Multiscale Simulation of Nanowear-Resistant Coatings

Nanowear-resistant coatings are critical for extending the service life of mechanical components, yet their performance optimization remains challenging due to the complex interplay between atomic-scale defects and macroscopic wear behavior. While experimental characterization struggles to resolve transient interfacial phenomena, multiscale simulations, integrating ab initio calculations, molecular dynamics, and continuum mechanics, have emerged as a powerful tool to decode structure-property relationships. This review systematically compares mainstream computational methods and analyzes their coupling strategies. Through case studies on metal alloy nanocoatings, we demonstrate how machine learning-accelerated simulations enable the targeted design of layered architectures with 30% improved wear resistance. Finally, we propose a protocol combining high-throughput simulation and topology optimization to guide future coating development.