Space research is becoming rapidly important for national security, scientific exploration and space commercialization. One bottleneck to enabling next-generation space technologies is the lack of predictive models and efficient discovery tools for advanced functional materials that can withstand the extreme space environments. This inefficiency is often a result of the overwhelmingly large space of candidate materials, which is often sparsely observed, even more so in the expected operating conditions. Additionally, the high cost associated with experimental characterization and first principles quantum mechanical calculations restricts the size of the available datasets. In light of these challenges, our vision is to accelerate the modeling and discovery of transformative materials by leveraging latest machine learning techniques, high-throughput computing and atomistic modeling. Our main focus lies in advancing energy technologies and thermal protection systems for space and hypersonic applications. Few directions we are looking at include:
Study of interactions between energy harvesting materials with high-energy protons for energy applications in space environments.
Development of physics-driven multi-objective optimization strategies for materials discovery with a focus on space actuation and thermal protection systems.
Development of uncertainty quantification methods for hypersonic flows and material models.