Large Language Models as Molecular Design Engines-Reference-Cited by-同舟云学术

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Large Language Models as Molecular Design Engines

Published:2024-09-04 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Bhattacharya Debjyoti¹^ORCID,Cassady Harrison J.²^ORCID,Hickner Michael A.²^ORCID,Reinhart Wesley F.¹³^ORCID

Affiliation:

1. Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States

2. Department of Chemical Engineering and Material Science, Michigan State University, East Lansing, Michigan 48824, United States

3. Institute for Computational and Data Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, United States

Funder

Energy Frontier Research Centers

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c01396

Reference45 articles.

1. Yang, Z.; Ye, W.; Lei, X.; Schweigert, D.; Kwon, H.K.; Khajeh, A. De novo design of polymer electrolytes with high conductivity using gpt-based and diffusion-based generative models. arXiv preprint arXiv:2312.06470, 2023.

2. Recent applications of machine learning in alloy design: A review

3. Understanding, discovery, and synthesis of 2D materials enabled by machine learning

4. Generative Models for De Novo Drug Design

5. De novo molecular design and generative models

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