Thermal transport in warm dense matter revealed by refraction-enhanced x-ray radiography with a deep-neural-network analysis

Autor: S. Jiang, O. L. Landen, H. D. Whitley, S. Hamel, R. London, D. S. Clark, P. Sterne, S. B. Hansen, S. X. Hu, G. W. Collins, Y. Ping
Rok vydání: 2023
Předmět:
Zdroj: Communications Physics. 6
ISSN: 2399-3650
DOI: 10.1038/s42005-023-01190-4
Popis: Transport properties of high energy density matter affect the evolution of many systems, ranging from the geodynamo in the Earth’s core, to hydrodynamic instability growth in inertial confinement fusion capsules. Large uncertainties of these properties are present in the warm dense matter regime where both plasma models and condensed matter models become invalid. To overcome this limit, we devise an experimental platform based on x-ray differential heating and time-resolved refraction-enhanced radiography coupled to a deep neural network. We retrieve the first measurement of thermal conductivity of CH and Be in the warm dense matter regime and compare our measurement with the most commonly adopted models. The discrepancies observed are related to the estimation of a correction term from electron-electron collisions. The results necessitate improvement of transport models in the warm dense matter regime and could impact the understanding of the implosion performance for inertial confinement fusion.
Databáze: OpenAIRE
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