Deductive Machine Learning Challenges and Opportunities in Chemical Applications

T Jin, BM Savoie - Annual Review of Chemical and Biomolecular …, 2023 - annualreviews.org
Contemporary machine learning algorithms have largely succeeded in automating the
development of mathematical models from data. Although this is a striking accomplishment …

Machine Learning-Assisted Exploration of a Two-Dimensional Nanoslit for Blast Furnace Gas Separation

F Huan, C Qiu, Y Sun, G Luo, S Deng… - Industrial & Engineering …, 2023 - ACS Publications
Diffusion-induced gas separation is crucial for industrial applications, while the
determination of specific conditions is still challenging. Here, molecular dynamics simulation …

[HTML][HTML] Evaluating ionic liquid toxicity with machine learning and structural similarity methods

R Shan, R Zhang, Y Gao, W Wang, W Zhu, L Xin… - Green Chemical …, 2024 - Elsevier
Ionic liquids (ILs) have garnered significant interest owing to their distinct physicochemical
traits. Nonetheless, their extensive application is curtailed by ecotoxicity concerns. This …

Modeling self‐diffusion coefficients of ionic liquids using ePC‐SAFT and FVT combined with Einstein relation

Z Zuo, X Lu, X Ji - AIChE Journal, 2024 - Wiley Online Library
The electrolyte perturbed‐chain statistical associating fluids theory (ePC‐SAFT) coupled
with free volume theory (FVT) was combined with Einstein relation, that is, ePC‐SAFT‐FVT …

[HTML][HTML] Screening HFC/HFO and ionic liquid for absorption refrigeration at the atomic scale by the prediction model of machine learning

J Chu, M He, GM Kontogeorgis, X Liu… - Green Chemical …, 2024 - Elsevier
Absorption refrigeration is a highly effective method for utilizing renewable energy, as it can
be driven by low-grade heat sources such as industrial waste heat, solar energy, and …