HME21_train

The training set from HME21. The high-temperature multi-element 2021 (HME21) dataset comprises approximately 25,000 configurations, including 37 elements, used in the training of a universal NNP called PreFerential Potential (PFP). The dataset specifically contains disordered and unstable structures...

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Bibliographische Detailangaben
Hauptverfasser:	Takamoto, So, Shinagawa, Chikashi, Motoki, Daisuke, Nakago, Kosuke, Wenwen Li, Kurata, Iori, Watanabe, Taku, Yayama, Yoshihiro, Iriguchi, Hiroki, Asano, Yusuke, Onodera, Tasuku, Ishii, Takafumi, Kudo, Takao, Ono, Hideki, Ryohto Sawada, Ryuichiro Ishitani, Ong, Marc, Yamaguchi, Taiki, Kataoka, Toshiki, Akihide Hayashi, Nontawat Charoenphakdee, Ibuka, Takeshi
Format:	Dataset
Sprache:	eng
Schlagworte:	AgPd_NPJ_2021 ColabFit Dataset https://id.loc.gov/authorities/subjects/sh85079324.html https://id.loc.gov/authorities/subjects/sh85082094.html Machine Learning Materials Science Research Areas/Atomic & molecular structure/Potential energy surfaces Research Areas/Electronic structure/Interatomic & molecular potentials Techniques/Computational Techniques/First-principles calculations Techniques/Computational Techniques/Machine Learning Techniques/Computational Techniques/Molecular Dynamics
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Beschreibung
Zusammenfassung:	The training set from HME21. The high-temperature multi-element 2021 (HME21) dataset comprises approximately 25,000 configurations, including 37 elements, used in the training of a universal NNP called PreFerential Potential (PFP). The dataset specifically contains disordered and unstable structures, and structures that include irregular substitutions, as well as varied temperature and density.
DOI:	10.60732/845cc1b5