Enabling accurate chemical modeling of shocked energetic materials using a machine learning interatomic potential

Pham, Cong Huy; Goldman, Nir; Fried, Laurence E.; Lindsey, Rebecca K.; Gaffney, Jim A.; Bremer, Peer-Timo

doi:10.1063/5.0312621

Title: Enabling accurate chemical modeling of shocked energetic materials using a machine learning interatomic potential

Journal Article · Fri Feb 13 00:00:00 UTC 2026 · Journal of Chemical Physics

DOI: https://doi.org/10.1063/5.0312621 · OSTI ID:3022615

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Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Univ. of California, Davis, CA (United States)
Univ. of Michigan, Ann Arbor, MI (United States)

Understanding the complex chemistry of organic materials under dynamic compression is important for many applications, but it is challenging due to the large number of reactions occurring at various time scales. Here, in this study, we develop a machine learning potential based on Chebyshev polynomials to study the insensitive energetic material 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) under detonation. We discuss a strategy for constructing diverse training data needed to capture the complex chemistry of TATB. Our potential demonstrates strong transferability across a wide range of thermodynamic conditions and other explosives, enabling accurate and reliable chemical modeling of organic materials under extreme conditions. The efficiency of our approach allows for simulations over several nanoseconds and for large system sizes, providing detailed insights into the chemistry of shocked TATB. The model accurately reproduces experimental Hugoniot equation of state data, and our simulations reveal the rapid formation of nitrogen-rich carbon clusters following shock. The methods and datasets developed here offer a robust framework for accurate chemical modeling of other shocked organic energetic materials.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 3022615

Report Number(s):: LLNL--JRNL-2012577

Journal Information:: Journal of Chemical Physics, Journal Name: Journal of Chemical Physics Journal Issue: 6 Vol. 164; ISSN 1089-7690; ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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