A small-data-driven model for predicting adsorption properties in polymeric thin films. Issue 78 (9th September 2022)

• Record Type: Journal Article
• Authors: Han, Uiyoung; Kang, Taegyu; Im, Jongho; Hong, Jinkee
• Is Part Of: Chemical communications. Volume 58:Issue 78(2022)
• Page Start: 10953
• Page End: 10956
• Publication Date: 2022-09-09
• Subjects: Chemistry -- Periodicals; 540
• DOI: 10.1039/d2cc03567g
• Languages: English
• ISSNs: 1359-7345

Abstract

Abstract : By performing regression analysis of the adsorption of a polymer, predictive modeling of the properties of a thin film even with a small data set is possible. 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.