Molecular modelling and machine learning for high-throughput screening of metal-organic frameworks for hydrogen storage-Reference-Cited by-同舟云学术

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Molecular modelling and machine learning for high-throughput screening of metal-organic frameworks for hydrogen storage

Published:2019-04-04 Issue:14-15 Volume:45 Page:1069-1081
ISSN:0892-7022
Container-title:Molecular Simulation
language:en
Short-container-title:Molecular Simulation

Author:

Bobbitt N. Scott¹,Snurr Randall Q.¹

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA

Funder

U.S. Department of Energy

Publisher

Informa UK Limited

Subject

Condensed Matter Physics,General Materials Science,General Chemical Engineering,Modeling and Simulation,Information Systems,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/08927022.2019.1597271

Reference101 articles.

1. Particulate photocatalysts for overall water splitting

2. Heterogeneous photocatalyst materials for water splitting

3. Photocatalytic Water Splitting: Recent Progress and Future Challenges

4. A review and recent developments in photocatalytic water-splitting using TiO2 for hydrogen production

5. Photocatalytic Water Splitting: Quantitative Approaches toward Photocatalyst by Design

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