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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Three-dimensional microstructure-explicit and void-explicit mesoscale simulations of detonation of HMX at millimeter sample size scale

Fully three-dimensional (3D) microstructure-explicit and void-explicit mesoscale simulations of the shock-to-detonation (SDT) process of pressed granular HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) are performed. The overall size scale of the models is up to 3 × 3 × 15 mm3, with ∼30 000 grains and 206 265 voids. The models account for the heterogeneous material microstructure, constituent distribution, constituent morphology, and voids. Loading conditions considered involve piston velocities in the range of 600–1200 m/s or pressures in the range of 4–8 GPa. The focus is on analyzing the SDT process and the effects of microstructure and voids on the run-to-detonation distance (RDD). Companion two-dimensional (2D) simulations are also carried out to assess the differences between 2D and 3D. Statistically equivalent microstructure sample sets (SEMSSs) are generated and used for both 2D and 3D, allowing the prediction of the statistical and probabilistic Pop plots (PPs). The predictions are in general agreement with trends in available experimental data in the literature. It is found that both the microstructure (heterogeneous grain size, morphology, and size distribution) and voids significantly affect the RDD and the PPs. These effects are systematically delineated and quantified via the use of SEMSSs with different combinations of attributes. A recently developed probabilistic formulation for the PPs is used to characterize the results, allowing uncertainties in the relations between the shock pressure and RDD arising from material heterogeneities to be quantified. The probabilistic formulation is further used to quantify the confidence levels in the ranked order of influences of different combinations of microstructure and voids on the PPs.

Miller, Christopher (ORCID:0000000206844381)↗
DOE OSTI2020

Phase equilibrium of liquid water and hexagonal ice from enhanced sampling molecular dynamics simulations

We study the phase equilibrium between liquid water and ice Ih modeled by the TIP4P/Ice interatomic potential using enhanced sampling molecular dynamics simulations. Our approach is based on the calculation of ice Ih-liquid free energy differences from simulations that visit reversibly both phases. The reversible interconversion is achieved by introducing a static bias potential as a function of an order parameter. The order parameter was tailored to crystallize the hexagonal diamond structure of oxygen in ice Ih. Furthermore, we analyze the effect of the system size on the ice Ih-liquid free energy differences, and we obtain a melting temperature of 270 K in the thermodynamic limit. This result is in agreement with estimates from thermodynamic integration (272 K) and coexistence simulations (270 K). Since the order parameter does not include information about the coordinates of the protons, the spontaneously formed solid configurations contain proton disorder as expected for ice Ih.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sample test array and recovery (STAR) platform at the National Ignition Facility

We have developed the Sample Test Array and Recovery (STAR) platform for the National Ignition Facility (NIF) for studying the thermal and hydrodynamic responses of materials in extreme environments. The STAR platform expands the range of obtainable fluences and quadruples the rate that materials experiments can be conducted at the NIF. Example configurations are demonstrated for fluences spanning 0.56–34 J/cm 2 with environmental isolation for post-shot material recovery and inspection and up to 1740 J/cm 2 without isolation, with surface heating rates of up to 2 × 10 14 K/s. Lastly, an example experiment involving thermally driven shock and spallation of aluminum alloy 7075 is briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Machine learning framework for quantum sampling of highly constrained, continuous optimization problems

In recent years, there is growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design problems into surrogate quadratic unconstrained binary optimization (QUBO) problems by employing a binary variational autoencoder and a factorization machine. The factorization machine is trained as a low-dimensional, binary surrogate model for the continuous design space and sampled using various QUBO samplers. Using the D-Wave Advantage hybrid sampler and simulated annealing, we demonstrate that by repeated resampling and retraining of the factorization machine, our framework finds designs that exhibit figures of merit exceeding those of its training set. We showcase the framework’s performance on two inverse design problems by optimizing (i) thermal emitter topologies for thermophotovoltaic applications and (ii) diffractive meta-gratings for highly efficient beam steering. This technique can be further scaled to leverage future developments in quantum optimization to solve advanced inverse design problems for science and engineering applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A parallel, distributed memory implementation of the adaptive sampling configuration interaction method

The many-body simulation of quantum systems is an active field of research that involves several different methods targeting various computing platforms. Many methods commonly employed, particularly coupled cluster methods, have been adapted to leverage the latest advances in modern high-performance computing. Selected configuration interaction (sCI) methods have seen extensive usage and development in recent years. However, the development of sCI methods targeting massively parallel resources has been explored only in a few research works. Here, we present a parallel, distributed memory implementation of the adaptive sampling configuration interaction approach (ASCI) for sCI. In particular, we will address the key concerns pertaining to the parallelization of the determinant search and selection, Hamiltonian formation, and the variational eigenvalue calculation for the ASCI method. Load balancing in the search step is achieved through the application of memory-efficient determinant constraints originally developed for the ASCI-PT2 method. The presented benchmarks demonstrate near optimal speedup for ASCI calculations of Cr 2 (24e, 30o) with 10 6 , 10 7 , and 3 × 10 8 variational determinants on up to 16 384 CPUs. Importantly, to the best of the authors’ knowledge, this is the largest variational ASCI calculation to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Identification of novel organic polar materials: A machine learning study with importance sampling

Recent advances in the synthesis of polar molecular materials have produced practical alternatives to ferroelectric ceramics, opening up exciting new avenues for their incorporation into modern electronic devices. However, in order to realize the full potential of polar polymer and molecular crystals for modern technological applications, it is paramount to assemble and evaluate all the available data for such compounds, identifying descriptors that could be associated with an emergence of ferroelectricity. In this paper, we utilized data-driven approaches to judiciously shortlist candidate materials from a wide chemical space that could possess ferroelectric functionalities. A machine learning study with importance sampling was employed to address the challenge of having a limited amount of available data on already-known organic ferroelectrics. Sets of molecular- and crystal-level descriptors were combined with a Random Forest Regression algorithm in order to predict the spontaneous polarization of the shortlisted compounds. First-principles simulations were performed to further validate the predictions obtained from the machine learning model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Measurements of Neutron Scattering from a Copper Sample Using a Quasi-Differential Method in the Region from 2 keV to 20 MeV

Neutron scattering from a copper sample was measured at Rensselaer Polytechnic Institute utilizing the quasi-differential method. The measurement spanned the energy range from 0.5 to 20 MeV using the high-energy scattering system and from 2 keV to 0.5 MeV using the new mid-energy scattering system. Copper was selected as a material of interest to measure due to large discrepancies between experiments and simulations of the Zeus benchmark. The Zeus benchmark consists of a copper reflected highly enriched uranium system, and the angular distribution of copper scattering was thought to potentially be the cause of the discrepancy. The copper measurements found differences in the scattering response particularly in the incident energy region from 1 to 2 MeV for the high-energy measurement and from 2 to 4 keV in the mid-energy system. These differences are particularly noticeable at angles near 90 deg in the high-energy system and back angles in the mid-energy system. Additionally, for ENDF/B-VIII.0 there is a large discrepancy at the forward angle in the energy range around 0.5 MeV. For these reasons, a new evaluation of copper scattering utilizing these results is recommended and perhaps could help to improve the agreement with the Zeus benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Following O and OH in He/O 2 and He/H 2 O gas mixtures—from the gas phase through the liquid phase to modifications on a biological sample

Abstract Applied cold atmospheric plasma allows for the controlled delivery of reactive oxygen and nitrogen species tailored for specific applications. Through the manipulation of the plasma parameters, feed gases, and careful consideration of the environment surrounding the treatment target, selective chemistries that preferentially influence the target can be produced and delivered. To demonstrate this, the COST reference microscale atmospheric pressure plasma jet is used to study the generation and transport of O and ⋅ OH from the gas phase through the liquid to the biological model target cysteine. Relative and absolute species densities of ⋅ OH and O are measured in the gas phase through laser induced fluorescence (LIF) and two-photon absorption LIF respectively. The transport of these species is followed into the liquid phase by hydrogen peroxide quantification and visualized by a fluorescence assay. Modifications to the model biological sample cysteine exposed to ⋅ OH and H 2 O 2 dominated chemistry (He/H 2 O (0.25%)) and O dominated chemistry (He/O 2 (0.6%)) is measured by FTIR spectroscopy. The origin of these species that modify cysteine is considered through the use of heavy water (H 2 18 O) and mass spectrometry. It is found that the reaction pathways differ significantly for He/O 2 and He/H 2 O. Hydrogen peroxide is formed mainly in the liquid phase in the presence of a substrate for He/O 2 whereas for He/H 2 O it forms in the gas phase. The liquid chemistry resulting from the He/O 2 admixture mainly targets the sulfur moiety of cysteine for oxidation up to irreversible oxidation states, while He/H 2 O treatment leads preferentially to reversible oxidation products. The more O or OH/H 2 O 2 dominated chemistry produced by the two gas admixtures studied offers the possibility to select species for target modification.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development and Understanding of Nb 3 Sn films for radiofrequency applications through a sample-host 9-cell cavity

Nb 3 Sn is a promising advanced material under development for superconducting radiofrequency cavities. Past efforts have been focused primarily on small development-scale cavities, but large, often multi-celled cavities, are needed for particle accelerator applications. In this work, we report on successful Nb 3 Sn coatings on Nb in a 1 m-long 9-cell Nb sample-host cavity at Fermilab. The geometry of the first coating with only one Sn source made it possible to study the influence of Sn flux on the microstructure. Based on these results, we postulate a connection between recently observed anomalously large thin grains and uncovered niobium spots observed in the past by other authors (Trenikhina et al 2018 Supercond. Sci. Technol. 32 015004). A phenomenological model to explain how these anomalously large grains could form is proposed. Overall, this model is invoked to provide possible explanations for literature results from several groups and to guide key process parameters to achieve uniform vapor-diffusion coatings, when applied to complex structures as the multi-cell cavity under study.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Spatially-resolved dynamic sampling of different phasic magnetic resonances of nanoparticle ensembles in a magnetotactic bacterium Magnetospirillum magnetotacticum

Abstract Nanoscaled magnetic particle ensembles are promising building blocks for realizing magnon based binary logic. Element-specific real-space monitoring of magnetic resonance modes with sampling rates in the GHz regime is imperative for the experimental verification of future complex magnonic devices. Here we present the observation of different phasic magnetic resonance modes using the element-specific technique of time-resolved scanning transmission x-ray microscopy within a chain of dipolarly coupled Fe 3 O 4 nanoparticles (40–50 nm particle size) inside a single cell of a magnetotactic bacterium Magnetospirillum magnetotacticum . The particles are probed with 25 nm resolution at the Fe L 3 x-ray absorption edge in response to a microwave excitation of 4.07 GHz. A plethora of resonance modes is observed within multiple particle segments oscillating in- and out-of-phase, well resembled by micromagnetic simulations.

time-resolved scanning transmission x-ray microsco↗
DOE OSTI2025

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗
DOE OSTI2025

Selecting samples of galaxies with fewer Fingers-of-God

The radial positions of galaxies inferred from their measured redshift appear distorted due to their peculiar velocities. We argue that the contribution from stochastic velocities — which gives rise to `Fingers-of-God' (FoG) anisotropy in the inferred maps — does not lend itself to perturbative modelling already on scales targeted by current experiments. To get around this limitation, we propose to remove FoG using data-driven indicators of their abundance that are local in nature and thus avoid selection biases. In particular, we show that the scale where the measured power spectrum quadrupole changes sign is tightly anti-correlated with both the satellite fraction and the velocity dispersion, and can thus be used to select galaxy samples with fewer FoG. In addition, we show that excluding galaxies in haloes more massive than a given mass threshold can help to discard many of the most problematic galaxies. Such selection could be achieved in practice using maps of the thermal Sunyaev-Zel'dovich distortion of the cosmic microwave background frequency spectrum. These techniques could potentially improve reconstructions of the large-scale velocity and displacement fields from the redshift-space positions of galaxies. They may also extend the reach of perturbative models for galaxy clustering, though in practice we find only marginal gains when fitting one-loop EFTofLSS models to simulations with mitigated FoG due to the relevance of other effects entering at two-loop order.

cosmological parameters from LSS↗
DOE OSTI2022

Measurement of integrated luminosities at BESIII for data samples at center-of-mass energies between 4.0 and 4.6 GeV*

Abstract The integrated luminosities of data samples collected in the BESIII experiment in 2016–2017 at center-of-mass energies between 4.19 and 4.28 GeV are measured with a precision better than 1% by analyzing large-angle Bhabha scattering events. The integrated luminosities of old datasets collected in 2010–2014 are updated by considering corrections related to detector performance, offsetting the effect of newly discovered readout errors in the electromagnetic calorimeter, which can haphazardly occur.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Multi-physics modeling of tungsten collector probe samples during the WEST C4 He campaign

Abstract We describe the results of a multi-scale, multi-physics modeling assessment of SOLPS-ITER, hPIC2, RustBCA and Xolotl, in which five single-crystal tungsten (W) samples were placed in a reciprocating collector probe and exposed to helium (He) plasma in the WEST fusion device. In our models, we considered a pure (100 %) He plasma, as well as one with oxygen (O) present (95% He 5% O) corresponding to the impurity concentration estimated during the C4 He campaign in WEST. Our SOLPS simulations approximately match experimental reciprocating Langmuir probe plasma measurements of plasma density and temperature. Using these plasma parameters as input, hPIC2 and RustBCA predict that the presence of oxygen impurities lead to a 15%–20% decrease in ion and heat fluxes to the surface, and an order of magnitude higher sputtering yields (compared with a pure He plasma). Xolotl predictions for the response of tungsten to plasma surface interactions (PSIs) agree with experimental LAMS analysis, and indicate large near-surface He concentrations, which quickly decay with depth. Our model also shows an increasing role of erosion—in removing the near-surface He—with time. Overall, slightly higher retention is predicted for tungsten exposed to a pure He plasma, with the largest differences in the near-surface gas content caused by the large oxygen-induced erosion. This highlights the important role that impurities play in PSI. Therefore, future work will focus on providing a fully self-consistent description of oxygen (and oxides, etc.) in our models, through multi-species implementation in GITR and inclusion of oxygen and tungsten oxide formation in Xolotl.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Development of a direct-sampling RF receiver for precision beam charge measurements in the MOLLER experiment

Here, we have developed and tested a direct-sampling RF receiver capable of measuring the amplitude of a 1497 MHz sinusoidal beam signal in 0.5 ms integration windows with a relative uncertainty of better than 10 parts per million. The receiver is intended for measuring signals from beam current monitoring cavities on the beamline of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The beam signal strength, frequency, and integration window fulfill the thus far unmet requirements of the upcoming MOLLER experiment to measure the beam charge for different helicity states.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The optimal use of segmentation for sampling calorimeters

One of the key design choices of any sampling calorimeter is how fine to make the longitudinal and transverse segmentation. Here, to inform this choice, we study the impact of calorimeter segmentation on energy reconstruction. To ensure that the trends are due entirely to hardware and not to a sub-optimal use of segmentation, we deploy deep neural networks to perform the reconstruction. These networks make use of all available information by representing the calorimeter as a point cloud. To demonstrate our approach, we simulate a detector similar to the forward calorimeter system intended for use in the ePIC detector, which will operate at the upcoming Electron Ion Collider. We find that for the energy estimation of isolated charged pion showers, relatively fine longitudinal segmentation is key to achieving an energy resolution that is better than 10% across the full phase space. These results provide a valuable benchmark for ongoing EIC detector optimizations and may also inform future studies involving high-granularity calorimeters in other experiments at various facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Critical points of the random cluster model with Newman–Ziff sampling

Here, we present a method for computing transition points of the random cluster model using a generalization of the Newman–Ziff algorithm, a celebrated technique in numerical percolation, to the random cluster model. The new method is straightforward to implement and works for real cluster weight q > 0. Furthermore, results for an arbitrary number of values of q can be found at once within a single simulation. Because the algorithm used to sweep through bond configurations is identical to that of Newman and Ziff, which was conceived for percolation, the method loses accuracy for large lattices when q > 1. However, by sampling the critical polynomial, accurate estimates of critical points in two dimensions can be found using relatively small lattice sizes, which we demonstrate here by computing critical points for non-integer values of q on the square lattice, to compare with the exact solution, and on the unsolved non-planar square matching lattice. The latter results would be much more difficult to obtain using other techniques.

97 MATHEMATICS AND COMPUTING↗