# Data-Driven Design of Multi-Element Thermal Insulating Thin Films for Advanced Thermal Management

https://mdr.nims.go.jp/datasets/a0f0f97b-b683-4260-a749-9c1e9a5af72a

## File

- [TACT2025-Abstract_Wu.pdf](https://mdr.nims.go.jp/filesets/5344f2ac-55a6-460a-94ee-14926dca3a8b/download) ([Detail](https://mdr.nims.go.jp/filesets/5344f2ac-55a6-460a-94ee-14926dca3a8b.md))

## Id

a0f0f97b-b683-4260-a749-9c1e9a5af72a

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## Visibility

open_to_public

## State

published

## Created at

2025-12-15T04:52:47.283689Z

## Updated at

2026-01-26T07:30:07.921881Z

## Published at

2026-01-26T04:08:59.638702Z

## Doi

https://doi.org/10.48505/nims.6165

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## Resource type

conference_presentation

## Manuscript type

na

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## Title

- title: Data-Driven Design of Multi-Element Thermal Insulating Thin Films for Advanced
    Thermal Management
  title_type: original
  lang: en

## Description

- description: "The design of thermal insulating coatings for advanced energy and
    electronic applications requires a deep understanding of both intrinsic and interfacial
    thermal transport. In this study, we present a data-driven workflow that integrates
    interfacial thermal resistance (ITR) modeling, low thermal conductivity screening,
    and inverse materials design for thin-film applications.\r\nWe first introduce
    our previously developed ITR prediction framework, built upon a curated experimental
    ITR database [1] and machine learning models [2], which enables the estimation
    of ITR based on interfacial chemical and structural information. Using this framework,
    we designed thermal insulating thin films with ultra-low thermal conductivities [3,4].\r\nBuilding
    on this foundation, we developed predictive models for bulk thermal conductivity
    using periodic descriptors [5], trained on inorganic compounds from the AtomWork-Adv.
    (AWA) database [6]. These compact and chemically meaningful descriptors enable
    efficient learning, achieving a prediction accuracy of R² ~0.8 for bulk thermal
    conductivity. Applying these models, we screened over 150,000 known materials
    in AWA and explored potential multi-element (>5) compositions for low thermal
    conductivity. While none of the screened materials fully satisfied practical constraints
    such as non-toxicity and low cost, the approach identified unexplored compositional
    systems worthy of further investigation.\r\nExperimental validation of these candidates
    is currently underway in collaboration with thin-film fabrication teams. This
    integrated pipeline—combining ITR modeling, bulk thermal property prediction,
    and multi-element composition design—offers a promising pathway toward the development
    of next-generation thermal management materials."
  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
  department: Center for Basic Research on Materials/Data-driven Materials Research
    Field/Data-driven Inorganic Materials Group
- name: Michiko Sasaki
  role: author
  orcid: https://orcid.org/0000-0002-2336-5788
  organization: National Institute for Materials Science
  department: Research Center for Materials Nanoarchitectonics (MANA)/Nanomaterials
    Field/Thermal Energy Materials Group
- name: Masahiro Goto
  role: author
  orcid: https://orcid.org/0000-0002-1003-2781
  organization: National Institute for Materials Science
  department: Research Center for Materials Nanoarchitectonics (MANA)/Nanomaterials
    Field/Thermal Energy Materials Group
- name: Yibin Xu
  role: author
  orcid: https://orcid.org/0000-0001-8600-8748
  organization: National Institute for Materials Science
  department: Center for Basic Research on Materials/Data-driven Materials Research
    Field/Data-driven Inorganic Materials Group

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## Keyword

- subject: interfacial thermal resistance
  schema: not_defined
- subject: Thermal Insulating Thin Film
  schema: not_defined
- subject: Data-Driven Design
  schema: not_defined
- subject: Multi-Element
  schema: not_defined
- subject: periodic descriptor
  schema: not_defined

## Rights

- identifier: http://rightsstatements.org/vocab/InC/1.0/

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## Data origin

- data_origin_type: other

## Embargo



## Journal



## Conference

name: TACT 2025 International Thin Films Conference
start_date: 2025-10-26
end_date: 2025-10-29
identifier: https://tact2025.conf.tw/site/page.aspx?pid=901&sid=1617&lang=en

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## Funding

- identifier: JPMJCR21O2
  funder_name: Japan Science and Technology Agency (JST) CREST
- identifier: 24K07349
  funder_name: 'Grant-in-Aid for Scientific Research (C) '
- identifier: 25K08337
  funder_name: Japan Society for the Promotion of Science (JSPS)

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## Fileset

- id: 5344f2ac-55a6-460a-94ee-14926dca3a8b
  filename: TACT2025-Abstract_Wu.pdf
  content_type: application/pdf
  size: 199258
  md5: 778abf9f02d4966ab8cd5b08fa407d18

## Thumbnail

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filename: TACT2025-Abstract_Wu.pdf