Machine Learning Accelerated Design and Discovery of Rare-earth Phosphates as Next Generation Environmental Barrier Coatings
Environmental barrier coatings (EBCs) are key components that can greatly enhance the performance/longevity of structural materials such as ceramic-matrix composites against active oxidation in high speed hot gas streams and corrosion in reactive engine environments. Multi-generation EBCs have evolved, mainly based on silicate-based systems, but they suffer from the volatility of silicon due to water vapor attack and corrosion of molten glass attack. Innovative design and discovery of EBCs with transformative performance are needed to meet even harsher environments of high temperature, high thermal flux and severe oxidation and corrosion for future aerospace and space systems.
This Designing Materials to Revolutionize and Engineer our Future (DMREF) project will explore an innovative concept of using multiple component rare-earth phosphates as advanced EBCs, and develop a science-based paradigm guided by machine learning (ML) for accelerated materials design and discovery. Both graduate and undergraduate students will be trained as the next-generation workforce in this data-driven materials research. K-12 students and underrepresented groups will be engaged through multiple outreach activities such as the Engineering Summer Exploration program at Rensselaer and the New Visions: Math, Engineering, Technology & Science program. Materials data and computational tools developed will be contributed to the MPContribs Portal for public access on the Materials Project platform to facilitate data-driven material design.