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Enhancing catalysis studies with chat generative pre-trained transformer (ChatGPT): Conversation with ChatGPT.
Ansari, Navid; Babaei, Vahid; Najafpour, Mohammad Mahdi.
Afiliação
  • Ansari N; Max Planck Institute for Informatics Saarbrücken, Germany.
  • Babaei V; Max Planck Institute for Informatics Saarbrücken, Germany.
  • Najafpour MM; Department of Chemistry, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran. mmnajafpour@iasbs.ac.ir.
Dalton Trans ; 53(8): 3534-3547, 2024 Feb 20.
Article em En | MEDLINE | ID: mdl-38275279
ABSTRACT
The progress made in natural language processing (NLP) and large language models (LLMs), such as generative pre-trained transformers, (GPT) has provided exciting opportunities for enhancing research across various fields. Within the realm of catalysis studies, GPT-driven models present valuable support in expediting the exploration and comprehension of catalytic processes. This research underscores the significance of ChatGPT in catalysis research, emphasizing its prowess as a valuable tool for furthering scientific inquiries. It suggests that for an outstanding oxygen evolution reaction (OER) catalyst as a case study, scientists can leverage ChatGPT to extract deeper insights and brainstorm innovative approaches to grasp the mechanism better and refine current systems.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Dalton Trans Assunto da revista: QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Dalton Trans Assunto da revista: QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido