What is it about?
We propose a first-principles model for estimating materials minimum lattice thermal conductivity that unifies different kinds of heat carriers. We apply the model to thousands of inorganic compounds and discovery a universal lower bound to the minimum lattice thermal conductivity, unveiling deep insights into its connection with the famous Cahill-Watson-Pohl model. We also construct machine learning models to enable accurate prediction of minimum lattice thermal conductivity and heat conduction in amorphous solids, thus opening the pathway for rational design of materials with low lattice thermal conductivity.
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Why is it important?
Lattice thermal conductivity, a fundamental property of materials, plays a vital role in various technological applications, including thermal energy conversion and management. Understanding its lower limit, known as the minimum thermal conductivity, is crucial but challenging, especially considering that the conventional phonon gas picture can break down in this limit. In this work, we propose a unified first-principles model for computing the minimum thermal conductivity and further bridge the knowledge gap between our model and the well-known Cahill-Watson-Pohl model.
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This page is a summary of: A unified understanding of minimum lattice thermal conductivity, Proceedings of the National Academy of Sciences, June 2023, Proceedings of the National Academy of Sciences,
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