Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Abstract Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Sp...

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Bibliographische Detailangaben
Hauptverfasser: Alejandro Rodriguez, Changpeng Lin, Hongao Yang, Mohammed Al-Fahdi, Chen Shen, Kamal Choudhary, Yong Zhao, Jianjun Hu, Bingyang Cao, Hongbin Zhang, Ming Hu
Format: Artikel
Sprache:English
Veröffentlicht: Nature Portfolio 2023-02-01
Schriftenreihe:npj Computational Materials
Online Zugang:https://doi.org/10.1038/s41524-023-00974-0

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