[HTML][HTML] A review on machine learning algorithms for the ionic liquid chemical space

S Koutsoukos, F Philippi, F Malaret, T Welton - Chemical science, 2021 - pubs.rsc.org
There are thousands of papers published every year investigating the properties and
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …

Imidazolium based ionic liquid-phase green catalytic reactions

P Migowski, P Lozano, J Dupont - Green Chemistry, 2023 - pubs.rsc.org
1, 3-Dialkyl imidazolium salts are amongst the most versatile family of ionic liquids (ILs) for
catalytic processes, acting as a solvents, supports or modifiers given their anisotropic-like …

Machine learning approach to map the thermal conductivity of over 2,000 neoteric solvents for green energy storage applications

T Lemaoui, AS Darwish, G Almustafa, A Boublia… - Energy Storage …, 2023 - Elsevier
Interest in green neoteric solvents, such as ionic liquids (ILs) and deep eutectic solvents
(DESs), has increased dramatically in recent years due to their highly tunable properties …

Accurate prediction of carbon dioxide capture by deep eutectic solvents using quantum chemistry and a neural network

M Mohan, O Demerdash, BA Simmons, JC Smith… - Green …, 2023 - pubs.rsc.org
Carbon dioxide (CO2) emissions from fossil fuel combustion are a significant source of
greenhouse gas, contributing in a major way to global warming and climate change. Carbon …

Thermo‐ and Photocatalytic Activation of CO2 in Ionic Liquids Nanodomains

MI Qadir, J Dupont - Angewandte Chemie International Edition, 2023 - Wiley Online Library
Ionic liquids (ILs) are considered to be potential material devices for CO2 capturing and
conversion to energy‐adducts. They form a cage (confined‐space) around the catalyst …

[HTML][HTML] Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents

I Salahshoori, A Baghban, A Yazdanbakhsh - RSC advances, 2023 - pubs.rsc.org
In recent years, deep eutectic solvents (DESs) have garnered considerable attention for their
potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO2) …

[HTML][HTML] Sigma profiles in deep learning: towards a universal molecular descriptor

DO Abranches, Y Zhang, EJ Maginn… - Chemical …, 2022 - pubs.rsc.org
This work showcases the remarkable ability of sigma profiles to function as molecular
descriptors in deep learning. The sigma profiles of 1432 compounds are used to train …

Multicriteria design of novel natural hydrophobic deep eutectic solvents for the extraction of perfluoroalkyl acids using COSMO-RS

S Eid, AS Darwish, T Lemaoui, F Banat… - Journal of Molecular …, 2023 - Elsevier
In this study, a molecular modeling approach was used to identify the most effective natural
hydrophobic deep eutectic solvents (HDESs) for extracting the emerging pollutants …

Predictive modeling of physicochemical properties and ionicity of ionic liquids for virtual screening of novel electrolytes

DM Makarov, YA Fadeeva, LE Shmukler - Journal of Molecular Liquids, 2023 - Elsevier
In this paper, we present three regression models developed for predicting electrical
conductivity, viscosity, and density of ionic liquids. Combining these machine learning …

Predicting viscosity of ionic liquids-water mixtures by bridging UNIFAC modeling with interpretable machine learning

M Huang, J Deng, G Jia - Journal of Molecular Liquids, 2023 - Elsevier
Predicting the viscosity of ionic liquids (ILs)-water mixtures precisely is considerable for
diversity applications in chemical industries. In this work, interpretable machine learning …