Calculation of the Detonation State of HN3 with Quantum Accuracy

Abstract

<div>HN<sub>3</sub> is a unique liquid energetic material that exhibits ultrafast detonation chemistry and a transition to metallic states during detonation. We combine the ChIMES many-body reactive force field and the extended-Lagrangian multiscale shock technique (MSST) molecular dynamics method to calculate the detonation properties of HN<sub>3</sub> with the accuracy of Kohn-Sham density-functional theory. ChIMES is based on a Chebyshev polynomial expansion and can accurately reproduce density-functional theory molecular dynamics (DFT-MD) simulations for a wide range of unreactive and decomposition conditions of liquid HN<sub>3</sub>. We show that addition of random displacement configurations and the energies of gas-phase equilibrium products in the training set allows ChIMES to efficiently explore the complex potential energy surface. Schemes for selecting force field parameters and the inclusion of stress tensor and energy data in the training set are examined. Structural and dynamical properties, as well as chemistry predictions for the resulting models are benchmarked against DFT-MD. We demonstrate that the inclusion of explicit four-body energy terms is necessary to capture the potential energy surface across a wide range of conditions. The present force field, which was fit to a balance of forces, energies, and stress tensors yields excellent agreement with DFT, while exhibiting an orders-of-magnitude increase in computational efficiency over DFT-MD. Our results generally retain the accuracy of DFT-MD while yielding a high degree of computational efficiency, allowing simulations to approach orders of magnitude larger time and spatial scales. The techniques and recipes for MD model creation we present allow for direct simulation of nanosecond shock compression experiments and calculation of the detonation properties of materials with the accuracy of Kohn-Sham density-functional theory.</div>

Machine‐Learning a Solution for Reactive Atomistic Simulations of Energetic Materials

“…To overcome this challenge, advanced linear solvers are employed, (e. g., LARS and LASSO) [53][54][55] which use absolute value-based regularization to automatically set parameters deemed inconsequential to zero; this has the effect of decreasing model size while increasing both stability and computational efficiency. Note that these algorithms can be distributed for application to large fitting problems (e. g., 10 4 -10 5 parameters) [23].…”

“…More recently, ChIMES models have been created to study shocked liquid hydrazoic acid (HN 3 , i. e., the simplest covalent azide-based EM) for which previous DFTB MSST simulations suggested rapid detonation chemistry [50]. In a previous study [23], a ChIMES model capable of accurately reproducing DFT-predicted material structure, dynamical properties, and chemistry for a wide range of unreactive and decomposition conditions of liquid HN 3 was developed. This model was then leveraged in MSST simulations to study shockwave-driven detonation of liquid HN 3 .…”

“…In contrast, ML-IAPs use a collection of basis functions to represent the potential energy and contain many more parameters (e. g., typically in the range 10 3 -10 5 ) than is typical for MM-IAPs, making them profoundly more flexible. For example, a single ML-IAP framework can be used to describe non-reactive, reactive, metallic, and/or insulating systems [20][21][22][23], whereas MM-IAPs generally require a different set of equations to describe each different system class. Note that this flexibility is particularly helpful in cases where the appropriate function form isn't known a priori, which is particularly relevant for the extreme conditions produced by functioning energetic materials.…”