Application of transfer learning to predict diffusion properties in metal–organic frameworks-Reference-Cited by-同舟云学术

Application of transfer learning to predict diffusion properties in metal–organic frameworks

Published:2022 Issue:9 Volume:7 Page:1056-1064
ISSN:2058-9689
Container-title:Molecular Systems Design & Engineering
language:en
Short-container-title:Mol. Syst. Des. Eng.

Author:

Lim Yunsung¹^ORCID,Kim Jihan¹

Affiliation:

1. Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291, Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Abstract

The knowledge leveraged from adsorption property can be used to induce enhancements in the prediction of diffusion property within metal–organic frameworks.

Funder

National Research Foundation of Korea

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/2022/ME/D2ME00082B

Reference53 articles.

1. Reticular synthesis and the design of new materials

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3. Metal–organic framework materials as catalysts

4. Electrically Conductive Metal–Organic Frameworks

5. Metal-organic frameworks and their derived materials for electrochemical energy storage and conversion: Promises and challenges

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