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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Elongation affinity, activation barrier, and stability of Aβ42 oligomers/fibrils in physiological saline

Amyloid-beta (Aβ) peptides, Aβ40 and the more neurotoxic Aβ42, have been the subject of many research efforts for Alzheimer's disease. In two recent independent investigations, the atomistic structure of Aβ42 fibril has been clearly established in the S-shaped conformation consisting of three β-sheets stabilized by salt bridges formed between the Lys28 sidechain and the C-terminus of Ala42. This structure distinctively differs from the long-known structure of Aβ40 in the β-hairpin shaped conformation consisting of two β-sheets. Recent in silico investigations based on all-atom models have reached closer agreement with the in vitro measurements of Aβ40 thermodynamics. In this study, we present an in silico investigation of Aβ42 thermodynamics. Using the established force field parameters in seven sets of all-atom simulations, we examined the stability of small Aβ42 oligomers in physiological saline. We computed the elongation affinity of the S-shaped Aβ42 fibril, reaching agreement with the experimental data. We also estimated the Arrhenius activation barrier along the elongation pathway (from the disordered conformation of a free Aβ42 peptide to its S-shaped conformation on a fibril) that amounts to about 16 kcal/mol, which is consistent with the experimental data. Based on these quantitative agreements, we conclude that aggregation of Aβ42 peptides into fibrils is thermodynamically slow without precipitation by extrinsic factors such as heparan sulfate proteoglycan and highlight the possibility to prevent Aβ42 aggregation by eliminating some precipitation factors or by increasing competitive agents to capture and transport free Aβ42 peptides from the cerebrospinal fluid. - Highlights: • Aβ42 fibril elongation affinity was computed with chemical accuracy, in agreement with in vitro data. • Small Aβ42 oligomers were found to be stable in physiological saline. • A long Aβ42 fibril-filament was shown to stabilize an Aβ dimer in its proximity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Elastic wave velocities of peridotite KLB‐1 at mantle pressures and implications for mantle velocity modeling

Abstract Compressional ( V P ) and shear ( V S ) wave velocities of a synthetic KLB‐1 peridotite were measured for the first time up to 10 GPa using ultrasonic interferometry. Analysis of the P and S wave velocities yielded K 0 = 123(1) GPa, K 0 ′ = 5.1(2), G 0 = 75(1) GPa, and G 0 ′= 1.3(1) for the bulk and shear moduli and their pressure derivatives. Comparison with Voigt‐Reuss‐Hill (VRH) calculations based on literature elasticity data for its constituent minerals indicates that the experimentally measured P and S wave velocities, densities, bulk sound velocities, and V P / V S ratios fall close to the lower limit of VRH averages associated with the uncertainties of the mineral elasticity data. A comparison with previous modeling of mantle compositions implies that the velocities for an aggregate with the pyrolitic composition of KLB‐1 are in close agreement with seismic data at the depths of the Earth's upper mantle.

Wang, Xuebing↗
DOE OSTI2023

Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]

These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. "Temporal complementarity and value of wind-PV hybrid systems across the United States." Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. “A Resource Assessment for FlexPower”. NREL Technical Report.

Harrison-Atlas, Dylan↗
DOE OSTI2015

A Designed Inhibitor of p53 Aggregation Rescues p53 Tumor Suppression in Ovarian Carcinomas

Half of all human cancers lose p53 function by missense mutations, with an unknown fraction of these containing p53 in a self-aggregated amyloid-like state. In this paper we show that a cell-penetrating peptide, ReACp53, designed to inhibit p53 amyloid formation, rescues p53 function in cancer cell lines and in organoids derived from high-grade serous ovarian carcinomas (HGSOC), an aggressive cancer characterized by ubiquitous p53 mutations. Rescued p53 behaves similarly to its wild-type counterpart in regulating target genes, reducing cell proliferation and increasing cell death. Intraperitoneal administration decreases tumor proliferation and shrinks xenografts in vivo. Our data show the effectiveness of targeting a specific aggregation defect of p53 and its potential applicability to HGSOCs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Evaluation of Uncertainties in the Anthropogenic SO 2 Emissions in the USA from the OMI Point Source Catalog

Satellite remote sensing is a promising method of monitoring emissions that may be missing in inventories, but the accuracy of these estimates is often not clear. We demonstrate here a comprehensive evaluation of errors in anthropogenic sulfur dioxide (SO 2 ) emission estimates from NASA’s OMI point source catalog for the contiguous US by comparing emissions from the catalog with high-quality emission inventory data over different dimensions including size of individual sources, aggregate vs individual source errors, and potential bias in individual source estimates over time. For sources that are included in the catalog, we find that errors in aggregate (sum of error for all included sources) are relatively low. Errors for individual sources in any given year can be substantial, however, with over- or underestimates in terms of total error ranging from –80 to 110 kt (roughly 10–90th percentile). In this study, we find that these errors are not necessarily random over time and that there can be consistently positive or negative biases for individual sources. We did not find any overall statistical relationship between the degree of isolation of a source and bias, either at a 40 or 70 km scales. For a sub-set of sources where inventory emissions over a radius of 70 km around an OMI detection are larger than twice the emissions within 40 km, the OMI value is consistently overestimated. We find, as expected, that emission sources not included in the catalog are the largest aggregate source of difference between the satellite estimates and inventories, especially in more recent years where source emission magnitudes have been decreasing and note that trends in satellite detections do not necessarily track trends in total emissions. We find that the OMI-based SO 2 emissions are accurate in aggregate, when summed over a number of sources, but must be interpreted more cautiously at the individual source level. Similar analyses would be valuable for other satellite emission estimates; however, in many cases, the appropriate high-quality reference data may need to be generated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Crowd-based spatial risk assessment of urban flooding: Results from a municipal flood hotline in Detroit, MI

Climate change is increasing the frequency and intensity of extreme precipitation events, raising the risk of urban flood disasters. This study uses a crowd-sourced municipal call database to characterize the spatial distribution of flood risk in Detroit, MI. Call data including dates and addresses were obtained from the City of Detroit Department of Public Works for 2021. Calls were mapped and aggregated to census tract counts and merged with neighborhood-level data. Associations of predictors with flood calls were tested using spatial regression models. Flooding calls were located throughout the city but were concentrated in specific areas. Multivariate models of census tract level call counts indicated that increased poverty and Black, immigrant, and older residents were positively associated with flood calls, while increased elevation was associated with protective effects. Longer distances from waste water interceptors were associated with higher risk for calls. Crowd-sourced flood hotline call data can be used for effective spatial flood risk assessment. Though flooding occurs throughout the city of Detroit, infrastructural, neighborhood, and household factors influence flooding extent. Limitations included the self-reported nature of calls. Future modeling efforts might include input from local stakeholders to improve spatial risk assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

CMS Space Monitoring

During the first LHC run, CMS stored about one hundred petabytes of data. Storage accounting and monitoring help to meet the challenges of storage management, such as efficient space utilization, fair share between users and groups and resource planning. We present a newly developed CMS space monitoring system based on the storage metadata dumps produced at the sites. The information extracted from the storage dumps is aggregated and uploaded to a central database. A web based data service is provided to retrieve the information for a given time interval and a range of sites, so it can be further aggregated and presented in the desired format. The system has been designed based on the analysis of CMS monitoring requirements and experiences of the other LHC experiments. In this paper, we demonstrate how the existing software components of the CMS data placement system, PhEDEx, have been re-used, dramatically reducing the development effort.

Ratnikova, N.↗
DOE OSTI2016

Combined Effects of Temperature and Irradiation on Concrete Damage

Aggregate radiation-induced volumetric expansion (RIVE) is a predominant mechanism in the formation of mechanical damage in the hardened cement paste (hcp) of irradiated concrete under fast-neutron flux (Giorla et al. 2015). Among the operating conditions difference between test reactors and light water reactors (LWRs), the difference of irradiation flux and temperature is significant. While a temperature increase is quite generally associated with a direct, or indirect (e.g., by dehydration) loss of mechanical properties (Maruyama et al. 2014), we found that it causes a partial annealing of irradiation amorphization of α-quartz, hence, reducing RIVE rate. Based on data collected by Bykov et al. (1981), an incremental RIVE model coupling neutron fluence and temperature is developed. The elastic properties and coefficient of thermal expansion (CTE) of irradiated polycrystalline quartz are interpreted through analytical homogenization of experimental data on irradiated α-quartz published by Mayer and Lecomte (1960). Moreover, the proposed model, implemented in the meso-scale simulation code AMIE, is compared to experimental data obtained on ordinary concrete made of quartz/quartzite aggregate (Dubrovskii et al. 1967). Substantial discrepancy, in terms of damage and volumetric expansion developments, is found when comparing irradiation scenarios assuming constant flux and temperature, as opposed to more realistic test reactor operation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2014

An open science resource for establishing reliability and reproducibility in functional connectomics

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Estimating Sediment Settling Velocities from a Theoretically Guided Data-Driven Approach

Sediment settling velocities are commonly estimated from analytical or process-based approaches. These approaches have theoretical constraints due to the incompletely resolved settling physics. A parametric data-driven approach was recently proposed without theoretical constraints, but it is limited by its mathematical assumptions. To overcome these limitations, here we apply a machine learning algorithm to an aggregated sediment settling experimental database and develops a nonparametric data-driven model to estimate the noncohesive sediment settling velocity in water. A cross-comparison against five process-based equations and a parametric data-driven equation demonstrates the higher accuracy and better consistency of the new model in estimating sediment settling velocities under various physical regimes. The new model also shows an easily implemented self-update capability by assimilating theoretical data derived from the process-based equations. The updated model, incorporating experimental and theoretical data of sediment settling processes, further improves the accuracy and reduces the uncertainty in estimating sediment settling velocities. This study demonstrates the capability of machine learning in sediment transport study and illustrates an alternative framework for other hydraulic engineering challenges.

42 ENGINEERING↗
DOE OSTI2020

A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet thresholding (or shrinkage) attempts to remove the noises existing in the signals while preserving inherent pattern characteristics in the reconstruction of true signals. For data-denoising purpose, we present a new wavelet thresholding procedure which employs the step-down testing idea of identifying active contrasts in unreplicated fractional factorial experiments. The proposed method employs bootstrapping methods to a step-down test for thresholding wavelet coefficients. By introducing the concept of a false discovery error rate in testing wavelet coefficients, we shrink the wavelet coefficients with p -values higher than the error rate. The error rate controls the expected proportion of wrongly accepted coefficients among chosen wavelet coefficients. Bootstrap samples are used to approximate the p -value for computational efficiency. We also present some guidelines for selecting the values of hyper-parameters which affect the performance in the step-down thresholding procedure. Based on some common testing signals and an air-conditioner sounds example, the comparison of our proposed procedure with other thresholding methods in the literature is performed. The analytical results show that the proposed procedure has a potential in data-denoising and data-reduction in a variety of signal reconstruction applications.

42 ENGINEERING↗
DOE OSTI2026

Ion-Specific Effects on PuO 2 Nanoparticle Aggregation and Dissolution in Concentrated Electrolytes

Hydrolytic PuO 2 nanoparticles (NPs) are a dominant aqueous Pu-bearing phase in high ionic strength nuclear wastes, yet their reactivity in nonideal brines remains poorly constrained. We quantify how electrolyte identity and concentration control PuO 2 NP aggregation and ligand-assisted dissolution in acidic, high salinity solutions (NaCl, NaNO 3 , NaClO 4 , Na 2 SO 4 , Na 2 C 2 O 4 up to 5 M). A multitechnique workflow combining liquid scintillation counting (operationally defined aqueous [Pu]), scattering/electrokinetic measurements (aggregate size and zeta potential), and spectroscopy (UV–vis, XPS, Raman) resolves electrolyte-dependent partitioning between colloidal and molecular Pu species. Weakly coordinating anions (ClO 4 – , Cl – , NO 3 – ) largely preserve the (aggregated) nanoparticulate fraction but generate distinct dissolved species at high concentration, i.e., Pu(IV)–nitrato complexes in NaNO 3 and Pu(VI)–chloro complexes in NaCl. In contrast, stronger ligands substantially perturb PuO 2 NP stability: sulfate promotes partial dissolution to Pu(IV)–sulfate complexes at low concentration but reduces aqueous [Pu] at higher sulfate levels via secondary Pu(IV) sulfate formation, whereas oxalate drives strong dissolution to aqueous Pu–oxalate complexes. Aged NPs show similar trends with reduced aqueous fractions and more dominant aggregation mechanisms. In conclusion, these spectroscopically constrained speciation data provide a foundation for incorporating PuO 2 NP reactivity into thermodynamic and reactive transport models for high salinity waste and brine environments.

Aggregation↗
DOE OSTI2022

A Framework for Inverse Prediction Using Functional Response Data

Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.

42 ENGINEERING↗
DOE OSTI2014

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

Scientific data analytics in high-performance computing environments has been evolving along with the advancement of computing capabilities. With the onset of exascale computing, the increasing gap between compute performance and I/O bandwidth has rendered the traditional post-simulation processing a tedious process. Despite the challenges due to increased data production, there exists an opportunity to benefit from "cheap" computing power to perform query-driven exploration and visualization during simulation time. To accelerate such analyses, applications traditionally augment, post-simulation, raw data with large indexes, which are then repeatedly utilized for data exploration. However, the generation of current state-of-the-art indexes involves a compute- and memory-intensive processing, thus rendering them inapplicable in an in situ context. In this paper we propose DIRAQ, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. DIRAQ's effective core-local, precision-based encoding approach incorporates an embedded compressed index that is 3---6 $$\times $$ ? smaller than current state-of-the-art indexing schemes. Its data-aware index adjustmentation improves performance of group-level index layout creation by up to 35 % and reduces the size of the generated index by up to 27 %. Moreover, DIRAQ's in network index merging strategy enables the creation of aggregated indexes that speed up spatial-context query responses by up to $$10\times $$ 10 ? versus alternative techniques. DIRAQ's topology-, data-, and memory-aware aggregation strategy results in efficient I/O and yields overall end-to-end encoding and I/O time that is less than that required to write the raw data with MPI collective I/O.

Computer Science↗
DOE OSTI2017

The POTRA domains of Toc75 exhibit chaperone-like function to facilitate import into chloroplasts

Protein trafficking across membranes is an essential function in cells; however, the exact mechanism for how this occurs is not well understood. In the endosymbionts, mitochondria and chloroplasts, the vast majority of proteins are synthesized in the cytoplasm as preproteins and then imported into the organelles via specialized machineries. In chloroplasts, protein import is accomplished by the TOC (translocon on the outer chloroplast membrane) and TIC (translocon on the inner chloroplast membrane) machineries in the outer and inner envelope membranes, respectively. TOC mediates initial recognition of preproteins at the outer membrane and includes a core membrane channel, Toc75, and two receptor proteins, Toc33/34 and Toc159, each containing GTPase domains that control preprotein binding and translocation. Toc75 is predicted to have a β-barrel fold consisting of an N-terminal intermembrane space (IMS) domain and a C-terminal 16-stranded β-barrel domain. Here we report the crystal structure of the N-terminal IMS domain of Toc75 from Arabidopsis thaliana , revealing three tandem polypeptide transport-associated (POTRA) domains, with POTRA2 containing an additional elongated helix not observed previously in other POTRA domains. Functional studies show an interaction with the preprotein, preSSU, which is mediated through POTRA2-3. POTRA2-3 also was found to have chaperone-like activity in an insulin aggregation assay, which we propose facilitates preprotein import. Furthermore, our data suggest a model in which the POTRA domains serve as a binding site for the preprotein as it emerges from the Toc75 channel and provide a chaperone-like activity to prevent misfolding or aggregation as the preprotein traverses the intermembrane space.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Ion Dynamics in Ionic-Liquid-Based Li-Ion Electrolytes Investigated by Neutron Scattering and Dielectric Spectroscopy

A detailed understanding of the diffusion mechanisms of ions in pure and doped ionic liquids remains an important aspect in the design of new ionic-liquid electrolytes for energy storage. Here, to gain more insight into the widely used imidazolium-based ionic liquids, the relationship between viscosity, ionic conductivity, diffusion coefficients, and reorientational dynamics in the ionic liquid 3-methyl-1-methylimidazolium bis(trifluoromethanesulfonyl)imide (DMIM-TFSI) with and without lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI) was examined. The diffusion coefficients for the DMIM + cation and the role of ion aggregates were investigated by using the quasielastic neutron scattering (QENS) and neutron spin echo techniques. Two diffusion mechanisms are observed for the DMIM + cation with and without Li-TFSI, that is, translational and local. The data additionally suggest that Li + ion transport along with ion aggregates, known as the vehicle mechanism, may play a significant role in the ion diffusion process. These dielectric-spectroscopy investigations in a broad temperature and frequency range reveal a typical α–β-relaxation scenario. The α relaxation mirrors the glassy freezing of the dipolar ions, and the β relaxation exhibits the signatures of a Johari–Goldstein relaxation. In contrast to the translational mode detected by neutron scattering, arising from the decoupled faster motion of the DMIM + ions, the α relaxation is well coupled to the dc charge transport, that is, the average translational motion of all three ion species in the material. Finally, the local diffusion process detected by QENS is only weakly dependent on temperature and viscosity and can be ascribed to the typical fast dynamics of glass-forming liquids.

25 ENERGY STORAGE↗
DOE OSTI2021

Cryo-electron tomography provides topological insights into mutant huntingtin exon 1 and polyQ aggregates

Huntington disease (HD) is a neurodegenerative trinucleotide repeat disorder caused by an expanded poly-glutamine (polyQ) tract in the mutant huntingtin (mHTT) protein. The formation and topology of filamentous mHTT inclusions in the brain (hallmarks of HD implicated in neurotoxicity) remain elusive. Using cryo-electron tomography and subtomogram averaging, here we show that mHTT exon 1 and polyQ-only aggregates in vitro are structurally heterogenous and filamentous, similar to prior observations with other methods. Yet, we find filaments in both types of aggregates under ~2 nm in width, thinner than previously reported, and regions forming large sheets. In addition, our data show a prevalent subpopulation of filaments exhibiting a lumpy slab morphology in both aggregates, supportive of the polyQ core model. This provides a basis for future cryoET studies of various aggregated mHTT and polyQ constructs to improve their structure-based modeling as well as their identification in cells without fusion tags.

59 BASIC BIOLOGICAL SCIENCES↗