High-ZT thermoelectrics cluster near κ_L/κ ≈ 0.5, which is used as a PGEC descriptor in ML models to screen 2522 ultralow-κ candidates from 104k compounds.
A general-purpose machine learning framework for predicting properties of inorganic materials.npj Computational Materials, 2(1):1–7, 2016
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Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design
High-ZT thermoelectrics cluster near κ_L/κ ≈ 0.5, which is used as a PGEC descriptor in ML models to screen 2522 ultralow-κ candidates from 104k compounds.