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Energetic Materials

Energetic materials comprise explosives, pyrotechnics, and propellants. The science of energetic materials is dedicated to developing a means to predict performance and safety characteristics with high fidelity. This is a particular challenge and is predicated on materials science and engineering, physics, chemistry, and dynamic response in extreme conditions. Fundamental elements of these complicated composite materials remain grand challenges—from the design of high-energy metastable molecules, to the engineering of composite formulations, to the processing parameters that link to safety and performance characteristics in as-yet undetermined ways. Key elements include crystalline mechanics, grain dynamics, multiphase interfaces, thermal and mechanical damage, and failure—all linked to multistep and high-rate chemistry and shock physics. A future revolution in our understanding and predictive capability for energetic materials behavior and responses is dependent upon sustained focus and advances in materials research and development.

36 MATERIALS SCIENCE↗

The Effects of Shockwave Pressures on Ultrafast Vibrational Energy Transfer in BNFF, a Hydrogen-Free Energetic Material

Energy conversion in energetic materials from shock-wave-induced lattice compression to bond breaking critically depends on vibrational coupling and energy transfer between intra- and intermolecular vibrations, though the details of the mechanisms remain unknown. Herein, we indirectly tune the strength of intermolecular interactions in 3,4-bis(3-nitrofurazan-4-yl)furoxan (BNFF), a hydrogen-free energetic material characterized by van der Waals interactions, by applying high static pressure using a diamond anvil cell and monitoring vibrational energy transfer (VET) with ultrafast broadband infrared pump–probe spectroscopy. As BNFF is compressed from ambient pressure to 9 GPa, we find that VET accelerates by ∼ 0.9 ps/GPa. Density functional theory is applied in tandem with experiments to assign mode character and elucidate VET pathways. In conclusion, we find that furazan ring O–N–O vibrations, which are high-frequency detonation-relevant vibrational modes, experience increased sensitivity to lattice compression under shockwave pressures. These findings provide new mechanistic insight into how intermolecular interactions govern the rate and selectivity of VET.

Energy transfer↗

Toward a machine-guided approach to energetic material discovery

In this article, we trained a machine learning (ML) model to connect microstructural details of an energetic material formulation to its performance for the purpose of guiding the discovery of new explosive formulations. Our hypothesis was that the algorithm would robustly learn the training data and produce an accurate surrogate model. Specifically, the algorithm learned the relationship between details of the void size distribution (VSD), initiating shock pressure, and the energetic material performance. We used realistic constraints on the VSD and a range of cases were ingested by a physically informed reactive flow model working within a hydrodynamic solver running on high-performance computing resources. The ML algorithm produced a surrogate model that accurately predicted known test points around the parameter space. In addition to the utility of the model and the process used for its development, we noted interesting comparisons between what we, the authors—subject matter experts, would heuristically conclude from the training data and the surrogate model predictions. We detected nuanced details that were missed by the surrogate model; however, these details are not important to an energetic material formulator. We concluded that the algorithm did indeed robustly learn the training data and produce an accurate surrogate model. We further concluded that the surrogate model is a powerful tool to guide the formulator in the absence of subject matter experts and limited-access computing resources.

42 ENGINEERING↗

Exploring pressure-dependent inelastic deformation and failure in bonded granular composites: An energetic materials perspective

In polymer-filled granular composites, damage may develop in mechanical loading prior to material failure. Damage mechanisms such as microcracking or plastic deformation in the binder phase can substantially alter the material’s mesostructure. For energetic materials, such as solid propellants and plastic bonded explosives, these mesostructural changes can have far reaching effects including degraded mechanical properties, potentially increased sensitivity to further insults, and changes in expected performance. Unfortunately, predicting damage is nontrivial due to the complex nature of these composites and the entangled interactions between inelastic mechanisms. In this work, we assess the current literature of experimental knowledge, focusing on the pressure-dependent shear response, and propose a simple simulation framework of bonded particles to study four limiting-case material formulations at both meso- and macro-scales. Further, to construct the four cases, we systematically vary the relative interfacial strength between the polymer binder and granular filler phase and also vary the polymer’s glass transition temperature relative to operating temperature which determines how much the binder can plastically deform. These simulations identify key trends in global mechanical response, such as the emergence of strain hardening or softening regimes with increasing pressure which qualitatively resemble experimental results. By quantifying the activation of different inelastic mechanisms, such as bonds breaking and plastically straining, we identify when each mechanism becomes relevant and provide insight into potential origins for changes in mechanical responses. The locations of broken bonds are also used to define larger, mesoscopic cracks to test various metrics of damage. We primarily focus on triaxial compression, but also test the opposite case of triaxial extension to highlight the impact of Lode angle on mechanical behavior.

36 MATERIALS SCIENCE↗

Coupled thermal/chemical/mechanical modeling of energetic materials in ALE3D

We must improve our ability to model the response of energetic materials to thermal stimuli and the processes involved in the energetic response. We have developed and used a time step option to efficiently and accurately compute the hours that the energetic material can take to react. Since on these longer film scales, materials can be expected to have significant motion, it is even more important to provide high-order advection for all components, including the chemical species. We show an example cook-off problem to illustrate these capabilities.

WEAPONS↗

An Eulerian crystal plasticity framework for modeling large anisotropic deformations in energetic materials under shocks

Here, this paper demonstrates a novel Eulerian computational framework for modeling anisotropic elastoplastic deformations of organic crystalline energetic materials (EM) under shocks. While Eulerian formulations are advantageous for handling large deformations, constitutive laws in such formulations have been limited to isotropic elastoplastic models, which may not fully capture the shock response of crystalline EM. The present Eulerian framework for high-strain rates, large deformation material dynamics of EM incorporates anisotropic isochoric elasticity via a hypo-elastic constitutive law and visco-plastic single-crystal models. The calculations are validated against atomistic calculations and experimental data and benchmarked against Lagrangian (finite element) crystal plasticity computations for shock-propagation in a monoclinic organic crystal, octahydro-1,3,5,7-tetranitro-1,3,5,7 tetrazocine (β-HMX). The Cauchy stress components and the resolved shear stresses calculated using the present Eulerian approach are shown to be in good agreement with the Lagrangian computations for different crystal orientations. The Eulerian framework is then used for computations of shock-induced inert void collapse in β-HMX to study the effects of crystal orientations on hotspot formation under different loading intensities. The computations show that the hotspot temperature distributions and the collapse profiles are sensitive to the crystal orientations at lower impact velocities (viz., 500 m/s); when the impact velocity is increased to 1000 m/s, the collapse is predominantly hydrodynamic and the role of anisotropy is modest. The present methodology will be useful to simulate energy localization in shocked porous energetic material microstructures and other situations where large deformations of single and polycrystals govern the thermomechanical response.

42 ENGINEERING↗

Understanding Trigger Linkage Dynamics in Energetic Materials Using Mixed Picramide Nitrate Ester Explosives

The ability to predict the handling sensitivity of new organic energetic materials has been a longstanding goal. We report the synthesis and characterization of six new nitropicramide energetic materials with mixed functional groups that mimic known explosives such as nitroglycerin, erythritol tetranitrate (ETN), and pentaerythritol tetranitrate (PETN). The molecules have been studied theoretically using quantum molecular dynamics (QMD) simulations and density functional theory (DFT) calculations to identify the weakest bond in the reactants - the trigger-linkages - which control handling sensitivity, and to quantify their specific enthalpies of explosion. In good accord with the drop weight impact sensitivity data, our calculations predict that the sensitivities of the molecules are very similar owing to the small variations of the energy output and rates of trigger linkage rupture. In addition, both the QMD and DFT calculations point to the nitropicramide N–NO 2 bonds as the trigger linkages rather than the more typical O–NO 2 bonds. We propose that the switch of the trigger linkage from the nitrate esters to the nitramine groups arises from the strongly electron withdrawing character of the adjacent trinitrobenzene groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗

Revolutionizing Energetic Materials Discovery and Design: The Role of Data Science and Machine Learning

Here this Special Issue of Propellants, Explosives, Pyrotechnics (PEP) is focused on energetic materials discovery and design using Data Science and Machine Learning (DS&ML). The application of DS&ML has proven to be transformative in many areas, where it has been shown to expedite analysis, enable extraction of greater quantities of information from datasets, and guide experiments. However, energetic materials and their applications present unique challenges that often hinder the use of standardized tools and practices. In spite of these challenges, important and compelling advancements are being made toward data-directed research in energetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Embracing Anisotropy – Opportunities and Challenges to the Functional Application of Advanced Manufacturing of Energetic Materials

The growing use of additive manufacturing (AM) to manipulate materials, such as metals and plastics, is a result of the desire to realize the potential benefits (i.e., cheaper, faster, and simpler production of complex parts) of the process and the efforts of countless researchers to reduce the method to practice for a broad range of materials. However, in the field of energetic materials (EMs), similar benefits have been broadly claimed, but the transition to practical, industrial applications is still not obvious. The translation of small-scale experimental results to real-world application will have unique challenges, especially due to the nature and requirements of EM functionality. Some of the benefits of AM, such as simpler and faster part creation, are more easily realized. However, attaining the most profound benefits, such as added functionality enabled by spatial gradations of composition or density, will require much more effort from the EMs community to put them into general use.

36 MATERIALS SCIENCE↗

Shock Sensitivity of energetic materials

Viscoplastic deformation is examined as the principal source of hot energy. Some shock sensitivity data on a proposed model is explained. A hollow sphere model is used to approximate complex porous matrix of energetic materials. Two pieces of shock sensitivity data are qualitatively compared with results of the proposed model. The first is the p2 tau law. The second is the desensitization of energetic materials by a ramp wave applied stress. An approach to improve the model based on experimental observations is outlined.

Kim, K.↗

Publishing Challenges in Energetic Materials Science

The editorial addressed the ethical dilemma that energetic materials scientists face in advancing their field for societal good and not providing information that could be used for nefarious purposes. The reaction to the editorial was heated, both pro and con. Here we concluded that PEP had done a good job in catalyzing a thoughtful debate in our community about what information should or should not be published.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of Probabilistic Shock Initiation Thresholds of Energetic Materials Through Evolution of Thermal-Mechanical Dissipation and Reactive Heating

The ignition threshold of an energetic material (EM) quantifies the macroscopic conditions for the onset of self-sustaining chemical reactions. The threshold is an important theoretical and practical measure of material attributes that relate to safety and reliability. Historically, the thresholds are measured experimentally. In this work, we present a new Lagrangian computational framework for establishing the probabilistic ignition thresholds of heterogeneous EM out of the evolutions of coupled mechanical-thermal-chemical processes using mesoscale simulations. Furthermore, the simulations explicitly account for microstructural heterogeneities, constituent properties, and interfacial processes and capture processes responsible for the development of material damage and the formation of hotspots in which chemical reactions initiate. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, heat conduction, reactive chemical heating, gaseous product generation, and convective heat transfer. To determine the ignition threshold, the minimum macroscopic loading required to achieve self-sustaining chemical reactions with a rate of reactive heat generation exceeding the rate of heat loss due to conduction and other dissipative mechanisms is determined. Probabilistic quantification of the processes and the thresholds are obtained via the use of statistically equivalent microstructure sample sets (SEMSS). The predictions are in agreement with available experimental data.

36 MATERIALS SCIENCE↗

Investigation into the Synthesis of Several TATB-Inspired Energetic Materials

The synthesis and characterization of several TATB-inspired energetic materials was explored. Despite their structural similarity to TATB, their behavior toward traditional synthetic pathways deviates significantly from that of the parent material. This change in expected reactivity is discussed and an efficient alternative synthesis is reported. The development of a simple and effective route to these TATB-type compounds opens the door to a potential new class of insensitive high explosives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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

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.

Chemistry↗

Effect of void positioning on the detonation sensitivity of a heterogeneous energetic material

We show although it is well-established that voids profoundly influence the initiation and reaction behaviors of heterogeneous energetic materials such as polymer-bonded explosives (PBX) and propellants, there has been little study of how void location in different constituents in the microstructures of such materials affect the macroscale behavior. Here, we use three-dimensional (3D) mesoscale simulations to study how void placement within the reactive grains versus the polymer binder influences the shock-to-detonation transition (SDT) in a polymer-bonded explosive. The material studied here has a microstructure comprised of 75% PETN (pentaerythritol tetranitrate) grains and 25% HTPB (hydroxyl-terminated polybutadiene) polymer binder by volume. Porosities up to 10% in the form of spherical voids distributed in both the grains and polymer are considered. An Arrhenius reactive burn relation is used to model the chemical kinetics of the PETN grains under shock loading, thereby resolving the heterogeneous detonation behavior of the PBX. The influence of void location on the shock initiation sensitivity of the material is quantitatively ranked by comparing the predicted run distance to detonation (RDD) for each sample. The analysis includes inherent quantification of uncertainties arising from the stochastic variations in the microstructure morphologies and void distributions by using statistically equivalent microstructure sample sets (SEMSS), leading to probabilistic formulations for the RDD as a function of shock pressure. The calculations reveal that the location of voids in the composite microstructure significantly affects the RDD. Specifically, voids exclusively within the grains cause the PBX to be more sensitive (having shorter RDD) than voids in the polymer binder. Unique probabilistic relationships are derived to map the probability of observing RDD for each void location material case, allowing for prediction of initiation behavior anywhere in the shock pressure – RDD space. These findings agree with trends reported in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Apparatus for skidding sensitivity testing of energetic materials

A remote-operated apparatus for testing the detonation sensitivity of energetic materials is detailed. Using an air ram and rotating disk, the normal force and transverse velocity of the impact plane are controlled independently, enabling the exploration of varying impact conditions over a wide parameter space. A microcontroller local to the apparatus is used to automate apparatus operation and ensure temporal alignment of the impacting ram head with the rotating disk. Calculation of the firing parameters and issuing of operational commands are handled by a remote computer and relayed to the local microcontoller for execution at the hardware level. Finally, impact forces are taken from fast strain measurements obtained from gauges incorporated into the ram head. Infrared imaging of explosive samples provides insight to the peak thermal temperatures experienced at the sample surface during the impact event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗