Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning
Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning
复制标题
超快电子衍射和科学机器学习的声子传输全景图
DOI:
10.1002/adma.202206997
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发表时间:
2022
影响因子:
29.4
通讯作者:
Hua, Chengyun
中科院分区:
文献类型:
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作者:
Chen, Zhantao;Shen, Xiaozhe;Andrejevic, Nina;Liu, Tongtong;Luo, Duan;Nguyen, Thanh;Drucker, Nathan C.;Kozina, Michael E.;Song, Qichen;Hua, Chengyun
One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving O(103)$\mathcal{O}({10^3})$ coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.
DOI:
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发表时间:
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期刊:
影响因子:
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作者:
通讯作者:
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影响因子:
4
作者:
M. Forghani;N. Hadjiconstantinou
通讯作者:
N. Hadjiconstantinou