Enhancing catalysis studies with chat generative pre-trained transformer (ChatGPT): Conversation with ChatGPT
Navid Ansari1, Vahid Babaei1, Mohammad Mahdi Najafpour2,3,4
1Max Planck Institute for Informatics Saarbrücken, Germany.
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.
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