[14p-P07-1~61] 1 Interdisciplinary Physics and Related Areas of Science and Technology (Poster)

[14p-P07-30] Machine learning proceeds understanding of the wettability of film surfaces.

〇Ryo Taguchi¹, Kenji Koga¹, Kazuki Tajima¹ (1.AIST)

Keywords:

wettability,machine learning,surface free energy

Contact angle measurement provides a simple method for evaluating surfaces of the film. However, the specific contributions of chemical bonds and compositions to the contact angle remain unclear. We believe that quantitatively elucidating the relation between surface chemical composition and contact angle produces a simple and powerful tool for obtaining chemical composition information from contact angles. In this study, we developed a machine learning model to predict contact angles from XPS spectra. Through feature importance analysis, we discuss the chemical compositions that contribute to surface wettability.