aceMachine-Learning-Driven Simulations of Hyperthermal Atomic Oxygen Impacts on (0001) Al2O3 for Low-Altitude Satellite Design
In Very Low Earth Orbit (VLEO), spacecraft encounter residual atmosphere primarily composed of atomic oxygen (AO). The drag and operational lifetime of these spacecraft are determined by the interaction between AO and the surface, which for aluminum is a passivation layer of Al2O3. We present a blueprint for developing machine-learned interatomic potentials for reactive gas-surface systems. Gaussian-Moment Neural Networks, implemented in apax, are trained using an active learning workflow that incorporates a spi…
Machine-learned interatomic potentials with spin-state switching simulate thousands of orbital-velocity oxygen impacts at near-first-principles accuracy, at far lower cost than ab initio dynamics, and expose flaws in conventional drag assumptions.
The simulated accommodation coefficient of 0.61 for an atomically smooth alumina surface is lower than values measured on real spacecraft, and the drag reproduction is only within a factor of 1.8.
Evidence
- Peer-reviewedACS Applied Materials & Interfaces2026-10-08
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Truvace Impact Record TRV-2026-1717, v1: “Machine-Learning-Driven Simulations of Hyperthermal Atomic Oxygen Impacts on (0001) Al2O3 for Low-Altitude Satellite Design.” Truvace, 2026-10-17. /record/TRV-2026-1717 (accessed at citation time). sha256 df627f38b6146794…
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