Abstract Nanoindentation with a Knoop indenter tip can reveal the plastic response of brittle materials, which is contained in the measured Knoop hardness anisotropy and force–displacement curves. Due to short length scales, details of the local dislocation distribution and dislocation stresses cannot be ignored in the analysis of experimental measurements. Inclusion of such effects leads to a non-local theory of plasticity, where gradients of strain fields are present in the expressions for stress. In this work, a non-local plasticity model is developed and implemented in the Abaqus finite element software. The geometrically necessary dislocations (GND) are quantified via the Nye tensor, and the backstress tensor is found from gradients of the Nye tensor by summation of dislocation stresses. Micro- and nanoindentation experiments on pentaerythritol tetranitrate (PETN) are simulated with the developed model. The average errors between simulated and measured micro- and nanohardness are around 13% and 25%, respectively, while the maximum errors are around 20% and 30%, respectively. The set of active slip systems for PETN that can match the experimental hardness anisotropy trends is { 110 } ⟨ 1 1 ¯ 1 ⟩ , { 100 } ⟨ 011 ⟩ , and { 101 } ⟨ 10 1 ¯ ⟩ . The GND hardening, the backstress, and the indenter shape are investigated in relation to the indentation size effects. The model predicts a weak effect of backstress on hardness, while the coupled effects of indenter shape and GND hardening are predominantly responsible for predicted size effects.

Critical temperatures for the ignition of cylindrical hot spots up to 0.5 μm in diameter in the secondary explosive cyclotetramethylene tetranitramine (HMX) have been computed using the kinetic Monte Carlo (kMC) method. By combining the thermal bit transfer model with effective single-step Arrhenius kinetics for the onset of thermal explosion, we are able to observe the homogeneous nucleation and growth of sustained deflagration reactions in HMX at the mesoscale. The kMC simulations capture the stochastic onset of thermal explosion seen in quantum molecular dynamics simulations at the nanometer length scales that are required to adequately resolve the temperature profile across a deflagration front. Deflagration velocities and hot spot critical temperatures have been evaluated for four sets of single-step Arrhenius kinetics for HMX that account for the effects of self-heating on the acceleration of the reaction rate in different ways. It is shown that the single-step Arrhenius kinetics proposed by Manner et al., Burnham and Weese, and Henson et al. give roughly similar hot spot critical temperatures, but a reparametrization of the 2001 Henson-Smilowitz kinetics to include the effects of self-heating on the reaction rate gives rise to significantly different behavior, with hot spot critical temperatures that are about 700 K higher than those from the other models. The origins of this behavior are discussed.

Predicting the drop-weight impact sensitivity () of energetic materials accurately and efficiently is a crucial step for the design of safe explosives. Traditional experimental determination of values is costly, time-consuming, and inherently uncertain. This work presents an approach for predicting of pure molecular explosives directly from two-dimensional molecular graphs, encoded as simplified molecular-input line-entry system (SMILES) strings, using physics-informed artificial intelligence (AI) models. To address limited experimental drop-weight impact sensitivity data, we augment our dataset of experimentally measured sensitivities of 625 unique high explosive molecules with physics-informed synthetic predictions for 1 additional real molecules containing energetic functional groups. Using the existing, publicly available Chemprop software-implementing a message-passing neural network encoder and feed-forward neural network predictor-we trained a robust predictive model that improves upon existing models. The proposed approach shows a reduction in predictive error of about 10% over an existing physics-informed model, which predicts from a hand-crafted set of descriptors. Our results demonstrate the feasibility and effectiveness of leveraging publicly available chemical databases and physics-informed models for accelerating the screening of energetic materials based solely on molecular graphs.

Nanoindentation can be leveraged to aid in the high fidelity modeling of dislocation mediated plasticity in pentaerythritol tetranitrate (PETN), an anisotropic energetic molecular crystal. Moreover, nanoindentation tip parameters such as tip geometry, size, and degree of acuity can be utilized to target anisotropic behavior. In this work, nanoindentation was conducted across a range of orientations on the (110) face of PETN to characterize resultant yield behavior, mechanical property measurements, and resultant slip behavior and fracture initiation. Three different indentation tips were utilized: a 3-sided pyramidal Berkovich tip, a 4-sided high aspect ratio Knoop tip, and a 90° conical tip. Ultimately, indenter tip radius was documented to impact yield behavior, whereas tip geometry affected larger scale processes such as slip, and tip acuity was the dominating factor that led to fracture. The axisymmetric conical tip, serving as a baseline, showed the least amount of variation in mechanical property measurements but also the largest distribution of maximum shear stress at which initial yielding occurred. Its high degree of acuity, however, was more prone to induce fracture at higher loads. The Knoop tip was shown to be suitable for average measurements, but also for elucidation of certain anisotropic features. A distinctly higher perceived hardness at 45° was measured with the Knoop tip, indicating less dislocation motion in that direction also observed in this work via scanning probe microscopy. Lastly, the commonly used Berkovich tip was a good compromise whereby it provided a representative volume element describing the average behavior of the material. These results can be utilized to target desired anisotropic behavior in a wider range of molecular crystals, as well as to inform theoretical considerations for dislocation mediated plasticity in PETN.

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-NO2 bonds as the trigger linkages rather than the more typical O-NO2 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.

We present a new integrated experimental and modeling effort that assesses the intrinsic sensitivity of energetic materials based on their reaction rates. The High Explosive Initiation Time (HEIT) experiment has been developed to provide a rapid assessment of the high-temperature reaction kinetics for the chemical decomposition of explosive materials. This effort is supported theoretically by quantum molecular dynamics (QMD) simulations that depict how different explosives can have vastly different adiabatic induction times at the same temperature. In this work, the ranking of explosive initiation properties between the HEIT experiment and QMD simulations is identical for six different energetic materials, even though they contain a variety of functional groups. We have also determined that the Arrhenius kinetics obtained by QMD simulations for homogeneous explosions connect remarkably well with those obtained from much longer duration one-dimensional time-to-explosion (ODTX) measurements. Kinetic Monte Carlo simulations have been developed to model the coupled heat transport and chemistry of the HEIT experiment to explicitly connect the experimental results with the Arrhenius rates for homogeneous explosions. These results confirm that ignition in the HEIT experiment is heterogeneous, where reactions start at the needle wall and propagate inward at a rate controlled by the thermal diffusivity and energy release. Overall, this work provides the first cohesive experimental and first-principles modeling effort to assess reaction kinetics of explosive chemical decomposition in the subshock regime and will be useful in predictive models needed for safety assessments.

The rate of discovery of new explosives with superior energy density and performance has largely stalled. Rapid property prediction through machine learning has the potential to accelerate the discovery of new molecules by screening of large numbers of molecules before they are ever synthesized. To support this goal, we assembled a 21,000-molecule database of experimentally synthesized molecules containing energetic functional groups. Using a combination of experimental density measurements and high throughput electronic structure and atomistic calculations, we calculated detonation velocities and pressures for all 21,000 compounds. Using these values, we trained machine learning models for the prediction of density, detonation velocity and detonation pressure. Notably, our model for crystal density surpassed the accuracy of all current models and decreased the root-mean square error (RMSE) of the previous best model by 20%. This improvement in model performance relative to past works is attributed to our handling of chiral-specified Simplified Molecular-Input Line-Entry System (SMILES) strings and introduction of a new molecular descriptor, MolDensity. To elucidate descriptor importance, we evaluated interpretable descriptors in terms of importance and compared the accuracy of a statistics-driven machine learning model against a model comprised of descriptors typically assumed to control material density. The inexpensive, yet highly accurate predictions from our models should enable creation of future artificial intelligence (AI) models that are able to screen large numbers (>106) of compounds to find the highest performing compounds in terms of crystal density, detonation velocity and detonation pressure.

The high temperature time-to-explosion experiment developed originally by Wenograd in the late 1950s has been revisited using modern standards and diagnostics. Our new High Explosives Initiation Time (HEIT) experiment heats small, 5 mg, samples of energetic materials contained within thin stainless steel hollow needles to temperatures up to 1673 K, the melting temperature of the steel, in a few 10s of microseconds using a 250 J desktop pulsed power system. Unlike Wenograd's original experiments, we detect the onset of thermal explosion via a high speed camera and optical fibers rather than electrically via the rupture of the needle. The test allows us to reliably obtain time-to-explosion as a function of input temperature, from which effective single step Arrhenius kinetics can be derived at the temperatures relevant to both common accident scenarios and shock initiation. Here, we describe in detail the calibration of the needle temperature as a function of input current and provide preliminary Arrhenius kinetics for the thermal explosion of RDX in the temperature interval 1500 > T > 850 K.

We have used molecular dynamics simulations to determine the transport properties of liquid pentaerythritol tetranitrate (PETN), an important energetic material. The density, rho, self-diffusion coefficient, D, thermal conductivity, kappa, and shear viscosity, mu, have been computed over pressures and temperatures relevant to the subshock regime (up to 1000 K and a few GPa), where PETN is known to melt prior to initiation. We find that the thermal conductivity kappa(P, T) can be represented by a simple analytical function that fits the data points with very good accuracy, even beyond the subshock regime, up to 2000 K and 20 GPa. The self-diffusion coefficient, D, exhibits nonmonotonic behavior, with notably the temperature-independent prefactor decreasing by several orders of magnitude between 0 and 2 GPa before remaining nearly constant after, and the activation energy varying little in the subshock regime before increasing linearly beyond. Lastly, the viscosity, mu, is well described by Nahme's law, which is fitted to the MD results and allows us to predict mu(P, T) for temperatures and pressures corresponding to the subshock regime. These results can be used to model the response of PETN to low-velocity impacts, where the material melts prior to the first reactions, and thermal conduction and viscosity play a crucial role.

The drop weight impact experiment is used routinely to provide an initial screening of the handling sensitivity of new explosives. Despite the ubiquity and simplicity of the drop weight impact test, the physical mechanisms responsible for generating temperatures sufficiently high for the initiation of explosive reactions are not well understood. Preliminary work has shown that temperatures sufficient for ignition are in theory achievable in steady-state Poiseuille flow at the flow velocities observed experimentally with temperature-dependent shear viscosities. However, it is far from certain that such steady-state flow conditions can be achieved in the drop weight impact test because of its short duration. Therefore, here we study heat generation both experimentally and numerically to quantify the temperature distributions in molten pentaerythritol tetranitrate (PETN). Drop weight experiments have been performed starting with PETN that has been melted on a transparent anvil. The experimental results are consistent with our finite element calculations that indicate that the temperature does not approach the level needed for ignition on the time scales of the experiment. Interestingly, ignition regularly occurs in solid samples under the same conditions, so we discuss the phenomenology of ignition of both solid and molten PETN in the drop weight test and provide constraints to numerical simulations.

There are few techniques available for chemists to obtain time-to-explosion data with known temperature inputs at the early stages of the design and synthesis of new explosives. In the 1960s, a technique was developed to rapidly heat milligram-quantities of confined explosives to ∼1000 K on microsecond timescales. Wenograd [Trans. Faraday Soc. 57, 1612 (1961)] loaded explosives inside stainless steel hypodermic needles, connected them to a fireset and rapidly discharged a capacitor through the steel. He obtained the temperature by measuring the needle resistance in a Wheatstone bridge arrangement and the time to explosion from a needle rupture. However, owing to the narrow-gauge needles used in the original research, the experiment was only possible with melt-castable explosives; it was never replicated, and modern diagnostics are now available with advances beyond the 1960s. Here, we report the development of the High Explosives Initiation Time (HEIT) test, which utilizes a 250 J pulsed power system to heat the needles. This work extends the Wenograd approach by using optical diagnostics, computational modeling, and advanced techniques to measure needle resistance and needle rupture. Preliminary rate information for pentaerythritol tetranitrate (PETN) will be presented.

The nonpolarizable force field for alkyl nitrates developed by Borodin et al. [J. Phys. Chem. B, 2008, 112, 734-742] has been employed to calculate selected properties of crystalline and liquid erythritol tetranitrate (ETN). The set of partial charges proposed by Borodin for pentaerythritol tetranitrate (PETN) was used except for a small correction to the H atom charges to ensure charge neutrality owing to the absence of the neopentyl carbon in ETN. The force field was used to compute the isothermal compression curve, lattice parameters, heat capacity, thermal expansivity, single crystal elastic constants, and Gruneisen parameters of crystalline ETN. The density- and temperature-dependent viscosities of liquid ETN are also reported. We anticipate that these data will be of some utility to the development of equations of state and thermomechanical models for ETN.

Tailoring the molecular properties that govern energetic material sensitivity is essential to improve safety and help develop new energetic materials. Despite this need, understanding the complex chemistry and physics of explosive initiation and propagation is still a challenge. Recent work by our group has reinforced the view that explosive sensitivity under sub-shock conditions is connected to the strength of the weakest covalent bond in the molecule, that is, its "trigger linkage." These correlations have been observed with different classes of energetic molecules and indicate that "trigger linkage" bond breaking, and heat of explosion are good indicators for the sensitivity trends. Herein we report the synthesis of aliphatic energetic materials with ethane, propane and neopentane backbones. Experimental and computational studies show that the trigger linkage model, based on results from quantum molecular dynamics simulations, correctly predicts trends observed in the impact sensitivity of the molecules. However, while the model predicts the impact sensitivities of the ethane series, the neopentane series has higher impact sensitivities than predicted, which is presumably influenced by crystal packing effects.

Pentaerythritol tetranitrate (PETN) has been used extensively in commercial detonators and other explosive applications for many decades. Here, we show the results of a comprehensive 1.5 year aging study of PETN in commercial detonators, addressing batch-to-batch variations, surface area changes, and comparisons of aged loose powders side-by-side with identically aged detonators. Function time analysis of the aged detonators has also been provided and discussed in the context of powder aging. This large-scale, statistically relevant study addresses long-standing questions on PETN aging without the complications from making comparisons between multiple batches of material. We have evaluated the aging time required to reach the maximum measured amount of PETN coarsening and estimated an activation barrier of similar to 123 kJ mol(-1), which is higher than literature values reported by Gee et al. It is possible that this discrepancy is due to the fact that that this study cannot quantify the relative contributions of surface diffusion versus sublimation processes. At the lower temperatures of 50 and 60 degrees C, we assume that surface diffusion dominates over sublimation processes, even at longer aging times. At the higher temperature of 75 degrees C, we assume that both surface diffusion and sublimation contribute at the early time points, which are included in the Arrhenius analysis for coarsening.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.