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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 343 records · Page 19

Solid-state prealkylation of electrode architectures to tune solid electrolyte interphase composition

Efficient electrochemical cycling of certain Si anodes is limited by irreversible Li consumption to form and continually reform the solid electrolyte interface (SEI) due to Si expansion/contraction and fracture. Prelithiation can compensate for these losses; however, the starting open circuit potential (VOC) becomes highly reducing and, therefore, the electrolyte reduction chemistry that influences the SEI composition can change. Herein, we compare SEI formation for electrodes prelithiated using Solid State Prealkylation of Electrode Architectures (SPEAR) versus traditional electrochemically lithiated architectures (ECLAR), focusing on SEI compositional changes as a function of stoichiometry (0.28 ≤ x ≤ 1.38 in LixSi). Increasing SPEAR prelithiation decreased the initial VOC of Si anodes vs. Li/Li+ from ∼3 V (Li0.28Si) to < 0.5 V for Li1.38Si, enabling simultaneous competitive reduction of EC, EMC, and LiPF6 at low potentials. Ex situ7Li and 29Si cross-polarization NMR and XPS reveal that SPEAR drives thicker SEI formation with substantially increased P/F contributions and a predominantly inorganic insoluble SEI (71.4% inorganic for Li1.38Si), consistent with accelerated LiPF6-derived POx/LiPFx/LiF formation relative to ECLAR analogs which exhibit carbonate-rich organic SEI compositions. Symmetric-cell EIS further indicates SPEAR-specific impedance features consistent with pore reduction (filling) during LixSi formation. In full cells, SPEAR prelithiation increases the initial coulombic efficiency (ICE) and accelerates SEI formation and stabilization with Li1.38Si reaching 99.4% coulombic efficiency (CE) by cycle 2.

Musgrove, Amanda [ORNL] (ORCID:0009000220910389)↗

Inverse methods for design of soft materials

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide a systematic means for navigating their inherently high-dimensional design spaces to create materials with targeted properties. Furthermore, while multiple physically motivated inverse strategies have been successfully implemented in silico, their translation to guiding experimental materials discovery has thus far been limited to a handful of proof-of-concept studies. In this perspective, we discuss recent advances in inverse methods for design of soft materials that address two challenges: (1) methodological limitations that prevent such approaches from satisfying design constraints and (2) computational challenges that limit the size and complexity of systems that can be addressed. Strategies that leverage machine learning have proven particularly effective, including methods to discover order parameters that characterize complex structural motifs and schemes to efficiently compute macroscopic properties from the underlying structure. We also highlight promising opportunities to improve the experimental realizability of materials designed computationally, including discovery of materials with functionality at multiple thermodynamic states, design of externally directed assembly protocols that are simple to implement in experiments, and strategies to improve the accuracy and computational efficiency of experimentally relevant models.

36 MATERIALS SCIENCE↗

Experimental observations of exploding bridgewire detonator function

Exploding bridgewire detonators are an industry standard technology used for over 75 years and valued for their precise timing and safety characteristics. Despite widespread use, their functional mechanism remains controversial with both shock and non-shock mechanisms attributed. In this work, we re-examine bridgewire detonator function with a suite of modern diagnostics and compare these observations with the existing literature. Traditional detonator observations consisted of voltage applied to the bridgewire and time dependent current, integral response measurements such as case motion and more recently Schlieren imaging of the detonator surface. In this work, we add visible light emission, X-ray transmission, proton radiography, and temperature measurements during detonator function in addition to voltage, current, and function times. The addition of in-situ observations of light emission, temperature, and density gives us new insight into the mechanisms of explosive bridgewire detonator function. We see a distinct separation in time, location, symmetry, and velocity of bridgewire output and detonation onset. During the time between bridgewire burst and the initiation of detonation, we observe a temperature ramp in the input pellet. In this paper, we present the suite of measurements and comparisons with the literature on integral response measurements.

42 ENGINEERING↗

Inverse design of equilibrium cluster fluids applied to a physically informed model

Inverse design strategies have proven highly useful for the discovery of interaction potentials that prompt self-assembly of a variety of interesting structures. However, often the optimized particle interactions do not have a direct relationship to experimental systems. In this work, we show that Relative Entropy minimization is able to discover physically meaningful parameter sets for a model interaction built from depletion attraction and electrostatic repulsion that yield self-assembly of size-specific clusters. Here, we then explore the sensitivity of the optimized interaction potentials with respect to deviations in the underlying physical quantities, showing that clustering behavior is largely preserved even as the optimized parameters are perturbed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncertainty Quantification for a Multi-phase Carbon Equation of State Model

Many physics models have tunable parameters that are calibrated by matching the model output to experimental or calculated data. However, given that calibration data often contain uncertainty and that different model parameter sets might result in a very similar simulated output for a finite calibration data set, it is advantageous to provide an ensemble of parameter sets that are consistent with the calibration data. Uncertainty quantification (UQ) provides a means to generate such an ensemble in a statistically rigorous fashion. In this work, we perform UQ for a multi-phase equation of state (EOS) model for carbon containing the diamond, graphite, and liquid phases. We use a Bayesian framework for the UQ and introduce a novel strategy for including phase diagram information in the calibration. The method is highly general and accurately reproduces the calibration data without any material-specific prior knowledge of the EOS model parameters.

36 MATERIALS SCIENCE↗

Treating random sequential addition via the replica method

While many physical processes are non-equilibrium in nature, the theory and modeling of such phenomena lag behind theoretical treatments of equilibrium systems. The diversity of powerful theoretical tools available to describe equilibrium systems has inspired strategies that map non-equilibrium systems onto equivalent equilibrium analogs so that interrogation with standard statistical mechanical approaches is possible. In this work, we revisit the mapping from the non-equilibrium random sequential addition process onto an equilibrium multi-component mixture via the replica method, allowing for theoretical predictions of non-equilibrium structural quantities. We validate the above approach by comparing the theoretical predictions to numerical simulations of random sequential addition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Epitaxial hexagonal boron nitride with high quantum efficiency

Two-dimensional (2D) hexagonal boron nitride (h-BN) is one of the few materials showing great promise for light emission in the far ultraviolet (UV)-C wavelength, which is more effective and safer in containing the transmission of microbial diseases than traditional UV light. In this report, we observed that h-BN, despite having an indirect energy bandgap, exhibits a remarkably high room-temperature quantum efficiency (~60%), which is orders of magnitude higher than that of other indirect bandgap material, and is enabled by strong excitonic effects and efficient exciton-phonon interactions. This study offers a new approach for the design and development of far UV-C optoelectronic devices as well as quantum photonic devices employing 2D semiconductor active regions.

36 MATERIALS SCIENCE↗

Flash x-ray radiography analysis of detonation wave propagation in additive-manufactured high explosives

Recent research has demonstrated that additive manufacturing (AM) can be used to produce directionally sensitive high explosives (HEs), but detonation wave propagation in AM HEs with variable internal structure has not been studied. In this work, samples were printed using a 73 wt. % octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine-based HE ink. Flash x-ray radiography imaging was used to observe density changes in two imaging planes of each sample during detonation, and high-speed imaging was used to calculate the detonation velocity at the HE surface. The detonation front initially appears to fail in internal channel regions of the HE, but late reactions occurred in two samples, which increased the material bulk density by 2.8%, possibly due to shock convergence phenomena. The calculated detonation wave pressure similarly increased, but the accuracy of the results is uncertain because of the deviation of the low bulk density printed samples from the cast charge principal isentrope. Here, this work demonstrates that structure can be effectively utilized to guide detonation wave propagation through HE charges.

3D printing↗

Uncertainty quantification for high explosive reactant and product equations of state

Equations of state (EOSs) are typically represented as physics-informed models with tunable parameters that are adjusted to replicate calibration data as closely as possible. Uncertainty quantification (UQ) allows for the development of an ensemble of EOS parameters that are consistent with the calibration data instead of a single EOS. In this work, we perform UQ for the reactant and product EOSs for a variety of high explosives (HEs). In doing so, we demonstrate a strategy for dealing with heterogeneous (both experimental and calculated) data. We also use a statistical distance metric to quantify the differences between the various HEs using the UQ results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaluation of silicon and indium gallium arsenide photodiodes as direct timing detectors for pulsed x-ray systems

Benchtop pulsed x-ray systems are commonly used to record dynamic material data on the order of nanoseconds, but pulse timing is often difficult to accurately determine. This study demonstrates that commercially available photodiodes can be used effectively for direct x-ray pulse detection without the need for visible light scintillators. X-ray pulses from four commercially available flash x-ray systems were quantified using one silicon and two indium gallium arsenide (InGaAs) photodiodes. The measured InGaAs pulse durations were strongly dependent on radiation dose in the non-linear operating regime, so the photodiodes were shielded to operate below the 2.5 V non-linear regime threshold. The average pulse duration and pulse arrival time jitter of the photodiodes for each x-ray source were within several nanoseconds with the exception of two sets of measurements that were affected by low instrument sensitivity and electrical noise. These results show that InGaAs photodiodes can be used as effective and repeatable stand-alone timing diagnostics for x-ray pulses as short as 20 ns or less.

47 OTHER INSTRUMENTATION↗

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and there are typically inherent degeneracies in fitting the EOS, there are actually multiple EOSs that might be consistent with calibration data. In this work, we perform uncertainty quantification (UQ) for the reactant and product equations of state for the high explosive PBX 9501 to yield an ensemble of EOSs that match the uncertain small-scale calibration data. We then simulate an experiment of an explosively formed penetrator repeatedly with different EOSs to both validate the UQ analysis and determine the effects of EOS uncertainty on the prediction of quantities of interest in the experiment. In general, we find good agreement between the simulation predictions and the experimental measurements, and we identify an EOS variable that contributes most directly to the spread in the predictions as the EOSs are varied.

36 MATERIALS SCIENCE↗

A Tutorial on Bayesian analysis of linear shock compression data

Gas gun and other shock compression experiments often produce shock wave velocity measurements that are linearly associated with particle velocity. Traditionally, this empirical relationship is quantified with a single Hugoniot curve that is estimated using least squares regression. However, for downstream modeling and simulation tasks, it is often more useful to have multiple Hugoniot curves in the pressure–volume plane that are consistent with the data. We employ Bayesian uncertainty quantification methods as a framework for propagating measurement uncertainty through to model parameters and predictions. Specifically, this Tutorial shows how to sample multiple Hugoniot curves in the pressure–volume plane that are consistent with the shock wave-particle velocity measurements in a two-step Bayesian approach. First, we obtain an analytical expression for the posterior distribution of the linear model parameters using Bayesian linear regression. Second, we propagate samples from the posterior distribution through the Rankine–Hugoniot equations to yield Hugoniot curves in the pressure–volume plane. The procedure is demonstrated with publicly available data on argon, copper, and nickel, and compared against bootstrapping and linear regression. The Bayesian procedure is shown to be interpretable, computationally inexpensive, and less sensitive than an alternative bootstrapping approach to the removal of the point in the copper dataset that has the largest particle velocity. As a Tutorial on Bayesian methodology for the shock compression community, we provide several derivations and explanations that make this paper self-contained, and make all code and data available at github.com/llnl/BALSCD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Discovery and characterization of a neutralizing pan-ELR+CXC chemokine monoclonal antibody

CXCR1 and CXCR2 signaling play a critical role in neutrophil migration, angiogenesis, and tumorigenesis and are therefore an attractive signaling axis to target in a variety of indications. In human, a total of seven chemokines signal through these receptors and comprise the ELR + CXC chemokine family, so named because of the conserved ELRCXC N-terminal motif. To fully antagonize CXCR1 and CXCR2 signaling, an effective therapeutic should block either both receptors or all seven ligands, yet neither approach has been fully realized clinically. In this work, we describe the generation and characterization of LY3041658, a humanized monoclonal antibody that binds and neutralizes all seven human and cynomolgus monkey ELR + CXC chemokines and three of five mouse and rat ELR+CXC chemokines with high affinity. LY3041658 is able to block ELR + CXC chemokine-induced Ca 2+ mobilization, CXCR2 internalization, and chemotaxis in vitro as well as neutrophil mobilization in vivo without affecting other neutrophil functions. In addition to the in vitro and in vivo activity, we characterized the epitope and structural basis for binding in detail through alanine scanning, crystallography, and mutagenesis. Together, these data provide a robust preclinical characterization of LY3041658 for which the efficacy and safety is being evaluated in human clinical trials for neutrophilic skin diseases.

59 BASIC BIOLOGICAL SCIENCES↗

Light cone dynamics in excitonic states of two-component Bose and Fermi gases

Herein we consider the non-equilibrium dynamics of two-component one dimensional quantum gases in the limit of extreme population imbalance where the minority species has but a single particle. We consider the situation where the gas is prepared in a state with a single spatially localized exciton: the single particle of the minority species is spatially localized while the density of the majority species in the vicinity of the minority particle sees a depression. Remarkably, we are able to consider cases where the gas contains on the order of $N$ = 100 particles, comparable to that studied in experiments on cold atomic gases. We are able to do so by exploiting the integrability of the gas together with the observation that the excitonic state can be constructed through a simple superposition of exact eigenstates of the gas. The number of states in this superposition, rather than being exponentially large in the number of particles, scales linearly with $N$. We study the evolution of such spatially localized states in both strongly interacting Bose and Fermi gases. The behavior of the light cones when the interaction strength and density of the gas is varied can be understood from exact results for the spin excitation spectrum in these systems. We argue that the light cone in both cases exhibits scaling collapse. However unique to the Bose gas, we show that the presence of gapped finite-momentum roton-like excitations provide the Bose gas dynamics with secondary light cones.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗