Machine Learning Approach for the Prediction of Eutectic Temperatures for Metal-Free Deep Eutectic Solvents-Reference-Cited by-同舟云学术

Machine Learning Approach for the Prediction of Eutectic Temperatures for Metal-Free Deep Eutectic Solvents

Published:2023-10-09 Issue:42 Volume:11 Page:15492-15502
ISSN:2168-0485
Container-title:ACS Sustainable Chemistry & Engineering
language:en
Short-container-title:ACS Sustainable Chem. Eng.

Author:

Lavrinenko Anastasia K.¹^ORCID,Chernyshov Ivan Yu.²,Pidko Evgeny A.²^ORCID

Affiliation:

1. International Institute “Solution Chemistry of Advanced Materials and Technologies”, ITMO University, Saint-Petersburg 191002, Russian Federation

2. Inorganic Systems Engineering Group, Department of Chemical Engineering, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands

Publisher

American Chemical Society (ACS)

Subject

Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.3c05207

Reference79 articles.

1. Should deep eutectic solvents be treated as a mixture of two components or as a pseudo-component?

2. A centrifuge method to determine the solid–liquid phase behavior of eutectic mixtures

3. Basics and properties of deep eutectic solvents: a review

4. A mini review on synthesis, properties and applications of deep eutectic solvents

5. Simulation of deep eutectic solvents: Progress to promises

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