Abstract
Multiscale polymer composite coatings offer a powerful route to engineer surfaces with multiple functionalities, including enhanced mechanical performance, tailored wettability, antimicrobial activity and improved durability. However, their performance depends on complex interactions between filler size, morphology, concentration, dispersion, processing conditions and the resulting surface and interfacial characteristics. These coupled effects make conventional trial-and-error optimisation time consuming and often limit reliable performance prediction.
This study explores how artificial intelligence and machine learning can support a more predictive approach to surface engineering. Experimental datasets generated from nano- and micro-reinforced polymer coatings can be combined with compositional, processing and surface descriptors to predict key performance metrics such as hardness, elastic modulus, creep resistance, contact angle and antimicrobial response. Machine learning models can also identify the most influential variables, capture nonlinear structure–property–performance relationships and support multiobjective optimisation where several coating functionalities must be balanced simultaneously.
By integrating experimental characterisation with data-driven modelling, coating development can progressively shift from empirical optimisation towards intelligent materials design. Such an approach can reduce experimental burden, accelerate materials screening and enable inverse design of coatings tailored to specific performance targets. The presentation will highlight the opportunities and challenges associated with AI-guided prediction of multifunctional coating behaviour and its potential to advance next-generation surface technologies for biomedical, manufacturing, aerospace and other high-performance engineering applications.

Biography

Dr. Jaya Verma is an Associate Professor at the Harbin Institute of Technology (HIT), China. She holds a PhD in Nanoscience and Nanotechnology and has research experience spanning nanomaterials, multifunctional polymer composite coatings, surface engineering, advanced manufacturing, and data driven materials design. She acquired 7 years of experience from reputed Universities around the world such as Indian Institute of Technology Delhi (IITD), India and London South Bank University, London (LSBU, UK) while worked on a Govt funded project from the UK funding Counsil which is administered from the University of Manchester in the UK.
Her research focuses on the development of multifunctional surfaces and coatings with enhanced mechanical, antimicrobial, superhydrophobic, corrosion resistant, and other functional properties. Her recent work also integrates artificial intelligence and machine learning with materials and manufacturing for performance prediction, optimisation, and intelligent materials design.
Dr. Verma has published extensively in international journals in the areas of nanomaterials, coatings, manufacturing, biomaterials, and AI enabled engineering, and is also an inventor on three Indian patents relating to multifunctional coatings and nanoparticle based technologies. Her current research interests include AI guided surface engineering, predictive materials modelling, multifunctional polymer composite coatings, nanomaterials, and intelligent materials design.