A deep learning package for many-body potential energy representation and molecular dynamics
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Updated
Aug 19, 2026 - Python
A deep learning package for many-body potential energy representation and molecular dynamics
A command line and python toolkit featured artificial intelligence × ab initio for complex chemistry systems research.
Automated scripts for DeePMD result plotting, testing, and outlier analysis in materials science.
Hybrid-Quantum Dynamics Analysis: a zero-base framework for ferroelectric phase transitions in PbTiO3, coupling VASP DFT baselines with ab initio molecular dynamics and DeepMD potentials, plus finite-size scaling to extrapolate the transition temperature.
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