Yen-Ju Wu
(National Institute for Materials Science
)
Description:
(abstract)Efficient heat dissipation is crucial for electronics. Interfacial thermal resistance (ITR) poses significant challenges, requiring innovative solutions. Machine learning enhances ITR predictions by analyzing large datasets. Inorganic, amorphous, and 2D materials offer advanced thermal management. Future research could benefit from improved data quality and hybrid models to further optimize next-generation electronic devices.
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Keyword: Interfacial thermal resistance, thermal management, electronics, machine learning
Date published: 2024-07-17
Publisher: Springer Science and Business Media LLC
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Funding:
Manuscript type: Author's version (Submitted manuscript)
MDR DOI: https://doi.org/10.48505/nims.4696
First published URL: https://doi.org/10.1038/s44287-024-00077-y
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Updated at: 2024-08-27 16:30:21 +0900
Published on MDR: 2024-08-27 16:30:22 +0900
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