Learning ab initio phase-field models
Simulating microstructure evolution requires quantum-mechanical accuracy and mesoscopic reach in length and time scales, a combination that no current method achieves. Classical phase-field models provide this reach, but their accuracy is limited by phenomenological free energies and mobilities. Here we develop a framework for learning ab initio phase-field models, where the mesoscopic equation is not postulated but derived from a Mori-Zwanzig projection of molecular dynamics onto species-density fields under explicit assumptions. The nonlocal free energy and mobility left unspecified by this equation are parametrized by neural networks and learned from short molecular dynamics trajectori...
| Authors | Mengyi Chen, Peichen Zhong, Zihan Zhang et al. |
|---|---|
| Primary category | cond-mat.stat-mech |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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