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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

A Comprehensive Search for Stable Pt-Pd Nanoalloy Configurations and Their Use as Tunable Catalysts

Using density-functional theory, we predict stable alloy configurations (ground states) for a 1 nm Pt–Pd cuboctahedral nanoparticle across the entire composition range and demonstrate their use as tunable alloy catalysts via hydrogen-adsorption studies. Unlike previous works, we use simulated annealing with a cluster expansion Hamiltonian to perform a rapid and comprehensive search that encompasses both high and low-symmetry configurations. The ground states show Pt(core)–Pd(shell) type configurations across all compositions but with specific Pd patterns. For catalysis studies at room temperatures, the ground states are more realistic structural models than the commonly assumed random alloy configurations. Using the ground states, we reveal that the hydrogen adsorption energy increases (decreases) monotonically with at. % Pt for the {111} hollow ({100} bridge) adsorption site. Such trends are useful for designing tunable Pd–Pt nanocatalysts for the hydrogen evolution reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Comprehensive Identification of Glycated Peptides and Their Glycation Motifs in Plasma and Erythrocytes of Control and Diabetic Subjects

Non-enzymatic glycation of proteins is implicated in diabetes mellitus and its related complications. In this report, we extend our previous development and refinement of proteomics-based methods for the analysis of non-enzymatically glycated proteins to comprehensively identify glycated proteins in normal and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated proteins. Semi-quantitative comparisons revealed a number of proteins with glycation levels significantly increased in diabetes relative to control samples and that erythrocyte proteins are more extensively glycated than plasma proteins. A glycation motif analysis revealed amino acids that are favored more than others in the protein primary structures in the vicinity of the glycation sites in both sample types. The glycated peptides and corresponding proteins reported here provide a foundation for the potential identification of novel markers for diabetes, glycemia, or diabetic complications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher-order products including an approximation of volume-weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self-describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase-changes at high temporal resolution. Bulk precipitation characteristics from a multi-site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high-quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗
DOE OSTI2022

An all optical approach for comprehensive in-operando analysis of radiative and nonradiative recombination processes in GaAs double heterostructures

We demonstrate an all optical approach that can surprisingly offer the possibility of yielding much more information than one would expect, pertinent to the carrier recombination dynamics via both radiative and nonradiative processes when only one dominant deep defect level is present in a semiconductor material. By applying a band-defect state coupling model that explicitly treats the inter-band radiative recombination and Shockley–Read–Hall (SRH) recombination via the deep defect states on an equal footing for any defect center occupation fraction, and analyzing photoluminescence (PL) as a function of excitation density over a wide range of the excitation density (e.g., 5–6 orders in magnitude), in conjunction with Raman measurements of the LO-phonon plasmon (LOPP) coupled mode, nearly all of the key parameters relevant to the recombination processes can be obtained. They include internal quantum efficiency (IQE), minority and majority carrier density, inter-band radiative recombination rate (W r ), minority carrier nonradiative recombination rate (W nr ), defect center occupation fraction (f), defect center density (N t ), and minority and majority carrier capture cross-sections (σ t and σ tM ). While some of this information is thought to be obtainable optically, such as IQE and the W r /W nr ratio, most of the other parameters are generally considered to be attainable only through electrical techniques, such as current-voltage (I-V) characteristics and deep level transient spectroscopy (DLTS). Following a procedure developed herein, this approach has been successfully applied to three GaAs double-heterostructures that exhibit two distinctly different nonradiative recombination characteristics. The method greatly enhances the usefulness of the simple PL technique to an unprecedented level, facilitating comprehensive material and device characterization without the need for any device processing.

14 SOLAR ENERGY↗
DOE OSTI2021

Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules

Proteins evolve through the modular rearrangement of elements known as domains. Extant, multidomain proteins are hypothesized to be the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) for comprehensively making all possible deletions of a protein. Using MISER, we generate a deletion landscape for the CRISPR protein Cas9. We find that the catalytically-dead Streptococcus pyogenes Cas9 can tolerate large single deletions in the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part II: comprehensive ternary design and validation

Abstract Here the discovery of refractory multi-principal element alloys (MPEAs) with high-temperature strength and stability is pursued within a constrained and application-relevant design space. A comprehensive approach is developed and applied to explore all 165 ternary systems in the Al-Ce-Fe-Hf-Mo-Nb-Ta-Ti-V-W-Zr family. A subset of ternary systems that contain large areas in composition–temperature space with high strength and robust BCC phase stability is found. Twelve sets of high-performing alloys are identified, each set optimized for one combination of phase constraint, optimization target, and temperature range. Preliminary mechanical tests support the viability of the method. This work highlights the importance of considering phase stability, exploring non-equiatomic regions of composition space, and applying application-relevant constraints. Parts I and II provide three down-selection techniques for identifying high-performing BCC refractory MPEAs, design guidelines, and many candidates predicted to have BCC phase stability and strengths 2–3 times higher than any reported to date.

36 MATERIALS SCIENCE↗
DOE OSTI2021

QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures—comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers)—as well as 100 non-equilibrium structural variations thereof to reach a total of ≈4.2 million molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties.

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

A comprehensive spectral assay library to quantify the Halobacterium salinarum NRC-1 proteome by DIA/SWATH-MS

Data-Independent Acquisition (DIA) is a mass spectrometry-based method to reliably identify and reproducibly quantify large fractions of a target proteome. The peptide-centric data analysis strategy employed in DIA requires a priori generated spectral assay libraries. Such assay libraries allow to extract quantitative data in a targeted approach and have been generated for human, mouse, zebrafish, E. coli and few other organisms. However, a spectral assay library for the extreme halophilic archaeon Halobacterium salinarum NRC-1, a model organism that contributed to several notable discoveries, is not publicly available yet. Here, we report a comprehensive spectral assay library to measure 2,563 of 2,646 annotated H. salinarum NRC-1 proteins. We demonstrate the utility of this library by measuring global protein abundances over time under standard growth conditions. The H. salinarum NRC-1 library includes 21,074 distinct peptides representing 97% of the predicted proteome and provides a new, valuable resource to confidently measure and quantify any protein of this archaeon. Data and spectral assay libraries are available via ProteomeXchange (PXD042770, PXD042774) and SWATHAtlas (SAL00312-SAL00319).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CHUWD-H v1.0: a comprehensive historical hourly weather database for U.S. urban energy system modeling

Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.0, a 23-year (1998-2020) gap-free and quality-controlled hourly weather dataset covering 550 weather station locations across all urban areas in the contiguous United States. CHUWD-H v1.0 synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and a reanalysis dataset through a multi-step gap filling approach. A 10-fold Monte Carlo cross-validation suggests that the accuracy of this gap filling approach surpasses that of conventional gap filling methods. Designed primarily for urban energy system modeling, CHUWD-H v1.0 should also support historical urban meteorological and climate studies, including the validation and evaluation of urban climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Integrative analysis of large scale transcriptome data draws a comprehensive landscape of Phaeodactylum tricornutum genome and evolutionary origin of diatoms

Diatoms are one of the most successful and ecologically important groups of eukaryotic phytoplankton in the modern ocean. Deciphering their genomes is a key step towards better understanding of their biological innovations, evolutionary origins, and ecological underpinnings. Here, we have used 90 RNA-Seq datasets from different growth conditions combined with published expressed sequence tags and protein sequences from multiple taxa to explore the genome of the model diatom Phaeodactylum tricornutum, and introduce 1,489 novel genes. The new annotation additionally permitted the discovery of extensive alternative splicing in diatoms, including intron retention and exon skipping, which increase the diversity of transcripts generated in changing environments. In addition, we have used up-to-date reference sequence libraries to dissect the taxonomic origins of diatom genes. We show that the P. tricornutum genome is enriched in lineage-specific genes, with up to 47% of the gene models present only possessing orthologues in other stramenopile groups. Finally, we have performed a comprehensive de novo annotation of repetitive elements showing novel classes of transposable elements such as SINE, MITE and TRIM/LARD. This work provides a solid foundation for future studies of diatom gene function, evolution and ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Catalytic conversion of cellulose and its derived sugars to 5-Hydroxymethylfurfural, levulinate esters, and sorbitol: a comprehensive review

Cellulose, an abundant, renewable, and sustainable non-edible carbon source from agriculture and forestry, has attracted great attention for producing diverse value-added chemicals and fuels. However, the rigid 3D structure of cellulose, maintained by an extensive hydrogen bonding network, hinders chemical conversion, requiring effective pretreatment to break down the crystalline structure. High-value cellulose-derived compounds such as 5-hydroxymethylfurfural (5-HMF), levulinate esters, and sorbitol, recognized as critical platform chemicals by the U.S. Department of Energy, are particularly attractive for versatile applications. This review provides a comprehensive overview of methodologies for the chemical synthesis of 5-HMF, levulinate esters, and sorbitol, focusing on direct catalytic conversion of cellulose. It delves into recent advancements in reaction systems and catalysts, highlighting catalytic pathways, selectivity, strategies for process optimization, and computational approaches, while discussing the challenges associated with the catalytic conversion of cellulose into these high-value products and offering potential strategies for enhancing future catalytic processes.

Huang, Kaixuan [Yancheng Teachers Univ. (China); N↗
DOE OSTI2015

A comprehensive map of genome-wide gene regulation in Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium responsible for 12 million active cases of tuberculosis (TB) worldwide. The complexity and critical regulatory components of MTB pathogenicity are still poorly understood despite extensive research efforts. In this study, we constructed the first systems-scale map of transcription factor (TF) binding sites and their regulatory target proteins in MTB. We constructed FLAG-tagged overexpression constructs for 206 TFs in MTB, used ChIP-seq to identify genome-wide binding events and surveyed global transcriptomic changes for each overexpressed TF. Here we present data for the most comprehensive map of MTB gene regulation to date. We also define elaborate quality control measures, extensive filtering steps, and the gene-level overlap between ChIP-seq and microarray datasets. Further, we describe the use of TF overexpression datasets to validate a global gene regulatory network model of MTB and describe an online source to explore the datasets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A Comprehensive View of Global Potential for Hydro-generated Electricity

In this study, we assess global hydropower potential using runoff and stream flow data, along with turbine technology performance, cost assumptions, and environmental considerations. The results provide the first comprehensive quantification of global hydropower potential including gross, technical, economic, and exploitable estimates. Total global potential of gross, technical, economic, and exploitable hydropower are estimated to be approximately 128, 39, 32, and 27 petawatt hours per year, respectively. The economic and exploitable potential of hydropower are calculated at less than 9 cents/kWh. We find that hydropower has the potential to supply a significant portion of the world energy needs, although this potential varies substantially by region. Globally, hydropower can potentially supply about 1.5 times the total electricity demand in 2005. Estimated hydropower resources in a number of countries are sufficient to accommodate their demand for electricity in 2005, e.g., Brazil (5.6 times), Russia (4.6 times), and Canada (3.5 times). A sensitivity analysis indicates that hydropower estimates are not highly sensitive to five key parameters: design flow (varying by -2% to +1% at less than 9 cents/kWh), cost and financing options (by -7% to +6%), turbine efficiency (by -10% to +10%), stream flow (by -10% to +10%), and fixed charge rate (by -6% to 5%). This sensitivity analysis emphasizes the reliable role of hydropower for future energy systems, when compared to other renewable energy resources with larger uncertainty in their future potentials.

Zhou, Yuyu↗
DOE OSTI2016

Acetylene adsorption on δ-MoC(001), TiC(001) and ZrC(001) surfaces: A comprehensive periodic DFT study

A comprehensive study of acetylene adsorption on δ-MoC(001), TiC(001) and ZrC(001) surfaces was carried out by means of calculations based on periodic density functional theory, using the Perdew–Burke–Ernzerhof exchange–correlation functional. It was found that the bonding of acetylene was significantly affected by the electronic and structural properties of the carbide surfaces. The adsorbate interacted with metal and/or carbon sites of the carbide. The interaction of acetylene with the TiC(001) and ZrC(001) surfaces was strong (binding energies higher than $-$3.5 eV), while moderate acetylene adsorption energies were observed on δ-MoC(001) ($-$1.78 eV to –0.66 eV). Adsorption energies, charge density difference plots and Mulliken charges suggested that the binding of the hydrocarbon to the surface had both ionic and covalent contributions. According to the C–C bond lengths obtained, the adsorbed molecule was modified from acetylene-like into ethylene-like on the δ-MoC(001) surface (desired behavior for hydrogenation reactions) but into ethane-like on TiC(001) and ZrC(001). The obtained results suggest that the δ-MoC(001) surface is expected to have the best performance in selective hydrogenation reactions to convert alkynes into alkenes. Another advantage of δ-MoC(001) is that, after C 2 H 2 adsorption, surface carbon sites remain available, which are necessary for H 2 dissociation. Furthermore, these sites were occupied when C 2 H 2 was adsorbed on TiC(001) and ZrC(001), limiting their application in the hydrogenation of alkynes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Improved molecular level identification of organic compounds using comprehensive two-dimensional chromatography, dual ionization energies and high resolution mass spectrometry

A new analytical methodology combining comprehensive two-dimensional gas chromatography (GC×GC), dual ionization energies and high resolution time of flight mass spectrometry has been developed that improves molecular level identification of organic compounds in complex environmental samples. GC×GC maximizes compound separation providing cleaner mass spectra by minimizing erroneous fragments from interferences and co-eluting peaks. Traditional electron ionization (EI, 70 eV) provides MS fragmentation patterns that can be matched to published EI MS libraries while vacuum ultraviolet photoionization (VUV, 10.5 eV) yields MS with reduced fragmentation enhancing the abundance of the molecular ion providing molecular formulas when combined with high resolution mass spectrometry. We demonstrate this new approach by applying it to a sample of organic aerosol. In this sample, 238 peaks were matched to EI MS library data with FM ≥ 800 but a fifth (42 compounds) were determined to be incorrectly identified because the molecular formula was not confirmed by the VUV MS data. This highlights the importance of using a complementary technique to confirm compound identifications even for peaks with very good matching statistics. In total, 171 compounds were identified by EI MS matching to library spectra with confirmation of the molecular formula from the high resolution VUV MS data and were not dependent on the matching statistics being above a threshold value. A large number of unidentified peaks were still observed with FM < 800, which in routine analysis would typically be neglected. Where possible, these peaks were assigned molecular formulas from the VUV MS data (211 in total). In total, the combination of EI and VUV MS data provides more than twice as much molecular level peak information than traditional approaches and improves confidence in the identification of individual organic compounds. The molecular formula data from the VUV MS data was used, in conjunction with GC×GC retention times and the observed EI MS, to generate a new, searchable EI MS library compatible with the standard NIST MS search program. This library is deliberately dynamic and editable so that other end users can add new entries and update existing entries as new information becomes available.A new analytical methodology has been developed to improve molecular level identification of organic compounds in complex samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A high-speed, high-performance, microfabricated comprehensive two-dimensional gas chromatograph

A small, consumable-free, low-power, ultra-high-speed comprehensive GC×GC system consisting of microfabricated columns, nanoelectromechanical system (NEMS) cantilever resonators for detection, and a valve-based stop-flow modulator is demonstrated. The separation of a highly polar 29-component mixture covering a boiling point range of 46 to 253 °C on a pair of microfabricated columns using a Staiger valve manifold in less than 7 seconds, and just over 4 seconds after the ensemble holdup time is demonstrated with a downstream FID. The analysis time of the second dimension was 160 ms, and peak widths in the second dimension range from 10–60 ms. A peak capacity of just over 300 was calculated for a separation of just over 6 s. Data from a continuous operation testing over 40 days and 20 000 runs of the GC×GC columns with the NEMS resonators using a 4-component test set is presented. As a result, the GC×GC-NEMS resonator system generated second-dimension peak widths as narrow as 8 ms with no discernable peak distortion due to under-sampling from the detector.

47 OTHER INSTRUMENTATION↗