Topological data analysis enhanced prediction of hydrogen storage in metal–organic frameworks (MOFs)-Reference-Cited by-同舟云学术

Topological data analysis enhanced prediction of hydrogen storage in metal–organic frameworks (MOFs)

Published:2024 Issue:2 Volume:5 Page:820-830
ISSN:2633-5409
Container-title:Materials Advances
language:en
Short-container-title:Mater. Adv.

Author:

Shekhar Shivanshu¹,Chowdhury Chandra²^ORCID

Affiliation:

1. Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, India

2. Institute of Catalysis Research and Technology (IKFT), Karlsruhe Institute of Technology (KIT), 76344 Eggenstein-Leopoldshafen, Germany

Abstract

Machine learning model has been developed for the prediction of hydrogen storage capacity of MOFs. To account the complex structure of MOFs, persistent homology is used.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/MA/D3MA00591G

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