Investigation on pore structure regulation of activated carbon derived from sargassum and its application in supercapacitor

Biomass-Derived Activated Porous Carbon from Foxtail Millet Husk to Utilizing High-Performance Symmetric Supercapacitor Applications

This study successfully demonstrates the synthesis of foxtail millet carbon-activated (FMCA) materials using a two-step carbonization process from foxtail millet husk (FMH). The pre-carbonized biomass-derived millet husk was chemically activated with KOH at 500 °C and subsequently carbonized in an inert argon atmosphere at 800 °C in a tubular furnace. XRD analysis revealed a diffraction peak at 2θ = 23.67°, corresponding to the (002) plane, indicating the presence of graphitic structures. The Raman analysis of FMCA materials showed an intensity ratio (IG/ID) of 1.13, signifying enhanced graphitic ordering and structural stability. The as-prepared FMC and FMCA electrode materials demonstrate efficient charge storage electrochemical symmetric devices. Electrochemical analysis revealed the charge-discharge curves and a specific capacitance of Csp (FMC//FMC) 55.47 F/g and (FMCA//FMCA) 82.94 F/g at 0.5 A/g. Additionally, the FMCA//FMCA symmetric device exhibits superior performance with a higher capacity retention of 94.89% over 5000 cycles. The results confirm the suitability of FMCA for energy storage applications, particularly in electrochemical double-layer capacitors (EDLCs), making it a promising material for next-generation supercapacitors.

Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials

The increasing demand for sustainable waste management has driven innovation in the production of activated carbon (AC) from waste. AC's textural properties, including its surface area (SA), total pore volume (TPV), and micropore volume (MPV), are critical for applications such as gas purification and wastewater treatment. However, the traditional assessment methods are expensive and complex. This study employed machine learning (ML) models to predict AC's properties and optimize its production process. Random Forest (RF), Decision Tree (DT), Gradient Boosting Regressor (GBR), support vector machines (SVM), and Artificial Neural Networks (ANN) were applied along with key input parameters, including raw material type, particle size, and activation conditions. A genetic algorithm (GA) integrated with the GBR model optimizes the synthesis process. The ML models, particularly RF and GBR, accurately predicted SA with R2 values exceeding 0.96. In contrast, the linear regression models were inadequate, with R2 values below 0.6, emphasizing the non-linear relationship between the inputs and outputs. Sensitivity analysis showed that the activation temperature, ratio of the activating agent to carbon, and particle size significantly affected the AC properties. Optimal properties were achieved under activation temperatures between 800 and 900 °C and activating-agent to the carbon ratio 3.8. This approach provides a scalable solution for enhancing AC production sustainability, while addressing critical waste management challenges.

Optimization of Green Extraction Techniques for Polyphenolics in Pinus brutia Bark Extract and Steam Gasification of the Remaining Fraction to Obtain Hydrogen-Rich Syngas and Activated Carbon

Utilization of renewable resources has become imperative, and considerable efforts have been devoted to tackling diverse global sustainability challenges, which contribute to the circular economy. The focus of this work was to optimize the extraction of polyphenolic compounds in Pinus brutia bark using microwave-assisted (MAE) and ultrasonically assisted (UAE) extractions and evaluate the biological efficacies of the extracts. Additionally, the residue of the extracted pine bark was subjected to steam gasification to produce hydrogen-rich syngas and activated carbon. The optimum process parameters for MAE were determined as 70 °C, 10 min, and 900 W, and 987.32 mg gallic acid equivalent (GAE), 23.7 mg quercetin/g extract, and 86.2% antioxidant activity were obtained. The optimum process parameters for UAE were determined as 70 °C, 20 min, and 50% power, and 811.84 mg gallic acid equivalent (GAE), 30.1 mg quercetin/g extract, and 90.8% antioxidant efficiency were obtained. The extracts obtained under optimized conditions were assessed for the bioactive phenolic compounds taxifolin, (-)-catechin, (-)-epicatechin, and (-)-epicatechin gallate by ultra performance liquid chromatography (UPLC). Especially in MAE (ethanol), taxifolin content was notable (34.0 mg/g extract), followed by UAE (ethanol) (23.5 mg/g extract). Compared to MAE (ethanol) and UAE (ethanol) with regards to catechin content, 1.05 mg/g extract and 0.81 mg/g extract were obtained, respectively. Catalytic and noncatalytic steam gasification of pine bark residue yielded 57.3 and 60.8 mol % H2, respectively. In addition, excellent tar reduction was achieved through utilizing a 10% boron-modified CaO alkali catalyst, and the obtained activated carbon exhibited 1358.32 m2/g Brunauer-Emmett-Teller (BET) surface area and 1.05 cm3/g total pore volume, which has potential use as an adsorbent for removing heavy metals and electrode material for supercapacitor application.

Multifunctional Strategies of Advanced Electrocatalysts for Efficient Urea Synthesis

The electrochemical reduction of nitrogenous species (such as N2, NO, NO2 -, and NO3 -) for urea synthesis under ambient conditions has been extensively studied due to their potential to realize carbon/nitrogen neutrality and mitigate environmental pollution, as well as provide a means to store renewable electricity generated from intermittent sources such as wind and solar power. However, the sluggish reaction kinetics and the scarcity of active sites on electrocatalysts have significantly hindered the advancement of their practical applications. Multifunctional engineering of electrocatalysts has been rationally designed and investigated to adjust their electronic structures, increase the density of active sites, and optimize the binding energies to enhance electrocatalytic performance. Here, surface engineering, defect engineering, doping engineering, and heterostructure engineering strategies for efficient nitrogen electro-reduction are comprehensively summarized. The role of each element in engineered electrocatalysts is elucidated at the atomic level, revealing the intrinsic active site, and understanding the relationship between atomic structure and catalytic performance. This review highlights the state-of-the-art progress of electrocatalytic reactions of waste nitrogenous species into urea. Moreover, this review outlines the challenges and opportunities for urea synthesis and aims to facilitate further research into the development of advanced electrocatalysts for a sustainable future.

Depicted simulation model for removal of second-generation antipsychotic drugs adsorbed on Zn-MOF: adsorption locator assessment

CONTEXT

Electronic durable behavior on the material surface was accompanied by a class of antipsychotic drugs (APD) to describe the surface modification in the designed adsorption model. Hierarchically Zn-MOF system was utilized for estimating its capacity for drug molecule removal. Geometrically optimized strategy on the studied systems was performed using DFT/GGA/PBE. FMOs analysis was depicted based on the same level of calculations, and molecular electrostatic potential surface (MEP) was generated for unadsorbed and adsorbed systems to illustrate the variation in the surface-active sites. By interpreting the electronic density of states (DOS), the atomic orbital can be identified as a major or minor electronic distribution by PDOS graph. Adsorption locating behavior was considered to detect the significant surface interaction mode between APD and Zn-MOF surface based on lower adsorption energy. The stability of the adsorbed model was best described through dynamic simulation analysis with time through elevated temperatures. The non-covalent interactions were described using RDG/NCI analysis to show the major favorable surface interaction predicting the highly stable adsorption system.

METHODS

The most accurate geometrical computations were performed using the materials studio software followed by surface cleavage and vacuum slab generation. The first principle of DFT was used to apply CASTEP module with GGA/PBE method for band structure and DOS calculations. Three systems of antipsychotic drugs were computationally studied using CASTEP simulation package and adsorbed on an optimized Zn-MOF surface. Adsorption locator module predicted the preferred adsorption mechanistic models, in which the first model was arranged to be more stable, to confirm the occurrence of some interactions in the adsorption mechanism.

Effect of synthesis conditions on the porous texture of activated carbons obtained from Tara Rubber by FeCl3 activation

This paper presents the results of an unique analysis of the influence of the mass ratio of activator FeCl3 to precursor and the temperature of the activation process on the formation of the porous structure of activated carbons obtained from Tara Rubber by FeCl3 activation. The study used the new numerical clustering based adsorption analysis method and the quenched solid density functional theory, taking into account, among other things, the heterogeneity of the analysed surface which is a new approach rarely used in the analysis of the porous structure of adsorbents. On the basis of the calculation results, it was concluded that the activated carbon with the most developed porous texture was obtained at a mass ratio (FeCl3:Tara Rubber) of 2, at an activation process temperature of 800 °C. This activated carbon is also characterised by the lowest degree of surface heterogeneity and at the same time, however, the widest range of micropores compared to activated carbons obtained at other mass ratios. The analyses carried out further demonstrated the valuable and complementary information obtained from the structure analysis methods and their high utility in practical applications, especially in the development of new industrial technologies for the production of adsorbents and the selection of optimal conditions for their production.

Miscanthus-Derived Energy Storage System Material Production

Carbon derived from various biomass sources has been evaluated as support material for thermal energy storage systems. However, process optimization of Miscanthus-derived carbon to be used for encapsulating phase change materials has not been reported to date. In this study, process optimization to evaluate the effects of selected operation parameters of pyrolysis time, temperature, and biomass:catalyst mass ratio on the surface area and pore volume of produced carbon is conducted using response surface methodology. In the process, ZnCl₂ is used as a catalyst to promote high pore volume and area formation. Two sets of optimum conditions with different pyrolysis operation parameters in order to produce carbons with the highest pore area and volume are determined as 614 °C, 53 min, and 1:2 biomass to catalyst ratio and 722 °C, 77 min, and 1:4 biomass to catalyst ratio with 1415.4 m²/g and 0.748 cm³/g and 1499.8 m²/g and 1.443 cm³/g total pore volume, respectively. Carbon material produced at 614 °C exhibits mostly micro- and mesosized pores, while carbon obtained at 722 °C comprises mostly of meso- and macroporous structures. Findings of this study demonstrate the significance of process optimization for designing porous carbon material to be used in thermal and electrochemical energy storage systems.

Biotemplating of Al2O3-Doped, CaO-Based Material from Bamboo Fiber for Efficient Solar Energy Storage

The high-temperature sintering of CaO-based materials leads to the serious decay of energy storage performance during the calcination/carbonation cycle. To overcome the loss in porosity problem, an efficient CaO-based material for thermal energy storage was synthesized using bamboo fiber as the biotemplate. The synthesis parameters (bamboo fiber addition, pyrolysis, Al2O3 loading) and the energy storage reaction characteristics of CaO-based energy storage material were optimized on the basis of cyclic calcination/carbonation experiments. The results show that the sacrificed biotemplate enhances the porosity of the synthetic material, denoting improved energy storage density. The cumulative energy storage density of the templated material over 50 cycles is 24,131.44 kJ/kg higher than that of limestone. The carbonation conversion and energy storage density of the templated CaO-based material doped with 5 wt.% Al2O3 and 0.5 g bamboo fiber reach 0.75 mol/mol and 2368.82 kJ/kg after 10 cycles, respectively, which is 2.7 times as high as that of original limestone. The maximum apparent carbonation rate of the templated CaO-based materials in the 1st cycle corresponds to a 240% increment compared to limestone. The maximum calcination rate of the synthetic CaO-based material in the 12th cycle remains 93%, as compared with the initial cycle. The microstructure analysis reveals that the hierarchically-stable structure during the cycle is beneficial for a more effective exposure of surface reactive sites for CaO and inward/outward diffusion for CO2 molecules through CaO. The method using the sacrificed biological template provides an advanced approach to fabricate porous materials, and the composite CaO-based material provides high-return solar energy storage for a potential application in industrial scale.

Physicochemical Modeling of Electrochemical Impedance in Solid-State Supercapacitors

Solid-state supercapacitors (SSCs) consist of porous carbon electrodes and gel-polymer electrolytes and are used in novel energy storage applications. The current study aims to simulate the impedance of SSCs using a clearly defined equivalent circuit (EC) model with the ultimate goal of improving their performance. To this end, a conventional mathematical and a physicochemical model were adapted. The impedance was measured by electrochemical impedance spectroscopy (EIS). An EC consisting of electrical elements was introduced for each modeling approach. The mathematical model was purely based on a best-fit method and utilized an EC with intuitive elements. In contrast, the physicochemical model was motivated by advanced theories and allowed meaningful associations with properties at the electrode, the electrolyte, and their interface. The physicochemical model showed a higher approximation ability (relative error of 3.7%) due to the interface impedance integration in a more complex circuit design. However, this model required more modeling and optimization effort. Moreover, the fitted parameters differed from the analytically calculated ones due to uncertainties in the SSC's microscale configuration, which need further investigations. Nevertheless, the results show that the proposed physicochemical model is promising in simulating EIS data of SSCs with the additional advantage of utilizing well-reasoned property-based EC elements.

Preparation of porous biochar and its application in supercapacitors

In this study, economical porous biochar was prepared from an apricot shell and used as an electrode material for a supercapacitor, showing excellent capacitance, cycling stability and rate performance.