Predicting lattice thermal conductivity from fundamental material properties using machine learning techniques
Guangzhao Qin, Yi Wei, Linfeng Yu, Jinyuan Xu, Joshua Ojih, Alejandro Rodriguez, Huimin Wang, Zhenzhen Qin, Ming Hu
Abstract
The well-trained machine learning models successfully capture the inherent correlation between fundamental properties and thermal conductivity for different types of materials, providing powerful tool for advanced thermal materials screening.
Topics & Concepts
Thermal conductivityMaterials scienceThermalLattice (music)Computer scienceArtificial intelligenceMachine learningComposite materialPhysicsThermodynamicsAcousticsMachine Learning in Materials ScienceThermal properties of materialsAdvanced Thermoelectric Materials and Devices