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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Bemnifosbuvir: An HCV NS5B Inhibitor With Multiple Modes of Action

Bemnifosbuvir (BEM) is a potent, pan-genotypic inhibitor targeting the hepatitis C virus (HCV) NS5B polymerase. Its antiviral activity was evaluated in an ascending dose phase I clinical trial involving 30 patients treated once a day for 7 days. After treatment initiation, plasma HCV RNA declined in a biphasic manner with a mean reduction of 2.3 log 10 IU/mL after 24 hours and 4.4 log10 IU/mL by day 7 for the highest dose. Alanine aminotransferase (ALT) also normalized in most patients. We employed a multiscale mathematical model fitted to the HCV RNA and ALT dynamics to quantify the antiviral activity and evaluate the modes of action of BEM. We found that models in which BEM only acted as a typical HCV RNA polymerase inhibitor and reduced the intracellular production of HCV RNA did not fit the data as well as models in which BEM had multiple modes of action, including suppressing viral assembly and secretion and enhancing intracellular HCV RNA degradation. BEM's effectiveness in inhibiting intracellular HCV RNA production increased with dose (150 mg/day: 88.2%, 300 mg/day: 98.8%, 600 mg/day: 99.5%), while inhibition of viral assembly and release was ~95% effective regardless of dose. We observed a dose-dependent enhancement in the degradation of intracellular HCV RNA, with degradation rates 1.5-fold higher in patients receiving 300 mg/day and 2.7-fold higher in those receiving 600 mg/day than in patients receiving 150 mg/day. No significant differences in antiviral activity were detected between HCV genotypes 1b and 3 or between patients with and without compensated cirrhosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Valence-to-core X-ray emission spectroscopy of titanium compounds using energy dispersive detectors

X-ray emission spectroscopy (XES) of transition metal compounds is a powerful tool for investigating the spin and oxidation state of the metal centers. Valence-to-core (vtc) XES is of special interest, as it contains information on the ligand nature, hybridization, and protonation. To date, most vtc-XES studies have been performed with high-brightness sources, such as synchrotrons, due to the weak fluorescence lines from vtc transitions. Here, we present a systematic study of the vtc-XES for different titanium compounds in a laboratory setting using an X-ray tube source and energy dispersive microcalorimeter sensors. With a full-width at half-maximum energy resolution of approximately 4 eV at the Ti Kβ lines, we measure the XES features of different titanium compounds and compare our results for the vtc line shapes and energies to previously published and newly acquired synchrotron data as well as to new theoretical calculations. Finally, we report simulations of the feasibility of performing time-resolved vtc-XES studies with a laser-based plasma source in a laboratory setting. Our results show that microcalorimeter sensors can already perform high-quality measurements of vtc-XES features in a laboratory setting under static conditions and that dynamic measurements will be possible in the future after reasonable technological developments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A practical approach to using the Genomic Standards Consortium MIxS reporting standard for comparative genomics and metagenomics

Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimal Information about any (x) Sequence (MIxS) reporting standard for genomic data. To facilitate use of the GSC’s MIxS reporting standard, we provide a description of the structure and terminology, how to navigate ontologies for required terms in MIxS, and demonstrate practical usage through a soil metagenome example.

standards, metadata, genome, metagenome, schema, v↗
DOE OSTI2020

Asymptotic behavior of meson transition form factors

One of the open issues in evaluations of the contribution from hadronic light-by-light scattering to the anomalous magnetic moment of the muon (g - 2)µ concerns the role of heavier scalar, axial-vector, and tensormeson intermediate states. The coupling of axial vectors to virtual photons is suppressed for small virtualities by the Landau–Yang theorem, but otherwise there are few rigorous constraints on the corresponding form factors. In this paper, we first derive the Lorentz decomposition of the two-photon matrix elements into scalar functions following the general recipe by Bardeen, Tung, and Tarrach. Based on this decomposition, we then calculate the asymptotic behavior of the meson transition form factors from a light-cone expansion in analogy to the asymptotic limits for the pseudoscalar transition form factor derived by Brodsky and Lepage. Finally, we compare our results to existing data as well as previous models employed in the literature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Measurement of the ${\Lambda}_c^{+}$ to D 0 production ratio in peripheral PbPb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

We report on a measurement of the ${\Lambda}_c^{+}$ to D 0 production ratio in peripheral PbPb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV with the LHCb detector in the forward rapidity region 2 < y < 4.5. The ${\Lambda}_c^{+}$ (D 0 ) hadrons are reconstructed via the decay channel ${\Lambda}_c^{+}$ → pK – π + (D 0 → K – π + ) for 2 < p T < 8 GeV/c and in the centrality range of about 65–90%. The results show no significant dependence on p T , y or the mean number of participating nucleons. They are also consistent with similar measurements obtained by the LHCb collaboration in pPb and Pbp collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV. The data agree well with predictions from PYTHIA in pp collisions at $\sqrt{s}$ = 5 TeV but are in tension with predictions of the Statistical Hadronization model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Integrated positron emission particle tracking (PEPT) and X-ray computed tomography (CT) imaging of flow phenomena in twisted tape swirl flow

Abstract A combined positron emission particle tracking (PEPT) and X-ray computed tomography (CT) technique is presented, and its utility is demonstrated through investigation of flow in a pipe with twisted tape swirl insert with varying flow conditions (diameter-based Reynolds numbers 16,300–63,300). A description of this technique is given, as well as data handling practices used to relate geometric information captured by CT to fluid flow data gathered via PEPT. It is found that the CT component is readily capable of capturing the stainless steel insert geometry in this present system, but the use of combined plastic and metal materials leads to artifacts in imaging of the plastic surface. Nonetheless, CT data are related to PEPT flow measurements, and average velocity fields are calculated via a pseudo-framing and interpolation scheme and used to visualize and interrogate key flow phenomena within the system. Radial velocity profiles of the mean flow characteristics are seen to collapse to a nearly common form across all flow conditions considered. Helical vortices are seen propagating through the flow field, generated by bypass flow around the gap between the insert and pipe wall, with additional coherent secondary flow structures seen in the higher Reynolds number cases. These findings enhance the understanding of the mixing mechanisms in these swirl flows and encourage the continued development of PEPT-CT methodologies for 3D flow measurements in optically inaccessible systems.

42 ENGINEERING↗
DOE OSTI2020

Uncertainty Quantification of Machine Learning Predicted Creep Property of Alumina-Forming Austenitic Alloys

The development of machine learning (ML) approaches in materials science offers the opportunity to exploit existing engineering and developmental alloy datasets, such as Oak Ridge National Laboratory (ORNL)’s consistently measured creep-rupture dataset for alumina-forming austenitic (AFA) alloys, to accelerate their further development. As a first step toward achieving ML insights for improved alloy design, the potential sources of uncertainty and their impacts on ML output are examined. It is observed that the selection of algorithms and features as well as data sampling significantly affects the performance of ML models, either positively or negatively. Further, the performance of various ML models in predicting the creep properties of AFA alloys is compared, with further evaluation by assessment of a small set of new developmental AFA alloys that were not part of the training dataset. The present study demonstrates that uncertainty quantification (UQ) is essential in materials science for evaluating the performance of ML algorithms with specifically selected feature sets and obtaining a comprehensive understanding of their limitations and the resultant capability of effective prediction in complex materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6

The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Onset dynamics of air-water menisci on rock fracture surfaces

Information on menisci dynamics and equilibrium contact angles, θ e , is needed for modeling multiphase flow of fluids in geologic formations. The wettability of fracture faces is relevant to applications such as waterflooding in enhanced oil recovery and evaluation of caprock integrity for geologic carbon sequestration. We investigated the vertical capillary rise of air-water menisci on exposed fracture faces for a sandstone, a shale, and three granites. The experimental design approximated that employed in the Wilhelmy plate method. Replicate fracture faces were prepared by fracturing cylindrical rock cores using the Brazilian method and splitting the fractured cores apart along their fracture planes. Meniscus onset was imaged from a cross-sectional perspective using dynamic neutron radiography, and quantified with change point analysis. An existing model for meniscus onset fitted the experimental data very well (median R 2 = 0.96). Capillary rise was typified by t 2/3 scaling (where t is time), followed by a constant equilibrium height, z e . The average time taken for the menisci to reach z e was 0.39 s, with no differences between rock types. The menisci achieved a greater vertical extent on the fracture faces of the sedimentary rocks as compared to those of the granites. Apparent θ e values were calculated from the best fit estimates of z e using the Wilhelmy plate equation for a smooth and planar vertical surface. Despite the fractal roughness of some of the fracture faces, there was a significant linear relationship (R 2 = 0.80) between the apparent θ e values and intrinsic θ e values measured on polished surfaces of the same rocks using the sessile drop method. The regression equation indicated the apparent θ e values were consistently greater than the intrinsic values. This overestimation may be due to averaging of pixels at the air-water-solid interface, a required step in the image analysis. Further exploration of the range of applicability and measurement accuracy of this proposed new technique would be valuable.

58 GEOSCIENCES↗
DOE OSTI2023

Online evolutionary neural architecture search for multivariate non-stationary time series forecasting

Time series forecasting (TSF) is one of the most important tasks in data science. TSF models are usually pre-trained with historical data and then applied on future unseen datapoints. However, real-world time series data is usually non-stationary and models trained offline usually face problems from data drift. Models trained and designed in an offline fashion can not quickly adapt to changes quickly or be deployed in real-time. To address these issues, this work presents the Online NeuroEvolution-based Neural Architecture Search (ONE-NAS) algorithm, which is a novel neural architecture search method capable of automatically designing and dynamically training recurrent neural networks (RNNs) for online forecasting tasks. Without any pre-training, ONE-NAS utilizes populations of RNNs that are continuously updated with new network structures and weights in response to new multivariate input data. ONE-NAS is tested on real-world, large-scale multivariate wind turbine data as well as the univariate Dow Jones Industrial Average (DJIA) dataset. These results demonstrate that ONE-NAS outperforms traditional statistical time series forecasting methods, including online linear regression, fixed long short-term memory (LSTM) and gated recurrent unit (GRU) models trained online, as well as state-of-the-art, online ARIMA strategies. Additionally, results show that utilizing multiple populations of RNNs which are periodically repopulated provide significant performance improvements, allowing this online neural network architecture design and training to be successful.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Prototype energy models for data centers

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Isotopic signatures as tools to reconstruct the primordial architecture of the Solar System

The significant reorganization of the early Solar System due to giant planet migration has hampered our understanding of where planetary bodies formed. Previously employed proxies for reconstructing the primordial planetary architecture, such as water content or oxidation state, are complicated by post-accretionary processes. Furthermore we investigate basaltic achondrites for their nucleosynthetic isotope signatures in the elements neodymium (Nd) and zirconium (Zr) and show that they are—similar to previously investigated chondritic meteorites—characterized by a relative deficit in isotopes produced by the s-process of nucleosynthesis. Importantly, these data are well correlated with nucleosynthetic signatures observed in other elements, demonstrating that s-process matter was heterogeneously distributed throughout the early Solar System. By comparing these isotopic signatures with potential proxies for Solar System reconstruction and computer modeling, we here argue that this isotopic heterogeneity in bulk meteoritic materials is linked to the original heliocentric distance of formation. Such scaling of nucleosynthetic signatures with heliocentric distance could permit reconstruction of the primordial architecture of the Solar System by ‘cosmolocating’ the accretion orbits of meteoritic parent bodies as a function of incorporated s-process matter.

58 GEOSCIENCES↗
DOE OSTI2020

Magnetothermal properties of Tm x Dy 1- x Al 2 ( x = 0.25, 0.50 and 0.75)

Here, we describe magnetic, thermal, and magnetocaloric properties of rare earth intermetallic compounds Tm x Dy 1-x Al 2 with 0.25, 0.5 and 0.75. Using model Hamiltonian we consider contributions of the crystalline electric field anisotropy in both Tm and Dy magnetic sublattices, disorder in exchange interactions among Tm-Tm, Dy-Dy and Tm-Dy magnetic ions, and the Zeeman effect. Employing earlier reported and new experimental measurements, we first determine a single free variable – the intersublattice magnetic exchange parameter – to properly model the temperature and magnetic field dependencies of heat capacity and magnetization, and then use the modeling results to explain the emergence of an anomalous spin reorientation transition and its influence on the magnetocaloric effect in the title compounds. Theoretical results agree with experimental data reasonably well.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Production of polyacrylonitrile/ionic covalent organic framework hybrid nanofibers for effective removal of chromium(VI) from water

Hexavalent Cr(VI) found in industrial wastewater is a proven carcinogen which causes serious health issues in humans around the world. This study presents a novel method to enhance the Cr(VI) oxyanion removal from wastewater by polyacrylonitrile (PAN) nanofibers through incorporation of a guanidinium-based ionic covalent organic framework (BT-DG) in the nanofibers structure. In this work, simple electrospinning technique was employed to produce PAN nanofibers and BT-DG was synthesized through condensation between benzene-1,3,5-tricarbaldehyde and N,N'-diaminoguanidine monohydrochloride. In-situ polymerization of BT-DG onto PAN nanofibers resulted in generation of hybrid PAN-BT-DG nanofibers. This modified PAN-BT-DG was characterized by obtaining its point of zero charge (PZC), differential scanning calorimeter (DSC), scanning electron microscopy (SEM) morphology and surface elements and oxidation states by X-ray photoelectron spectroscopy (XPS). PAN-BT-DG exhibited positive surface charge below pH 4, making it an outstanding adsorbent, for Cr(VI) removal. Cr(VI) adsorption onto PAN-BT-DG followed pseudo second order kinetics and adsorption data fitted well to Freundlich isotherm model. Highest Cr(VI) removal was obtained at 55 °C with a maximum Langmuir adsorption capacity of 173 mg/g at pH 3. Kinetic studies revealed that Cr(VI) adsorption onto PAN-BT-DG is endothermic and thermodynamically feasible. Desorption studies were conducted on PAN-BT-DG using 1 M NaOH as the stripping solvent and PAN-BT-DG exhibited excellent regeneration after five consecutive cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the transferability of residence time distributions in two 10-km long river sections with similar hydromorphic units

Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface and their residence time distributions (RTDs) in the subsurface are important for managing the water quality and ecosystem health in dynamic river corridors. However, direct simulating high-spatial resolution HEFs and RTDs can be time-consuming, especially for watershed-scale modeling. Efficient surrogate models linking RTDs to hydromorphic units (HUs) can be alternatives for simulating RTDs in large-scale models. A common concern of these surrogate models, though, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this issue, this work evaluates the HEFs and resulting RTD-HU relationships for two 10-km long river corridors along the Columbia River leveraging a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework we previously developed. Applying such a framework at the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. Finally, our comparison shows that the similarity and transferability of the RTD-HU relationship is very low for the two investigated river sections, which suggests that devising a general algorithm to estimate RTDs based solely on surface water hydrodynamics and short-distance river channel topography data, as well as HU classification, might be nearly impossible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of zirconium carbide microspheres synthesized via internal gelation

Microspheres of zirconium carbide with grain size 40-320 nm were synthesized using internal gelation techniques and characterized by scanning electron microscopy, synchrotron X-ray diffraction, and neutron total scattering. Compared with a polycrystalline benchmark ZrC sample prepared by plasma vapor phase deposition, the microspheres display lower variance in grain size and considerably lower microstrain representative of a more homogenous internal microstructure. However, excess carbon was present in the microspheres, evident in both the X-ray and neutron diffraction data as well as a corresponding hypostoichiometric ZrC phase. Furthermore, the excess carbon phase is assumed to be pockets of carbon that remained unreacted through the combined internal gelation and subsequent carbothermic reduction synthesis process. Atomic-scale structural characterization with neutron PDF analysis confirmed the presence of localized nano-sized domains of graphite-like carbon material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Avalanche gain and its effect on energy resolution in GEM-based detectors

Here, we present avalanche gain and associated resolution measurements recorded with a 4 He:CO 2 (70:30) gas mixture and pure SF 6 , a Negative Ion (NI) gas. SF 6 is of particular interest to the directional dark matter detection community, as its low thermal diffusion helps to retain recoil ionization track features over long drift lengths. With the aid of a general form of the reduced first Townsend coefficient (RFTC), multiple GEM-based detector data sets are used to study the high-gain behavior of the 4 He:CO 2 gas mixture. The high-gain data is well described purely in terms of the reduced electric field strength and the number of GEMs, and the robust relationship between the RFTC and the average, reduced, electric field strength across the GEMs is emphasized. The associated (pulse-height) resolution measurements are used to discuss the variance of the avalanche distribution and to describe and estimate the lower limits of energy resolution one should expect to measure using a simple relationship with the RFTC. In the end, a description of avalanche gain, its effect on energy resolution, and the contributing experimental parameters in GEM-based detectors is developed over a broad parameter space for further use.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗