Exploring scenarios for enhanced fuel compression and performance on the National Ignition Facility with machine-learning-aided design techniques

• Published in: Physics of plasmas Vol. 32; no. 4
• Main Authors: Schmit, P. F., Weber, C. R., Clark, D. S., Kritcher, A. L., MacLaren, S. A.
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01.04.2025
• Subjects: Ablation; Compressive strength; Density; Design improvements; Design optimization; Fuels; Ignition; Implosions; Machine learning; Melting; Payloads; Physics; Statistical models; Workflow

Recent fusion experiments on the National Ignition Facility (NIF) have achieved ignition, producing multi-MJ fusion yields for input laser energies of roughly 2 MJ [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Building on the success of the target designs that have achieved ignition, w...