Elucidating Phase Transformations in Nanoscale Carbon

Shock compression can produce technologically relevant carbon nanoparticles (CNPs) by driving carbon-rich precursors to extreme temperature and pressure, inducing nucleation of liquid carbon that solidifies during post-shock expansion. This route is appealing relative to low-pressure methods because it is orders of magnitude faster and potentially tunable via shock strength, duration, and compression/expansion rates. However, the rapid nature of this process has hindered experimental characterization efforts, precluding the mechanistic understanding needed for tunable deployment. To address this gap, we present machine-learning-accelerated atomistic simulations that probe (1) how particle size drives shifts in the high-pressure CNP phase diagram, and (2) mechanisms and kinetics of CNP solidification. Ultimately, these insights can help guide future shock-experiments to enable tunable synthesis of these materials.