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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Close-up view of the interplay between lattice distortions and charge density waves: Case study on rare-earth nickel carbides

Using variable temperature total x-ray scattering and large-scale structure modeling, we study the temperature and composition evolution of lattice distortions and charge density waves (CDWs) in the archetypal strongly correlated system RENi⁢ C 2 (RE=Dy, Tb, Gd, and Sm). Joint analysis of reciprocal and real space data reveals the presence of strong lattice distortions that, depending on the RE species and temperature, appear periodic or remain local, forming a complex CDW phase diagram. Apparently, the CDWs in RENi⁢ C 2 materials arise from a common to the system lattice instability involving diverse distortion modes that persist when magnetic order also sets in at very low temperature. In conclusion, the results support the notion that intrinsic lattice distortions are important to the emergence of exotic electronic phases in strongly correlated systems and call for their further investigation using the advanced approach adopted here.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evidence for pseudo–Jahn-Teller distortions in the charge density wave phase of 1$\textit{T}-\text{TiSe}_2$

Here, the charge density wave (CDW) instability in 1$\textit{T}-\text{TiSe}_2$ is revisited to investigate its electronic and structural origins using angle resolved photoemission spectroscopy (ARPES), neutron diffraction, and density functional theory (DFT) calculations. The evidence for Jahn-Teller (JT)-like distortions in the CDW state is provided from the local structure analysis that shows splitting of the Ti-Se bonds into short and long. The magnitude of the split is inconsistent with the commonly accepted Di Salvo model for the structural distortions in the CDW phase. From the APRES data, it is deduced that a nontrivial temperature-dependent energy shift of the Se $4\textit{p}$ valence bands occurs, but is absent for the Ti $3\textit{d}$ conduction bands. Collectively, these observations suggest that a JT-like mechanism is most likely central to the CDW instability in 1$\textit{T}-\text{TiSe}_2$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Renormalization of one-pion exchange in chiral effective field theory for antinucleon-nucleon scattering

The renormalization of iterated one-pion exchange (OPE) is studied in Chiral Effective Field Theory ($\chi$EFT) for the antinucleon-nucleon ($\overline{N}N$) system. The OPE potential is cut off at a certain distance and contact interactions are represented by a complex spherical well with the same radius. We investigate the dependence on the cutoff radius of the phase shifts, inelasticities, and mixing angles for the low partial waves in $\overline{N}N$ scattering. We show that renormalization requires additional contact interactions compared to the expectation based on naive dimensional analysis. Results after renormalization are compared with the state-of-the-art energy-dependent partial-wave analysis of $\overline{N}N$ data. We compare our conclusions with applications of $\chi$EFT to the nucleon-nucleon system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

First Measurement of the |𝑡| Dependence of Incoherent 𝐽/𝜓 Photonuclear Production

The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 TeV. This rapidity interval corresponds to a Bjorken-x range (0.3–1.4)×10 -3 . Cross sections are given in five |t| intervals in the range 0.04 < |t |< 1 GeV 2 and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A Suppression-based STDP Rule Resilient to Jitter Noise in Spike Patterns for Neuromorphic Computing

Multi-spike models of synaptic plasticity, such as the triplet and suppression spike-timing-dependent plasticity (STDP) rules, exhibit better alignment with neurophysiological data in the brain compared to the pair-based STDP rule. Previous studies have empirically shown that the pair-based STDP rule can detect spatiotemporal spike patterns hidden in equally dense distractor spike trains in an unsupervised manner. However, it fails to detect spike patterns influenced by jitter noise. Given that spiking neural networks (SNNs) exhibit variability in generated spike trains in response to the same inputs, it becomes imperative to have learning rules capable of detecting spike patterns even in the presence of jitter noise. In this study, we introduce a simplified suppression-based STDP rule that demonstrates significantly enhanced tolerance to jitter in spike patterns compared to the pair-based STDP rule. Unlike the ideal suppression STDP rule, characterized by an exponential learning window and requiring high-resolution synapses, the simplified rule limits the synaptic efficacy update to a single bit at any given instant. Moreover, it employs 4-bit fixed-point synapses, facilitating straightforward implementation in neuromorphic hardware.

Gautam, Ashish [ORNL]↗
DOE OSTI2025

A Computational Procedure for Assessing I$_{c}(\varepsilon$) in Nb$_{3}$Sn/Bi-2212 Hybrid Magnets

The critical current of superconductors is commonly measured by testing unloaded wires under an external magnetic field. While stressed by intense Lorentz forces, the existing HTS/LTS superconductors are prone to a reduction in critical current before reaching their structural mechanical limit. Here, in this work, the magnetic and mechanical analysis of the FNAL 4-layer Bi-2212/Nb$_{3}$Sn hybrid dipole magnet is reported, aimed at predicting the critical current degradation for both the superconductors during powering at 16T. All the Rutherford cables in the coils of the hybrid magnet were modeled at the strand level in Ansys APDL with the heterogeneous cable model. Utilizing this detailed geometry, it was possible to evaluate the effects of strain on the critical current degradation for both the Nb$_{3}$Sn and Bi-2212 superconductors under the intense Lorentz forces. The analysis presented in this paper integrates strain-dependent critical current laws, with parameters derived from experimental data, to simulate the hybrid magnet's performance for all possible current-powering configurations. The proposed methodology enables a detailed assessment of conductor integrity and I$_{C}(\varepsilon$) reduction in existing hybrid magnet designs, providing a versatile and rigorous framework for optimizing future high-field hybrid magnets.

D'Agliano, A. [Lawrence Berkeley National Laborato↗
DOE OSTI2022

Machine Learning for the Discovery, Design, and Engineering of Materials

Machine learning (ML) has become a part of the fabric of high-throughput screening and computational discovery of materials. Despite its increasingly central role, challenges remain in fully realizing the promise of ML. This is especially true for the practical acceleration of the engineering of robust materials and the development of design strategies that surpass trial and error or high-throughput screening alone. Depending on the quantity being predicted and the experimental data available, ML can either outperform physics-based models, be used to accelerate such models, or be integrated with them to improve their performance. We cover recent advances in algorithms and in their application that are starting to make inroads toward ( a) the discovery of new materials through large-scale enumerative screening, ( b) the design of materials through identification of rules and principles that govern materials properties, and ( c) the engineering of practical materials by satisfying multiple objectives. We conclude with opportunities for further advancement to realize ML as a widespread tool for practical computational materials design.

Chemistry↗
DOE OSTI2020

Phase Transitions in (Mg,Fe) 2 SiO 4 Olivine under Shock Compression

The response of forsterite, Mg 2 SiO 4 , under dynamic compression is of fundamental importance for understanding its phase transformations and high-pressure behavior. Here, we have carried out an in situ X-ray diffraction study of laser-shocked polycrystalline and single-crystal forsterite from 19 to 122 GPa using the Matter in Extreme Conditions end-station of the Linac Coherent Light Source. Under laser-based shock loading, forsterite does not transform to the high-pressure equilibrium assemblage of MgSiO 3 bridgmanite and MgO periclase, as has been suggested previously. Instead, we observe forsterite and forsterite III, a metastable polymorph of Mg 2 SiO 4 , coexisting in a mixed-phase region from 33 to 75 GPa for both polycrystalline and single-crystal samples. Densities inferred from X-ray diffraction are consistent with earlier gas-gun shock data. At higher stress, the response is sample-dependent. Polycrystalline samples undergo amorphization above 79 GPa. For [010]- and [001]-oriented crystals, a mixture of crystalline and amorphous material is observed to 108 GPa, whereas the [100]-oriented forsterite adopts an unknown phase at 122 GPa. The first two sharp diffraction peaks of amorphous Mg 2 SiO 4 show a similar trend with compression as those observed for MgSiO 3 in both recent static- and laser-driven shock experiments. This study provides new insight into the transformation of forsterite under nanosecond-duration shock loading. This work emphasizes the importance of formation of metastable phases along the Hugoniot and adds to evidence that the 300-K single-crystal diamond anvil cell experiments have relevance for understanding structures formed under shock compression. In particular, the metastable phase forsterite III has now been shown to form under dynamic compression from 10s to 100s of nanoseconds as well as under 300-K static compression. Upon compression to higher pressures, Mg 2 SiO 4 transforms to an amorphous phase. These results have broad relevance for understanding the behavior of silicates under dynamic compression.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Proceedings of RIKEN BNL Research Center Workshop: Predictions for sPHENIX [Slides]

To complete the RHIC mission, sPHENIX was specifically designed to measure jet and heavy-flavor observables with a level of precision not previously achievable at RHIC. This will enhance our understanding of the quark-gluon plasma (QGP) properties and their temperature dependence beyond what is possible with existing and planned data from the LHC and other RHIC experiments. A major goal of the sPHENIX program is to address the question of the approach to thermalization of the quark-gluon plasma and its transport properties using hard probes such as jets and heavy flavor. The current three-year run plan includes Au+Au, p+Au and p+p collisions at 200 GeV. The Au+Au dataset provides a large QGP system to study the QGP properties. The p+Au dataset will allow for additional studies of the intriguing behavior observed in flow measurements from other RHIC experiments as well as transport properties of cold QCD matter and proton/nuclear structure. The p+p collisions provide a necessary reference for Au+Au and p+Au collisions and also allow for additional studies of proton structure. Anticipated measurements include but are not limited to, jet substructure observables, photon and heavy flavor tagged jets as well as comparisons of the production of the different upsilon states in all three collision systems. To maximize the rich physics sPHENIX is capable of accessing, this workshop will enhance the discussions between the experimentalists making the measurements and the theorists whose models will be tested and constrained by the new data. Since sPHENIX will start taking data in early 2023, this workshop is timely for theorists wishing to make final predictions of anticipated observables before data collection commences. In addition, it will provide an opportunity for theorists and experimentalists to propose and discuss new observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Systematic Extraction of Pion Parton Distributions Using Threshold Resummation and Applications to Pion TMDs

Following our recent Monte Carlo determination of the pion?s PDFs from Drell-Yan (DY) and leading neutron electroproduction data from the Jefferson Lab Angular Momentum (JAM) collaboration, we extend the analysis by including effects from threshold resummation. At higher orders in the strong coupling, ?S, soft gluon emissions cause large logarithmic corrections, which become important in the qq¯ channel of the DY partonic cross section near threshold. These corrections can be summed over all orders of ?S. However, different prescriptions exist for how the threshold resummation is implemented, for instance, using varying levels of approximation in the Minimal Prescription with cosine, expansion, and double Mellin methods. We present the Monte Carlo results of the first simultaneous fit of the valence, sea, and gluon distributions in the pion taking into account the ambiguities in the resummation calculations. The wide ranges of valence distributions at large x and the effective behavior of the valence distribution as x approaches 1 is discussed. While the PDFs are extracted through collinear factorization, we additionally present a dedicated study to the low and large lepton pair transverse momentum distributions (TMDs) in the same DY experimental data. By adjusting the nonperturbative TMD components, we analyze the degree of compatibility between data and theory across all regions of transverse momentum dependence. We attempt to match the description of the low transverse momentum region using Collins-Soper-Sterman (CSS) formalism and the large transverse momentum region, which is best described using collinear factorization.

Sato, Nobuo↗
DOE OSTI2023

High-Temperature Thermodynamics of Uranium from Ab Initio Modeling

We present high-temperature thermodynamic properties for uranium in its γ phase (γ-U) from first-principles, relativistic, and anharmonic theory. The results are compared to CALPHAD modeling. The ab initio electronic structure is obtained from density-functional theory (DFT) that includes spin–orbit coupling and an added self-consistent orbital-polarization (OP) mechanism for more accurate treatment of magnetism. The first-principles method is coupled to a lattice dynamics scheme that is used to model anharmonic lattice vibrations, namely, Self-Consistent Ab Initio Lattice Dynamics (SCAILD). The methodology can be summarized in the acronym DFT + OP + SCAILD. Upon thermal expansion, γ-U develops non-negligible magnetic moments that are included for the first time in thermodynamic theory. The all-electron DFT approach is shown to model γ-U better than the commonly used pseudopotential method. In addition to CALPHAD, DFT + OP + SCAILD thermodynamic properties are compared with other ab initio and semiempirical modeling and experiments. Our first-principles approach produces Gibbs free energy that is essentially identical to CALPHAD. The DFT + OP + SCAILD heat capacity is close to CALPHAD and most experimental data and is predicted to have a significant thermal dependence due to the electronic contribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting

A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance of different machine learning models under different supervised learning regimes and minimal input features. Specifically, the day-ahead forecasting capability of Bayesian neural network (BNN), support vector regression (SVR), and regression tree (RT) models was investigated by employing the same dataset for training and performance verification, thus enabling a valid comparison. The training regime analysis demonstrated that the performance of the investigated models was strongly dependent on the timeframe of the train set, training data sequence, and application of irradiance condition filters. Furthermore, accurate results were obtained utilizing only the measured power output and other calculated parameters for training. Consequently, useful information is provided for establishing a robust day-ahead forecasting methodology that utilizes calculated input parameters and an optimal supervised learning approach. Finally, the obtained results demonstrated that the optimally constructed BNN outperformed all other machine learning models achieving forecasting accuracies lower than 5%.

14 SOLAR ENERGY↗
DOE OSTI2024

Probing the Connection between IceCube Neutrinos and MOJAVE AGN

Active galactic nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multimessenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established, which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and 10 yr of neutrino data from IceCube. We also use a time-dependent approach, which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses, and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are ~3% and ~9% for the time-averaged and time-dependent cases, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Evidence for X-Ray Emission in Excess to the Jet-afterglow Decay 3.5 yr after the Binary Neutron Star Merger GW 170817: A New Emission Component

For the first ~3 yrs after the binary neutron star merger event GW 170817, the radio and X-ray radiation has been dominated by emission from a structured relativistic off-axis jet propagating into a low-density medium with n < 0.01 cm -3 . We report on observational evidence for an excess of X-ray emission at δt > 900 days after the merger. With L x ≈ 5 × 10 38 erg s -1 at 1234 days, the recently detected X-ray emission represents a ≥ 3.2σ (Gaussian equivalent) deviation from the universal post-jet-break model that best fits the multiwavelength afterglow at earlier times. In the context of JetFit afterglow models, current data represent a departure with statistical significance ≥ 3.1σ, depending on the fireball collimation, with the most realistic models showing excesses at the level of ≥ 3.7σ. A lack of detectable 3 GHz radio emission suggests a harder broadband spectrum than the jet afterglow. These properties are consistent with the emergence of a new emission component such as synchrotron radiation from a mildly relativistic shock generated by the expanding merger ejecta, i.e., a kilonova afterglow. In this context, we present a set of ab initio numerical relativity binary neutron star (BNS) merger simulations that show that an X-ray excess supports the presence of a high-velocity tail in the merger ejecta, and argues against the prompt collapse of the merger remnant into a black hole. Radiation from accretion processes on the compact-object remnant represents a viable alternative. Neither a kilonova afterglow nor accretion-powered emission have been observed before, as detections of BNS mergers at this phase of evolution are unprecedented

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Priority-enabled Load Balancing for Dispersed Computing

Opportunistic managed access to local in-network compute resources can improve the performance of distributed applications and reduce the dependence on shared network resources. Instead of backhauling application data to a centralized cloud data center for processing, networked services may be adaptively and continuously dispersed into shared compute resources that are closer to the source of need. While this approach has several benefits, support for mission-aware access to computation is often an afterthought, and is implemented as a brittle extension over traditional load-balancer solutions.In this work, we investigate the design of two priority-aware resource allocation strategies and two load-balancing dispatching strategies as first class citizens in an open-source dispersed computing middleware. We present a control theoretic analysis of these load-balancing primitives to identify weaknesses and strengths in our design, and recommend future directions. In parallel, we prototype two priority-aware allocation algorithms to validate our priority predictions. In initial experiments our prototype shows substantial gains in processing prioritized load. Finally, we make our source-code and experimental configurations open source.

Paulos, Aaron↗
DOE OSTI2022

Scalable access to shared files in a distributed system

Logic may pre-populate cache of compute nodes allocated to a user's session. Logic may access an image file of a global filesystem, the image file to comprise a first set of one or more files associated with a user session and a second set of one or more files upon which execution of the first set will depend. Logic may store the image file in local data storage of each compute node of a spanning tree of compute nodes allocated for the user session. Logic may unpack the image file based on the data. Logic may configure the local environment of each compute node in the spanning tree to identify a location in local memory of each of the files. And logic may initiate execution of a local filesystem service in each of the compute nodes of the spanning tree.

Oganezov, Alexander↗
DOE OSTI2026

INL Intern Poster Session

Characterization of off-gas constituents from nuclear fuel reprocessing can be measured using a residual gas analyzer. Characterization of this off-gas is important in a closed fuel cycle, where gasses such as Nox, Kr, I, and C-14 need to be removed from reprocessing plants to meet regulatory requirements. Both Kr and Xe have low chemical reactivity, making capture and separation difficult. Solid sorbents can be used to capture these gases as an alternative to cryogenic distillation, which is energy intensive and hazardous. AgZ-PAN and HZ-PAN are two solid sorbents that have demonstrated selective capture of Xe and Kr. A residual gas analyzer can be used to obtain breakthrough curves that demonstrate how well this adsorption and separation occur. The breakthrough curve is dependent on packing density, column size, and flow rate. Data obtained from the RGA was verified with a gas chromatographer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Error Characteristics and Scale Dependence of Current Satellite Precipitation Estimates Products in Hydrological Modeling

Satellite precipitation estimates (SPEs) are promising alternatives to gauge observations for hydrological applications (e.g., streamflow simulation), especially in remote areas with sparse observation networks. However, the existing SPEs products are still biased due to imperfections in retrieval algorithms, data sources and post-processing, which makes the effective use of SPEs a challenge, especially at different spatial and temporal scales. In this study, we used a distributed hydrological model to evaluate the simulated discharge from eight quasi-global SPEs at different spatial scales and explored their potential scale effects of SPEs on a cascade of basins ranging from approximately 100 to 130,000 km 2 . The results indicate that, regardless of the difference in the accuracy of various SPEs, there is indeed a scale effect in their application in discharge simulation. Specifically, when the catchment area is larger than 20,000 km2, the overall performance of discharge simulation emerges an ascending trend with the increase of catchment area due to the river routing and spatial averaging. Whereas below 20,000 km 2 , the discharge simulation capability of the SPEs is more randomized and relies heavily on local precipitation accuracy. Our study also highlights the need to evaluate SPEs or other precipitation products (e.g., merge product or reanalysis data) not only at the limited station scale, but also at a finer scale depending on the practical application requirements. Here we have verified that the existing SPEs are scale-dependent in hydrological simulation, and they are not enough to be directly used in very fine scale distributed hydrological simulations (e.g., flash flood). More advanced retrieval algorithms, data sources and bias correction methods are needed to further improve the overall quality of SPEs.

DTVGM↗