Journal of environmental sciences (China)
39481934
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...
The pharmaceutical industry is increasingly drawn to the research of innovative drug delivery systems through the use of supercritical CO (scCO)-based techniques. Measuring the solubility of drugs in scCO at varying conditions is a crucial parameter ...
Generative deep learning models enable data-driven de novo design of molecules with tailored features. Chemical language models (CLM) trained on string representations of molecules such as SMILES have been successfully employed to design new chemical...
Due to its sea urchin-like structure, Schwertmannite is commonly applied for heavy metals (HMs) pollutant adsorption. The adsorption influence parameters of Schwertmannite are numerous, the traditional experimental enumeration is powerless. In recent...
Journal of chemical information and modeling
39689297
A challenge to materials discovery is the identification of the physical features that are most correlated to a given target material property without redundancy. Such variables necessarily comprise the optimal search domain in subsequent material de...
Cadmium (Cd) is a bio-essential trace metal in the ocean that can be toxic at high concentrations, significantly impacting the marine environment and phytoplankton growth. Its distribution pattern is closely proportional to that of phosphate (PO), al...
Caffeine, considered an emerging contaminant, serves as an indicator of anthropic influence on water resources. This research employs various modeling techniques, including Artificial Neural Networks (ANN), Random Forest (RF), and more, along with hy...
Generally, herbicides used in Brazil follow manufacturer's recommendations, which often do not consider soil attributes. Statistical models that include the physicochemical properties of the soil involved in herbicide retention processes could enable...
Neural networks : the official journal of the International Neural Network Society
39756120
Modelling atmospheric chemistry is complex and computationally intense. Given the recent success of Deep neural networks in digital signal processing, we propose a Neural Network Emulator for fast chemical concentration modelling. We consider atmosph...
The nano-self-assembly of natural organic matter (NOM) profoundly influences the occurrence and fate of NOM and pollutants in large-scale complex environments. Machine learning (ML) offers a promising and robust tool for interpreting and predicting t...