Predictive stochastic analysis of massive filter-based electrochemical reaction networks-Reference-Cited by-同舟云学术

Predictive stochastic analysis of massive filter-based electrochemical reaction networks

Published:2023 Issue:1 Volume:2 Page:123-137
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Barter Daniel¹,Clark Spotte-Smith Evan Walter²³^ORCID,Redkar Nikita S.³⁴,Khanwale Aniruddh²³⁵,Dwaraknath Shyam⁶^ORCID,Persson Kristin A.²⁷^ORCID,Blau Samuel M.¹^ORCID

Affiliation:

1. Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

2. Department of Materials Science and Engineering, University of California, Berkeley, CA 94720, USA

3. Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

4. Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA

5. Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA

6. Luxembourg Institute of Science and Technology, Luxembourg

7. Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

Abstract

New methods for chemical reaction network construction and analysis enable the discovery of novel products and mechanisms in battery electrochemistry.

Funder

U.S. Department of Energy

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/DD/D2DD00117A

Reference74 articles.

1. The Exploration of Chemical Reaction Networks

2. Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities

3. Toward Predicting Full Catalytic Cycle Using Automatic Reaction Path Search Method: A Case Study on HCo(CO)3-Catalyzed Hydroformylation

4. AB INITIO MOLECULAR DYNAMICS WITH DENSITY FUNCTIONAL THEORY

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