Unraveling the structure and thermophysical property of heterogeneous eutectic salt by machine learning potential for solar thermal energy storage

Wenguang Zhang; Heqing Tian; Tianyu Liu

doi:10.1016/j.susmat.2025.e01451

Photo by Wolfgang Hasselmann on Unsplash

Why is it important?

This work provide a new perspective to use DP-GEN active ML strategy to precisely predict structure and thermal property of heterogeneous molten salt systems.

This page is a summary of: Unraveling the structure and thermophysical property of heterogeneous eutectic salt by machine learning potential for solar thermal energy storage, Sustainable Materials and Technologies, October 2025, Elsevier,
DOI: 10.1016/j.susmat.2025.e01451.
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Unraveling the structure and thermophysical property of heterogeneous eutectic salt by machine learning potential for solar thermal energy storage
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Dr. Heqing Tian
Zhengzhou University

Thermal energy storage of molten salt

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