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AI estimation of partition functions with the PULSE method for the thermodynamic properties of disordered compounds
Predicting the thermodynamic properties of chemically disordered materials is constrained by the combinatorial growth of possible atomic configurations, which makes conventional sampling approaches computationally costly. In this work, we extend the PULSE (Partition function Unsupervised Learning Sa
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