Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces-Reference-Cited by-同舟云学术

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Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Published:2024-09-10 Issue: Volume: Page:
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Zare Mehdi¹,Sahsah Dia¹^ORCID,Saleheen Mohammad¹,Behler Jörg²³^ORCID,Heyden Andreas¹^ORCID

Affiliation:

1. Department of Chemical Engineering, University of South Carolina, Columbia, South Carolina 29208, United States

2. Lehrstuhl für Theoretische Chemie II, Ruhr-Universität Bochum, Bochum 44780, Germany

3. Research Center Chemical Sciences and Sustainability, Research Alliance Ruhr, Bochum 44780, Germany

Funder

Basic Energy Sciences

Deutsche Forschungsgemeinschaft

South Carolina Smart State Center for Strategic Approaches to the Generation of Electricity

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.4c00869

Reference129 articles.

1. Zur Quantentheorie der Molekeln

2. Unified Approach for Molecular Dynamics and Density-Functional Theory

3. The Role and Perspective of Ab Initio Molecular Dynamics in the Study of Biological Systems

4. Ab initio molecular dynamics: Concepts, recent developments, and future trends

5. Methanol at the water–platinum interface studied by ab initio molecular dynamics

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