Tushar Kanti Mandal

This research focuses on developing a robust phase field model to predict and enhance the corrosion resistance of coatings for biomedical applications, particularly in magnesium (Mg) alloys. These alloys offer excellent mechanical properties and biocompatibility but suffer from accelerated corrosion due to low electronegativity. The study investigates the interplay between pitting corrosion, micro-crack formation, and the breakdown of impermeable Mg(OH)₂ layers, linking these mechanisms to non-uniform corrosion behavior. It incorporates the effects of coating microstructure, alloy composition, and biological factors. Virtual testing of coated substrates under physiological conditions will assess performance from lab-scale specimens to real-scale implants. The ultimate goal is to design next-generation coatings that inhibit corrosion, improving the durability and serviceability of biomedical implants.

This research aims to develop a multiscale modelling framework to predict fracture and fatigue behaviour in additively manufactured (AM) and repaired components. Addressing challenges such as microstructural heterogeneities, residual stresses, and defects, the model integrates crystal plasticity for micro-scale analysis and phase-field fracture methods for macro-scale failure predictions. By coupling fatigue indicators with adaptive numerical techniques, the framework captures crack initiation, propagation, and structural integrity under operational conditions. This approach provides a computationally efficient tool for optimising AM processes and repair strategies, ensuring safe and reliable applications in aerospace, automotive, energy, and space industries.