# Data-driven approaches for designing thermal insulating materials

https://mdr.nims.go.jp/datasets/5b0ed1d9-24b5-46aa-a76b-11cec74260cf

## File

- [Abstract for 7th Academic Collaboration Seminar.pdf](https://mdr.nims.go.jp/filesets/5b161366-364e-4548-8daa-428ead230c41/download) ([Detail](https://mdr.nims.go.jp/filesets/5b161366-364e-4548-8daa-428ead230c41.md))

## Id

5b0ed1d9-24b5-46aa-a76b-11cec74260cf

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-12-20T01:28:39.421033Z

## Updated at

2024-12-25T07:30:37.078908Z

## Published at

2024-12-25T07:30:37.266729Z

## Doi

https://doi.org/10.48505/nims.5218

## First published url



## Date published



## Recorded date published



## Resource type

conference_presentation

## Manuscript type

na

## Collection



## Title

- title: Data-driven approaches for designing thermal insulating materials
  title_type: original
  lang: en

## Description

- description: "The design of high-performance thermal insulating materials is crucial
    for efficient thermal management in modern applications. This presentation highlights
    how data-driven methodologies, particularly machine learning, can accelerate the
    development of thermal insulators by integrating experimental data with predictive
    modeling techniques. A key focus is the creation of accurate models for interfacial
    thermal resistance (ITR), which combine experimental measurements and machine
    learning algorithms to optimize heat flow across material interfaces.\r\nCase
    studies will be presented to demonstrate the application of these models to thin-film
    thermal insulators, showcasing how data-driven strategies identify critical structural
    and material parameters that improve performance. By leveraging high-throughput
    analysis and experimental insights, these approaches provide a framework for rapidly
    designing materials with tailored thermal properties. This work underscores the
    transformative potential of data-driven innovation in addressing design challenges
    and advancing sustainable solutions in energy and thermal management."
  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: 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

## Contact agent



## Publisher



## Managing organization



## Keyword

- subject: Interfacial thermal resistance
  schema: not_defined
- subject: machine learning
  schema: not_defined
- subject: thermal insulator
  schema: not_defined
- subject: data-driven technique
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal



## Conference

name: 7th Academic Collaboration Seminar (ACS) NTUST - NIMS  workshop
start_date: 2024-12-18
end_date: 2024-12-18

## Related item



## Funding



## 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



## Software



## Custom property



## Fileset

- id: 5b161366-364e-4548-8daa-428ead230c41
  filename: Abstract for 7th Academic Collaboration Seminar.pdf
  content_type: application/pdf
  size: 105916
  md5: 1f9f9d5dcdf4f8b05d2398eeeba16d4f

## Thumbnail

fileset_id: 5b161366-364e-4548-8daa-428ead230c41
filename: Abstract for 7th Academic Collaboration Seminar.pdf