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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 631 records · Page 35

DataSet for Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic-inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. To understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31-calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ~2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31-calcite interactions. These studies provide the first experimental evidence to confirm that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template. However, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31-calcite interface has advanced our fundamental understanding of the atomic interactions at the organic-inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Saccuzzo Close, Emily Grace [Pacific Northwest Nat↗

Next-generation sequencing dataset of genome-scale CRISPRi in Synechococcus sp. PCC 7002 across seven conditions

A 33,298-member sgRNA library developed for Synechococus sp. PCC 7002 was screened with two replicates across seven growth conditions and sequenced with Illumina NextSeq (paired end, 2x150 bp) for a total of ~700M reads. The original plasmid library and the library after transformation into a dCas9-containing and dCas9-absent strain were also sequenced as a reference for initial sgRNA abundance.

genome- wide screens environmental acclimation spe↗

Comparison of GOES16 Data with the TRACER-ESCAPE Field Campaign Dataset for Convection Characterization: A Selection of Case Studies and Lessons Learnt

Convective updrafts are one of the main characteristics of convective clouds, responsible for the convective mass flux and the redistribution of energy and condensate in the atmosphere. During the early stages of their lifecycle, convective clouds experience rapid cloud-top ascent manifested by a decrease in the geostationary IR brightness temperature (𝑇⁢𝐵 𝐼⁢𝑅 ). Under the assumption that the convective cloud top behaves like a black body, the ascent rate of the convective cloud top can be estimated as ($\frac{∂𝑇⁢𝐵_{𝐼⁢𝑅}}{∂𝑡}$), and it can be used to infer the near cloud-top convective updraft. The temporal resolution of the geostationary IR measurements and non-uniform beam-filling effects can influence the convective updraft estimation. However, the main shortcoming until today was the lack of independent verification of the strength of the convective updraft. Here, Doppler radar observations from the ESCAPE and TRACER field experiments provide independent estimates of the convective updraft velocity at higher spatiotemporal resolution throughout the convective core column and can be used to evaluate the updraft velocity estimates from the IR cooling rate for limited samples. Isolated convective cells were tracked with dedicated radar (RHIs and PPIs) scans throughout their lifecycle. Radial Doppler velocity measurements near the convective cloud top are used to provide estimates of convective updrafts. These data are compared with the geostationary IR and VIS channels (from the GOES satellite) to characterize the convection evolution and lifecycle based on cloud-top cooling rates.

TRACER/ESCAPE field campaign↗

Detecting Anomalous Images in Astronomical Datasets

Abstract Environmental and instrumental conditions can cause anomalies in astronomical images, which can potentially bias all kinds of measurements if not excluded. Detection of the anomalous images is usually done by human eyes, which is slow and sometimes not accurate. This is an important issue in weak lensing studies, particularly in the era of large-scale galaxy surveys, in which image qualities are crucial for the success of galaxy shape measurements. In this work we present two automatic methods for detecting anomalous images in astronomical data sets. The anomalous features can be divided into two types: one is associated with the source images, and the other appears on the background. Our first method, called the entropy method, utilizes the randomness of the orientation distribution of the source shapes and the background gradients to quantify the likelihood of an exposure being anomalous. Our second method involves training a neural network (autoencoder) to detect anomalies. We evaluate the effectiveness of the entropy method on the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) and Dark Energy Camera Legacy Survey (DECaLS DR3) data. In CFHTLenS, with 1171 exposures, the entropy method outperforms human inspection by detecting 12 of the 13 anomalous exposures found during human inspection and uncovering 10 new ones. In DECaLS DR3, with 17112 exposures, the entropy method detects a significant number of anomalous exposures while keeping a low false-positive rate. We find that although the neural network performs relatively well in detecting source anomalies, its current performance is not as good as the entropy method.

Astronomy & Astrophysics↗

Atom probe datasets from neutron irradiated Fe-Cr alloys

A series of model Fe–Cr alloys containing 3–18 at.% Cr was neutron irradiated at a nominal temperature of 563 K to 1.82 dpa. Solute distributions were analyzed by atom probe tomography, which revealed α′ precipitation for alloys containing more than 9 at.% Cr. Both the Cr concentration dependence of α′ precipitation and the measured matrix compositions are in agreement with the recently published Fe–Cr phase diagrams. An irradiation-accelerated precipitation process is strongly suggested. Irradiation was carried out in the Advance Test Reactor (ATR) at Idaho National Laboratory. A series of six Fe–Cr alloys of nominal compositions 3, 6, 9, 12, 15 and 18 at.% Cr was irradiated at a neutron fluence (E > 1 MeV) of 1.1 × 1021 n cm−2 at 563 ± 15 K and to a damage level of 1.82 displacements per atom (dpa). Nominal neutron flux and dpa rate are 2.3 × 1014 n cm−2 s−1 and 3.4 × 10−7 dpa s−1, respectively. The microstructures of the Fe–Cr alloys were studied by atom probe tomography (APT) using a Cameca 4000X HR instrument. APT specimens were prepared by a standard lift-out process using a Quanta 3D 200i dual beam scanning electron microscope ensuring that the analyses were performed away from grain boundaries.

Bachhav, Mukesh↗

1000 Soils Pilot Dataset, version 8, May 2025

This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data. A beta visualization tool is available for some data types at https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback. Data completed include: Geochemistry, texture, respiration, and enzyme activities FTICR-MS organic matter chemistry Microbial biomass C and N TOC/TDN of water-extractable OM X-ray computed tomography (derived metrics available here, raw data available upon request) Metagenomes; a variety of data formats are available upon request Soil hydraulic properties Data in progress: LC-MS/MS in development, timeline TBD, inquire for status 1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and 1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography. icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates. 1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information. Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information. Readme File_v4.xlsx is the readme file. Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions. The following file and all raw data are available upon request: icr_by_mass_for_single_sample_analysis_only.csv contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs. For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet Acknowledgment: Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at https://sc-data.emsl.pnnl.gov/.

biogeochemistry↗

Extended Heat Transfer Model Dataset

Data repository for the paper: Molerus and Wirth's Heat Transfer Model for Bubbling Fluidized Beds: Proposal for an Extended Model Including Immersed Tube Banks and Particle Cross-Flow Powder Technology 2025

contact time↗

Dataset from Manuscript: CO2 Electroreduction on Borated Copper Surfaces: Boron Active Sites, not Copper

(1) hcoverage-gcga: .db files with structures and data from GCGA sampling at various potentials (2) hcoverage-gcdft/vaspSC-finished.db: .db file with GCDFT calculations and structures on the sub-ensemble of various H coverages on CuB(3) int_ts: Optimized structures of intermediates and transition states for HER (H26.db and H39.db for LC and HC respectively), B migration (H33.db and H34.db), and CORR (H26.db and H39.db for LC and HC respectively)

Boron↗

3D Continuous Forcing Dataset from 3D Constrained Variational Analysis at SGP

The continuous 3D large-scale forcing (VARANAL3D) data set derived from 3D constrained variational analysis (3DCVA) extends the conventional constrained variational analysis method by incorporating multiple sub-columns within the analysis domain. This advancement introduces spatial variability into the large-scale forcing fields, thereby enriching the data set’s applicability. The VARANAL3D data set spans from 2004 to 2018 and covers a region of 5˚×4.5˚ domain around the ARM SGP site. The analysis domain is divided into 10×9 sub-columns with 0.5˚ resolution. The 3D large-scale forcing data provides necessary variables to drive and evaluate single-column models (SCM), cloud-resolving models (CRM) ,and large-eddy simulations (LES), as well as information for testing model sensitivity to spatial variability of the large-scale forcing data, facilitating more rigorous testing and refinement of physical processes in SCM/CRM/LES.

54 ENVIRONMENTAL SCIENCES↗

Thermal Cooling Water Datasets for Electric Sector Modeling

This spreadsheet contains data inputs associated with representations of water (i.e., use, supply, costs) for thermo-electric based production. Values in this spreadsheet have been used to support multiple transmission-related planning studies, using models such as Regional Energy Deployment System Model (ReEDS). More information about associated studies can be found in Miara et al., 2019 (DOI: 10.1021/acs.est.9b03037); Cohen et al., 2022 (DOI: 10.1016/j.apenergy.2022.119193); and Cohen et al., 2024 (DOI TBD). Within these transmission-related studies, the values present in this spreadsheet are assigned for simulation of both existing units as well as new capacity build-outs. A summary of worksheets' content as well as associated sources are captured below.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fuel Cell Inverter Dataset

This data set contains the three phase AC voltage, three phase AC current, DC voltage and DC current. These data sets were captured during fuel cell inverter operation in grid-connected dispatch, islanded load changes, transition from grid-connected mode to islanded mode and vice-versa.

25 ENERGY STORAGE↗

High-Fidelity Simulation Aerodynamics Dataset of NACA 0012 and 0021 Airfoils

The repository contains time series data of pressure, viscous and moment forces for the NACA 0012 and 0021 airfoils at angles of attack (AOA), 5, 17, 30, 45, 60 and 90 degrees. The data was generated during the high-fidelity simulations of the airfoils using the open-source CFD code, Nalu-Wind (https://github.com/Exawind/nalu-wind). The research objective was to study the effects of mesh resolution and turbulence model on the three-dimensional deep stall aerodynamics of the airfoils, which has been published in the Journal of Turbulence (https://doi.org/10.1080/14685248.2023.2225141). Several meshes of the O-grid type were generated using the modified Pointwise Glyph script of Carrigan (https://github.com/pointwise/AirfoilMesh) by varying the wall normal and spanwise resolutions. Note that, the geometry was extruded by four chord lengths in the spanwise direction. In the paper, we showed that Improved Delayed Detached Eddy Simulation (IDDES) hybrid RANS/LES turbulence model with a minimum of 24 cells per chord length in the spanwise direction is necessary to correctly predict the loads in the deep stall regime. Under the NACA 0012 airfoil directory, the data for several combinations of wall-normal and spanwise resolutions are presented in each of the AOA subdirectories. The corresponding experimental data for the lift and drag polars can be found in the "exp_data" subdirectory. The directory for the NACA 0021 airfoil consists of CFD force data and airfoil polars for Reynolds numbers 2.7e5 and 2.0e6.

17 WIND ENERGY↗

Adsorption of neodymium, dysprosium, and ytterbium to goethite under varying aqueous chemistry conditions [dataset]

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (< 5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (> 5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. A SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. This predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗