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Presenter: Dr. Thomas Purcell
Abstract:
New efficient and cost-effective thermal insulators are needed for numerous sustainability and energy applications, such as thermoelectrics and thermal barrier coatings. However, advancements in this field are often hindered by the scarcity of available data and the significant effort required to acquire new data, both computationally and experimentally. For such applications, reliable surrogate models that help guide materials space exploration using easily accessible materials properties are urgently needed.
Here, I present a general, high-throughput framework for calculating the thermal transport properties of a material from first-principles. By using the workflow to calculate the structural, harmonic, and anharmonic properties of a material I am able to create a set of physically meaningful descriptors for the thermal conductivity, κL, of a material. Using these descriptors, I apply the sure-independence screening and sparsifying operator (SISSO)2 approach to build an analytical model that describes κL, and then extract out the most important input properties using a variance-based sensitivity analysis. Utilizing the information gained from the analysis, I screen over a set of 732 materials and find 80 ultra-insulating materials in the region of materials space that is likely to contain new thermal insulators. Finally, I confirm four of these predictions by calculating their thermal conductivity using the ab initio Green-Kubo technique.