Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors-Reference-Cited by-同舟云学术

Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors

Published:2023 Issue:10 Volume:8 Page:1257-1274
ISSN:2058-9689
Container-title:Molecular Systems Design & Engineering
language:en
Short-container-title:Mol. Syst. Des. Eng.

Author:

Bobbitt N. Scott¹^ORCID,Allers Joshua P.¹,Harvey Jacob A.¹^ORCID,Poe Derrick²,Wemhoner Jordyn D.¹^ORCID,Keth Jane¹,Greathouse Jeffery A.¹^ORCID

Affiliation:

1. Sandia National Laboratories, Albuquerque, NM, 87185, USA

2. Argonne National Laboratory, Lemont, IL 60439, USA

Abstract

Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage.

Funder

U.S. Department of Energy

Laboratory Directed Research and Development

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,Industrial and Manufacturing Engineering,Process Chemistry and Technology,Energy Engineering and Power Technology,Biomedical Engineering,Chemical Engineering (miscellaneous),Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/ME/D3ME00033H

Reference101 articles.

1. Applications of ionic liquids in the chemical industry

2. D.Rooney , J.Jacquemin and R. L.Gardas , Thermophysical Properties of Ionic Liquids, in Ionic Liquids , ed. B. Kirchner , Springer-Verlag Berlin , Berlin , 2009 , vol. 290 , pp. 185–212

3. Ionic liquids synthesis and applications: An overview

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