Atom computingGPT: [Program Sharing] AtomGPT Program: Atomic Generation Pre Training Converter for F

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================================Share1A J Phys. Chem. Lett.: AtomGPT Program - A Program for Atomic Generation Pre trained Converter for Forward and Reverse Material Design. Thank you for the original work of this paper.

The person================================secondaryLarge scale language models (LLMs) such as generative pre trained converters (GPT) have shown potential for various commercial applications, but their applicability in material design still needs to be explored with AtomGPT.

Introduced as a model specifically designed and developed for materials based on transformer architecture, this study demonstrates the ability to predict atomic properties and generate structures. The combination of chemical and structural textual descriptions can effectively predict materialsMaterial properties, their accuracytakeThe graphical neural network model is equivalent, including the formation of energy and two typesNo,Same method.

In addition to the electronic bandgap and superconducting transition temperature, AtomGPT can generate atomic structures for tasks such as designing new superconductors, and its predictions have been verified through density functional theory calculations. This work paves the way for the use of LLMs in forward and reverse material design, providing insights for material discovery and optimization1An effective method.

”- Taken from the abstract of the article================================

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