Machine learning for accelerated prediction of the Seebeck coefficient at arbitrary carrier concentration
Hongmei Yuan, Shulin Han, Rui Hu, Wen-Na Jiao, Mengke Li, Huijun Liu, Ying Fang
Topics & Concepts
Seebeck coefficientThermoelectric effectArtificial neural networkMaterials scienceIndependence (probability theory)Correlation coefficientPower (physics)Thermoelectric materialsMetrologyCondensed matter physicsMachine learningComputer scienceThermodynamicsPhysicsStatisticsMathematicsAdvanced Thermoelectric Materials and DevicesHeusler alloys: electronic and magnetic propertiesMachine Learning in Materials Science