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Found 3 papers, 1 papers with code
Efficient exploration of high-Tc superconductors by a gradient-based composition design
We propose a material design method via gradient-based optimization on compositions, overcoming the limitations of traditional methods: exhaustive database searches and conditional generation models.
Enhancing Inverse Problem Solutions with Accurate Surrogate Simulators and Promising Candidates
In this study, we investigated the impact of surrogate simulators' accuracy on the solutions and discovered that the more accurate the surrogate simulator is, the better the solutions become.
Persistent homology-based descriptor for machine-learning potential of amorphous structures
A promising method to achieve this is machine-learning potentials, which is an alternative to computationally demanding ab initio calculations.
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