# Interfacial thermal management of inorganic thin films from predictions to applications via materials informatics

https://mdr.nims.go.jp/datasets/237d2684-6d54-4c67-83bc-a8893ee3e48a

## Files

- [abstract.pdf](https://mdr.nims.go.jp/filesets/fa80e400-30de-40c2-966a-e143f75f90c5/download) ([Detail](https://mdr.nims.go.jp/filesets/fa80e400-30de-40c2-966a-e143f75f90c5.md))

## Id

237d2684-6d54-4c67-83bc-a8893ee3e48a

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-03-13T07:46:46.046449Z

## Updated at

2023-03-22T06:34:00.393579Z

## Published at

2023-03-23T07:28:18.096457Z

## Doi

https://doi.org/10.48505/nims.3871

## First published url

https://pacifichem.org/

## Date published

2021-12-16

## Recorded date published



## Resource type

conference_presentation

## Manuscript type

authors_original

## Collection



## Title

- title: Interfacial thermal management of inorganic thin films from predictions to
    applications via materials informatics
  title_type: original
  lang: en

## Description

- description: 'Interfacial heat transfer plays a crucial role in materials design
    and device performance. High interfacial thermal resistances (ITRs) affect the
    device efficiency and increase the energy consumption. On the contrary, high ITRs
    can enhance the figure of merit of thermoelectric materials by achieving ultra-low
    thermal conductivity via nanostructuring. Lots of factors affect ITRs making ITRs
    prediction a high-dimensional mathematical problem. We proposed an unprecedented
    ITRs predictive model considering the physical, chemical, and material properties
    to address it. Those descriptors assist the models in reducing the mismatch between
    predicted and experimental values and reaching high predictive performance of
    96%, which is much higher than the common-used acoustic mismatch model and diffuse
    mismatch model of 60%. Here, two examples of the interfacial thermal management
    via materials informatics will be demonstrated: the Bi/Si composite thin films
    for thermal insulators and Au/MoS2 monolayer for high efficient 2D-material electronic
    devices. The former is selected from the ITRs predictive model and achieve an
    ultra-low thermal conductivity among porous-free composite thin films. The ultralow
    thermal conductivity is attributed to the high Bi/Si interfacial area by nanostructuring
    via combinatorial sputtering. The latter is an improvement of thermal transport
    at Au/MoS2 monolayer interfaces by tuning the interfacial chemical condition.
    The ITRs database clearly shows the interlayer effect such as oxygen plasma treatment
    at interface on the ITRs, leading to the findings that adequate oxygen adsorbates
    at the Au/MoS2 interface improve the thermal and electrical conductance, in agreement
    with the DFT simulated results. By means of the broad exploration of materials
    informatics (machine learning), the hints from the database and prediction could
    accelerate the materials development. More details and further undiscovered issues
    will also be discussed in the talk.'
  description_type: abstract
  lang: eng

## Creator

- name: WU, Yen-Ju
  role: author
  orcid: https://orcid.org/0000-0003-2647-3407
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System/Data-driven
    Inorganic Materials Group
  ror: https://ror.org/026v1ze26
- name: XU, Yibin
  role: author
  orcid: https://orcid.org/0000-0001-8600-8748
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System/Data-driven
    Inorganic Materials Group
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: Pacific Basin Societies 2021

## Managing organization



## Keyword

- subject: thin film, materials informatics, Interfacial thermal management
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal



## Conference

name: Pacifichem 2021
start_date: 2021-12-16
end_date: 2021-12-21
identifier: https://pacifichem.org/

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## Fileset

- id: fa80e400-30de-40c2-966a-e143f75f90c5
  filename: abstract.pdf
  content_type: application/pdf
  size: 65246
  md5: c5dedaa0bc188126ceb96a667024b605

## Thumbnail

fileset_id: fa80e400-30de-40c2-966a-e143f75f90c5
filename: abstract.pdf