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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

First Measurement of Charged Current Muon Neutrino-Induced Kaon Production on Argon

The Micro Booster Neutrino Experiment (MicroBooNE) is a liquid argon time projection chamber (LArTPC) neutrino detector with an 85-ton active volume, located on-axis to the Booster Neutrino Beamline (BNB) at Fermilab. The detector is exposed to a neutrino flux with average energy of 800 MeV and was designed to study neutrino interactions on argon, particularly in the 1 GeV energy range. Among its main goals is the investigation of neutrino-induced strange particle production at final-state, with a specific interest on charged kaons ($K^{+}$). The understanding of this neutrino interaction is crucial for refining background models in future nucleon decay searches on others LArTPCs experiments such as the Deep Underground Neutrino Experiment (DUNE). Additionally, the techniques developed for the identification of neutrino-induced $K^{+}$ will contribute to improving particle identification methods in LArTPC-based detectors. This thesis is reporting the first-ever measurement of the flux-integrated cross section for charged-current muon neutrino-induced $K^{+}$ production on argon, determined to be $7.93 \pm 3.27(\text{stat.}) \pm 2.92(\text{syst.}) \times 10^{-42}$ cm$^2$/nucleon, based on the MicroBooNE dataset corresponding to $6.88 \times 10^{20}$ Protons on Target (POT).

Rodriguez Rondon, Jairo H. [South Dakota Sch. Mine↗
DOE OSTI2024

Amide-Engineered Metal–Organic Porous Liquids Toward Enhanced CO 2 Photoreduction Performance

The development of alternative catalytic systems toward high-performance CO 2 photoreduction is considered to be a promising approach to address the future energy demand and reduce the CO 2 emissions. However, CO 2 molecules are thermodynamically stable in nature, and thus the adsorption and activation of CO 2 on the surface of catalysts are the key factors to determine the conversion efficiency. Herein, a porous liquid (NH 2 -UIO-66 PL) is demonstrated for efficiently facilitating the adsorption and activation of CO 2 by modification of metal–organic framework (NH 2 -UIO-66) with ionic liquid via amide bonds. CdS/NH 2 -UIO-66 PL exhibits high-performance CO 2 -to-CO photoreduction with CO yield of 71.37 µmol g -1 h -1 and selectivity of 100%. Experiments and theoretical calculations show that the introduced amide moieties not only enriched the electron density at Zr 4+ active sites but also stabilize *COOH intermediate. In conclusion, the achievements provide an effective strategy for the development of metal–organic frameworks for energy catalysis.

*COOH reaction pathway↗
DOE OSTI2023

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Deposit geometry and oxygen concentration spatial variations due to composition change in printed functionally graded components

Functionally graded materials (FGMs) with site specific chemical composition are commonly manufactured by directed energy deposition (DED). Although previous work fabricated an FGM with a compositional variation between a ferritic and austenitic alloy, difficulties arose due to variations in deposit shape with composition change. This problem also occurs for FGMs in literature; however, unlike other cases, the thermophysical properties of these two alloys were similar throughout the build. Here, we investigate the role of chemical composition and surface-active elements on deposit geometry during the manufacture of FGMs by laser DED. Single-track experiments for the relevant FGM compositions are analyzed with results from a well-tested, three-dimensional, transient numerical heat transfer and fluid flow model and thermodynamic calculations. Experiments showed deposit shape varied as a function of composition for constant laser power and scan speed. Thermodynamic analysis indicated that the oxygen solubility in the fusion zone varied significantly for each composition used for the FGM. Numerical modeling revealed that the change in fluid flow caused by Marangoni convection due to dissolved oxygen in the fusion zone were mainly responsible for the changes in deposit shape observed in experiments. Finally, because oxygen can be introduced into the fusion zone through the feedstock as well as the surrounding atmosphere, these findings elucidate a previously unconsidered aspect of process control during DED fabrication of FGMs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Search for an Anomalous Excess of Single Photons in the MicroBooNE Neutrino Experiment

Neutrinos are some of the most elusive particles in the standard model, being incredibly common throughout the universe, but interacting with detectors incredibly rarely. Certain properties of neutrinos remain difficult to measure, including their masses, their CP violation properties, and whether or not they are their own antiparticles. Additionally, there have been several anomalous results in neutrino experiments which remain unexplained. MicroBooNE was built in order to study these anomalous results using a more capable detector technology, the Liquid Argon Time Projection Chamber. Specifically, MicroBooNE is able to search for an anomalous excess of low energy electromagnetic showers, which was previously observed by the MiniBooNE experiment. In particular, MicroBooNE is able to study whether the excess could consist of electron showers or photon showers. In this thesis, I describe a search for this anomalous excess by targeting neutral current Delta radiative decays, the largest expected source of single photons in MicroBooNE. We observe data consistent with our nominal expectation, but cannot rule out all potential sources of additional single photon events, particularly those with no visible proton activity. There remains significant potential to probe this channel in even more detail using MicroBooNE and other experiments in the near future.Hagaman, Lee

Hagaman, Lee [Chicago U.]↗
DOE OSTI2021

Spatiotemporal control of liquid crystal structure and dynamics through activity patterning

Active materials are capable of converting free energy into mechanical work to produce autonomous motion, and exhibit striking collective dynamics that biology relies on for essential functions. Controlling those dynamics and transport in synthetic systems has been particularly challenging. Here, we introduce the concept of spatially structured activity as a means of controlling and manipulating transport in active nematic liquid crystals consisting of actin filaments and light-sensitive myosin motors. In this work, simulations and experiments are used to demonstrate that topological defects can be generated at will and then constrained to move along specified trajectories by inducing local stresses in an otherwise passive material. These results provide a foundation for the design of autonomous and reconfigurable microfluidic systems where transport is controlled by modulating activity with light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Benchmarking boron carbide equation of state using computation and experiment

Boron carbide ( B 4 C ) is of both fundamental scientific and practical interest due to its structural complexity and how it changes upon compression, as well as its many industrial uses and potential for use in inertial confinement fusion (ICF) and high-energy density physics experiments. Here, we report the results of a comprehensive computational study of the equation of state (EOS) of B 4 C in the liquid, warm dense matter, and plasma phases. Our calculations are cross-validated by comparisons with Hugoniot measurements up to 61 megabar from planar shock experiments performed at the National Ignition Facility (NIF). Our computational methods include path integral Monte Carlo, activity expansion, as well as all-electron Green's function Korringa-Kohn-Rostoker and molecular dynamics that are both based on density functional theory. We calculate the pressure-internal energy EOS of B 4 C over a broad range of temperatures ( ~ 6 × 10 3 – 5 × 10 8 K) and densities (0.025–50 g / cm 3 ). We assess that the largest discrepancies between theoretical predictions are ≲ 5 % near the compression maximum at 1– 2 × 10 6 K. This is the warm-dense state in which the K shell significantly ionizes and has posed grand challenges to theory and experiment. By comparing with different EOS models, we find a Purgatorio model (LEOS 2122) that agrees with our calculations. The maximum discrepancies in pressure between our first-principles predictions and LEOS 2122 are ~ 18 % and occur at temperatures between 6 × 10 3 – 2 × 10 5 K, which we believe originate from differences in the ion thermal term and the cold curve that are modeled in LEOS 2122 in comparison with our first-principles calculations. To account for potential differences in the ion thermal term, we have developed three new equation-of-state models that are consistent with theoretical calculations and experiment. We apply these new models to 1D hydrodynamic simulations of a polar direct-drive NIF implosion, demonstrating that these new models are now available for future ICF design studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Bison Verification and Validation Activities for TRISO

Numerical modeling and simulation (M&S) tools play a key role in the research, development, and overall safety assessments of next-generation nuclear energy systems. One such tool, Bison, is a nuclear fuel performance code that is applicable to many fuel forms (e.g., light-water reactor fuel, oxide and metallic fuel for fast reactors, tri-structural isotropic (TRISO) fuel, and plate fuel), and it uses the finite element method to model the thermo- mechanical response of nuclear fuels. One fuel form widely utilized in Generation-IV high-temperature gas-cooled and fluoride- salt-cooled nuclear reactor concepts is TRISO fuel. Recently, Bison’s capabilities were significantly expanded to enable it to model the performance of TRISO particles and compacts. It is important that Bison’s computational results be reliable and predictive, since this code is used to inform high-consequence decisions. The various processes developed to address this issue generally entail two fundamental steps: verification and validation (V&V). Verification ensures that the code functions correctly and is reliable. Code/solution verification, code benchmark, and software quality assurance exercises are examples of verification activities. On the other hand, validation is the process of assessing a code’s capability to accurately model physical problems. Comparisons between code results and experiments quantify the validation level. Application of V&V procedures is crucial to the development of computational tools that are free of coding mistakes and can accurately represent reality. The current study presents an overview of Bison V&V activities relevant to the TRISO fuel concept, which include code/solution verification exercises, CRP-6 Benchmark—a Coordinated Research Program through the International Atomic Energy Agency (IAEA)—exercises, and validation exercises with the Advanced Gas Reactor (AGR)- 1/2/3/4 experiment series.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Cross-slip and easy-glide CRSS in titanium: Theoretical predictions and in-situ TEM measurements

This study investigates the mechanics of prismatic and first-order pyramidal $\langle$a$\rangle$ slip in titanium (Ti), elucidating the physics of easy-glide and cross-slip through a combination of theory and experiments. Screw-character prismatic (Pr) dislocations in Ti are of particular interest because their complex cores can be stable or unstable, leading to activation by either cross-slip or planar glide. To investigate these mechanisms, site-specific micro tensile samples were prepared using focused ion beam (FIB) milling and mounted on a push-to-pull (PTP) device for in-situ transmission electron microscopy (TEM) tensile testing. The in-situ experiments provide direct observations of the onset of dislocation motion and the precise determination of the critical resolved shear stress (CRSS) for the activated mechanisms, and its evolution with load cycling. A comprehensive theory has been developed to predict the CRSS values for easy glide, cross-slip, and multiplication of dislocations. Predicted critical stresses for pyramidal (π)-to-Pr and reverse cross-slip agree closely with the experimental measurements. The latter cross-slip stress is a factor of two higher than that of unobstructed planar slip. The model accounts for overlapping dislocation cores and employs a Wigner-Seitz based cell to evaluate misfit energies. By combining ab initio density functional theory (DFT) with anisotropic elasticity, the framework identifies minimum energy pathways for dislocation glide, which can be intermittent and zig-zag. A simplified expression utilizing (π) and Pr Schmid factor ratios is proposed for critical stress corresponding to (π)-to-Pr cross-slip transition. The results are strongly dependent on crystal orientation, underscoring non-Schmid behavior. Overall, this study explores key critical stress parameters essential for informing higher-scale simulations of plasticity in Ti.

Critical stress↗
DOE OSTI2023

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗
DOE OSTI2021

2'-O methylation of RNA cap in SARS-CoV-2 captured by serial crystallography

The genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronavirus has a capping modification at the 5'-untranslated region (UTR) to prevent its degradation by host nucleases. These modifications are performed by the Nsp10/14 and Nsp10/16 heterodimers using S-adenosylmethionine as the methyl donor. Nsp10/16 heterodimer is responsible for the methylation at the ribose 2'-O position of the first nucleotide. To investigate the conformational changes of the complex during 2'-O methyltransferase activity, we used a fixed-target serial synchrotron crystallography method at room temperature. We determined crystal structures of Nsp10/16 with substrates and products that revealed the states before and after methylation, occurring within the crystals during the experiments. Here we report the crystal structure of Nsp10/16 in complex with Cap-1 analog ( m7 GpppA m2'-O ). Inhibition of Nsp16 activity may reduce viral proliferation, making this protein an attractive drug target.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

No evidence of top–down effects by ants on litter decomposition in a temperate grassland

Ants play multiple roles in ecosystems, but their ability to affect decomposition processes in temperate grasslands is relatively unknown. We investigated whether the suppression of ant populations influenced litter decomposition in grasslands via predation of some decomposers (e.g., mites and springtails) and/or microbial activity and composition. We performed two successful ant suppression treatments (seven weeks, 37% suppression, year 1, 10 weeks, 70% suppression, year 2) over the course of a 59-week experiment. We then assayed the effects of ant suppression using coarse- and fine-mesh litterbags and evaluated litter chemistry, microbial and arthropod communities, and microbial enzyme activity. Ant suppression efforts reduced ant abundance and altered ant, arthropod decomposer, and non-ant predator community composition. However, ant suppression did not affect decomposer arthropod abundance, litter mass loss, microbial composition, or enzyme activity in litterbags. Litterbag mesh size did not alter microbial composition, perhaps due to a failure to exclude decomposers, as mites and springtails were more or equally abundant in fine-mesh bags. Nevertheless, mesh size did change litter chemistry, suggesting that mesh size-mediated microenvironments affect decomposition environment regardless of invertebrate exclusion. Coarse-mesh litterbags had higher concentrations of microbial sugars, lignin, and N and lower concentrations of litter C and crystalline cellulose than fine-mesh litterbags. Litterbag mesh size may alter decomposition processes irrespective of invertebrate abundance. We found no evidence that ant predation was an important driver of decomposer populations or decomposition in these systems, and we suspect redundancy at the top of the detrital food web dilutes the role of ants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Heat activates the AAA+ HslUV protease by melting an axial autoinhibitory plug

At low temperatures, protein degradation by the AAA+ HslUV protease is very slow. New crystal structures reveal that residues in the intermediate domain of the HslU 6 unfoldase can plug its axial channel, blocking productive substrate binding and subsequent unfolding, translocation, and degradation by the HslV 12 peptidase. Biochemical experiments with wild-type and mutant enzymes support a model in which heat-induced melting of this autoinhibitory plug activates HslUV proteolysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effect of ion interactions on the Raman spectrum of NO 3 − : Toward monitoring of low-activity nuclear waste at Hanford

Raman spectroscopy is a valuable in-situ technique for many applications. The concentrations of species in complex ionic mixtures of nuclear waste can be estimated using Raman measurements. However, it has been experimentally observed that ion interactions can cause a modification of Raman peak intensities and positions. The present work explores the nonlinear behavior associated with the nitrate anion, NO 3 − , which is present in abundance in low activity nuclear waste. We examine changes in the main Raman peak of the nitrate anion in the presence of other ions. A wide range of concentrations are covered, including those expected during direct-feed low-activity waste (DFLAW) processing at the Hanford site in the State of Washington. The experiments showed that the ions interact and associate to form ion pairs, which results in a blue shift (i.e., a shift towards higher wavenumbers) in the main Raman peak of nitrate. The results indicate that cation concentration is a better predictor of the peak shift, compared to ionic strength, both for binary and multicomponent mixtures. These findings have direct implications on the development of spectra-to-composition models for the DFLAW system, since they show deviations from the linearity assumptions used in common chemometric models.

42 ENGINEERING↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CONFLUX: A standardized framework to calculate reactor antineutrino flux

Nuclear fission reactors are abundant sources of antineutrinos for neutrino physics experiments. The flux and spectrum of antineutrinos emitted by a reactor can indicate its activity and composition, suggesting potential applications of neutrino measurements beyond fundamental scientific studies that may be valuable to society. The utility of reactor antineutrinos for applications and fundamental science is dependent on the availability of precise predictions of these emissions. For example, in the last decade, disagreements between reactor antineutrino measurements and models have inspired revision of reactor antineutrino calculations and standard nuclear databases as well as searches for new fundamental particles not predicted by the Standard Model of particle physics. Past predictions and descriptions of the methods used to generate them are documented to varying degrees in the literature, with different modeling teams incorporating a range of methods, input data, and assumptions. The resulting difficulty in accessing or reproducing past models and reconciling results from differing approaches complicates the future study and application of reactor antineutrinos. The CONFLUX (Calculation Of Neutrino FLUX) software framework is a neutrino prediction tool built with the goal of simplifying, standardizing, and democratizing the process of reactor antineutrino flux calculations. CONFLUX includes three primary methods for calculating the antineutrino emissions of nuclear reactors or individual beta decays that incorporate common nuclear data and beta decay theory. The software is prepackaged with the current nuclear databases, including ENDF.B/VIII, JEFF-3.3, and ENSDF, and it includes the capability to predict time-dependent reactor emissions, adjust nuclear database or beta decay inputs/assumptions, and propagate related sources of uncertainty. Here, this paper describes the CONFLUX software structure, details the methods used for flux and spectrum calculations, and provides examples of potential use cases.

Zhang, Xianyi [Lawrence Livermore National Laborat↗
DOE OSTI2021

Effects of laminin-111 peptide coatings on rat neural stem/progenitor cell culture

Neurons require adhesive scaffolds for their growth and differentiation. Laminins are a major cell adhesive component of basement membranes and have various biological activities in the peripheral and central nervous systems. Here, we evaluated the biological activities of 5 peptides derived from laminin-111 as a scaffold for mouse neuroblastoma Neuro2a cells and rat neural stem/progenitor cells (NPCs). The 5 peptides showed Neuro2a cell attachment activity similar to that of poly-d-lysine. However, when NPCs were cultured on the peptides, 2 syndecan-binding peptides, AG73 (RKRLQVQLSIRT, mouse laminin α1 chain 2719-2730) and C16 (KAFDITYVRLKF, laminin γ1 chain 139–150), demonstrated significantly higher cell attachment and neurite extension activities than other peptides including integrin-binding ones. Long-term cell culture experiments showed that both AG73 and C16 supported the growth of neurons and astrocytes that had differentiated from NPCs. Furthermore, C16 markedly promoted the expression of neuronal markers such as synaptosomal-associated protein-25 and syntaxin 1A. These results indicate that AG73 and C16 are useful for NPC cultures and that C16 can be applied to specialized research on synapses in differentiated neurons. These peptides have the potential for use as valuable biomaterials for NPC research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

First-Row Transition Metal Antimonates for the Oxygen Reduction Reaction

The development of inexpensive and abundant catalysts with high activity, selectivity, and stability for the oxygen reduction reaction (ORR) is imperative for the widespread implementation of fuel cell devices. Herein, we present a combined theoretical–experimental approach to discover and design first-row transition metal antimonates as excellent electrocatalytic materials for the ORR. Theoretically, we identify first-row transition metal antimonates–MSb 2 O 6 , where M = Mn, Fe, Co, and Ni–as nonprecious metal catalysts with good oxygen binding energetics, conductivity, thermodynamic phase stability, and aqueous stability. Among the considered antimonates, MnSb 2 O 6 shows the highest theoretical ORR activity based on the 4e – ORR kinetic volcano. Experimentally, nanoparticulate transition metal antimonate catalysts are found to have a minimum of a 2.5-fold enhancement in intrinsic mass activity (on transition metal mass basis) relative to the corresponding transition metal oxide at 0.7 V vs RHE in 0.1 M KOH. MnSb 2 O 6 is the most active catalyst under these conditions, with a 3.5-fold enhancement on a per Mn mass activity basis and 25-fold enhancement on a surface area basis over its antimony-free counterpart. Electrocatalytic and material stability are demonstrated over a 5 h chronopotentiometry experiment in the stability window identified by theoretical Pourbaix analysis. Furthermore, this study further highlights the stable and electrically conductive antimonate structure as a framework to tune the activity and selectivity of nonprecious metal oxide active sites for ORR catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗