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A public database of thermoelectric materials and system-identified material representation for data-driven discovery

Chemistry

A public database of thermoelectric materials and system-identified material representation for data-driven discovery

G. S. Na and H. Chang

Discover the exciting ESTM dataset, showcasing experimentally synthesized thermoelectric materials with remarkable predictive models! Conducted by Gyoung S. Na and Hyunju Chang, this research demonstrates how a novel material descriptor, SIMD, significantly enhances prediction accuracy and aids in high-throughput screening for superior thermoelectric materials.

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Playback language: English
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