Big-data-accelerated aperiodic Si/Ge superlattice prediction for quenching thermal conduction via pattern analysis

Big-data-accelerated aperiodic Si/Ge superlattice prediction for quenching thermal conduction via pattern analysis

Thermal conductivity of material is one of the basic physical properties and plays an important role in manipulating thermal energy. In order to accelerate the prediction of material structure with desired thermal property, machine learning algorithm has been widely adopted. However, in the optimiza...

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Bibliographic Details
Main Authors: Yida Liu, Run Hu, Yan Wang, Jinglong Ma, Zhangcan Yang, Xiaobing Luo
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:Energy and AI
Subjects:
Aperiodic superlattice
Pattern analysis
Thermal conductivity
Machine learning
Atomic Green's function
Online Access:http://www.sciencedirect.com/science/article/pii/S266654682030046X

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http://www.sciencedirect.com/science/article/pii/S266654682030046X

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