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cond-mat.mtrl-sci2026
How Can Machine Learning Accelerate CALPHAD Free Energy Modeling?
Chen Shen, Muhammad Waqas Qureshi, Mark Asta +2
The CALPHAD framework provides a rigorous basis for thermodynamic modeling, yet its ability to predict new chemistries is restricted by limited data and by functional forms that re…
cond-mat.mtrl-sci2025
MP-ALOE: An r2SCAN dataset for universal machine learning interatomic potentials
Matthew C. Kuner, Aaron D. Kaplan, Kristin A. Persson +2
We present MP-ALOE, a dataset of nearly 1 million DFT calculations using the accurate r2SCAN meta-generalized gradient approximation. Covering 89 elements, MP-ALOE was created usin…
cond-mat.mtrl-sci2024
SuperSalt: Equivariant Neural Network Force Fields for Multicomponent Molten Salts System
Chen Shen, Siamak Attarian, Yixuan Zhang +4
Molten salts are crucial for clean energy applications, yet exploring their thermophysical properties across diverse chemical space remains challenging. We present the development…