# Electrically Conductive Thermally Insulating Bi-Si Nanocomposites by Interface Design for Thermal Management

https://mdr.nims.go.jp/datasets/69088a8c-a419-492e-a8bb-70575b8d2d62

## File

- [manuscript(BiSi)-compressed.pdf](https://mdr.nims.go.jp/filesets/138a32f2-abb0-4ef8-8916-f6fd390a5afd/download) ([Detail](https://mdr.nims.go.jp/filesets/138a32f2-abb0-4ef8-8916-f6fd390a5afd.md))
- [Supporting information.pdf](https://mdr.nims.go.jp/filesets/c5619730-16d0-4070-bf8e-bfe925530578/download) ([Detail](https://mdr.nims.go.jp/filesets/c5619730-16d0-4070-bf8e-bfe925530578.md))

## Id

69088a8c-a419-492e-a8bb-70575b8d2d62

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-03-13T08:03:17.166963Z

## Updated at

2024-01-05T13:12:22.254820Z

## Published at

2023-06-26T11:15:56.830605Z

## Doi

https://doi.org/10.48505/nims.4194

## First published url

https://doi.org/10.1021/acsanm.8b00575

## Date published

2018-07-27

## Recorded date published

2018-7-27

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: Electrically Conductive Thermally Insulating Bi-Si Nanocomposites by Interface
    Design for Thermal Management
  title_type: original
  lang: en

## Description

- description: We demonstrate, both by experiments and by data informatics, an alternative
    strategy to achieve ultralow thermal conductivity in a dense solid. The interfacial
    thermal resistance (ITR) prediction of the machine learning model is implemented
    in a nanoscale field. The size dependence on ITR is considered and applied to
    the interface design of nanostructuring. The Bi/Si system was selected from 2025
    kinds of interfaces through the interface thermal resistance prediction model
    by machine learning. The BiSi nanocomposite, which was composed of crystallized
    Bi and amorphous Si, was designed with various parameters by a laboratory-built
    combinatorial sputtering system. Electrically conductive, thermally insulating
    BiSi nanocomposites were reported for the first time and have a thermal conductivity
    as low as 0.16 W m–1 K–1. The ultralow thermal conductivity is attributed to the
    high ratio between the interfacial surface area and the volume because of the
    small Bi particle size and high Si/Bi atomic ratio. By introducing the informatics
    method, the potential candidates can be discovered and realized for thermoelectric
    applications.
  description_type: abstract
  lang: eng

## 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
- name: Michiko Sasaki
  role: author
  orcid: https://orcid.org/0000-0002-2336-5788
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Masahiro Goto
  role: author
  orcid: https://orcid.org/0000-0002-1003-2781
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Lie Fang
  role: author
  orcid: https://orcid.org/0000-0003-4706-0521
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Yibin Xu
  role: author
  orcid: https://orcid.org/0000-0001-8600-8748
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: American Chemical Society (ACS)

## Managing organization



## Keyword

- subject: thermal insulating thin film, interface thermal resistance, interface design,
    nanostructuring, nanocomposite, machine learning
  schema: not_defined

## Rights

- description: This document is the Accepted Manuscript version of a Published Work
    that appeared in final form in ACS APPLIED NANO MATERIALS, copyright © 2018 American
    Chemical Society after peer review and technical editing by the publisher. To
    access the final edited and published work see https://doi.org/10.1021/acsanm.8b00575.
  identifier: http://rightsstatements.org/vocab/InC/1.0/

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: ACS APPLIED NANO MATERIALS
  issn: '25740970'
  volume: '1'
  issue: '7'
  start_page: 3355
  end_page: 3363

## Conference



## Related item



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## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



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## Custom property



## Fileset

- id: 138a32f2-abb0-4ef8-8916-f6fd390a5afd
  filename: manuscript(BiSi)-compressed.pdf
  content_type: application/pdf
  size: 1154196
  md5: 9e26af56905fdeeb71bf59c9b09188ac
- id: c5619730-16d0-4070-bf8e-bfe925530578
  filename: Supporting information.pdf
  content_type: application/pdf
  size: 687644
  md5: 1bdd49cc8a282677f56a4af2e2850513

## Thumbnail

fileset_id: 138a32f2-abb0-4ef8-8916-f6fd390a5afd
filename: manuscript(BiSi)-compressed.pdf