranes gradually decreased. This behavior can be attributed to the relatively lower water affinity of SPS compared with chitosan, as well as the electrostatic interactions between the amino groups of chitosan and the sulfonic acid groups of SPS, which reduce the free volume within the membrane structure [16,44]. The CSSPS40/SiO\u003csub\u003e2\u003c/sub\u003e membrane shows slightly higher water uptake than CSSPS40, owing to the hydrophilic nature of SiO\u003csub\u003e2\u003c/sub\u003e and the presence of hydroxyl groups on its surface. Moreover, the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibits higher water uptake than CSSPS40/SiO\u003csub\u003e2\u003c/sub\u003e, which is mainly attributed to the sulfonic acid groups on the surface of the functionalized nanoparticles that can form hydrogen bonds with water molecules, thereby enhancing the membrane hydrophilicity [28].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBesides the total water uptake, the state of water molecules within the fabricated membranes is also an important factor to consider. Generally, the water absorbed by hydrophilic groups can be classified into two categories: bound water and free water. Bound water refers to water molecules that surround ionic groups and form hydrogen bonds within ionic domains, thereby facilitating various transport mechanisms and enhancing proton transport across the membrane. In contrast, free water consists of water molecules that occupy the free volume within the membrane structure [45]. The amounts of bound and free water in the fabricated membranes are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The incorporation of SPS into the CS matrix in the CSSPS40 membrane, as well as the addition of S-SiO\u003csub\u003e2\u003c/sub\u003e, increases the proportion of bound water relative to free water, which is beneficial for proton conduction. This behavior can be attributed to the presence of sulfonic acid (\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH) groups in SPS and S-SiO\u003csub\u003e2\u003c/sub\u003e, which promote the formation and stabilization of bound water molecules within the membrane through hydrogen-bonding interactions [46].\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\u003eThe water state values, and surface roughness of the prepared membranes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSPS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSSPS40\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIEC (meq.\u0026nbsp;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater uptake (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean roughness (nm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRms roughness (nm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e342.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eλ\u003csub\u003ef\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eλ\u003csub\u003eb\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBound water (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e: λ: the total number of water molecules per proton-conducting group. λ\u003csub\u003eb\u003c/sub\u003e: the number of bound water molecules per a proton-conducting group. λ\u003csub\u003ef\u003c/sub\u003e: the number of free water molecules per a proton-conducting group. χ: the ratio of bound water to free water content.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAFM was employed to investigate the surface morphology of chitosan-based membranes incorporating SPS and S-SiO\u003csub\u003e2\u003c/sub\u003e, with the corresponding roughness data summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. The pristine CS membrane exhibited a relatively uniform and homogeneous surface, although its roughness was higher than that of SPS. Upon the incorporation of SPS (CSSPS40), the surface roughness (S\u003csub\u003eq\u003c/sub\u003e) increased markedly from 16.5 nm to 28.1 nm, which can be attributed to the formation of heterogeneous microdomains arising from electrostatic interactions between the amino groups of CS and the sulfonic acid groups of SPS, as well as the partial disruption of polymer crystallinity leading to a more amorphous surface structure. This morphological evolution is in agreement with the observed trend in water uptake [7]. The CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibited only a slight further increase in surface roughness compared to CSSPS40, suggesting improved interfacial compatibility and uniform dispersion of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles within the matrix [15].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe surface hydrophilicity of the membranes was evaluated by contact angle measurements, and the corresponding results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. As compared to the pristine CS membrane, the CSSPS40 membrane exhibited a higher contact angle, indicating a moderate reduction in surface hydrophilicity upon the incorporation of SPS. This behavior can be attributed to the combined effects of altered surface morphology and microphase separation within the blended matrix, as evidenced by the increased surface roughness observed in AFM analysis [31].\u003c/p\u003e \u003cp\u003eThe CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibited a lower contact angle compared to the CSSPS40 membrane, indicating an increase in surface hydrophilicity after the incorporation of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles. This behavior can be attributed to the presence of hydrophilic functional groups, particularly sulfonic acid and hydroxyl groups, on the surface of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, which enhance the affinity of the membrane surface toward water molecules. The improved hydrophilicity is consistent with the observed increase in water uptake for the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane. The presence of these polar functional groups promotes stronger hydrogen-bonding interactions with water and facilitates the formation of hydrophilic domains within the polymer matrix, thereby enabling greater water absorption. Consequently, the reduced contact angle and increased water uptake collectively confirm that the incorporation of S-SiO\u003csub\u003e2\u003c/sub\u003e enhances the overall hydrophilic character of the membrane, which is beneficial for proton transport in proton exchange membrane applications [47].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn a fuel cell environment, the electrochemical reactions occurring at the anode and cathode generate highly reactive oxygen species, including hydroperoxyl (HOO˙) and hydroxyl (HO˙) radicals, which can attack polymer backbones and functional groups, ultimately leading to membrane degradation and performance loss [48]. Therefore, ensuring adequate oxidative stability is essential for the long-term durability of proton exchange membranes. The oxidative stability of the prepared membranes was assessed through weight-loss measurements after exposure to Fenton\u0026rsquo;s reagent, and the corresponding results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e. The pristine SPS membrane exhibited moderate stability, with a weight loss of 5.0 wt.%. The CSSPS40 membrane demonstrated a significantly lower weight loss (12.4 wt.%) compared to the pristine CS membrane (20 wt.%), indicating improved resistance to oxidative attack. This enhancement is attributed to the protective effect of SPS, where the \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups interact with chitosan\u0026rsquo;s \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e groups through ionic cross-linking and hydrogen bonding, thereby reducing the susceptibility of the polymer chains to radical-induced degradation [49]. Furthermore, the incorporation of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles further improved the membrane\u0026rsquo;s oxidation resistance, with the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e sample exhibiting a reduced weight loss of 11.3 wt.%. This improvement arises from strong interfacial interactions between the nanoparticles and the polymer matrix, which help stabilize the membrane structure and hinder radical penetration [50]. Overall, the results confirm that the synthesized membranes possess good oxidative stability, making them suitable candidates for DMFC applications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLow methanol permeability is a critical requirement for improving the efficiency of DMFCs. In PEMs, methanol crossover predominantly occurs due to the combined effects of concentration gradient\u0026ndash;driven diffusion and electro-osmotic drag between the anode and cathode compartments [51]. The diffusion of methanol is governed by several physicochemical parameters, including the free void volume within the membrane, the molecular dimensions of the penetrant, and the segmental mobility of the polymer chains [52]. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the incorporation of SPS into the chitosan matrix and the subsequent increase in SPS content led to a substantial reduction in methanol permeability. This decrease can be attributed to electrostatic interactions between chitosan and SPS, which constrain polymer chain mobility, diminish free volume, and thereby reduce the effective channels available for methanol transport [16,52,53]. Further decreases in permeability were observed upon embedding SiO\u003csub\u003e2\u003c/sub\u003e and S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, as the presence of these inorganic fillers introduced tortuous diffusion pathways that hinder methanol permeation [54]. Interestingly, nanocomposite membranes containing S-SiO\u003csub\u003e2\u003c/sub\u003e exhibited slightly higher methanol crossover than their SiO\u003csub\u003e2\u003c/sub\u003e-based counterparts, a phenomenon associated with the increased water uptake of S-SiO\u003csub\u003e2\u003c/sub\u003e-modified membranes that facilitates methanol diffusion through hydrated domains. Overall, the results confirm that the incorporation of SPS and inorganic nanoparticles into the chitosan matrix effectively suppresses methanol crossover while maintaining desirable electrochemical properties, demonstrating excellent potential for high-performance DMFC applications.\u003c/p\u003e \u003cp\u003eHigh proton conduction is also essential for ensuring high performance of a PEM in a DMFC structure. On the molecular level, proton transition in hydrated conditions can be defined by two main mechanisms: the vehicle mechanism and the proton hopping mechanism, which is generally known as the Grotthuss mechanism [55,56]. In the Grotthuss mechanism, protons jump from one proton conducting site, such as \u0026ndash;NH\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, H\u003csub\u003e3\u003c/sub\u003eO\u003csup\u003e+\u003c/sup\u003e or \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, to another site across the membrane by forming and breaking hydrogen bonds. In contrast, in the vehicle mechanism, due to electrochemical differences, protons attach to the vehicle sites, such as water molecules, and diffuse through the aqueous or other liquid media [57].\u003c/p\u003e \u003cp\u003eThe proton conductivity of the prepared membranes at 25\u0026deg;C is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The pristine CS membrane exhibits a proton conductivity of 0.008 S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which is mainly associated with proton transport through hydrogen-bonded networks formed by the hydrophilic \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e and \u0026ndash;OH groups of chitosan. With the incorporation of SPS into the chitosan matrix, the conductivity gradually increases and reaches 0.0089 S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for the CSSPS30 membrane. This improvement is attributed to the strong electrostatic interactions and hydrogen bonding between the \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups of SPS, the adsorbed sulfuric acid molecules acting as crosslinking agents, and the \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e groups of chitosan, which contribute to the formation of interconnected hydrogen-bond networks that facilitate proton hopping along continuous conduction pathways [58]. However, when the SPS content is increased to 40 wt.% (CSSPS40), the proton conductivity slightly decreases to 0.0087 S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The excessive SPS incorporation may disturb the optimal microstructural organization of the polymer network and reduce the connectivity of proton-conducting domains. As a result, the continuity of proton transport pathways becomes partially limited, restricting proton mobility. In addition, the lower proton conductivity of SPS, as well as the relatively lower water uptake observed for the CSSPS40 membrane may further hinder the formation of extended hydrogen-bonded networks required for efficient proton transfer through the Grotthuss mechanism.\u003c/p\u003e \u003cp\u003eThe incorporation of inorganic nanoparticles further enhances the proton conductivity of the membranes. The CSSPS40/SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibits higher conductivity due to the hydrophilic nature of silica nanoparticles, which improve water retention and increase the IEC, thereby facilitating the formation of more continuous hydrated pathways for proton transport. The CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane shows the highest conductivity among all samples (0.0101 S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). This superior performance is attributed to the presence of sulfonic acid groups grafted onto the surface of S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles, which provide additional proton-conducting sites and promote stronger hydrogen-bond networks within the membrane. Consequently, these functionalized nanoparticles shorten the proton hopping distance and enhance proton migration mainly through the Grotthuss mechanism [59].\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\u003eThe electrochemical characteristics of the prepared membranes at 25\u0026deg;C.\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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" 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\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProton conductivity (\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMethanol permeability (\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e cm\u003csup\u003e2\u003c/sup\u003e. s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelectivity (S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\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\u003eSPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24,615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27,035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30,281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34,901\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39,908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS40/SiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52,840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54,010\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=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e illustrates the discussed proton transport mechanism in the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e nanocomposite membrane. Proton conduction is facilitated by the cooperative interactions between chitosan, SPS, and S-SiO\u003csub\u003e2\u003c/sub\u003e. Acid\u0026ndash;base interactions between the \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e groups of chitosan and the \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups of SPS and S-SiO\u003csub\u003e2\u003c/sub\u003e lead to the formation of ionic pairs (\u0026ndash;NH\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e/\u0026ndash;SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e), generating interconnected ionic domains within the membrane. The hydrophilic \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH and \u0026ndash;OH groups enhance water retention and promote the formation of hydrogen-bonded networks, enabling proton transport through both the vehicle (H\u003csub\u003e3\u003c/sub\u003eO\u003csup\u003e+\u003c/sup\u003e diffusion) and Grotthuss (proton hopping) mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn ideal proton exchange membrane (PEM) should simultaneously exhibit high proton conductivity and low methanol permeability; therefore, membrane selectivity is a key parameter for evaluating PEM performance in DMFCs. Because proton conductivity and methanol permeability directly reflect the transport behavior of protons and fuel molecules, their ratio provides a reliable indicator of the membrane\u0026rsquo;s practical applicability. Accordingly, a high selectivity value is essential for PEMs intended for DMFC operation [60].\u003c/p\u003e \u003cp\u003eThe selectivity values of the prepared membranes at 25\u0026deg;C are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among the blend membranes with different SPS contents, the CSSPS40 membrane shows the highest selectivity (39,908 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), indicating that 40 wt.% SPS represents the optimal composition for achieving a balanced combination of proton transport and methanol barrier properties. Moreover, the incorporation of inorganic fillers further enhances membrane selectivity. In particular, the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibits the highest selectivity of all investigated samples (54,010 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), which is more than twice that of the pristine CS membrane (24,615 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e compares the proton conductivity, methanol permeability, and membrane selectivity parameters of several previously reported chitosan-based PEMs with those of the studied polyelectrolyte membrane (CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e) and recast Nafion. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e membrane exhibits a selectivity value higher than that of recast Nafion, indicating its strong potential as a promising PEM candidate for DMFC applications.\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\u003eCharacteristics of chitosan-based PEMs reported for DMFC applications.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMembrane Components\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProton conductivity (S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMethanol permeability (cm\u003csup\u003e2\u003c/sup\u003e. s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelectivity (S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.87 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54,010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePure chitosan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.38\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[61]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfonated chitosan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30,851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[61]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/sulfonated polyvinylidene fluoride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.12 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e at 30\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 30\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16,900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[16]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/sulfonated chitosan/sulfonated graphene oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e151,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[40]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/polyvinyl alcohol/organophosphorus acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 20\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116,666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[62]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/phosphotungstic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96,774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[63]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/Nafion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.01 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37,569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[12]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitosan/phosphomolybdic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55,555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[64]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecast Nafion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e at 25\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[65]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this work, chitosan-based blend membranes containing different amounts of SPS (acid\u0026ndash;base blend) were fabricated using the solution-casting technique. Among the prepared membranes, the CSSPS40 membrane exhibited the highest selectivity parameter and was therefore identified as the optimal composition. Blending chitosan with SPS reduced the methanol permeability of the membranes, while the presence of sulfonic acid groups facilitated proton transport through the Grotthuss mechanism via acid\u0026ndash;base interactions between chitosan and SPS. Furthermore, the incorporation of SiO\u003csub\u003e2\u003c/sub\u003e and sulfonated SiO\u003csub\u003e2\u003c/sub\u003e (S-SiO\u003csub\u003e2\u003c/sub\u003e) nanoparticles into the optimal blend membrane effectively reduced methanol crossover and enhanced proton conductivity. The blend nanocomposite membrane, CSSPS40/S-SiO\u003csub\u003e2\u003c/sub\u003e, exhibited a proton conductivity of 10.1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e S. cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and a methanol permeability of 1.87 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e cm\u003csup\u003e2\u003c/sup\u003e. S\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, resulting in a selectivity of approximately 54,010 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, which is the highest among all the prepared membranes.\u003c/p\u003e \u003cp\u003eIn addition to its improved electrochemical performance, the selected membrane can also be considered an economically attractive option due to the use of abundant and relatively low-cost materials such as chitosan, SPS and silica nanoparticles. Therefore, the developed membrane shows strong potential as a promising and cost-effective candidate for future direct methanol fuel cell (DMFC) applications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMahdi Tohidian: Supervisor, Revising the manuscriptShayan Navabi:Experiments, Data generation, writing the manuscript\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003eThis research was financially supported by Amirkabir University of Technology, Tehran, Iran.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu J, Wang F, Fan X, Chu J, Cheng F, Hu F, et al. Phosphoric acid-doped Gemini quaternary ammonium-grafted SPEEK membranes with superhigh proton conductivity and mechanical strength for direct methanol fuel cells. J Memb Sci 2023;672:121431. https://doi.org/https://doi.org/10.1016/j.memsci.2023.121431.\u003c/li\u003e\n\u003cli\u003eNg WW, Thiam HS, Pang YL, Lim YS, Wong J, Saw LH. Self-sustainable, self-healable sulfonated graphene oxide incorporated nafion/poly(vinyl alcohol) proton exchange membrane for direct methanol fuel cell applications. J Environ Chem Eng 2023;11:111151. https://doi.org/https://doi.org/10.1016/j.jece.2023.111151.\u003c/li\u003e\n\u003cli\u003eHemmasi E, Tohidian M, Makki H. Morphology and Transport Study of Acid\u0026ndash;Base Blend Proton Exchange Membranes by Molecular Simulations: Case of Chitosan/Nafion. J Phys Chem B 2023;127:10624\u0026ndash;35. https://doi.org/10.1021/acs.jpcb.3c05332.\u003c/li\u003e\n\u003cli\u003eFeng S, Kondo S, Kikuchi T, Christiani L, Hwang B, Sasaki K, et al. Development of a Heat-Treated Polymer\u0026ndash;Polymer Type Charge-Transfer Blend Membrane for Application in Polymer Electrolyte Fuel Cells. 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Polyelectrolyte Nanocomposite Membranes, Based on Chitosan-phosphotungstic Acid Complex and Montmorillonite for Fuel Cells Applications. J Macromol Sci Part B 2013;52:1226\u0026ndash;41. https://doi.org/10.1080/00222348.2013.763565.\u003c/li\u003e\n\u003cli\u003eCui Z, Xing W, Liu C, Liao J, Zhang H. Chitosan/heteropolyacid composite membranes for direct methanol fuel cell. J Power Sources 2009;188:24\u0026ndash;9. https://doi.org/10.1016/j.jpowsour.2008.11.108.\u003c/li\u003e\n\u003cli\u003eHasani-Sadrabadi MM, Dashtimoghadam E, Majedi F. Investigation of a Double Layer Membrane for Direct Methanol Fuel Cell Applications. ECS Meet Abstr 2009;MA2009-02:1094. https://doi.org/10.1149/MA2009-02/10/1094.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"materials-for-renewable-and-sustainable-energy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Materials for Renewable and Sustainable Energy](https://link.springer.com/journal/40243)","snPcode":"40243","submissionUrl":"https://submission.springernature.com/new-submission/40243/3","title":"Materials for Renewable and Sustainable Energy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Direct methanol fuel cell, Proton conductivity, Methanol permeability, Sulfonated polymers, Acid–base membranes","lastPublishedDoi":"10.21203/rs.3.rs-9426945/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9426945/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, proton exchange membranes (PEMs) based on chitosan, sulfonated polystyrene (SPS), and pristine or modified nanosilica were fabricated for direct methanol fuel cell (DMFC) applications. Membranes containing different SPS contents were prepared, and polystyrene was sulfonated to an optimal degree of sulfonation determined by evaluating its hydrolytic stability.\u003c/p\u003e \u003cp\u003eProton conductivity and methanol permeability were measured to determine the membrane selectivity parameter, defined as the ratio of proton conductivity to methanol permeability. Among the prepared membranes, the membrane containing 40 wt.% SPS exhibited the highest selectivity parameter (39,908 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) and was therefore identified as the optimal composition.\u003c/p\u003e \u003cp\u003eTo improve membrane performance, nanocomposite membranes containing 2 wt.% silica nanoparticles (SiO\u003csub\u003e2\u003c/sub\u003e) or sulfonated silica nanoparticles (S-SiO\u003csub\u003e2\u003c/sub\u003e) were separately prepared using the optimal chitosan/SPS blend. The incorporation of SPS increased the glass transition temperature and decreased the crystallinity of the chitosan matrix due to electrostatic interactions between the \u0026ndash;SO\u003csub\u003e3\u003c/sub\u003eH groups of SPS and the \u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e groups of chitosan.\u003c/p\u003e \u003cp\u003eFurthermore, the nanocomposite membranes exhibited higher proton conductivity and lower methanol permeability compared with the optimal blend membrane. The membrane containing S-SiO\u003csub\u003e2\u003c/sub\u003e nanoparticles showed the highest selectivity (54,010 S. s. cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), indicating its strong potential as an alternative proton exchange membrane for DMFC applications.\u003c/p\u003e","manuscriptTitle":"Development of Chitosan–Sulfonated Polystyrene–Sulfonated Nanosilica Nanocomposite Proton Exchange Membranes for Direct Methanol Fuel Cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 09:07:00","doi":"10.21203/rs.3.rs-9426945/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-04T10:10:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T20:59:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T20:04:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T08:41:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197470223240816873836386585865030512830","date":"2026-04-21T18:54:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175309433615105519802040545212224629818","date":"2026-04-21T12:49:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84120929744700846910445411775519858482","date":"2026-04-20T21:40:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T16:15:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-18T06:23:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-18T06:23:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Materials for Renewable and Sustainable Energy","date":"2026-04-15T12:17:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"materials-for-renewable-and-sustainable-energy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Materials for Renewable and Sustainable Energy](https://link.springer.com/journal/40243)","snPcode":"40243","submissionUrl":"https://submission.springernature.com/new-submission/40243/3","title":"Materials for Renewable and Sustainable Energy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b167b182-af0b-464d-97f3-7e168d5d1059","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T10:10:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T20:59:54+00:00","index":21,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T20:04:09+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T10:25:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 09:07:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9426945","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9426945","identity":"rs-9426945","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}