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Fried, Laurence E. (ORCID:0000000294377700)

Publications and source records attributed to Fried, Laurence E. (ORCID:0000000294377700).

Temperature-based reactive flow model for triaminotrinitrobenzene (TATB) plastic bonded explosives

A new reactive flow model is presented for triaminotrinitrobenzene (TATB)-based plastic bonded explosives, applicable to shock initiation and steady detonation problems of differing initial temperature. Temperature disequilibrium is assumed between unreacted explosive, material in the vicinity of compressed defects (called hot spots), and reaction products. The model incorporates temperature-dependent decomposition reaction rates. Particularly, Arrhenius model parameters were derived from quantum-based molecular dynamics simulations of TATB decomposition. Further, a model of detonation carbon aggregation is incorporated, describing the slow release of energy inherent to detonation in TATB-based materials. Model parameters were calibrated against gas gun shock initiation experiments and steady detonation rate stick tests. The predictive ability of the model in the shock initiation regime is tested against recent thin pulse experiments. The model is found to perform equally well in predicting the size-effect curve of ambient, cold, and hot rate sticks. The present work demonstrates the viability of incorporating results from subscale simulations into a continuum-scale reactive flow model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗