A small-data-driven model for predicting adsorption properties in polymeric thin films. Issue 78 (9th September 2022) - Han, Uiyoung; Kang, Taegyu; Im, Jongho; Hong, Jinkee
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.