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The theoretical prediction of thermal conductivity in many layered oxides remains challenging, primarily due to their structural complexity and low symmetry. This paper provides a strategy to predict the thermal conductivity of layered oxides by machine-learning using a deep neural network model.
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This page is a summary of: Thermal conductivity of the layered titanate K0.8Li0.27Ti1.73O4 explored by a deep learning interatomic potential, The Journal of Chemical Physics, March 2025, American Institute of Physics,
DOI: 10.1063/5.0255515.
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