Cellulose nanofibrils (CNFs) are promising renewable materials, but high fibrillation energy remains a major barrier to industrial adoption. This narrative, mechanism-focused review examines CNF production from an engineering perspective, integrating the coupled roles of feedstock structure, interfacial chemistry, hydrodynamic stress transfer, and process boundary definition. This review examines energy consumption in CNF production by linking interfacial cohesion within cellulose fiber walls, hydrodynamic stress generation in fibrillation devices, and nonproductive energy-dissipation pathways. The principal mechanical routes—high-pressure homogenization, microfluidization, grinding and refining, and high-consistency extrusion—are compared with chemical, enzymatic, and interfacial pretreatments that reduce cohesive resistance or suppress re-agglomeration. Attention is given to feedstock composition, hornification history, solids content, and process boundary definitions, because these factors strongly influence both specific energy consumption and total process energy. Across the literature, meaningful energy reduction is achieved not by equipment choice alone but by co-optimizing feedstock design, pretreatment chemistry, and stress-transfer efficiency while limiting viscous losses, elastic recovery, and fibril reassociation. The review also highlights persistent comparability problems caused by inconsistent reporting of solids content, pass number, product quality, and system boundaries. A unified framework is proposed in which energy-efficient CNF production depends on three coupled objectives: lowering interfacial cohesion, improving productive stress localization, and reducing dissipation across the full process chain while evaluating energy demand against clearly defined process boundaries and product quality endpoints.
Mexico’s highly biodiverse agro-industrial sector is a cornerstone of its economy, prominently featuring a robust sugarcane industry that ranks seventh globally in sugar production. This industry utilizes 52% of the country’s industrial water resources, hence producing substantial quantities of complex wastewater. To address this critical environmental challenge, this study evaluates a continuous electrocoagulation process applied to sugarcane mill effluents. The study examines the effectiveness of removing essential water quality indicators, chemical oxygen demand (COD), turbidity, and total solids (TSs), total suspended solids (TSSs), and total dissolved solids (TDSs), by evaluating the influence of the hydraulic retention time (HRT) and current intensity. Investigations were performed in a 20 L continuous-flow Imhoff reactor fitted with aluminum electrodes. Ideal operational parameters were attained with a hydraulic retention time of 120 min and a current intensity of 1.5 amperes. Within these parameters, the system attained notable removal efficiencies: 69% for COD, 78% for turbidity, 60% for total solids, 94% for suspended particles, and 55% for dissolved solids. These findings indicate that the incorporation of continuous electrocoagulation into an Imhoff tank design offers a highly efficient and scalable first treatment to reduce the ecological effects of sugarcane agro-industrial effluents.
Natural bitumens are promising alternative hydrocarbon resources, but their high resin–asphaltene content and strong coke-forming tendency limit their efficient conversion into valuable liquid products. This study elucidates the molecular transformations of resin and asphaltene fractions during thermocatalytic upgrading of natural bitumens from the Beke and Munaily Mola deposits in West Kazakhstan. Cracking experiments were conducted at 450 °C for 60 min using thermal treatment, fly-ash-derived ferrospheres, and di-tert-butyl peroxide (DTBP) as a radical-generating additive. Elemental analysis, average-molecular-weight determination, and nuclear magnetic resonance (NMR) spectroscopy were combined with structural-group analysis to establish changes in the molecular architecture of the heavy fractions. Thermal cracking produced 68–74% liquid products, while DTBP increased the liquid yield to 70% for Beke bitumen and 87% for Munaily Mola bitumen and substantially suppressed coke formation. Cracking promoted extensive degradation of aliphatic and naphthenic fragments, dealkylation, cyclization, dehydrogenation, and aromatization, resulting in increased aromaticity and lower molecular weight of the asphaltenes. The average molecular weight of Beke asphaltenes decreased from approximately 2044 to 1003 amu in the presence of ferrospheres. Although ferrospheres enhanced asphaltene destruction, they increased coke formation under the investigated conditions. These findings demonstrate that radical stabilization is critical for directing heavy-component conversion toward liquid products and provide a molecular basis for optimizing catalytic upgrading of natural bitumen.
Ibuprofen (IBU), a widely used anti-inflammatory drug, is increasingly found in aquatic environments, particularly in pharmaceutical wastewater, raising concerns about its persistence and ecological risks. This study investigates IBU removal using a bioelectrochemical system (BES) under laboratory conditions with synthetic pharmaceutical wastewater (SPWW) and halophilic microbiomes from two hypersaline sediments of Chott El-Djerid (CJ–S1 and CJ–S2). Three bioanode reactors were operated at +0.1 V/SCE for 15 days with IBU concentrations of 60 and 150 ppm, with or without glucose (Glc) (20 ppm) as a co-substrate. IBU degradation was confirmed by LC-MS, COD removal, and FTIR analyses, showing removal efficiencies approaching 100%. Electrochemical performance varied with the inoculum: CJ–S2 produced a higher current density (38.02 ± 0.15 mA m−2) than CJ–S1. Metataxonomic analysis revealed strong enrichment of Chromohalobacter spp., while the combination of CJ–S2, 60 ppm IBU, and Glc promoted a more diverse consortium dominated by Halomonas spp. and Bacillus shackletonii. These findings highlight that microbial origin and co-substrate availability critically shape bacterial community structure, electroactivity, and degradation efficiency. The CJ–S2 microbiome is a promising candidate for developing robust electroactive bioanodes for treating pharmaceutical wastewater.
Hydrothermal synthesis is a bottom-up, liquid-phase synthesis method and a heterogeneous reaction, utilizing a water solvent at a temperature of >25 °C and a pressure of ≥1 atm to dissolve and to precipitate crystalline or amorphous materials or to get solutions by using a reflux, autoclave, or flow reactor. Microwave-assisted hydrothermal and supercritical flow reactors successfully reduced the synthesis times from hours or days to minutes and seconds. Substitutions for precursors, reductors, or stabilizer chemicals with plant extracts successfully created greener hydrothermal methods, but they still need relatively long times (hours) and high temperatures (>100 °C). The stronger critical perseptives include the inhibited standarization and reproducibility due to plant species variant, plant growth conditions, and plant extraction methods. The plant extract can’t substitute surfactant as mesoporous template or the organic solvents for water-organic sol-vent mixture, and it is possibly photodegraded by microwave. Strategies to reduce time and temperature by mechanical hydrothermal synthesis using plant extracts, with safety prioritized, utilizing non-toxic products, degradable products, and non-harmful reactants, are suggested for future research. One mechanistic question is still not resolved: how distiguish crystalization mechanism by using the temperature reduction method and by using temperature different method.
Liquid holdup (HL) prediction in gas–liquid two-phase flows (TPF) has been studied extensively for decades. However, existing reviews and empirical correlations have largely treated key controlling parameters, particularly liquid viscosity and pipe inclination, as independent or secondary factors. This review is based on prior studies by providing a systematic synthesis of the coupled effect of high viscosity (200–800 mPa·s) and pipe inclination (0° to 90°) on both general liquid holdup (HL) and slug liquid holdup (HLs). These effects are regime-dependent: negligible in low-viscosity flows but dominant in high-viscosity, large-diameter, and undulating pipelines. The review identifies two critical limitations of current models: their systematic underprediction for high-viscosity fluids and their failure to account for inclination-driven HL variations, which can be as high as 10–30%. Consequently, this review advocates a paradigm shift toward data-driven intelligent models (e.g., Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs)) trained on comprehensive, well-curated datasets that explicitly capture the viscosity–inclination coupling. These hybrid models, which combine data-driven learning with physical constraints, provide the most viable path to overcome the fundamental limitations of current correlations and achieve accurate HL and HLs prediction for the design and operation of real-world, undulating pipeline systems handling viscous fluids.
This study presents an integrated and sustainable approach for the valorization of polystyrene (PS) plastic waste into methanol, contributing to circular carbon utilization and waste-to-fuel strategies. Two simulation models were developed in Aspen plus. In Case 1, PS is converted to syngas through steam gasification, followed by its conversion into methanol. In Case 2, a steam methane reforming (SMR) unit is integrated with the gasification unit, using the heat from the gasifier-derived syngas to boost hydrogen production and overall methanol yield. This integration boosts the hydrogen-to-carbon ratio, doubling methanol production in Case 2 compared to Case 1. In terms of energy performance, Case 2 exhibits a process efficiency of 81% and exergy efficiency of 73%, both significantly higher than 48% and 60%, compared to Case 1. From an economic standpoint, Case 2 requires greater capital investment and annual operational expenditure, yet it proves to be more cost-effective in the long run compared to Case 1 due to the higher methanol production. The methanol production cost is reduced by 50%, from $1.001/kg in Case 1 to $0.505/kg in Case 2. These improvements are driven by increased throughput and process integration that supports sustainable and circular carbon management.
This study presents a first-principles dynamic model for the electrochemical production of lithium hydroxide (LiOH) in a bench-scale cation exchange membrane (CEM) cell. Its distinguishing feature is a single, dynamically coupled description of the whole cell, in which the lumped Ordinary Differential Equation (ODE) dynamics of the anodic and cathodic chambers are coupled to a spatially resolved Nernst–Planck (PDE) model of membrane ion transport. The model resolves the transient induction period of ion crossover and captures the association kinetics of Li+ and OH−, cathodic water reduction, and the back-migration and neutralization of OH− at the anode, with the local electric field represented by a non-linear potential gradient. Solved by the Method of Lines and reduced through symbolic treatment of the Robin boundary conditions to a consistent ODE system, it yields a numerically robust framework for this stiff, strongly coupled problem. Two process-level results emerge: the membrane strongly attenuates cross-chamber disturbances, largely decoupling the anode and cathode, and it reaches a quasi-steady state far faster than the bulk chambers—a separation of time scales expected to widen at larger volume-to-surface-area ratios. These insights inform scale-up strategies and multiscale control architectures for the cell.
This study presents a numerical comparison of dimensional and non-dimensional implementations of the classical benchmark problem of steady natural convection in a two-dimensional differentially heated square cavity over the Rayleigh-number range 103 ≤ Ra ≤ 1012. The novelty of this work lies in the systematic comparison of both formulations under identical numerical conditions, providing an implementation-oriented assessment of their benchmark accuracy, mesh sensitivity, continuation strategy, and computational efficiency. The governing equations of mass, momentum, and energy conservation were solved under the Boussinesq approximation using primitive variables and the finite-element method. Since both formulations are theoretically equivalent descriptions of the same physical problem, the purpose of this work is not to reassess their physical validity, but to examine their numerical behavior under identical benchmark conditions in terms of mesh sensitivity, continuation strategy, benchmark accuracy, and computational efficiency. In the dimensional implementation, temperature differences of 1, 10, 25, and 50 K were considered, and the corresponding cavity lengths were determined from the Rayleigh-number definition. The main calculations were performed with ΔT = 25 K, while ΔT = 50 K was retained only as an exploratory sensitivity case. Boundary-layer refinement was applied along the vertical walls over the range 103 ≤ Ra ≤ 1012. The results show that, once the near-wall gradients are properly resolved, both implementations predict essentially identical average Nusselt numbers, with a maximum relative difference of 0.022%. Temperature contours, stream-function distributions, and centerline profiles also exhibited the same structural behavior in both cases. For the reference mesh, the dimensional implementation exhibited a lower computational cost than the non-dimensional implementation, resulting in an approximately 31% reduction in computation time. These results demonstrate that solving the governing equations directly in dimensional variables provides a numerically efficient and physically interpretable alternative while preserving the benchmark accuracy of the classical non-dimensional formulation.
Hydrothermal carbonization (HTC) of digested dairy manure produces hydrochar and a nitrogen-rich post-liquid. This study evaluated a submerged tubular expanded polytetrafluoroethylene (ePTFE) gas-permeable membrane (GPM) system for ammonia recovery from post-HTC liquid derived from digested dairy manure, focusing on the effects of feed temperature, acid circulation rate, and feed volume-to-membrane surface area ratio (FV/MS). Compared with filtered digested manure, the post-HTC liquid had a similar total ammoniacal nitrogen (TAN) concentration (1151 vs. 1164 mg N L−1) but a slightly higher pH (8.38 vs. 7.94), which favored ammonia transfer. Increasing feed temperature from 20 to 60 °C raised 24 h TAN recovery from 63.5% to 99.6% and average TAN transfer flux from 11.1 to 17.7 g m−2 d−1, although it also increased water vapor crossover and diluted the acid trapping solution. Increasing acid circulation from 10 to 30 mL min−1 improved 48 h TAN recovery from 85.2% to 94.0%, while a further increase to 50 mL min−1 produced only a small additional gain. In contrast, elevating FV/MS from 0.015 to 0.045 m3 m−2 reduced 48 h TAN recovery from 94.0% to 59.6% while increasing average TAN transfer flux from 8.2 to 16.2 g m−2 d−1 because larger feed volumes sustained the concentration driving force for a longer period. Nitrogen mass balance showed that more than 94–99% of the initial TAN was accounted under most conditions, with only a small fraction lost to volatilization.
Inverse fuzzy model control (IFMC) is an attractive strategy for regulating nonlinear thermal processes, where complex heat-transfer dynamics, disturbances, and actuator constraints challenge conventional control approaches. However, traditional direct and indirect inverse schemes often exhibit limited generalization and sensitivity to noise. This paper presents a data-driven inverse fuzzy control framework for temperature regulation in thermal systems, combining Takagi–Sugeno modeling, functional cancelation feedback, and auxiliary-input optimization. Gaussian antecedents and affine consequents are jointly identified via nonlinear least squares from input–output data generated by the theoretical PHE model. The same theoretical model is used as the numerical plant in all closed-loop simulations, whereas the forward and inverse fuzzy models are constructed only from the generated data and do not use the analytical PHE equations during identification or online inference. The learned inverse model estimates control actions that achieve the desired temperature trajectory while respecting actuator constraints. The method is evaluated in simulation on a plate heat exchanger (PHE) benchmark under tracking and disturbance-rejection scenarios. Results show accurate temperature regulation, smooth actuator behavior, and disturbance rejection in the tested scenarios. Compared with a numerically tuned PI baseline, the proposed approach reduces tracking RMSE by 27.5% and the standard deviation of the primary control current by 9.6% in the reported simulation scenario, indicating improved tracking and smoother primary actuation. In general, the proposed framework provides an interpretable and efficient solution for nonlinear thermal processes, with potential applications in energy systems, heat exchangers, and related thermal engineering technologies.
Nanocolloid research has undergone a complete transformation, renouncing the empirical estimation of properties and relying on real case scenarios. The main objective of this paper is to compare a large number of samples that were experimentally studied in terms of thermophysical properties in order to be able to draw a conclusion in terms of the heat transfer efficiency of a certain surfactant addition to a 2 wt.% TiO2 nanoparticle-enhanced fluid. The analysis discusses both the advantages and drawbacks in terms of surfactant type and concentration influence over the Prandtl number, thermal diffusivity, and Nusselt number, as well as the heat transfer coefficient for different Reynolds numbers in laminar flow. The investigation also includes a different figure of merits and performance evaluation criteria that are extensively employed in the literature in order to have a complete overview of the efficiency of surfactants in improving nanocolloids. In conclusion, even if surfactants are considered for improving nanocolloid stability, their drawbacks have not been debated in depth in the open literature. The main conclusion that arises from this study outlines that among all tested samples, F127 at a concentration of 0.25 wt.% consistently demonstrates the best overall performance, achieving an optimal balance between enhanced thermal properties and acceptable pumping requirements.
The performance and durability of lithium metal solid-state batteries are governed by the dynamic evolution of the lithium/solid-electrolyte (Li/SSE) interface, where electrochemical reactions, mass transport, and mechanical constraints are intrinsically coupled. This review presents an integrated electro-chemo-mechanical framework that links interfacial stripping dynamics to distinct degradation regimes controlled by current density, stack pressure, and thermal activation. We show that stable cycling emerges only within a narrow flux-balance window in which lithium creep and vacancy diffusion compensate stripping-induced volume loss without triggering electrolyte fracture or filament penetration. By synthesizing recent experimental, modeling, and materials engineering advances, the review maps the transitions between void-dominated instability, pressure-assisted stabilization, and stress-limited failure. Particular emphasis is placed on adaptive pressure strategies, compliant interlayer design, and microstructural interface engineering as pathways to expand the operational stability window. The analysis highlights that interfacial stability is not solely a materials property but a systems-level outcome arising from coupled electro-mechanical boundary conditions and temperature-dependent transport processes. This perspective provides design principles for developing next-generation solid-state batteries capable of stable high-rate cycling and long-term reliability.
Cotton fabrics are widely used due to their comfort and biodegradability; however, their intrinsic hydrophilicity limits their performance in advanced applications. In this work, a fluorine-free approach for imparting durable hydrophobicity to cotton was developed based on thiol-ene crosslinking of polysiloxane networks formed on the fiber surface. Two thiol-functional polysiloxanes differing in -SH group content were combined with four vinyl-functional organosilicon crosslinkers under UV (2,2-dimethoxy-2-phenylacetophenone (DMPA)) and thermal (2,2 '-azobis(2-methylpropionitrile) (AIBN)) initiation. FT-IR analysis confirmed the presence of siloxane structures, while SEM-EDS revealed stable silicon- and sulfur-containing layers. SEM observations showed continuous coatings without blocking the textile structure. Water contact angle (WCA) measurements demonstrated that hydrophobic performance strongly depends on thiol content and crosslinker structure, with the highest values obtained for the thiol-rich polysiloxane and tetrafunctional vinyl crosslinker. All modified fabrics exhibited high durability, with minimal changes in WCA and complete droplet stability (1800 s) after washing. In the case of the lower-functionality polysiloxane, an increase in hydrophobicity after washing was observed, attributed to the reorganization of siloxane chains. These results demonstrate that thiol-ene crosslinking provides an effective strategy for designing durable, fluorine-free hydrophobic coatings on cotton.
The depletion of natural resources has emerged as a major global concern, accelerating the transition from petroleum-based to renewable materials. The development of biobased ‘active’ materials is emerging especially in food packaging to ensure safety and functionality. Such packaging systems containing bioactive ingredients provide effective antioxidant, antimicrobial, and UV-protective features extending food shelf life. In this context, plant-derived secondary metabolites have gained substantial interest as functional reinforcements. These compounds not only provide food protection but also contribute to environmental safety owing to their inherent biocompatibility, biodegradability, and compostability. However, their high production costs remain a major challenge to large-scale applications. Therefore, the valorization of agro-food byproducts/wastes has been increasingly promoted. This review aims to discuss the combined use of plant secondary metabolites and biopolymers for the development of innovative packaging solutions, highlighting recent advances and functional performance. Furthermore, key challenges limiting their real-world applicability are addressed. In particular, the intrinsic hydrophilicity of many biobased materials compromises their moisture barrier and mechanical stability. To overcome this limitation, the use of biobased hydrophobic ingredients including natural waxes has emerged as a sustainable and effective approach to enhance water resistance while preserving the bioactive functionality of the packaging materials.
The facet-dependent catalytic behavior of MgO in non-thermal plasma (NTP)-driven CO2 decomposition is systematically investigated by combining experimental measurements and density functional theory (DFT) calculations. Three MgO catalysts with dominant exposure of the (100), (110), and (111) facets are synthesized. CO2 temperature-programmed desorption (CO2-TPD) shows that CO2 adsorption capacity follows the order MgO(110) > MgO(111) > MgO(100), consistent with DFT-derived adsorption energies. DFT energy profiles reveal that although MgO(110) binds CO2 most strongly, it suffers from excessively strong CO adsorption (5.84 eV), inhibiting product desorption. In contrast, MgO(111) offers a favorable CO2 adsorption energy combined with a remarkably low CO desorption energy (0.71 eV), enabling rapid turnover. Electronic structure analyses demonstrate substantial charge transfer from MgO(111) to CO2 (up to 1.76 |e|) and pronounced orbital hybridization near the Fermi level, which are further enhanced under plasma conditions. Plasma-catalytic tests at 0.8 W show that MgO(111) achieves the highest CO2 conversion (60.7%) with excellent selectivity toward CO (95.3%) and O-2 (94.4%), outperforming MgO(110) and MgO(100). Increasing the input power from 0.8 to 2.5 W raises conversion to 78.1% but reduces energy efficiency due to increased gas heating or non-productive pathways. Overall, the (111)-enriched MgO is identified as an efficient and selective catalyst for NTP-based CO2 splitting, owing to its optimal balance of adsorption strength, facile CO desorption, strong charge transfer, and plasma-catalyst synergy. This work highlights the importance of facet engineering and power optimization for designing oxide-based plasma catalysts toward energy-efficient CO2 utilization.
The production of inexpensive, effective sorbents from natural materials for the purification of water bodies and/or soils is a pressing problem. Therefore, the purpose of this manuscript is to summarize current approaches to the use of brown coal (lignite) and its processing products (humic acids, HAs) as sorbents for the purification of aqueous and soil environments from heavy metal ions and other pollutants. Modification of lignite (chemical, biological, physicochemical) or the creation of lignite–mineral composites significantly increases its sorption capacity and stability: after modification, the sorption capacity can reach more than 85 mg of heavy metals per g of sorbent, which is only 3 times lower than that of specialized, expensive sorbents. Also, good results are achieved in the case of sorption of water-soluble organic drugs, dyes, etc. Humic acids obtained from brown coal have better selectivity and efficiency than the original lignite, and slightly worse than the modified one, in terms of removing cadmium, lead, copper, and other toxic elements; and also, can complex with organic xenobiotics. Current research trends indicate growing interest in multifunctional composite sorbents, environmentally friendly extraction technologies, and the development of materials with enhanced selectivity and regeneration ability. Future studies should focus on improving the understanding of sorption mechanisms, optimizing modification strategies, scaling up lignite-based technologies for practical environmental applications, and developing waste-free technologies to produce sorbents from lignite.
Plasma gasification is a sustainable and advanced technology for the safe and efficient treatment of municipal solid waste (MSW). In this process, a plasma torch serves as the primary heating source to convert MSW into syngas and inert vitrified slag. The produced syngas can be used for various downstream applications, including power generation. In this study, an updraft plasma gasifier is modeled using the Aspen Plus process simulator, with municipal solid waste from Lahore, Pakistan, used as the feedstock. Air is selected as a plasma-forming gas due to its low cost and widespread availability. The primary aim of this research is to analyze the effect of specific torch power and the air-to-feed mass flow ratio on syngas molar composition, syngas higher heating value (HHV), and cold gas efficiency (CGE), and to maximize gasifier performance. CGE of the gasifier is optimized using a surrogate-based model integrated with a genetic algorithm (GA). An artificial neural network (ANN) is employed as the surrogate model for the optimization of CGE. The novelty of this work lies in two key aspects: firstly, this is among the first studies to specifically model and simulate plasma gasification of Lahore’s MSW, capturing its unique waste composition characteristics; and secondly, the integration of process simulation with a data-driven optimization framework using an ANN surrogate model. A total of 1521 data points were generated from the Aspen Plus simulation to train the ANN model and perform optimization in MATLAB. The optimized CGE was found to be 90.6%. Validation of the ANN-GA optimization was carried out by implementing the optimized input parameters in the Aspen Plus gasifier model. The resulting CGE shows a percent relative error of only 0.11% compared to the MATLAB-predicted value, confirming the accuracy of the surrogate model. Furthermore, comparison with the base case simulation reveals that the optimized operating conditions lead to an 8.6% increase in cold gas efficiency, demonstrating the effectiveness of the proposed optimization approach.
Among the various CO2 capture technologies, chemical absorption is currently one of the most widely applied methods in industrial practice. In this study, density functional theory was employed to investigate the reaction mechanisms of CO2 absorption by typical alkanolamine solvents. Reaction pathways between CO2 and four representative alkanolamines—monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA), and methyldiethanolamine (MDEA)—were constructed and analyzed. By evaluating the activation energy barriers of different amines, the thermodynamic characteristics and reaction feasibility of the CO2 absorption process were systematically elucidated. The results show that the primary amine MEA exhibits the lowest activation energy barrier (32.02 kJ/mol), indicating the most favorable reaction kinetics, while the secondary amine DEA shows a slightly higher barrier of 47.35 kJ/mol. As tertiary amines, TEA and MDEA exhibit significantly higher activation energy barriers, indicating slower reaction kinetics; however, they generally possess higher CO2 loading capacities and less stable reaction products, which facilitate solvent regeneration. The activation energy barriers of MDEA and TEA were calculated to be 54.53 kJ/mol and 94.17 kJ/mol, respectively, indicating that MDEA reacts more readily with CO2 than TEA.
This study aims to develop a sustainable, low-cost, and high-performance supercapacitor electrode by valorizing waste date seeds (Phoenix dactylifera) into activated carbon and integrating it with a polymer-based hydrogel electrolyte. Waste date seeds were successfully converted into high-performance activated carbon through hydrothermal carbonization followed by sulfuric acid (H2SO4) chemical activation. The obtained date seed activated carbon (DSAC) was applied as an electrode material and incorporated into a hydrogel electrolyte for supercapacitor applications. Structural, thermal, and morphological analyses using SEM, FTIR, XRD, and TGA confirmed the formation of a predominantly microporous carbon framework enriched with oxygen-containing functional groups, indicating effective carbonization and activation. The porous structure and surface chemistry contributed to enhanced electrochemical behavior. The electrochemical behavior of the prepared DSAC electrode was investigated through cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD) analyses. The material exhibited a highest specific capacitance of 179 F g-1 at a scan rate of 5 mV s-1 and 159 F g-1 at a current density of 0.2 A g-1, demonstrating reliable and stable capacitive characteristics suitable for biomass-derived carbon-based supercapacitor applications. The device also exhibited excellent cycling stability over 5500 cycles, confirming long-term durability. The results demonstrate a promising and environmentally friendly strategy for advanced energy storage systems. Furthermore, the sustainability and cost-effectiveness of the proposed approach are attributed to the utilization of abundant date seed biomass and the simplicity of the hydrothermal-chemical activation process. The enhanced electrochemical performance is primarily associated with the hierarchical porous structure of the activated carbon and the improved ion transport facilitated by the hydrogel electrolyte, which collectively contribute to stable capacitive behavior and long-term cycling durability.
