FIG. 1. Sketch of universal materials model of deep-learning DFT Hamiltonian (DeepH) (IMAGE)

Science China Press

FIG. 1. Sketch of universal materials model of deep-learning DFT Hamiltonian (DeepH)

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(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material structure as input and generates the corresponding DFT Hamiltonian, enabling straightforward derivation of various material properties. (b) Working principle of DeepH, which learns and predicts DFT Hamiltonian matrix blocks separately based on local-structure information.

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