Neural-network Density Functional Theory Based on Variational Energy Minimization

Deep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this field primarily relies on data-driven supervised learning, making the developments of neural networks a...

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Veröffentlicht in:	arXiv.org 2024-08
Hauptverfasser:	Yang, Li, Tang, Zechen, Chen, Zezhou, Sun, Minghui, Zhao, Boheng, He, Li, Tao, Honggeng, Yuan, Zilong, Duan, Wenhui, Xu, Yong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Back propagation networks Computation Deep learning Density functional theory Machine learning Neural networks Physics - Computational Physics Physics - Materials Science Supervised learning Unsupervised learning
Online-Zugang:	Volltext
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