Computational Multi-Models Enabled Design of Safe Sustainable Multi-Component High-Entropy Coatings

• Published in: MATEC web of conferences 2024-01, Vol.401, p.14001
• Main Authors: Fuentes Gonzalo G., Qin Yi, Dong Hanshan, Fasano Matteo, Charitidis Costas, Piticescu Radu, Koumoulos Elias P., Mekras Nikos, Lucas Stephane, Durante Sergio, Gabriel Herbert, Beregaña José Félix
• Format: Article
• Language: English
• ISSN: 2261-236X
• DOI: 10.1051/matecconf/202440114001

The project M2DESCO is directed at addressing new challenges for developing next-generation high-entropy-alloy-based multi-component green (free of toxic substances) and sustainable (rare earth free & minimum critical metal elements) coatings with predictable functionalities, performance and life - aiming at increasing wear resistance by 100%, corrosion/oxidation resistance by 50~60 %, and effectively reducing the criticality of coating materials by at least 70%. To achieve these goals, the project is to integrate artificial intelligence/machine learning AI/ML underpinned, highly effective and highly efficient Computational Modelling that is guided by a novel Safe and Sustainability by Design Framework and facilitated by high-throughput characterisations and evaluations, to speed up the material-design to coating-product development process (reducing the development cycle-time by 400~500%). At the same time, M2DESCO is to enable optimal alloy/material design and coating process optimisation for high efficiency and high quality, so to reduce the overall product manufacturing cost (due to use of the new tooling developed) by 20%. The advancement of M2DESCO will contribute significantly to combating the loss in EU region caused by corrosion and wear, to the enhancement of the global profile and leadership of the EU material modelling/research community, to strengthening of the innovation capability of the EU coating industry/business.