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.
Thermoelectric material performance (zT) predictions with machine learning.ACS Applied Materials & Interfaces, 17(1):1662–1673, 2024
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cond-mat.mtrl-sci 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.