Seeking for Low Thermal Conductivity Atomic Configurations in SiGe Alloys with Bayesian Optimization
Jiahao Yan, Han Wei, Han Xie, Xiaokun Gu and Hua Bao
1 University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, 200240, China
2 Artificial Intelligence Lab, SAIC Motor Corporation, Shanghai, 200433, China
3 Institute of Engineering Thermophysics, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
# These authors contributed equally.
Abstract
The emergence of data-driven science has opened up new avenues for understanding the thermophysical properties of materials. For decades, alloys are known to possess very low thermal conductivity, but the extreme thermal conductivity that can be achieved by alloying has never been identified. In this work, we combine the Bayesian optimization with a high throughput thermal conductivity calculation to search for the lowest thermal conductivity atomic configuration of SiGe alloy. It is found layered structures are most beneficial for reducing the thermal conductivity among all atomic configurations, which is attributed to the strong branch-folding effect. Furthermore, the roles of interface roughness and layer thicknesses in producing the lowest thermal conductivity are investigated. Through another comprehensive search using Bayesian optimization, the layered structure with smooth interfaces and optimized layer thickness arrangement is eventually identified as the optimal structure with the lowest thermal conductivity.
Publication details
Received: 18 Apr 2020
Revised: 18 Apr 2020
Accepted: 01 May 2020
Published online: 02 May 2020
Article type:
Research Paper
DOI:
10.30919/esee8c356
Volume:
8
Page:
56-64
Citation:
ES Energy & Environment, 2020, 8, 56-64
Permissions:
Copyright
Number of downloads:
3342
Citation Information:
16
Description:
The atomic structures of Si Ge alloy with the lowest and highest thermal conductivity are found by t....
The atomic structures of Si Ge alloy with the lowest and highest thermal conductivity are found by the Bayesian optimization.
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