The quantification and identification of components in archaeological micromorphology remain subjective and challenging, particularly for early-career researchers. To address this, we developed a deep learning tool for the automatic segmentation of t...
Biochar, a carbon-enriched material derived from pyrolyzed biomass, has evolved from an ancient farming practice into a mature carbon sequestration technology, emerging as a pivotal strategy for achieving carbon neutrality. Nevertheless, heterogeneou...
The precise prediction of adsorption process is significant in the optimization of pollutant removal systems. In this research, deep fuzzy neural network (DFNN) model was developed for the prediction of Zn(II) removal efficiency using alkaline activa...
This study focuses on the valorization of coconut shell biochar (CCB) as a sustainable reinforcement in polylactic acid (PLA) biocomposites, targeting enhanced mechanical performance. PLA/CCB composites were fabricated by varying injection molding pa...
Environmental geochemistry and health
Aug 30, 2025
The contribution analysis of influencing factors governing biochar-mediated heavy metal adsorption in aqueous systems holds significant implications for cost-effective water remediation. Current studies predominantly rely on single-model approaches t...
The release of hazardous volatile organic compounds (HVOCs) from biochar poses a potential threat to both human health and the environment. This study investigates how low pyrolysis temperature (HTT) and the chemical characteristics of lignocellulosi...
The transformation of ozone (O) into hydroxyl radical (OH) during the ozonation was evaluated in the presence of granular activated carbon (GAC) and biofilm-covered granular activated carbon (BGAC). While both GAC and BGAC accelerated O decomposition...
This study presents a comprehensive approach for optimizing biochar-augmented anaerobic digestion (AD) system through an interpretable stacking ensemble deep learning model. Extensive experimental data were compiled, incorporating feedstock character...
Recent advancements in machine learning (ML) technologies have significantly enhanced their applications in environmental sciences, particularly in the domains of soil and water remediation. This paper reviews recent studies that employ ML to optimiz...
Per- and polyfluoroalkyl substances (PFAS) are a group of fluorinated chemicals that cause potential risk in PFAS-impacted soil and water. The adsorption efficiency of 30 PFAS mixtures using different adsorbents in environmentally relevant concentrat...
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