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This research demonstrates how machine learning interatomic potentials enhance exploration of disordered multi-component solid-state electrolytes, suggesting new possibilities in material science.
Machine learning interatomic potentials (MLIPs) are rapidly emerging as powerful tools for materials simulations, offering a promising pathway to explore complex systems beyond the reach of traditional methods. This study...
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Deng et al. (2025) studied this question.
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