Cited by 147Machine Learning in Materials ScienceArtificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Do Large Language Models Understand Chemistry? A Conversation with ChatGPT

Castro Nascimento, Cayque Monteiro, Pimentel, André Silva·2023·Journal of Chemical Information and Modeling

Abstract

Large language models (LLMs) have promised a revolution in answering complex questions using the ChatGPT model. Its application in chemistry is still in its infancy. This viewpoint addresses the question of how well ChatGPT understands chemistry by posing five simple tasks in different subareas of chemistry.

Integrity signals

Registry

Crossref · 10.1021/acs.jcim.3c00285

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22 of 22 references verified0 citation errors · 0 not checkable

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  • ChatGPT's accuracy on five straightforward chemistry tasks ranged from 25% to 100%.

    “Castro Nascimento and Pimentel [18] presented five straightforward tasks from various subareas of chemistry to assess ChatGPT's comprehension of the subject, with accuracy ranging from 25% to 100%.”

    From A Survey on Evaluation of Large Language Models (2024) · cites this paper as [18]

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Authors
Castro Nascimento, C. M., & Pimentel, A. S.
Affiliations
  • Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, P.O. Box 38097, Rio de Janeiro, RJ 22451-900, Brazil
  • Pontifícia Universidade Católica do Rio de Janeiro (BR)
Corresponding author
Pimentel, André Silva
Venue
Journal of Chemical Information and Modeling
Published
2023-03-16
Volume
63
Issue
6
Pages
1649-1655
ISSN
  • 1549-9596 (ISSN-L)
  • 1549-960X
OpenAlex
W4327564965
Cited by
147
References
22
Citations by year
2026: 21 · 2025: 49 · 2024: 43 · 2023: 34
FWCI
10.93
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Chemical Information and Modeling (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (302554/2017-3, 310166/2020-9, 465259/2014-6, 573560/2008-0)
  • Funda??o de Amparo ? Pesquisa do Estado de S?o Paulo (2014/50983-3)
  • Funda??o Carlos Chagas Filho de Amparo ? Pesquisa do Estado do Rio de Janeiro (201.186/2022, 210.104/2020, E-26/010.000983/2019)
  • Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (001)
Topics
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
large language models, ChatGPT, chemical knowledge
MeSH terms
Communication, Language

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