Artificial intelligence in chemistry: current trends and future directions
ZJ Baum, X Yu, PY Ayala, Y Zhao… - Journal of Chemical …, 2021 - ACS Publications
The application of artificial intelligence (AI) to chemistry has grown tremendously in recent
years. In this Review, we studied the growth and distribution of AI-related chemistry …
years. In this Review, we studied the growth and distribution of AI-related chemistry …
Deep learning based regression and multiclass models for acute oral toxicity prediction with automatic chemical feature extraction
Median lethal death, LD50, is a general indicator of compound acute oral toxicity (AOT).
Various in silico methods were developed for AOT prediction to reduce costs and time. In …
Various in silico methods were developed for AOT prediction to reduce costs and time. In …
Chemometrics for selection, prediction, and classification of sustainable solutions for green chemistry—A review
M Bystrzanowska, M Tobiszewski - Symmetry, 2020 - mdpi.com
In this review, we present the applications of chemometric techniques for green and
sustainable chemistry. The techniques, such as cluster analysis, principal component …
sustainable chemistry. The techniques, such as cluster analysis, principal component …
QSPR estimation models of normal boiling point and relative liquid density of pure hydrocarbons using MLR and MLP-ANN methods
This work aimed to predict the normal boiling point temperature (Tb) and relative liquid
density (d20) of petroleum fractions and pure hydrocarbons, through a multi-layer …
density (d20) of petroleum fractions and pure hydrocarbons, through a multi-layer …
New QSPR models for predicting critical temperature of binary organic mixtures using linear and nonlinear methods
Y Pan, F Yang, H Zhang, Y Yan, X Ping, M Yu… - Fluid Phase Equilibria, 2023 - Elsevier
The critical temperature is an important parameter in the design and selection of binary
organic mixtures. Rapid and accurate prediction has been a focus of research. Strong …
organic mixtures. Rapid and accurate prediction has been a focus of research. Strong …
QSAR modeling in ecotoxicological risk assessment: application to the prediction of acute contact toxicity of pesticides on bees (Apis mellifera L.)
Despite their indisputable importance around the world, the pesticides can be dangerous for
a range of species of ecological importance such as honeybees (Apis mellifera L.). Thus, a …
a range of species of ecological importance such as honeybees (Apis mellifera L.). Thus, a …
Electrochemical degradation of ciprofloxacin from water: Modeling and prediction using ANN and LSSVM
P Abbasi, EB Moghadam - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
Ciprofloxacin is a widely used antibiotic that is also a persistent contamination that causes
major health and environmental risks. This study investigated the electrochemical removal of …
major health and environmental risks. This study investigated the electrochemical removal of …
[PDF][PDF] Modeling and optimization of small-scale NF/RO seawater desalination using the artificial neural network (ANN)
The performance of seawater hybrid NF/RO desalination plant including permeate
conductivity; permeate flow rate and permeate recovery. Under different feed parameters …
conductivity; permeate flow rate and permeate recovery. Under different feed parameters …
Prediction of the antibacterial activity of garlic extract on E. coli, S. aureus and B. subtilis by determining the diameter of the inhibition zones using artificial neural …
D Atsamnia, M Hamadache, S Hanini… - LWT-Food Science and …, 2017 - Elsevier
The aim of this study was to devise a model that predicts the inhibition zone diameter using
artificial neural networks. The concentration, temperature and the exposure time of our …
artificial neural networks. The concentration, temperature and the exposure time of our …
QSPR Modelling of the Solubility of Drug and Drug‐like Compounds in Supercritical Carbon Dioxide
Quantitative structure–property relationship (QSPR) modeling was investigated to predict
drug and drug‐like compounds solubility in supercritical carbon dioxide. A dataset of 148 …
drug and drug‐like compounds solubility in supercritical carbon dioxide. A dataset of 148 …