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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Measurement of prompt D 0 , D + , D *+ , and DS+$ {\mathrm{D}}_{\mathrm{S}}^{+} $ production in p–Pb collisions at sNN$ \sqrt{{\mathrm{s}}_{\mathrm{NN}}} $ = 5.02 TeV

The measurement of the production of prompt D 0 , D + , D *+, and $D_S^+$ mesons in proton–lead (p–Pb) collisions at the centre-of-mass energy per nucleon pair of \mathrm{\sqrt{s_{NN}}}$ = 5.02 TeV, with an integrated luminosity of 292 ± 11 μb -1 , are reported. Differential production cross sections are measured at mid-rapidity (-96 < y cms < 0.04) as a function of transverse momentum (p T ) in the intervals 0 < p T < 36 GeV/c for D 0 , 1 < p T < 36 GeV/c for D + and D *+ , and 2 < p T < 24 GeV/c for D + mesons. For each species, the nuclear modification factor R pPb is calculated as a function of p T using a proton-proton (pp) reference measured at the same collision energy. The results are compatible with unity in the whole p T range. The average of the non-strange D mesons R pPb is compared with theoretical model predictions that include initial-state effects and parton transport model predictions. The p T dependence of the D 0 , D + , and D *+ nuclear modification factors is also reported in the interval 1 < p T < 36 GeV/c as a function of the collision centrality, and the central-to-peripheral ratios are computed from the D-meson yields measured in different centrality classes. The results are further compared with charged-particle measurements and a similar trend is observed in all the centrality classes. The ratios of the p T -differential cross sections of D 0 , D + , D *+ , and $D_S^+$ mesons are also reported. The $D_S^+$ and D + yields are compared as a function of the charged-particle multiplicity for several p T intervals. No modification in the relative abundances of the four species is observed with respect to pp collisions within the statistical and systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Special Issue: Geostatistics and Machine Learning

Abstract Recent years have seen a steady growth in the number of papers that apply machine learning methods to problems in the earth sciences. Although they have different origins, machine learning and geostatistics share concepts and methods. For example, the kriging formalism can be cast in the machine learning framework of Gaussian process regression. Machine learning, with its focus on algorithms and ability to seek, identify, and exploit hidden structures in big data sets, is providing new tools for exploration and prediction in the earth sciences. Geostatistics, on the other hand, offers interpretable models of spatial (and spatiotemporal) dependence. This special issue on Geostatistics and Machine Learning aims to investigate applications of machine learning methods as well as hybrid approaches combining machine learning and geostatistics which advance our understanding and predictive ability of spatial processes.

58 GEOSCIENCES↗
DOE OSTI2020

Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas

Estimation of daily suspended sediment concentration (SSC) is required for water resources and environment management. In this paper, a copula-based stochastic method was proposed for daily SSC simulation. Here, the multivariate copula function, constructed based on a bivariate copula and two bivariate conditional probability distributions, was used to model the temporal and cross dependence structures in daily SSCs. Then, the daily SSCs were generated by sampling from the multivariate conditional distribution. As a result, synthetic long-term SSCs data beyond the limited observation period can be provided for water resources managers, which plays a critical role in accurately estimating frequency and magnitude of extreme SSCs events. The proposed method was under rigorous examination by applying to a case study at Pingshan station in the Jinsha River Basin, China. Results showed that the generated daily SSC sequences not only had a high degree of accuracy in preserving the statistical characteristics of the daily SSC observations, but also captured both the temporal correlation and the cross-correlation between the daily streamflow and daily SSC. Specifically, the average daily relative error values corresponding to mean, standard deviation, skewness, lag-1 temporal correlation, and cross correlation were 0.87%, 4.24%, 7.52%, 0.51% and 2.02%, respectively. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resources management such as frequency analysis and risk assessment of extreme SSC events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Steric effects of central dogma processes on the compaction and segregation of bacterial nucleoids

The bacterial cytoplasm is characterized by a distinctive membrane-less organelle, the nucleoid, which harbors the chromosomal DNA. Here, we investigate the steric effects of dynamic processes associated with transcription and translation on the structure of this organelle using coarse-grained molecular dynamics simulations that incorporate out-of-equilibrium reactions. Our model captures the scale of the entire cell and incorporates a reaction-diffusion system for ribosomes and polyribosomes, coupling their nonequilibrium kinetics to DNA excluded volume interactions. Our findings demonstrate that out-of-equilibrium reactions increase the size of the nucleoid and the number of ribosomes in this subcellular region. In addition, we show that nucleoid size is proportional to transcriptional activity. Our model reproduces the time-dependent change in nucleoid size observed in rifampicin treatment experiments, where the pool of polyribosomes is depleted. Furthermore, we find that these active processes are essential for complete sister chromosome separation and correct nucleoid positioning within the cell. Overall, our study reveals the effects of the central dogma processes on the internal organization and localization of bacterial nucleoids.

Chang, Mu-Hung [Univ. of Tennessee, Knoxville, TN ↗
DOE OSTI2022

Geometric learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity

The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpinning of those phenomenological laws have long been criticized as barriers to creating realistic models. In this work, geometric machine learning on graph data (e.g. finite element solutions) is used as a means to establish a connection between nonlinear dimensional reduction techniques and plasticity models. Geometric learning-based encoding on graphs allows the embedding of rich time-history data onto a low-dimensional Euclidean space such that the evolution of plastic deformation can be predicted in the embedded feature space. Finally, a corresponding decoder can then convert these low-dimensional internal variables back into a weighted graph such that the dominating topological features of plastic deformation can be observed and analyzed.

42 ENGINEERING↗
DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗
DOE OSTI2024

Concurrent measurement of strain and chemical reaction rates in a calcite grain pack undergoing pressure solution: Evidence for surface-reaction controlled dissolution

Pressure solution is inferred to be a significant contributor to sediment compaction and lithification, especially in carbonate sediments. For a sediment deforming primarily by pressure solution, the compaction rate should be directly related to the rate of calcite dissolution, transport along grain contacts, and calcite reprecipitation. Previous experimental work has shown that there is evidence that deformation in wet calcite grain packs is consistent with control by pressure solution, but considerable ambiguity remains regarding the rate limiting mechanism. We present the results of laboratory compaction experiments designed to directly measure calcite dissolution and precipitation rates (recrystallization rates) concurrently with strain rate to test whether measured rates are consistent with predicted rates both in absolute magnitude and time evolution. Recrystallization rates are measured using trace element chemistry (Sr/Ca, Mg/Ca) and isotopes (87Sr/86Sr) of fluids flowing slowly through a compacting grain pack as it is being triaxially compressed. Imaging techniques are used to characterize the grain contacts and strain effects in the post-experiment grain pack. Our data show that calcite recrystallization rates calculated from all three geochemical parameters are in approximate agreement and that the rates closely track strain rate. The geochemically inferred rates are close to predicted rates in absolute magnitude. Uncertainty in grain contact dimensions makes distinguishing between surface reaction control and diffusion control difficult. Measured reaction rates decrease faster than predicted from standard pressure solution creep flow laws. This inconsistency may indicate that calcite dissolution rates at grain contacts are more complex, and more time-dependent, than suggested by geometric models designed to predict grain contact stresses.

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

Electrical conductivity of TaO x as function of composition and temperature

The ability to model the resistive switching devices depends on input material parameters and is particularly sensitive to values of electrical conductivity of the functional material as a function of composition and temperature. Here we report the results of conductivity measurements of TaO x with 0 AC ) changing from 0.34 eV at x=2.36 to 0.016 eV at x=1.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2023

Comparison of inclusive and photon-tagged jet suppression in 5.02 TeV Pb+Pb collisions with ATLAS

Parton energy loss in the quark–gluon plasma (QGP) is studied with a measurement of photon-tagged jet production in 1.7 nb –1 of Pb+Pb data and 260 pb –1 of pp data, both at $\sqrt{^S{\text{NN}}}$ = 5.02 TeV, with the ATLAS detector. The process $pp$ → γ +jet+X and its analogue in Pb+Pb collisions is measured in events containing an isolated photon with transverse momentum ($p_{\text{T}}$) above 50 GeV and reported as a function of jet $p_{\text{T}}$. This selection results in a sample of jets with a steeply falling $p_{\text{T}}$ distribution that are mostly initiated by the showering of quarks. The $pp$ and Pb+Pb measurements are used to report the nuclear modification factor, $R_{\text{AA}}$, and the fractional energy loss, $S_{\text{loss}}$, for photon-tagged jets. In addition, the results are compared with the analogous ones for inclusive jets, which have a significantly smaller quark-initiated fraction. The $R_{\text{AA}}$ and $S_{\text{loss}}$ values are found to be significantly different between those for photon-tagged jets and inclusive jets, demonstrating that energy loss in the QGP is sensitive to the colour-charge of the initiating parton. Finally, the results are also compared with a variety of theoretical models of colour-charge-dependent energy loss.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Structural and thermal properties and the origin of the ultralow thermal conductivity in the defect stannite CuIn 2 Se 4

Phase-pure CuIn 2 Se 4 , a ternary metal chalcogenide that forms in a disordered stannite crystal structure, was synthesized to investigate the structure thermal property relationships as well as reveal the origin of the ultralow thermal conductivity this material possesses over a large temperature range. Modeling of the temperature-dependent heat capacity and thermal conductivity revealed distinctive thermal properties and large lattice anharmonicity. Electron localization function calculations highlight the asymmetric bonding inherent to CuIn 2 Se 4 , which together with lattice anharmonicity directly impacts the thermal properties. Our findings reveal the specific atomic arrangement and bonding governing the thermal properties of this ternary metal chalcogenide. Our findings underscore the specific atomic arrangement and bonding governing the thermal properties in this ternary chalcogenide. This study advances the fundamental understanding of stannites, and our findings can be applied to these and other multinary metal chalcogenides of interest for applications where low thermal conductivity is desirable.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Northward propagation of the Gulf of Elat-Aqaba constrained by cosmogenic burial ages and magnetostratigraphy of onshore sediments

The Gulf of Elat-Aqaba (GEA), located in the southern part of the Dead Sea Transform (DST), is one of the most active segments of the Dead Sea fault system. Yet, some fundamental details concerning its evolution in space and time are still not fully understood. To better constrain the tectonic history of this region, we study a succession of alluvial, lacustrine, and fluvial deposits in the north-western edge of the GEA, which belong to the Quaternary Eilot and Garof Fms. The Eilot Fm. represents low-energy shallow freshwater bodies and sabkhas, which predate the development of the deep part of the basin. Later, in response to the subsidence of the basin, the Garof Fm. was deposited in alluvial fans that built up following the increase in the depositional energy. Cosmogenic burial ages combined with magnetostratigraphy show that these Fms. were deposited as early as 3.03 Ma and as late as 1.65 Ma, depending on the applied age model. Considering the present depth of the northern GEA, this age indicates a maximum subsidence rate of the head of the GEA of ~1.98mm/yr. We suggest that faults along the onshore margin of the deep basin were active during the deposition of the Garof Fm. and subsequently became inactive, while the faulting activity migrated toward the center of the basin. In conclusion, closed Holocene basins north of the present seashore, such as the Elat and Evrona playas, which may represent a modern analogue to the Plio-Pleistocene morphology, raise the possibility that the GEA head is still propagating northward.

58 GEOSCIENCES↗
DOE OSTI2023

Towards a predictive, physics-based friction model for the dynamics of jointed structures

Bolted connections are ubiquitous in mechanical designs and pose a significant challenge to understanding and predicting the vibration response of assembled structures. The present paper develops a physics-based rough contact model of the frictional interactions within a joint. This model sums over the probable interactions of asperities – defined as locally maximum surface features – to determine the contact forces. Here, the tangential contact forces vary smoothly between sticking and slipping and allow the model to better capture the qualitative trends of experimental amplitude dependent frequency and damping than previous studies. Furthermore, the novel model is generalized to allow for arbitrarily varying normal pressure including potential separation to better represent the interfacial dynamics. This includes developing a new, computationally tractable approximation to the analytical Mindlin partial slip solution for tangential loading of contacting spheres. Further, the results highlight the importance of accurately characterizing the as-built topology of the interface, the plastic behavior of the contacting asperities, the relevant length scale of asperities, and the eccentricity of asperities. A predictive friction coefficient based on plasticity provides a poor match to experiments, so fitting the friction coefficient is also considered. Numerical results are compared to experiments on the Brake-Reuß Beam to assess the predictive potential of the models. While blind predictions over-predict the slip limit, the current model presents a significant improvement in physics-based modeling and highlights areas for ongoing research.

42 ENGINEERING↗
DOE OSTI2024

Venturing into Unexplored Phase Space: Synthesis, Structure, and Properties of MgCo 3 B 2 Featuring a Rumpled Kagomé Network

MgCo 3 B 2 , a novel ternary boride in a previously unexplored phase space, was synthesized using the hydride route. In situ powder X-ray diffraction and DFT calculations aided in the discovery of this compound, whose structure was then determined by single-crystal X-ray diffraction. Like the closely related CeCo 3 B 2 , MgCo 3 B 2 crystallizes in centrosymmetric space group P6/mmm (a = 4.883(2) Å, c = 2.926(2) Å at 210 K, Z = 1). Unlike CeCo 3 B 2 , however, it adopts a disordered structure that features a rumpled Kagomé network of Co atoms, and Mg atoms fill the channels of a Co–B framework. Although the structural disorder leads to motifs that are similar to those observed in MgNi 3 B 2 and other related ternary borides, no evidence of an ordered superstructure was found by single-crystal X-ray diffraction or high-resolution powder X-ray diffraction. In the case of CeCo 3 B 2 , boron atoms occupy the center of regular Co 6 trigonal prisms; in MgCo 3 B 2 , boron atoms are shifted from the center of the prism to form B–B dimers with roughly the same length as those found in MgNi 3 B 2 . Magnetic susceptibility data exhibit an unusual temperature dependence that cannot be convincingly modeled by the modified Curie–Weiss equation, consistent with DFT calculations predicting a nonmagnetic ground state. Intrinsic susceptibility at 300 K is 1.42 × 10 –3 emu/mol Oe, which is comparable to that of paramagnetic YCo 3 B 2 and CeCo 3 B 2 with a similar structure and composition. Here, this study showcases the efficacy of combining several methodologies to discover new solids in unexplored phase spaces. This approach includes in situ PXRD data to monitor reactions of precursors upon heating, a diffusion-enhanced synthesis method, and DFT assessment of compound stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Coherent and Dynamic Small Polaron Delocalization in CuFeO 2

Small polarons remain a bottleneck in realizing efficient transition metal oxide devices. Routes to engineer small polaron coupling to electronic states and lattice modes to control carrier localization remain unclear. Here, we measure small polaron formation in CuFeO 2 using transient extreme ultraviolet reflection spectroscopy and compare to theoretical predictions in realistically parametrized Holstein models, demonstrating that polaron localization depends on coupling to high-frequency versus low-frequency phonon bath components. We measure small polaron formation on a comparable ∼100 fs timescale to other Fe(III) compounds. Dynamic delocalization of the polaron follows formation through a coherent lattice expansion between Fe–O layers and charge-sharing with surrounding Fe(IV) states. Simulations reveal two major factors dictate polaron formation timescales: phonon density and reorganization energy distributions between acoustic and optical modes, matching experimental findings. Our work shows how electronic-structural coupling in a polaron-host material can be leveraged to suppress polaronic effects for various applications.

Hematite↗
DOE OSTI2025

Robust Biaxial Anisotropy and Switchable Néel Vectors in LaFeO 3 Epitaxial Films

Antiferromagnets with highly stable but switchable Néel vectors are desired for antiferromagnetic spintronics with ultrafast speed and terahertz frequencies. Electrical switching of antiferromagnetic insulators has been demonstrated using binary antiferromagnets, while large families of complex antiferromagnets such as perovskites are largely unexplored. Here, we show that epitaxial LaFeO 3 thin films on SrTiO 3 (001) exhibit clear, robust biaxial anisotropy with a spin-flop field of a few tesla. Angular-dependent spin-Hall magnetoresistance (SMR) characterizations of Pt/LaFeO 3 bilayers with the current channel along SrTiO 3 [100] and [110] reveal distinct, intriguing shapes and field dependence. Simulations using a macrospin model accurately describe the main behavior and fine features of the SMR data from which key antiferromagnetic parameters are extracted. Furthermore, remanent SMR measurement confirms the high fidelity of the Néel vector along either easy axis of the biaxial anisotropy, indicating that epitaxial films of LaFeO 3 and potentially other perovskite antiferromagnets offer an attractive platform for antiferromagnetic spintronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Effects of Quantum Dot Loading on the Radioluminescence Efficiency in Quantum-Dot-Embedded Composites

Nanoparticle-embedded plastic scintillators are an emerging technology for fast, large-area, high-resolution radiation detection and imaging. Here, this study investigates the properties of such composites, focusing on the effects of the quantum dot (QD) concentration on the radioluminescence (RL) intensity, spectra, and dynamics. Experiments using CdSe/CdS QDs in a polymer reveal a superlinear increase in RL with the QD concentration despite optical losses from inner filtering and interparticle interactions. When corrected for inner filtering, RL shows a quadratic concentration dependence, consistent with simple analytical models of improving the secondary electron capture. Practically, the benefits of high QD concentrations are muted by optical losses, but the findings apply to other systems with insulating hosts. In addition to manipulating emission for large effective Stokes shifts, future improvements may come from hosts with higher stopping power and better charge transport, which enable more effective funneling of excitations but without concomitant optical losses associated with high nanoparticle concentrations.

Auger recombination↗
DOE OSTI2021

Temperature Effect on Photoelectrochemical Water Splitting: A Model Study Based on BiVO 4 Photoanodes

Photoelectrochemical (PEC) water splitting is typically studied at room temperature. In this work, the temperature effect on PEC water splitting is studied using crystalline BiVO4 thin film photoanode as a model system. Systematic temperature-dependent electrochemical study demonstrates that the PEC activity is boosted at elevated electrolyte temperatures and indicates that thermal energy plays a main role in improving charge carrier transport in the bulk of BiVO 4 . Irreversible surface reconstruction is observed after PEC reactions at elevated temperature in the presence of hole scavengers, with regularly spaced stripes emerging on BiVO4 grains. The surface-reconstructed photoanode exhibits up to 40% improvement in photocurrent densities and ~0.25 V shift of photocurrent onset to favorable direction. Detailed investigation shows the formation of amorphous layer without stoichiometric change at the reconstructed surface. Furthermore, this work provides insights of temperature effect on photoelectrode in solar water splitting and reveals the non-negligible effect of hole scavengers in photoelectrochemical measurement.

36 MATERIALS SCIENCE↗