Local surrogate models for harmonic vibrational entropy in multilattices achieve linear scaling with sublattice-resolved locality proofs and controlled truncation error on finite-range models.
Calculation of dislocation binding to helium-vacancy defects in tungsten using hybrid ab initio-machine learning methods
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Hybrid QM/ML forcefield framework couples DFT with MLIPs to enable scalable, chemically accurate simulations of solute-dislocation interactions, demonstrated on Sn/Fe segregation in Zr and magnetic effects in steel.
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A Hybrid Quantum Mechanics Machine Learning Forcefield (QM/ML) Framework for Accurate Solute-Dislocation Interaction Simulations
Hybrid QM/ML forcefield framework couples DFT with MLIPs to enable scalable, chemically accurate simulations of solute-dislocation interactions, demonstrated on Sn/Fe segregation in Zr and magnetic effects in steel.