Fermentation residues are compositionally heterogeneous by-products of biohydrogen, ethanol, anaerobic digestion, antibiotic, pharmaceutical, food, beverage, and other biorefinery processes. Their conversion to fermentation-residue-derived biochar offers opportunities for carbon retention, contaminant management, nutrient recovery, and advanced carbon-material production. This review critically evaluates fermentation-residue-derived biochar through a residue-to-function framework linking feedstock origin, fermentation history, moisture and ash characteristics, conversion-route selection, carbonization mechanisms, post-treatment, material properties, application performance, and environmental safety. A structured literature-search strategy, bibliometric analysis, and evidence hierarchy were used to distinguish direct fermentation-residue-derived biochar studies from mechanistically relevant conventional-biochar literature. The evidence shows that dry or mechanically dewatered residues are most compatible with pyrolysis, whereas high-moisture sludges and liquid effluents may favor hydrothermal or recovery-based routes. Material functionality is governed by pore hierarchy, mineral phases, heteroatom chemistry, carbonization degree, surface charge, conductivity, contaminant fate, regeneration, and leaching stability. Direct evidence is strongest for aqueous remediation, heavy-metal adsorption, phosphate recovery, selected soil applications, and supercapacitor carbons derived from antibiotic or anaerobic-digestion residues. By contrast, gas purification, fuel-cell electrodes, hydrogen-related catalysis, construction materials, and polymer composites remain less mature because much of the available evidence is comparative. Future translation requires residue-specific quality control, realistic application testing, contaminant thresholds, process integration, techno-economic analysis, life-cycle assessment, and application-specific certification. Fermentation-residue-derived biochar should therefore be regarded as a family of engineered residue-derived carbons whose value depends on matching feedstock chemistry, conversion pathway, product properties, and end-use requirements within integrated circular biorefineries.
Underground hydrogen storage in unconventional reservoirs has emerged as a promising solution for large-scale, low-carbon energy buffering, yet its feasibility remains governed by complex rock–fluid interactions that are not fully understood. This review critically examines the wettability, interfacial properties, and pore-scale transport mechanisms controlling hydrogen behaviour in shale, coal, and other low-permeability formations. Key influencing factors such as pressure, temperature, salinity, mineralogy, total organic carbon, organic acids, cushion-gas composition, and brine chemistry are systematically analyzed to clarify their roles in modifying contact angle, interfacial tension, and capillary sealing.Results from multi-phase experiments show that hydrogen exposure can drive wettability transitions that alter injectivity, storage security, and withdrawal efficiency, while cushion gases such as methane and carbon dioxide substantially modify contact angle and interfacial tension trends relative to pure hydrogen systems. Adsorption-diffusion dynamics further complicate storage behavior: hydrogen exhibits weak adsorption but rapid diffusivity, particularly within inorganic nanopores, increasing its mobility and potential leakage risk in poorly sealed formations. Mineralogical heterogeneity, kerogen maturity, and the presence of organic acids significantly affect both trapping and wettability stability. A bibliometric analysis highlights a young but rapidly expanding research domain, with major contributions concentrated in key hydrogen-focused countries.Overall, the review identifies critical knowledge gaps - including the need for standardized high-pressure, high-temperature wettability protocols, integrated adsorption-diffusion-wettability models, and mechanistic simulations-underscoring the importance of advancing experimental and theoretical frameworks to ensure safe and efficient underground hydrogen storage deployment.
The growing global demand for unconventional energy sources has increased the need for strategic site selection for power generation plants. So, the need to find the best location for wind power plant installation becomes more and more important. Selecting best locations for wind power plant installation is critical to improving efficiency and economic viability. In this study, the authors built a detailed evaluation system with using six main criteria and twenty-five sub criteria on fifteen potential sites across India. There are ten experts involved in the decision process. To address uncertainty and fuzziness in the site selection process an Integrated Fuzzy Analytic Hierarchy Process (AHP)- Fuzzy Stepwise Weight Evaluation Ratio Analysis(F-SWARA) with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is applied for expert weight determination and ranking of potential sites. This analysis identifies Kutch district as the highest-ranked among the fifteen preselected sites, while Leh is ranked the least favorable sites. A sensitivity analysis was conducted to confirms the robustness of the proposed approach by changing criteria weights with three different scenarios even rank stability maintained while variations in criteria and sub criteria. The study presents a robust fuzzy hybrid MCDM framework for renewable energy infrastructure planning, providing decision makers with an effective approach to set up wind power plant site selection across large and geographically diverse regions. Moreover, the proposed framework can be use in different geographical locations and thereby serving as a scalable decision support system for sustainable energy infrastructure development.
Biomass-derived porous carbons are promising adsorbents for environmental remediation, yet the relationships between pyrolysis conditions, pore architecture and adsorption behaviour remain incompletely resolved. In this work, nitrogen adsorption–desorption, BET surface area analysis, SEM imaging and isotherm modelling were employed to elucidate the influence of pyrolysis temperature (500- 700 °C) on the morphological and textural properties of biomass-derived carbons. The isotherms evolved from Type II for the raw biomass to Type IV and Type I for the carbonised samples, evidencing a transition from macro-/non-porous structures to mesoporous and predominantly microporous frameworks. Among the tested models, Dubinin-Astakhov and Dubinin-Radushkevich provided the most reliable fits, with a pronounced maximum in micropore-filling capacity at 600 °C coinciding with the highest BET-derived capacity and Type I behaviour. Elemental composition and SEM observations confirmed temperature-dependent restructuring of the carbon matrix, whereas the evolution from Type II to Type IV and Type I nitrogen adsorption isotherms reflected the corresponding transition from macro-/non-porous structures to mesoporous and predominantly microporous frameworks, as determined from gas adsorption analysis. Collectively, these results establish a direct link between pyrolysis temperature, N2 adsorption-desorption behaviour, and micropore development in sugarcane-bagasse-derived carbons within the tested non-activated system. The main contribution of this work is the integrated comparison of pyrolysis temperature, IUPAC N2 isotherm classification, and nonlinear gas-phase isotherm model fitting (Langmuir, Freundlich, Toth, D-R, and D-A) for sugarcane-bagasse-derived carbon materials. The findings identify 600 °C as the most favourable pyrolysis temperature in this series and provide a quantitative basis for subsequent, application-specific adsorption studies, rather than claiming demonstrated performance in pollutant removal or other end uses.
Global collaboration is essential to develop clean energy solutions in the fight against the climate crisis. Clean energy is derived from naturally replenished resources, such as solar, wind, geothermal, and tidal power. Although solar and wind energy are inherently variable and weather-dependent, their global share is growing rapidly, making a reliable and stable energy supply from these sources increasingly important. As wind power plants become heavily integrated into modern power systems, their low dispatch ability necessitates the use of reliable and accurate forecasting models. Precise forecasting is fundamental not only for grid stability but also for evaluating the operational efficiency of wind turbines. This study employs a Long Short-Term Memory (LSTM) model to forecast wind energy in Surakarta, Indonesia, a region with significant wind energy potential. The LSTM architecture is utilized to analyze temporal data patterns and predict wind speed as well as turbine power output. The proposed model is configured with multiple stacked LSTM layers consisting of 100, 100, and 50 units, trained for 500 epochs. The resulting Mean Squared Error (MSE) of 0.005 demonstrates the model's high predictive accuracy. These results indicate that the proposed LSTM model is effective in capturing temporal dependencies and can be reliably used for wind power forecasting based on meteorological parameters.
