# Revolutionizing electronics with advanced interfacial heat management

https://mdr.nims.go.jp/datasets/a7447bbc-b9af-47dc-b235-6d1382038849

## File

- [Comments.pdf](https://mdr.nims.go.jp/filesets/2ba80af6-1e36-41b6-9f5a-aa3efd95d7f7/download) ([Detail](https://mdr.nims.go.jp/filesets/2ba80af6-1e36-41b6-9f5a-aa3efd95d7f7.md))

## Id

a7447bbc-b9af-47dc-b235-6d1382038849

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-08-19T05:58:51.503764Z

## Updated at

2024-08-27T07:30:21.846243Z

## Published at

2024-08-27T07:30:22.337203Z

## Doi

https://doi.org/10.48505/nims.4696

## First published url

https://doi.org/10.1038/s44287-024-00077-y

## Date published

2024-07-17

## Recorded date published



## Resource type

journal_article

## Manuscript type

authors_original

## Collection



## Title

- title: Revolutionizing electronics with advanced interfacial heat management
  title_type: original
  lang: en

## Description

- description: 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.
  description_type: abstract
  lang: und

## Creator

- name: Yen-Ju Wu
  role: author
  orcid: https://orcid.org/0000-0003-2647-3407
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: Springer Science and Business Media LLC

## Managing organization



## Keyword

- subject: Interfacial thermal resistance
  schema: not_defined
- subject: thermal management
  schema: not_defined
- subject: electronics
  schema: not_defined
- subject: machine learning
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

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## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Nature Reviews Electrical Engineering
  issn: '29481201'
  volume: '1'
  issue: '8'
  start_page: 489
  end_page: 490

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## Specimen



## Chemical composition



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## Fileset

- id: 2ba80af6-1e36-41b6-9f5a-aa3efd95d7f7
  filename: Comments.pdf
  content_type: application/pdf
  size: 175010
  md5: d0b35005e89ed2121c56c25521090a34

## Thumbnail

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filename: Comments.pdf