Panoramic mapping of phonon transport from ultrafast electron diffraction and machine learning

Zhantao Chen; Xiaozhe Shen; Nina Andrejevic; Tongtong Liu; Duan Luo; Thanh Nguyen; Nathan C. Drucker; Michael E. Kozina; Qichen Song; Chengyun Hua; Gang Chen; Xijie Wang; Jing Kong; Mingda Li

arXiv · 2202.06199

Panoramic mapping of phonon transport from ultrafast electron diffraction and machine learning

Zhantao Chen·Xiaozhe Shen·Nina Andrejevic·Tongtong Liu·Duan Luo·Thanh Nguyen·Nathan C. Drucker·Michael E. Kozina·Qichen Song·Chengyun Hua·Gang Chen·Xijie Wang·Jing Kong·Mingda Li

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Abstract

One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate mode-based transport information. Although recent advances in computation lead to mode-based information, it is hindered by unknown defects in bulk region and at interfaces. Here we present a framework that can reveal microscopic phonon transport information in heterostructures, integrating state-of-the-art ultrafast electron diffraction (UED) with advanced scientific machine learning. Taking advantage of the dual temporal and reciprocal-space resolution in UED, we are able to reliably recover the frequency-dependent interfacial transmittance with possible extension to frequency-dependent relaxation times of the heterostructure. This enables a direct reconstruction of real-space, real-time, frequency-resolved phonon dynamics across an interface. Our work provides a new pathway to experimentally probe phonon transport mechanisms with unprecedented details.

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Zhantao Chen, Xiaozhe Shen, Nina Andrejevic, Tongtong Liu, Duan Luo, Thanh Nguyen, Nathan C. Drucker, Michael E. Kozina, Qichen Song, Chengyun Hua, Gang Chen, Xijie Wang, Jing Kong, Mingda Li. 2022-02-13. Panoramic mapping of phonon transport from ultrafast electron diffraction and machine learning. https://arxiv.org/abs/2202.06199

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