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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optoelectronic and material properties of solution-processed Earth-abundant Cu 2 BaSn(S, Se) 4 films for solar cell applications

Copper barium thioselenostannate, Cu 2 BaSnS 4-x Se x (CBTSSe), absorbers employ low-toxicity and abundant metals while offering low-cost manufacturing options, controllable stoichiometry and band gap tunability (from 2 eV at x = 0 to 1.55 eV at x = 3). CBTSSe can therefore be considered a prospective candidate for maintaining or improving upon the advantages of already commercialized Cu(In,Ga)(S,Se) 2 (CIGSSe) and CdTe absorbers. Here, we focus on solution-deposited stoichiometric CBTSSe films with band gap of 1.59 eV (x ≈ 3) and explore the fundamental film properties. Temperature- and excitation-dependent photoluminescence studies reveal a dominant defect emission at ~1.5 eV and a second deep defect feature at 1.15 eV. From time-resolved terahertz measurements, we find a charge carrier (electron and hole sum) mobility of ~140 cm 2 /Vs—i.e., comparable to values in CIGSSe or Cu 2 ZnSnS 4-x Se x (CZTSSe)—as well as a two-component minority carrier lifetime. A longer-lived lifetime component (~2 ns) arises from bulk recombination. However, strong recombination at the (bare) surface leads to a ~50 ps lifetime, inferior to state-of-the-art CIGSSe or CZTSSe absorbers. This recombination issue may worsen for CBTSSe/CdS interfaces, due to a cliff-like band alignment with 0.6 eV band offset, as revealed by ultraviolet photoemission spectroscopy. A low number of charge carriers within the absorber further contributes to a high series resistance. Employing these films, we also report the highest performance achieved from solution-processed trigonal CBTSSe thin-film photovoltaic devices, with open circuit voltage, short-circuit current density, fill factor and efficiency of 470 mV, 14.3 mA/cm 2 , 43.6% and 2.9%, respectively. The physical measurements provided on the stoichiometric solution-processed CBTSSe absorber further point to critical areas for future improvement of CBTSSe and related photovoltaic cells in the quest for higher efficiency devices based on earth abundant metals.

14 SOLAR ENERGY↗
DOE OSTI2025

Magneto-optical Evidence of the Tilting Effect in Coupled Weyl Bands

Theories have revealed the universality of the band tilting effect in topological Weyl semimetals (WSMs) and its implications for the material physical properties. However, the experimental identification of tilted Weyl bands remains less explored. Here, we report the magneto-optical evidence of the tilting effect in WSM niobium phosphide. Specifically, we observe Landau level transitions with rich features that are well reproduced within a model of coupled tilted Weyl points. Our analysis indicates that the tilting effect relaxes the selection rules and leads to transitions that would otherwise be forbidden in the non-tilt case. Additionally, we observe unconventional interband transitions with flat and negative magnetic field dispersions, highlighting the importance of coupling between Weyl points. Our results not only emphasize the significance of the tilting effect in the optical responses of WSMs but also demonstrate magneto-optics as an effective tool for probing the tilting effect in electronic band structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Atomic structure and Mott nature of the insulating charge density wave phase of 1T-TaS 2

Here, using x-ray pair distribution function (PDF) analysis and computer modeling, we explore structure models for the complex charge density wave (CDW) phases of layered 1T-TaS 2 that both well capture their atomic-level features and are amenable to electronic structure calculations. The models give the most probable position of constituent atoms in terms of 3D repetitive unit cells comprising a minimum number of Ta–S layers. Structure modeling results confirm the emergence of star-of-David (SD) like clusters of Ta atoms in the high-temperature incommensurate (IC) CDW phase and show that, contrary to the suggestions of recent studies, the low-temperature commensurate (C) CDW phase expands upon cooling thus reducing lattice strain. The C-CDW phase is also found to preserve the stacking sequence of Ta–S layers found in the room temperature, nearly commensurate (NC) CDW phase to a large extent. DFT based on the PDF refined model shows that bulk C-CDW 1T-TaS 2 also preserves the insulating state of individual layers of SD clusters, favoring the Mott physics description of the metal-to-insulator (NC-CDW to C-CDW) phase transition in 1T-TaS 2 . Our work highlights the importance of using precise crystal structure models in determining the nature of electronic phases in complex materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Experimental and theoretical study of weakly coherent mode in I-mode edge plasmas in the EAST tokamak

The I-mode is a promising operation mode for fusion in the future, featuring high-temperature and low-density confinement, but the reason why the temperature and density are decoupled remains an important aspect to be explored. The experimental results from the experimental advanced superconducting tokamak (EAST) showed that the weakly coherent mode (WCM) is directly related to sustaining the I-mode and that the peak amplitude of the WCM is proportional to the temperature in the pedestal. Here, simulating the experimental data from EAST with the six-field model of BOUT++, we find a density perturbation close to the frequency of the WCM observed in the experiment. By testing all the physical terms in this model, we find that the density perturbation and particle transport are directly related to the drift Alfvén wave (DAW) mode. Additionally we use the SymPIC program (Xiao et al Plasma Sci. Technol. 20 110501; Phys. Plasmas 22 112504; Plasma Sci. Technol. 23 055102) to simulate the same experimental data and find that the frequency range of the WCM is close to both experimental and BOUT++ results. Therefore, the WCM of the I-mode can be considered to be driven by the DAW, which helps improve the transport of the I-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Vascular dysfunction in hemorrhagic viral fevers: opportunities for organotypic modeling

The hemorrhagic fever viruses (HFVs) cause severe or fatal infections in humans. Named after their common symptom hemorrhage, these viruses induce significant vascular dysfunction by affecting endothelial cells, altering immunity, and disrupting the clotting system. Despite advances in treatments, such as cytokine blocking therapies, disease modifying treatment for this class of pathogen remains elusive. Improved understanding of the pathogenesis of these infections could provide new avenues to treatment. While animal models and traditional 2D cell cultures have contributed insight into the mechanisms by which these pathogens affect the vasculature, these models fall short in replicating in vivo human vascular dynamics. The emergence of microphysiological systems (MPSs) offers promising avenues for modeling these complex interactions. These MPS or ‘organ-on-chip’ models present opportunities to better mimic human vascular responses and thus aid in treatment development. In this review, we explore the impact of HFV on the vasculature by causing endothelial dysfunction, blood clotting irregularities, and immune dysregulation. We highlight how existing MPS have elucidated features of HFV pathogenesis as well as discuss existing knowledge gaps and the challenges in modeling these interactions using MPS. Understanding the intricate mechanisms of vascular dysfunction caused by HFV is crucial in developing therapies not only for these infections, but also for other vasculotropic conditions like sepsis.

42 ENGINEERING↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2020

Convectively Forced Diurnal Gravity Waves in the Maritime Continent

Long-lived, zonally propagating diurnal rainfall disturbances are a highly pronounced and common feature in the Maritime Continent (MC). A recent study argues that these disturbances can be explained as diurnally phase-locked gravity waves. Here we explore the origins of these waves through regional cloud-permitting numerical model experiments. The gravity waves are reproduced and isolated in the model framework through the combined use of realistic geography and diurnally cyclic lateral boundary conditions representative of both characteristic easterly and westerly background zonal flow regimes. These flow regimes are characteristic of the Madden–Julian oscillation (MJO) suppressed and active phase in the MC, respectively. Tests are conducted wherein Borneo, Sumatra, or both islands and/or their orography are removed. These tests imply that the diurnal gravity waves are excited and maintained directly by latent heating from the vigorous mesoscale convective systems (MCSs) that form nocturnally in both Borneo and Sumatra. Removing orography has only a secondary impact on both the MCSs and the gravity waves, implying that it is not critical to these waves. We therefore hypothesize that diurnal gravity waves are fundamentally driven by mesoscale organized deep convection, and are only sensitive to orography to the measure that the convection is affected by the orography and its mesoscale flows. Factor separation further reveals that the nonlinear interaction of synchronized diurnal cycles in Sumatra and Borneo slightly amplifies this gravity wave mode compared to if either island existed in isolation. This nonlinear feedback appears most prominently at longitudes directly between the two islands.

Ruppert, Jr., James H.↗
DOE OSTI2024

Targeted Biomining and Machine Learning Approaches in Critical Minerals Revealed by a Biogeochemical Survey of a Coal Mine Drainage Remediation System

Abandoned coal mine drainage (AMD) remediation systems in Pennsylvania can concentrate critical minerals and materials (CMM) at levels comparable to mining-grade ores. Remediation systems have varying engineering features and are open to the environment, resulting in diverse microbial colonization and seasonal climate influences that may impact CMM speciation. The location of CMMs, the types of bacterial communities tolerant of these pollutant conditions, and the influence of localized climate on CMM rich remediation systems are not well characterized. Through a one-year spatiotemporal survey of biogeochemistry at a remediation system, we have initiated the process to address these questions. Rare Earth Elements (REE) ranged 180-1,200 ppm and greater than 1,500 bacterial ASVs were classified via 16S sequencing. Analyses indicate biogeochemical differences are heavily influenced by engineering features. Additionally, REE precipitants correlate strongly with the elements Al, Cu, Zn, Be, and U. Unearthing these trends has refined our line of inquiry to explore biological mining opportunities more closely with these metals. Furthermore, we created a Machine Learning Model for predicting AMD REE content, with 89% accuracy, using the data from this study and several others. Further training data is required to create a more reputable model. Recently, global research efforts have prioritized modeling work or the use of the few historical surveys to design experiments. Through our data, we challenge this approach, emphasizing the importance of expanding fundamental survey efforts prior to advanced product design and experimentation.

critical minerals↗
DOE OSTI2020

Dimensionality Reduction of SDSS Spectra with Variational Autoencoders

High-resolution galaxy spectra contain much information about galactic physics, but the high dimensionality of these spectra makes it difficult to fully utilize the information they contain. We apply variational autoencoders (VAEs), a nonlinear dimensionality reduction technique, to a sample of spectra from the Sloan Digital Sky Survey (SDSS). In contrast to principal component analysis (PCA), a widely used technique, VAEs can capture nonlinear relationships between latent parameters and the data. We find that a VAE can reconstruct the SDSS spectra well with only six latent parameters, outperforming PCA with the same number of components. Different galaxy classes are naturally separated in this latent space, without class labels having been given to the VAE. The VAE latent space is interpretable because the VAE can be used to make synthetic spectra at any point in latent space. For example, making synthetic spectra along tracks in latent space yields sequences of realistic spectra that interpolate between two different types of galaxies. Using the latent space to find outliers may yield interesting spectra: in our small sample, we immediately find unusual data artifacts and stars misclassified as galaxies. In this exploratory work, we show that VAEs create compact, interpretable latent spaces that capture nonlinear features of the data. While a VAE takes substantial time to train (≈1 day for 48,000 spectra), once trained, VAEs can enable the fast exploration of large astronomical data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Using automated machine learning for the upscaling of gross primary productivity

Estimating gross primary productivity (GPP) over space and time is fundamental for understanding the response of the terrestrial biosphere to climate change. Eddy covariance flux towers provide in situ estimates of GPP at the ecosystem scale, but their sparse geographical distribution limits larger-scale inference. Machine learning (ML) techniques have been used to address this problem by extrapolating local GPP measurements over space using satellite remote sensing data. However, the accuracy of the regression model can be affected by uncertainties introduced by model selection, parameterization, and choice of explanatory features, among others. Recent advances in automated ML (AutoML) provide a novel automated way to select and synthesize different ML models. In this work, we explore the potential of AutoML by training three major AutoML frameworks on eddy covariance measurements of GPP at 243 globally distributed sites. We compared their ability to predict GPP and its spatial and temporal variability based on different sets of remote sensing explanatory variables. Explanatory variables from only Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and photosynthetically active radiation explained over 70 % of the monthly variability in GPP, while satellite-derived proxies for canopy structure, photosynthetic activity, environmental stressors, and meteorological variables from reanalysis (ERA5-Land) further improved the frameworks' predictive ability. We found that the AutoML framework Auto-sklearn consistently outperformed other AutoML frameworks as well as a classical random forest regressor in predicting GPP but with small performance differences, reaching an r 2 of up to 0.75. We deployed the best-performing framework to generate global wall-to-wall maps highlighting GPP patterns in good agreement with satellite-derived reference data. This research benchmarks the application of AutoML in GPP estimation and assesses its potential and limitations in quantifying global photosynthetic activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Recent Advances in Radiation-Induced Actinide Redox Chemistry

The actinide series boasts many unique physical and chemical features worthy of both fundamental and applied study. However, the chemical influence of their inherent radiation field is often overlooked, especially as we begin to explore the late actinides in more detail than ever possible before. From the perspective of used nuclear fuel reprocessing, the absorption of ionizing radiation induces the formation of a variety of transient and steady-state excited states, radicals, ions, and molecular degradation products, many of which are highly redox active and can lead to significant changes in a reprocessing solvent system’s physical and chemical properties. For example, radiolysis of the actinides can drive steady-state redox distributions and the formation of non-traditional oxidation states which can complicate their separation and recovery from fission products. This scenario is further exacerbated when complexation is taken into account. Consequently, a molecular-level understanding of radiation effects on the actinides over multiple time, distance, and material domains is essential for supporting innovation in used nuclear fuel reprocessing technologies. Attaining this knowledge necessitates a firm grasp of actinide radiation chemistry to develop predictive, mechanistic, multiscale models to support engineering efforts. Presented here are several recent studies that highlight recent advances in actinide radiation chemistry, in particular, the effect of actinide complexation on ligand reactivity towards radiation-induced transients.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Novel Hybrid Current Limiter for Grid-Forming Inverter Control During Unbalanced Faults: Preprint

Grid-forming (GFM) inverter controls have illustrated many desirable features to enable bulk integration of renewable sources into the future power grid. However, the performance of GFM inverters during unbalanced faults remains under-explored. In this paper, a novel current-limiting method is proposed for GFM inverters to handle unbalanced fault conditions while providing voltage support to the main grid. The proposed current limiter combines concepts of dynamic virtual-impedance and current-reference saturation limiting, all built-up in the stationary reference frame to achieve improved current-limiting performance under unbalanced load/fault conditions. System-wide full-order transient simulations with multiple GFM inverters demonstrate the potential of the method and benchmark the performance against state-of-the-art current limiters. Simulation results portray improved voltage balancing performance of the proposed method compared to both current-reference saturation and virtual-impedance limiting.

controller anti windup↗
DOE OSTI2025

Development and Validation of MALAMUTE model for Electric Field Assisted Sintering of Structural Materials

Fusion power plant designs feature extreme material performance requirements for structural material candidates. In addition to conventional alloys, more advanced composites and oxide dispersion strengthened (ODS) alloys are being explored, however, achieving the desired microstructures to maximize performance using traditional manufacturing methods can be challenging. The advanced manufacturing (AM) electric field-assisted sintering (EFAS) technique offers improved control over the final microstructure through higher heating and cooling rates and moderate pressures. Modeling and simulation tools show promise in elucidating the process-structure-property-performance (PSPP) correlation for AM-produced parts, including the EFAS process. An inherently multiscale process, the EFAS technique aligns well with the multiscale modeling capability of the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE)[cite]. We present here an electro-thermo-mechanical approach to modeling the EFAS process using the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) code. Prediction of the field and gradient distributions across the EFAS tooling is required to accurately describe the conditions for the lower-scale microstructural evolution models. In this work we present the MALAMUTE model developed to predict the electrical potential, temperature, and mechanical stress distribution across the EFAS graphite tooling and part at the larger engineering-scale. Validation of the MALAMUTE engineering-scale model is completed using data from experimental densification and pre-densified runs of iron powder via EFAS at 1000oC. These runs were conducted using a Thermal Technology DCS-5 EFAS system. Data collected during the experiment runs include the direct current (DC) supplied to the graphite tooling, the temperature of the graphite tooling as measured with a pyrometer, and the force applied to the top of the graphite tooling stack, and the data were recorded every 10 seconds. Our validation approach used the current and force data from the EFAS run as boundary condition inputs to the MAMALUTE simulation; the temperature data were used to evaluate the MALAMUTE EFAS model prediction. Results of the MALAMUTE simulations are employed to connect the external pyrometer temperature measurement to the temperature profile across the part undergoing consolidation. We investigate the impact of material property variation and mesh deformation on the temperature profile as predicted by MALAMUTE. We conclude by highlighting projects where the MALAMUTE EFAS modeling and simulation capabilities will be used to assist experimental design.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Quantum model learning agent: characterisation of quantum systems through machine learning

Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distil empirically. Here, we report an algorithm—the quantum model learning agent (QMLA)—to reverse engineer Hamiltonian descriptions of a target system. We test the performance of QMLA on a number of simulated experiments, demonstrating several mechanisms for the design of candidate Hamiltonian models and simultaneously entertaining numerous hypotheses about the nature of the physical interactions governing the system under study. QMLA is shown to identify the true model in the majority of instances, when provided with limited a priori information, and control of the experimental setup. Our protocol can explore Ising, Heisenberg and Hubbard families of models in parallel, reliably identifying the family which best describes the system dynamics. We demonstrate QMLA operating on large model spaces by incorporating a genetic algorithm to formulate new hypothetical models. The selection of models whose features propagate to the next generation is based upon an objective function inspired by the Elo rating scheme, typically used to rate competitors in games such as chess and football. In all instances, our protocol finds models that exhibit F 1 score ≥ 0.88 when compared with the true model, and it precisely identifies the true model in 72% of cases, whilst exploring a space of over 250 000 potential models. By testing which interactions actually occur in the target system, QMLA is a viable tool for both the exploration of fundamental physics and the characterisation and calibration of quantum devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Elucidation of complex respiratory chains: a straightforward strategy to monitor electron transfer between cytochromes

Abstract Cytochromes are electron transfer (ET) proteins essential in various biological systems, playing crucial roles in the respiratory chains of bacteria. These proteins are particularly abundant in electrogenic microorganisms and are responsible for the efficient delivery of electrons to the cells’ exterior. The capability of sending electrons outside the cells open new avenues to be explored for emerging biotechnological applications in bioremediation, microbial electrosynthesis, and bioenergy fields. To develop these applications, it is critical to identify the different redox partners and to elucidate the stepwise ET along the respiratory paths. However, investigating direct ET events between proteins with identical features in nearly all spectroscopic techniques is extremely challenging. Nuclear magnetic resonance (NMR) spectroscopy offers the possibility to overcome this difficulty by analysing the alterations of the spectral signatures of each protein caused by electron exchange events. The uncrowded NMR spectral regions containing the heme resonances of the cytochromes display unique and distinct signatures in the reduced and oxidized states, which can be explored to monitor ET within the redox complex. In this study, we present a strategy for a fast and straightforward monitorization of ET between c-type cytochromes, using as model a triheme periplasmic cytochrome and a membrane-associated monoheme cytochrome from the electrogenic bacterium Geobacter sulfurreducens. The comparison between the 1D 1H NMR spectra obtained for samples containing the two cytochromes and for samples containing the individual proteins clearly demonstrated a unidirectional ET within the redox complex. This strategy provides a simple and straightforward means to elucidate complex biologic respiratory ET chains.

Morgado, Leonor (ORCID:0000000237605180)↗
DOE OSTI2021

Disentangling observable dependence in SCET I and SCET II anomalous dimensions: angularities at two loops

The resummation of radiative corrections to collider jet observables using soft collinear effective theory is encoded in differential renormalization group equations (RGEs), with anomalous dimensions depending on the observable under consideration. This observable dependence arises from the ultraviolet (UV) singular structure of real phase space integrals in the effective field theory. We show that the observable dependence of anomalous dimensions in SCET I problems can be disentangled by introducing a suitable UV regulator in real radiation integrals. Resummation in the presence of the new regulator can be performed by solving a two-dimensional system of RGEs in the collinear and soft sectors, and resembles many features of resummation in SCET II theories by means of the rapidity renormalization group. We study the properties of SCET I with the additional regulator and explore the connection with the system of RGEs in SCET II theories, highlighting some universal patterns that can be exploited in perturbative calculations. As an application, we compute the two-loop soft and jet anomalous dimensions for a family of recoil-free angularities and give new analytic results. This allows us to study the relations between the SCET I and SCET II limits for these observables. We also discuss how the extra UV regulator can be exploited to calculate anomalous dimensions numerically, and the prospects for numerical resummation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Enhancing detection of topological order by local error correction

The exploration of topologically-ordered states of matter is a long-standing goal at the interface of several subfields of the physical sciences. Such states feature intriguing physical properties such as long-range entanglement, emergent gauge fields and non-local correlations, and can aid in realization of scalable fault-tolerant quantum computation. However, these same features also make creation, detection, and characterization of topologically-ordered states particularly challenging. Motivated by recent experimental demonstrations, we introduce a paradigm for quantifying topological states—locally error-corrected decoration (LED)—by combining methods of error correction with ideas of renormalization-group flow. Our approach allows for efficient and robust identification of topological order, and is applicable in the presence of incoherent noise sources, making it particularly suitable for realistic experiments. We demonstrate the power of LED using numerical simulations of the toric code under a variety of perturbations. We subsequently apply it to an experimental realization, providing new insights into a quantum spin liquid created on a Rydberg-atom simulator. Finally, we extend LED to generic topological phases, including those with non-abelian order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

LLNL Explosives Anisotropy Research

Lawrence Livermore National Laboratory scientists and engineers led a multi-institutional team in executing a series of high explosives tests that successfully demonstrated fundamental principles of anisotropy, a possible enabler for improved weapon and munition safety. Working under snowy and frigid conditions on Idaho’s Snake River Plain, a 13-member team from LLNL carried out 52 explosives shots over four days in mid-November at the Idaho National Laboratory’s (INL) National Security Test Range (NSTR) to complete the study. The broader anisotropy (ANISO) team included high explosives handlers and volunteers from INL, Los Alamos National Laboratory, Marine Raiders from the Marine Special Operations Command and members of the U.S. Special Operations Command. The purpose of the study was to explore theoretical methods of creating anisotropic explosives — explosives that perform differently depending on the direction the detonation wave moves through the explosive — by engineering certain physical features in the charges and obtaining basic data from testing. The work is part of an overall effort by the Lab to develop anisotropic explosives that could be used in munitions to reduce the severity and lethality of an unintended detonation without sacrificing performance. The data gathered from the study will be used to design and construct follow-on experiments at LLNL’s High Explosives Applications Facility (HEAF) and validate computer models for future anisotropic assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗