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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 235 records · Page 13

Peak‐in‐Valley Metal Nano‐Architectures via E‐Beam‐Guided Metal Oxide Redox

Focused electron beams enable nanoscale material modification via localized etching or deposition. In liquid-phase electron-beam-mediated processing, radiolysis-driven redox reactions present an opportunity to control both etching and deposition simultaneously. Here, this duality using a water-ammonia solvent as a tunable redox mediator on copper surfaces is demonstrated. At lower ammonia concentrations, the oxidation process dominates, etching copper to sub-50-nm depths. The copper ions and ion-complexes released during this initial oxidation step are reduced by solvated electrons resulting in metal deposition into the etched sites, over longer e-beam exposures, producing characteristic peak-in-valley nanostructures. Conversely, at higher ammonia concentrations copper-ammine ion complexation and radiolytic oxidizing species scavenging by ammonia occur at higher rates, creating a reducing environment conducive to rapid beam-guided copper deposition. Reaction-transport simulations and experiments are performed to show the effects of ammonia-mediated radiolysis chemistry, describing the direct influence of solvent concentration on redox balance and the outcome of e-beam guided processing. By uniting both etching and deposition within a single framework, this work provides a versatile route for controlled surface nanostructuring.

copper nanostructures↗

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Creation of Multi-Principal Element Alloy NiCoCr Nanostructures via Nanosecond Laser-Induced Dewetting

The multi-principal element alloy nanoparticles (MPEA NPs), a new class of nanomaterials, present a highly rewarding opportunity to explore new or vastly different functional properties than the traditional mono/bi/multimetallic nanostructures due to their unique characteristics of atomic-level homogeneous mixing of constituent elements in the nanoconfinements. Here, in this paper, the successful creation of NiCoCr nanoparticles, a well-known MPEA system is reported, using ultrafast nanosecond laser-induced dewetting of alloy thin films. Nanoparticle formation occurs by spontaneously breaking the energetically unstable thin films in a melt state under laser-induced hydrodynamic instability and subsequently accumulating in a droplet shape via surface energy minimization. While NiCoCr alloy shows a stark contrast in physical properties compared to individual metallic constituents, i.e., Ni, Co, and Cr, yet the transient nature of the laser-driven process facilitates a homogeneous distribution of the constituents (Ni, Co, and Cr) in the nanoparticles. Using high-resolution chemical analysis and scanning nanodiffraction, the environmental stability and grain arrangement in the nanoparticles are further investigated. Thermal transport simulations reveal that the ultrashort (≈100 ns) melt-state lifetime of NiCoCr during the dewetting event helps retain the constituent elements in a single-phase solid solution with homogenous distribution and opens the pathway to create the unique MPEA nanoparticles with laser-induced dewetting process.

36 MATERIALS SCIENCE↗

Fingerprinting Superconductors by Disentangling Andreev and Quasiparticle Currents Across Tunable Tunnel Junctions

Tunneling Andreev reflection (TAR) spectroscopy provides a new approach to identify superconducting pairing symmetry at the atomic scale. Using atomistic superconducting transport simulations, we reveal the mechanism by which TAR can distinguish between pairing symmetries, which is complementary to traditional conductance-based techniques. In particular, owing to the additivity of the excess tunneling decay rate, the TAR spectrum is a weighted average of the contributions from quasiparticle currents, Andreev reflection, and higher-order scattering processes, and their relative weights depend on both the superconducting order parameter and the coupling strength. Within the local tunneling model, TAR dominates mid-gap conductance for s-wave superconductors, is suppressed for d-wave, and coexists with quasiparticle tunneling in sign-changing symmetries if the expectation value for the superconducting gap remains finite. Meanwhile, higher-order processes generally enhance the TAR signal when GN exceeds approximately 0.1G0. As a result, TAR provides a rich spectral fingerprint of the underlying pairing symmetry and electronic structure, enabling atomically resolved identification of unconventional superconducting states.

Maksymovych, Petro [Clemson University]↗

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle $θ_s$ is defined based on melt pool overlap geometry, and the range of $θ_s$ over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. Importantly, these results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.

36 MATERIALS SCIENCE↗

Chemical impacts of subsurface CO 2 and brine on shallow groundwater quality

Leakage from geologic CO 2 sequestration (GCS) sites to overlying shallow drinking water aquifers is a tangible risk. A primary purpose of this study is to assess the potential impacts of CO 2 leakage into a fresh-water aquifer with associated CO 2 -water-sediment interactions. Here, the study site is the Ogallala aquifer overlying an active demonstration-scale GCS site in north Texas, USA. Using the results of combined batch experiments and reactive transport simulations, we discuss the effects of salinity on potential trace metal release and the potential for groundwater quality recovery after leakage ceases.

54 ENVIRONMENTAL SCIENCES↗

Possible impacts of molten salt reactors on the International Monitoring System

Molten salt reactors (MSRs) are gaining support as many countries look for ways to increase power generation and replace aging nuclear energy production facilities. MSRs have inherently safe designs, are scalable in size, can burn transuranic wastes from traditional solid fuel nuclear reactors, can store excess heat in thermal reservoirs for water desalination, and can be used to produce medical isotopes as part of the real-time liquid-fuel recycling process. The ability to remove 135 Xe in real time from the fuel improves the power production in an MSR because 135 Xe is the most significant neutron-absorbing isotope generated by nuclear fission. Xenon-135, and other radioactive gases, are removed by sparging the fuel with an inert gas while the liquid fuel is recirculated from the reactor inner core through the heat exchangers. Without effective abatement technologies, large amounts of radioactive gas could be released during the sparging process. This work examines the potential impact of radioxenon releases on samplers used by the International Monitoring System (IMS) to detect nuclear explosions. Here, atmospheric transport simulations from seven hypothetical MSRs on different continents were used to evaluate the holdup time needed before release of radioxenon so IMS samplers would register few detections. Abatement technologies that retain radioxenon isotopes for at least 120 d before their release will be needed to mitigate the impacts from a molten salt breeder reactor used to replace a nuclear power plant. A holdup time of about 150 d is needed to reduce emissions to the average level of current nuclear power plants.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

For this work, we numerically evaluated photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively) on stream corridor transport. Correctly separating HSZ and SSZ effects is critical to estimating the hydro-biogeochemical function of a stream because HSZs and SSZs expose solutes to significantly different biogeochemical conditions, like sunlight exposure, microbial processes, and oxygen availability. Our numerical experiments used a multiscale river-corridor transport model implemented in the ATS code, which accommodates multiple storage zones with distinct travel time distributions and biogeochemical reactions. For parameter inferences, we used Bayesian inverse modeling. We found that breakthrough curves for photo-decaying tracers from day and night injection can delineate surface and hyporheic transient storage contributions, but only when interpreted jointly through a two-storage zone model. Numerical experiments that used only daytime injection or interpreted breakthrough curves with a single storage zone model yielded good fit to breakthrough curves, but parameter estimates were biased and controlling processes misattributed, examples of good model fits for the wrong reasons. Using those biased parameter estimates in reactive transport simulations resulted in significantly different projections of denitrification, which underscores the potential for stream function to be mischaracterized if tracer tests are interpreted through an inappropriately simplified model for transient storage. More generally, this study highlights the role of modeling in evaluating the experimental design and identifying the potential of system mischaracterization and its implications.

54 ENVIRONMENTAL SCIENCES↗

Correlated characterization of 20 Ne-implanted targets using nuclear reaction analysis, Rutherford backscattering spectrometry, and ion transport modeling

In this article, we present the preparation and characterization of a large sample of implanted noble gas targets for use in precision nuclear astrophysics measurements with intense proton beams. Tantalum and titanium backings were prepared using wet-acid etching, outgassed via resistive heating, and implanted with 20 Ne + beams from differing ion sources. These experimental targets were investigated using both nuclear reaction analysis techniques on the 1169-keV resonance in 20 Ne(p, $\gamma$) 21 Na and Rutherford backscattering spectrometry analysis with 2-MeV α-particle beams. Results from these analyses reveal small target-to-target variations in stoichiometry, while exhibiting excellent agreement independent of ion-beam analysis method. We also present a self-consistent validation of the nuclear reaction analysis results using ion transport simulations in TRIM-2013 that rely on input parameters from SIMNRA scattering-yield fits to Rutherford backscattering spectra. In addition to a complete description of the implantation profile, this analysis method provides an alternate solution for characterizing a large sample of implanted targets when no suitable resonances are available for nuclear reaction analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enabling event-by-event precision in γ-ray cascades for neutron-induced reactions

Neutron-induced γ-ray spectra provide key inputs for modern active interrogation applications. A precise modeling of the nuclear reaction and subsequent emission of γ rays is challenging and often impossible due to limitations on evaluated data file formats and nuclear transport simulation codes. We present a framework that addresses these challenges by combining experimental data and reaction-model calculation outputs into an extended candidate version of the Generalized Nuclear Data Structure (GNDS) file, the successor format for the legacy Evaluated Nuclear Data File (ENDF-6). This proposed GNDS hierarchical format contains all the necessary ingredients for inline γ-ray cascade reproduction with event-by-event precision, including continuum–continuum and continuum–discrete transitions following neutron-capture and inelastic neutron scattering reactions. Cascade-event generation based on our approach demonstrates improved energy conservation on an event-by-event basis and permits the use of γ-γ coincidences in applications. This work offers, for the first time, a method to generate neutron-capture and inelastic neutron-scattering γ-ray cascades where energy conservation, correlations, and experimental primaries are fully accounted for.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Immortal rays: Rethinking random ray neutron transport on GPU architectures

The Random Ray Method (TRRM) is a recently developed adaptation of the Method of Characteristics for neutral particle transport simulations. TRRM has demonstrated excellent performance on 3D nuclear reactor benchmark problems using CPU-based compute systems. When porting to GPU-based systems, however, new performance challenges arise that are unique to processors targeting massive fine-grained parallelism. For smaller problems, or for large problems that are domain decomposed across many computational nodes, the problem size per node has insufficient parallelism to saturate GPU node resources, thus greatly limiting speedup. In this study, we report on a newly developed “immortal ray” variant of TRRM. Here, the immortal ray technique exposes significantly more fine-grained parallelism by fundamentally reformulating the numerical details of ray discretization, resulting in performance tradeoffs with significant overall benefit on GPUs. For very small 2D simulation problems we found the new immortal ray variant allowed for up to a 4.4x speedup when run on a single GPU. For larger 3D simulation problems we found the new variant improved strong scaling by 3x when run on the Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

Ambiguities in the hadro-chemical freeze-out of Au+Au collisions at SIS18 energies and how to resolve them

The thermal fit to preliminary HADES data of Au+Au collisions at $\sqrt{s_{NN}}$=2.4 GeV shows two degenerate solutions at T≈50 MeV and T≈70 MeV. The analysis of the same particle yields in a transport simulation of the UrQMD model yields the same features, i.e. two distinct temperatures for the chemical freeze-out. While both solutions yield the same number of hadrons after resonance decays, the feeddown contribution is very different for both cases. This highlights that two systems with different chemical composition can yield the same multiplicities after resonance decays. The nature of these two minima is further investigated by studying the time-dependent particle yields and extracted thermodynamic properties of the UrQMD model. It is confirmed, that the evolution of the high temperature solution resembles cooling and expansion of a hot and dense fireball. The low temperature solution displays an unphysical evolution: heating and compression of matter with a decrease of entropy. These results imply that the thermal model analysis of systems produced in low energy nuclear collisions is ambiguous but can be interpreted by taking also the time evolution and resonance contributions into account.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ab-initio nucleon-nucleon correlations and their impact on high energy 16 O+ 16 O collisions

Investigating nucleon-nucleon correlations inherent to the strong nuclear force is one of the core goals in nuclear physics research. We showcase the unique opportunities offered by collisions of 16 O nuclei at high-energy facilities to reveal detailed many-body properties of the nuclear ground state. We interface existing knowledge about the geometry of 16 O coming from ab-initio calculations of nuclear structure with transport simulations of high-energy 16 O+ 16 O collisions. Bulk observables in these processes, such as the elliptic flow or the fluctuations of the mean transverse momentum, are found to depend significantly on the input nuclear model and to be sensitive to realistic clustering and short-range repulsive correlations, effectively opening a new avenue to probe these features experimentally. This finding demonstrates collisions of oxygen nuclei as a tool to elucidate initial conditions of small collision systems while fostering connections with effective field theories of nuclei rooted in quantum chromodynamics (QCD).

Zhang, Chunjian [Fudan University, Shanghai (China↗

Analytic model for neutral penetration and plasma fueling

Neutral atoms recycled from wall interaction interact with confined plasma, thereby refuelling it, most strongly in the region closest to the wall. This occurs near the X-point in diverted configurations, or else near the wall itself in limited configurations. A progression of analytic models is developed for neutral density in the vicinity of a planar or linear source in an ionising domain. First-principles neutral transport simulations with DEGAS2 are used throughout to test the validity and limits of the model when using equivalent sources. The model is further generalised for strong plasma gradients or the inclusion of charge exchange. An important part of the problem of neutral fuelling from recycling is thereby isolated and solved with a closed-form analytic model. A key finding is that charge exchange with the confined plasma can be significantly simplified with a reasonable sacrifice of accuracy by treating it as a loss. The several assumptions inherent to the model (and the simulations with which it is compared) can be adapted according to the particular behaviour of neutrals in the divertor and the manner in which they cross the separatrix.

fusion plasma↗

Impact of Urban Pollution on Organic-Mediated New-Particle Formation and Particle Number Concentration in the Amazon Rainforest

A major challenge in assessing the impact of aerosols on climate change is to understand how human activities change aerosol loading and properties relative to the pristine-preindustrial baseline. Here we combine chemical transport simulation and field measurements to investigate the effect of anthropogenic pollution from an isolated metropolis on particle number concentration over the preindustrial-like Amazon rainforest through various new-particle formation (NPF) mechanisms and primary particle emissions. To represent organic-mediated NPF, we employ a state-of-the-art model that systematically simulates the formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes, and further update the model to improve organic NPF simulations under human-influenced conditions. Results show that urban pollution from the metropolis increases particle number concentration by a factor of 5–25 over the downwind region (within 200 km from city center) compared to background conditions. Overall, our model indicates that NPF contributes over 70% of the total particle number in the downwind region except immediately adjacent to the sources. Among different NPF mechanisms, the ternary NPF involving organics and sulfuric acid overwhelmingly dominates. The improved understanding of particle formation mechanisms will help better quantify anthropogenic aerosol forcing from pristine-preindustrial times to present day.

54 ENVIRONMENTAL SCIENCES↗

Inhibition of Chromium(III) Oxidation through Manganese(IV) Oxide Passivation and Iron(II) Abiotic Reduction

Manganese (Mn) oxides are strong oxidants that are ubiquitous in soils and can oxidize redox-active metals, including chromium (Cr). In soil environments, trivalent chromium (Cr(III)) is a benign, immobile micronutrient, whereas the hexavalent Cr(VI) form is present as a highly mobile, toxic chromate oxyanion. Although many studies have characterized the capacity of Mn(III/IV) oxides to oxidize Cr(III) to toxic Cr(VI), the oxidative capacity of Mn oxides in the presence of potentially passivating soil constituents, specifically reduced soluble iron (Fe(II) aq ), remains unresolved. We hypothesized that chemical processes at redox interfaces, such as diffusion-limited environments within soil aggregates, can lead to decreased Cr(VI) production from Mn oxide-driven oxidation due to passivation by Fe(II) aq . A multichamber diffusion-limited reactor was used to simulate transport at soil redox interfaces and investigate the capacity of poorly crystalline and crystalline Mn oxides to oxidize solid Cr(III) minerals to Cr(VI) in the presence of Fe(II) aq . As predicted, Cr(VI) was produced through the Mn oxide-catalyzed oxidation of Cr(III) at a rate controlled by the solubility of Cr(OH) 3 . However, in the presence of Fe(II) aq , the concentration of aqueous Cr(VI) decreased as a function of the Fe(II) aq concentration, where high concentrations of Fe(II) aq completely inhibited Cr(VI) production, likely through both the passivation of the Mn oxide and the direct reduction of Cr(VI) by Fe(II). At both low (14 μM) and high (100 μM) Fe(II) aq concentrations, the iron oxide minerals hematite (Fe 2 O 3 ) and goethite (α-FeOOH) were associated with the Mn oxides, which can cause surface passivation, a likely role that decreases Cr(III) oxidation. Additionally, the Cr(III) oxidation rate decreased with increasing crystallinity of the Mn oxides whether or not Fe(II) was present.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ionization-Induced Subcycle Metallization of Nanoparticles in Few-Cycle Pulses

Strong-field laser-matter interactions in nanoscale targets offer unique avenues for the generation and detailed characterization of matter under extreme conditions. Field-driven, sub-cycle ionization-induced metallization of nanoscale solids in intense laser fields has been predicted (Peltz et al. Time-Resolved X-ray Imaging of Anisotropic Nano-plasma Expansion. Phys. Rev. Lett. 2014, 113, 133401), but its observation was hampered by a lack of a smoking gun. Here, we report the ultrafast metallization of isolated dielectric and semiconducting nanoparticles under intense few-cycle laser pulses. The highest-energy electron emission is found to be a decisive proof that shows a characteristic cutoff modification to a metallic limit for intensities high enough to ignite carrier avalanching in the volume of the particles. Furthermore, semiclassical Mean-field Mie Monte-Carlo transport simulations reveal the underlying dynamics and explain the observed evolution by near-field driven electron backscattering from the metallizing target.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

Abstract Identification of a heterogeneous conductivity field and reconstruction of a contaminant release history are key aspects of subsurface remediation. These two goals are achieved by combining model predictions with sparse and noisy hydraulic head and concentration measurements. Solution of this inverse problem is notoriously difficult due to, in part, high dimensionality of the parameter space and high computational cost of repeated forward solves. We use a convolutional adversarial autoencoder (CAAE) to parameterize a heterogeneous non‐Gaussian conductivity field via a low‐dimensional latent representation. A three‐dimensional dense convolutional encoder‐decoder (DenseED) network serves as a forward surrogate of the flow and transport model. The CAAE‐DenseED surrogate is fed into the ensemble smoother with multiple data assimilation (ESMDA) algorithm to sample from the Bayesian posterior distribution of the unknown parameters, forming a CAAE‐DenseED‐ESMDA inversion framework. The resulting CAAE‐DenseED‐ESMDA inversion strategy is used to identify a three‐dimensional contaminant source and conductivity field. A comparison of the inversion results from CAAE‐ESMDA with physical flow and transport simulator and from CAAE‐DenseED‐ESMDA shows that the latter yields accurate reconstruction results at the fraction of the computational cost of the former.

Zhou, Zitong↗