Combining Deep Learning Neural Networks with Genetic Algorithms to Map Nanocluster Configuration Spaces with Quantum Accuracy at Low Computational Cost-Reference-Cited by-同舟云学术

Combining Deep Learning Neural Networks with Genetic Algorithms to Map Nanocluster Configuration Spaces with Quantum Accuracy at Low Computational Cost

Published:2023-08-14 Issue:16 Volume:63 Page:5045-5055
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

von der Heyde Johnathan¹,Malone Walter²^ORCID,Zaman Nusaiba¹,Kara Abdelkader¹^ORCID

Affiliation:

1. Department of Physics, University of Central Florida, 4000 Central Florida Blvd., Orlando, Florida 32816, United States

2. Department of Physics, Tuskegee University, 1200 W. Montgomery Rd., Tuskegee, Alabama 36088, United States

Funder

National Science Foundation

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.3c00609

Reference58 articles.

1. Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

2. Transferable Machine-Learning Model of the Electron Density

3. Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks

4. Bond order predictions using deep neural networks

5. Discovering a Transferable Charge Assignment Model Using Machine Learning

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