Thallium is a highly toxic element, which is widely found all over the world. Adsorption is one of the most common techniques for thallium removal. Traditional adsorption studies face several limitations, such as a limited ability to predict adsorpti...
Per- and polyfluoroalkyl substances (PFASs) contamination poses an environmental concern due to their ability to bioaccumulate in aquatic species and adversely impact human health. Experimental bioconcentration factor (log BCF) data of freshwater fis...
The recalcitrant nature of extracellular polymeric substances (EPS) in sewage sludge severely limits dewatering efficiency. While advanced oxidation processes (AOPs) disrupt EPS matrices, their optimization remains challenging. This study integrates ...
Journal of chemical information and modeling
Aug 11, 2025
Accurate prediction of chemical reaction yields is crucial for optimizing organic synthesis, potentially reducing time and resources spent on experimentation. With the rise of artificial intelligence (AI), there is growing interest in leveraging AI-b...
The partitioning of molecules between an aqueous and an organic medium is of major interest for pharmaceutical development and the chemical industry. It characterizes the impact of substances to the environment and to humans, e.g., their accumulation...
Chemical reaction neural networks (CRNN) and density functional theory (DFT) are gaining attention in biomass pyrolysis mechanism research. Reaction pathways are often speculated based on a single method, influenced by expert knowledge. To address th...
Journal of chemical information and modeling
May 12, 2025
In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equation systems is derived from an empirical model of...
Journal of environmental sciences (China)
May 1, 2025
Based on observed meteorological elements, photolysis rates (J-values) and pollutant concentrations, an automated J-values predicting system by machine learning (J-ML) has been developed to reproduce and predict the J-values of OD, NO, HONO, HO, HCHO...
Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Artificial intelligence (AI) offers new possibilities for hit and lead finding in medicinal chemistry. Several instances of AI have been used for prospective de novo drug design. Among these, chemical language models have been shown to perform well i...
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