The 77th JSAP Autumn Meeting, 2016

Presentation information

Oral presentation

Joint Session M "Phonon Engineering" » Joint Session M "Phonon Engineering"

[14p-B12-1~18] 22.1 Joint Session M "Phonon Engineering"

Wed. Sep 14, 2016 1:30 PM - 6:15 PM B12 (Exhibition Hall)

Tsunehiro Takeuchi(Toyota Tech. Inst.), Takanobu Watanabe(Waseda Univ.), Takahiro Yamamoto(Tokyo Univ. of Sci.), Takao Mori(NIMS)

5:15 PM - 5:30 PM

[14p-B12-15] Designing Nanostructures for Interfacial Phonon Transport via Bayesian Optimization

〇(P)Shenghong Ju1,2, Takuma Shiga1,2, Lei Feng1, Zhufeng Hou2, Koji Tsuda1,2, Junichiro Shiomi1,2 (1.Univ. of Tokyo, 2.NIMS)

Keywords:Bayesian optimization, Nanostructure interface, Phonon transport

The typical alloy and superlattices nanostructures for interfacial phonon transport were designed and optimized by using Bayesian optimization. The alloy structure optimization deals with an interfacial Si/Ge alloy region, and the problem to be solved is how to organize the alloy atoms to obtain the best and worst interfacial thermal conductance for a given volume fraction. Through Bayesian optimization, eight structures with highest thermal conductance and one unique structure with lowest thermal conductance were successfully found. The highest conductance is around 2.3 times of the lowest one. The optimal structures were obtained by calculating only around 4% of the total candidates, saving the computational resources considerably. The Si/Ge superlattices structures with fixed layer numbers were also optimized by arranging the Si/Ge layer order to obtain the minimum thermal conductance. For given superlattice thickness, the layer thickness and interface numbers are two competitive parameters, which gives rise to the optimal structure with minimum conductance. The interference effect in superlattices was also characterized by comparing the phonon transmission from direct atomistic Green’s function and cascade model. The presented optimization of alloy and superlattices structures for interfacial phonon transport has shown the effectiveness and advantage of material informatics in designing nanostructures to control heat conduction.