Lattice thermal conductivity (κL) is a crucial physical property of crystals with applications in thermal management, such as heat dissipation, insulation, and thermoelectric energy conversion. However, accurately and rapidly determining κL poses a considerable challenge. In this study, we introduce a formula that achieves high precision (mean relative error = 8.97 %) and provides fast predictions, taking less than 1 min, for κL across a wide range of inorganic binary and ternary materials. Our interpretable, dimensionally aligned and physical grounded formula forecasts κL values for 4601 binary and 6995 ternary materials in the Materials Project database. Notably, we predict undiscovered high κL values for AlBN2 (κL = 101 W m−1 K−1) and the undetected low κL Cs2Se (κL = 0.98 W m−1 K−1) at room temperature. This method for determining κL streamlines the traditionally time-consuming process associated with complex phonon physics. It provides insights into microscopic heat transport and facilitates the design and screening of materials with targeted and extreme κL values through the application of phonon engineering. Our findings offer opportunities for controlling and optimizing macroscopic transport properties of materials by engineering their bulk modulus, shear modulus, and Grüneisen parameter.

中文翻译：

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晶体晶格热导率的可解释公式


晶格热导率 （κL） 是晶体的关键物理特性，可用于热管理，例如散热、绝缘和热电能转换。然而，准确快速地测定 κL 带来了相当大的挑战。在本研究中，我们引入了一个公式，该公式可实现高精度（平均相对误差 = 8.97 %），并在不到 1 分钟的时间内对各种无机二元和三元材料的 κL 进行快速预测。我们的可解释、尺寸对齐和物理接地公式可预测材料项目数据库中 4601 种二元材料和 6995 种三元材料的 κL 值。值得注意的是，我们预测了室温下 AlBN2 （κL = 101 W m-1 K-1） 和未检测到的低 κL Cs2Se （κL = 0.98 W m-1 K-1） 的未被发现的高 κL 值。这种确定 κL 的方法简化了传统上与复杂声子物理学相关的耗时过程。它提供了对微观热传递的见解，并通过声子工程的应用促进了具有目标和极端 κL 值的材料的设计和筛选。我们的研究结果为通过设计材料的体积模量、剪切模量和 Grüneisen 参数来控制和优化材料的宏观传输特性提供了机会。