Wettability Estimation on Polymer Film Surfaces With Artificial Neural Network Methodology

ÖZSOY S. A., AÇIKEL S. M., ULUSLU A. A., AYDEMİR C.

PLASMA PROCESSES AND POLYMERS, vol.23, no.2, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 2
  • Publication Date: 2026
  • Doi Number: 10.1002/ppap.70090
  • Journal Name: PLASMA PROCESSES AND POLYMERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Compendex, INSPEC
  • Istanbul University Affiliated: No

Abstract

When printing on polymer film surfaces with low ink acceptance, the surface energy and wettability need to be increased to achieve good adhesion. To alter the surface energy, wettability or biocompatibility of polymer films, their surfaces need to be chemically functionalized. Nevertheless, given the myriad varieties of film materials to be printed, predicting their ideal surface energy for optimal printing proves to be a challenging task. In the last part of the study, low-cost, fast, and safe artificial intelligence-based modeling was used to predict the wettability, without performing contact angle testing. By using the improved structure of the ANN, the wettability of polymer films after surface treatment can be determined simply and quickly without the need for any other tests.