A small-data-driven model for predicting adsorption properties in polymeric thin films

Uiyoung Han, Taegyu Kang, Jongho Im, Jinkee Hong

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial intelligence allowing data-driven prediction of physicochemical properties of polymers is rapidly emerging as a powerful tool for advancing material science. Here, we developed a methodology to use polymer adsorption data as predictable data by analyzing causal relationships between polymer properties and experimental results instead of using big polymer data.

Original languageEnglish
Pages (from-to)10953-10956
Number of pages4
JournalChemical Communications
Volume58
Issue number78
DOIs
Publication statusPublished - 2022 Aug 31

Bibliographical note

Publisher Copyright:
© 2022 The Royal Society of Chemistry.

All Science Journal Classification (ASJC) codes

  • Catalysis
  • Electronic, Optical and Magnetic Materials
  • Ceramics and Composites
  • Chemistry(all)
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Materials Chemistry

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