AtomGPT: Atomistic Generative Pretrained Transformer for Forward and Inverse Materials Design

Large language models (LLMs) such as generative pretrained transformers (GPTs) have shown potential for various commercial applications, but their applicability for materials design remains underexplored. In this Letter, AtomGPT is introduced as a model specifically developed for materials design ba...

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Veröffentlicht in:	The journal of physical chemistry letters 2024-07, Vol.15 (27), p.6909-6917
1. Verfasser:	Choudhary, Kamal
Format:	Artikel
Sprache:	eng
Schlagworte:	Physical Insights into Materials and Molecular Properties
Online-Zugang:	Volltext
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