Thermochemical Data Fusion Using Graph Representation Learning-Reference-Cited by-同舟云学术

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Thermochemical Data Fusion Using Graph Representation Learning

Published:2020-09-23 Issue:10 Volume:60 Page:4673-4683
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Bhattacharjee Himaghna¹²^ORCID,Vlachos Dionisios G.¹²^ORCID

Affiliation:

1. Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States

2. Catalysis Center for Energy Innovation and RAPID Manufacturing Institute, 221 Academy Street, Newark, Delaware 19716, United States

Funder

U.S. Department of Energy

State of Delaware

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.0c00699

Reference61 articles.

1. Self-Consistent Equations Including Exchange and Correlation Effects

2. Computational predictions of energy materials using density functional theory

3. A benchmark database for adsorption bond energies to transition metal surfaces and comparison to selected DFT functionals

4. Density functional theory in surface chemistry and catalysis

5. A review of multiscale modeling of metal-catalyzed reactions: Mechanism development for complexity and emergent behavior

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2. AIMSim: An accessible cheminformatics platform for similarity operations on chemicals datasets;Computer Physics Communications;2023-02

3. Machine Learning for Combustion Chemistry;Lecture Notes in Energy;2023

4. Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization;Chemical Reviews;2022-06-27

5. Accurate Thermochemistry of Complex Lignin Structures via Density Functional Theory, Group Additivity, and Machine Learning;ACS Sustainable Chemistry & Engineering;2021-02-15

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