ABSTRACT: The space industry is experiencing unprecedented growth with projections of more than 200,000 satellite launches in the next decade. Most new spacecraft rely on electric (plasma) thrusters, making plasma propulsion a key technology for both Low-Earth Orbit operations and deep space exploration. Computational modeling is a powerful tool for better understanding of the physical mechanism and design of high-performance devices. However, despite the ever-increasing compute power, a consistent simulation at all levels is difficult due to the extremely complex dynamics of multi-component plasmas interacting with bounding surfaces.

In this talk, I will introduce a new class of high-fidelity models of plasmas based on my personal experience on plasma dynamics, chemical and surface kinetics. Three main areas will be explored in the talk, that are (1) extraction of fundamental data and data needs for plasma models, (2) fast and accurate numerical algorithms for plasma kinetics, and (3) high-fidelity models for plasma-material interaction. The models are applied and validated against experimental data in a wide variety of plasmas, including direct-current (DC), radio-frequency (RF), and microwave plasmas.

Finally, I will introduce new challenges and research opportunities for development of unbiased data-driven surrogate models to understand the interplay between surface kinetics and plasma dynamics, which is essential for developing new plasma-based propulsion systems

BIOSKETCH: Luca Vialetto is a Stanford Energy Postdoctoral Fellow in the Department of Aeronautics and Astronautics, specializing on plasma modeling for aerospace. He earned his Ph.D. in Applied Physics from the Eindhoven University of Technology (Netherlands) in 2021, where he focused on plasma models for In-Situ Resource Utilization. Before joining Stanford, he was a postdoctoral researcher at Kiel University (Germany), working on machine learning to enhance low-temperature plasma models. His research interests span computational plasma physics and chemistry, data-driven models, surface kinetics, and electric propulsion. Vialetto is a board member of the Plasma Data Exchange Project (LXCat team), which facilitates the collection, distribution, and open-source sharing of data for low-temperature plasma modeling. He has received international awards, including the 2021 Student Award for Excellence given by the American Physical Society, and the 2023 Rutherford Plasma Physics Communication Prize given by IOP Publisher (Oxford).