Machine-learning-based prediction of hydrogen adsorption capacity at varied temperatures and pressures for MOFs adsorbents-Reference-Cited by-同舟云学术

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Machine-learning-based prediction of hydrogen adsorption capacity at varied temperatures and pressures for MOFs adsorbents

Published:2022-09 Issue: Volume:138 Page:104479
ISSN:1876-1070
Container-title:Journal of the Taiwan Institute of Chemical Engineers
language:en
Short-container-title:Journal of the Taiwan Institute of Chemical Engineers

Author:

Zhang Xuan,Zheng Qing-Rong,He Hong-Zhou

Funder

Natural Science Foundation of Fujian Province

Xiamen Municipal Bureau of Science and Technology

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Chemical Engineering,General Chemistry

Reference39 articles.

1. A review on current trends in potential use of metal-organic framework for hydrogen storage;Shet;Int J Hydrog Energy,2021

2. Control of interpenetration and structural transformations in the interpenetrated MOFs;Gupta;Coord Chem Rev,2021

3. Hydrogen storage in metal-organic frameworks;Hu;Adv Mater,2010

4. A collection of more than 900 gas mixture adsorption experiments in porous materials from literature meta-analysis;Cai;Ind Eng Chem Res,2021

5. Fragment database FDB-17;Visini;J Chem Inf Model,2017

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