In-Situ Treatment of Flexible Polylactic Acid (PLA) using Non-Thermal Plasma and Various Electrode Geometries: Towards Developing Advanced Analytical and Machine Learning based Hybrid Methodologies to Study The Wettability Characteristics usin

Polymer and polymer composite-based 3D printing processes allow users to fabricate multiple prototypes and proofs of concept, making it an excellent method for testing concepts in the early stages of development. However, the layer-by-layer printing procedure can result in issues with surface properties and the strength of the finished printed geometry, making the product an inaccurate representation of the design. The current work involves the in-situ treatment of biocompatible and flexible-PLA, with non-thermal and room-temperature microplasma-based corona discharge to address this problem and try to optimize the surface properties. The work also involves the evaluation of the effects of plasma-treated 3D printed polymer materials as compared to non-treated samples. This will involve tailoring the polymer properties in the layer-by-layer process to create stronger and more cohesive bonds between each layer through the modification of the surface characteristics of each of the printed layers. Advanced hybrid machine learning models will be developed in combination with analytical methods and empirical data sets to develop strategies for tailoring surface properties of these materials. Additionally, the work involves the characterization of the surface electrical properties using impedance spectroscopy, surface energy and topographical properties using profilometry, and hydrophobic or hydrophilic properties using water contact angle measurements. This will provide valuable insights into the effects of room temperature-based plasma-based surface modification of the printed layers towards enhancement of surface properties of the samples and which electrode will be the most effective.