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231226s2023 xx |||||o 00| ||eng c |
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|a 10.1002/adma.202206997
|2 doi
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|a pubmed24n1165.xml
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|a (DE-627)NLM349535493
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|a (NLM)36440651
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
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|a Chen, Zhantao
|e verfasserin
|4 aut
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| 245 |
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|a Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning
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|c 2023
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 13.01.2023
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|a Date Revised 13.01.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2022 The Authors. Advanced Materials published by Wiley-VCH GmbH.
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|a 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 ( 10 3 ) $\mathcal{O}({10^3})$ 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
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|a Journal Article
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|a phonon
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|a scientific machine learning
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|a thermal transport
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|a ultrafast diffraction
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|a Shen, Xiaozhe
|e verfasserin
|4 aut
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|a Andrejevic, Nina
|e verfasserin
|4 aut
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|a Liu, Tongtong
|e verfasserin
|4 aut
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|a Luo, Duan
|e verfasserin
|4 aut
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|a Nguyen, Thanh
|e verfasserin
|4 aut
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|a Drucker, Nathan C
|e verfasserin
|4 aut
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|a Kozina, Michael E
|e verfasserin
|4 aut
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|a Song, Qichen
|e verfasserin
|4 aut
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|a Hua, Chengyun
|e verfasserin
|4 aut
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|a Chen, Gang
|e verfasserin
|4 aut
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| 700 |
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|a Wang, Xijie
|e verfasserin
|4 aut
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|a Kong, Jing
|e verfasserin
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|a Li, Mingda
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Advanced materials (Deerfield Beach, Fla.)
|d 1998
|g 35(2023), 2 vom: 08. Jan., Seite e2206997
|w (DE-627)NLM098206397
|x 1521-4095
|7 nnns
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| 773 |
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|g volume:35
|g year:2023
|g number:2
|g day:08
|g month:01
|g pages:e2206997
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|u http://dx.doi.org/10.1002/adma.202206997
|3 Volltext
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