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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rare Earth and Transition Metal Containing Glasses

Transition metal (TM) and rare earth (RE) ions have been incorporated into many glass systems such as silicate, phosphate, and borosilicate-based oxide glasses, as well as in halide and chalcogenide glasses, that find applications ranging from optical, photonic, and magnetic devices, solid-state battery, to nuclear waste disposal. Understanding the structural role of RE and TM in these glasses can help to develop glass compositions for targeted applications with either high-optical emission efficiency, electrical conductivity, or chemical durability. In this chapter, we first provide a general introduction of the applications and structural features of RE and TM in glasses, then the critical aspects of molecular dynamics (MD) simulations of these glasses such as interatomic potentials, structural analysis tools to study RE and TM ions in glasses and their clustering behaviors, Quantitative Structure–Property Analysis (QSPR), diffusion and dynamic property calculations, and electronic structure calculations to understand electronic defects such as charge trapping and radiation effects are introduced. Three representative case studies are presented: the first one is on MD simulations of erbium- and europium-doped silica and silicate glasses, as well as cerium doped aluminophosphate glasses, that revealed the effect of glass composition on RE ion local structure and clustering behavior. Electronic structure calculations of cerium-doped glass show how the existence of multioxidation states help to mediate radiation-induced damages caused by excited electron–hole pairs was also discussed. The second one focuses on alkali vanadophosphate glasses where the existence of two vanadium oxidation states help to provide electronic conduction in the glasses while alkali ions provide ionic conduction. MD simulations were used to understand vanadium environments and other structural aspects in the phosphate glasses, as well as the ionic transport behaviors of alkali ions. The third case study is on zirconium-containing borosilicate and aluminosilicate glasses that find wide applications in nuclear waste disposal. MD simulations help to provide structural details of zirconium ions that are validated by diffraction and EXAFS spectra. The structural information was used to interpret changes of mechanical properties and chemical durability by using QSPR and other analyses-based MD-generated structure models.

Du, Jincheng↗
DOE OSTI2024

Ultrafast Symmetry Control in Photoexcited Quantum Dots

Symmetry control is essential for realizing unconventional properties, such as ferroelectricity, nonlinear optical responses, and complex topological order, thus it holds promise for the design of emerging quantum and photonic systems. Nevertheless, fast and reversible control of symmetry in materials remains a challenge, especially for nanoscale systems. Here, reversible symmetry changes are unveiled in colloidal lead chalcogenide quantum dots on picosecond timescales. Using a combination of ultrafast electron diffraction and total X-ray scattering, in conjunction with atomic-scale structural modeling and first-principles calculations, it is revealed that symmetry-broken lead sulfide quantum dots restore to a centrosymmetric phase upon photoexcitation. The symmetry restoration is driven by photoexcited electronic carriers, which suppress lead off-centering for about 100 ps. Furthermore, the change in symmetry is closely correlated with the electronic properties, and the bandgap transiently red-shifts in the symmetry-restored quantum dots. Overall, this study elucidates reversible symmetry changes in colloidal quantum dots, and more broadly defines a new methodology to optically control symmetry in nanoscale systems on ultrafast timescales.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Lanthanum induced lattice strain improves hydrogen sulfide capacities of copper oxide adsorbents

This work probes the effects of La on reactions involving CuO sorbents and H 2 S in gaseous streams. La-CuO sorbents with nominal La/Cu atomic ratios of 1:2 achieved higher capacities (27 and 36 g H 2 S per 100 g sorbent) compared to CuO sorbents (25 g H 2 S per 100 g sorbent). Here, comparison of the La-CuO sorbents using energy dispersive x-ray spectroscopy and La L 3 -edge XAS suggested that increased capacity resulted from more uniform dispersion of La within the CuO phase (3.3 wt.% vs. 1.0 wt.% La). X-Ray absorption near edge structure analysis suggested more electron-rich Cu species in La-CuO samples, while extended X-ray absorption fine structure modeling showed an increase in single-scattering path lengths for neighboring and near-neighbor atoms. These changes suggest that La induces strain in the Cu-O lattice, thereby increasing H 2 S capacity by reducing energy barriers associated with surface reactions between oxygen atoms and adsorbed H 2 S molecules.

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

Amino Acid Residues Controlling Domain Interaction and Interdomain Electron Transfer in Cellobiose Dehydrogenase

The function of cellobiose dehydrogenase (CDH) in biosensors, biofuel cells, and as a physiological redox partner of lytic polysaccharide monooxygenase (LPMO) is based on its role as an electron donor. Before donating electrons to LPMO or electrodes, an interdomain electron transfer from the catalytic FAD-containing dehydrogenase domain to the electron shuttling cytochrome domain of CDH is required. This study investigates the role of two crucial amino acids located at the dehydrogenase domain on domain interaction and interdomain electron transfer by structure-based engineering. The electron transfer kinetics of wild-type Myriococcum thermophilum CDH and its variants M309A, R698S, and M309A/R698S were analyzed by stopped-flow spectrophotometry and structural effects were studied by small-angle X-ray scattering. The data show that R698 is essential to pull the cytochrome domain close to the dehydrogenase domain and orient the heme propionate group towards the FAD, while M309 is an integral part of the electron transfer pathway – its mutation reducing the interdomain electron transfer 10-fold. Structural models and molecular dynamics simulations pinpoint the action of these two residues on the domain interaction and interdomain electron transfer.

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

Evaluating next-generation intensity–duration–frequency curves for design flood estimates in the snow-dominated western United States

Civil infrastructure such as culverts and bridges are commonly designed using precipitation-based intensity-duration-frequency (PREC-IDF) curves, which assume that the occurrence of precipitation is in the form of rainfall and immediately available for the rainfall-runoff process. In snow-dominated regions, where most winter precipitation occurs as snow that melts during spring to early summer, the use of standard PREC-IDF curves may lead to substantial underestimation of design floods and high failure risk of infrastructure. In this context, we developed next-generation IDF (NG-IDF) curves that characterize the actual water reaching the land surface (i.e., rainfall plus snowmelt) to enhance standard infrastructure design in snow-dominated regions. This study evaluates the performance of NG-IDF curves coupled with U.S. Department of Agriculture Technical Release 55 hydrologic model in estimating design floods for 246 snowy locations in different hydroclimate regimes of the western United States. Design flood estimates from a well-validated continuous simulation using a physics-based hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM), were used as the performance benchmark. Compared with the benchmark estimates, the standard PREC-IDF curves led to substantial errors in design flood estimates while the NG-IDF curves significantly reduced these errors. For example, the averaged error in the 50-year design flood estimates over the 246 locations was reduced from 31% with the use of PREC-IDF curves to 12% with the use of NG-IDF curves. Despite the different model structures, the single-event NG-IDF approach versus the continuous simulation DHSVM did not exhibit statistically significant differences in 91% of the 246 locations for the 50-year design flood estimates. We find this indicates a satisfactory performance of NG-IDF curves to estimate design flow under the conditions tested in the snow-dominated western United States. This article also presents technical suggestions and the limitations of infrastructure design using NG-IDF curves for regulatory agencies and practicing engineers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗
DOE OSTI2020

The Energy Modeling Forum (EMF)-30 Study on Short-Lived Climate Forcers: Introduction and Overview

The Energy Modeling Forum (EMF)-30 inter-comparison study on short-lived climate forcers (SLCFs) focuses on black carbon (BC) and methane, two of the most important warming SLCFs. The potential impact on climate change of methane and BC-focused emission reductions in the transport and residential sectors were quantified using nine integrated assessment models and a simple climate model. These SLCF reductions reduced global temperatures by 0.18–0.26 °C in 2050 across the models for central climate parameters, with methane being the dominant contributor. The incremental impact of SLCF-focused reductions is much smaller when combined with a broader climate policy. Individual modeling groups examined the health benefits of air pollutant reductions, climate policy co-benefits, and quantified market impacts from air pollutant damages. Model structure and set-up impact on results are discussed along with areas for future work.

Smith, Steven J.↗
DOE OSTI2025

Projections of future climate for U.S. national assessments: past, present, future

Climate assessments consolidate our understanding of possible future climate conditions as represented by climate projections, which are largely based on the output of global climate models. Over the past 30 years, the scientific insights gained from climate projections have been refined through model structural improvements, emerging constraints on climate feedbacks, and increased computational efficiency. Within the same period, the process of assessing and evaluating information from climate projections has become more defined and targeted to inform users. As the size and audience of climate assessments has expanded, the framing, relevancy, and accessibility of projections has become increasingly important. This paper reviews the use of climate projections in national climate assessments (NCA) while highlighting challenges and opportunities that have emerged over time. Reflections and lessons learned address the continuous process to understand the broadening assessment audience and evolving user needs. Insights for future NCA development include (1) identifying benchmarks and standards for evaluating downscaled datasets, (2) expanding efforts to gather research gaps and user needs to inform how climate projections are presented in the assessment (3) providing practitioner guidance on the use, interpretation, and reporting of climate projections and uncertainty to better inform decision-making.

Assessment↗
DOE OSTI2019

Numerical analysis of temperature and stress fields in hybrid indium antimonide arrays detector with laser irradiation

Thermal-stress effects are the major cause of failure in infrared focal-plane arrays detector, during laser irradiation. Based on the established three-dimensional structural model of hybrid indium antimonide infrared focal-plane arrays, the temperature and stress fields of hybrid indium antimonide detectors irradiated by 1.064-μm Gauss pulsed laser are studied, considering the temperature-dependent material parameters. The results indicate that the temperature increase and thermal stress effects are different, in each layer. Especially in indium antimonide chip, which is the uppermost layer of the indium antimonide detector that directly absorbs laser energy, the temperature shows not a smooth decrease as laser intensity from centre to outside, but a concentric-ringed ripple decrease with discontinuous high temperature extremum areas; which induces its own unique stress distributions: during the laser irradiation region, the thermal stress in areas above indium bumps is much lower than that in areas above underfill, but the stress distribution outside the laser irradiation region is exactly the opposite. The temperature and stress distribution in other materials are also different from that in indium antimonide chip. The main reason is that each material has different thermal properties, especially indium bump and underfill, which are alternative distribution in middle layers, have quite different thermal parameters. All these make the temperature and stress distribution in each layer having own characteristics. In addition, the change trend of the maximum temperature and stress in each layer in accordance with the laser pulse number are also studied. The maximum stress as well as temperature always occurs in the indium antimonide chip.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Cannabis monoterpene synthases: evaluating structure–function relationships

Terpene synthases catalyze the first committed step in the biosynthesis of terpenes, a structurally diverse class of natural products that also encompasses volatiles derived from precursors in the C10 to C15 range (termed monoterpenes and sesquiterpenes, respectively). In the review section of this article, we are providing information about all functionally characterized monoterpene synthases (MTSs) and sesquiterpene synthases (STSs) of Cannabis sativa L. We are also exploring the locations of MTSs and STSs in the chromosome-level assembly of the reference chemovar CBDRx. A follow-up computational structure–function analysis focuses on MTSs, as there is already a rich literature available on the topic. More specifically, by employing sequence comparisons and homology structural modeling, we infer which amino acid residues are likely to constrain the available space in the active site of cannabis MTSs. The emphasis of these studies was to investigate why some MTSs accept only a C10 diphosphate as substrate, while mixed MTS/STS enzymes also accommodate a C15 diphosphate. Here, by combining a literature review and computational analyses in a hybrid format, we are laying the foundation for future studies to better understand the determinants of substrate and product specificity in these fascinating enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Perfect quantum state transfer on diamond fractal graphs

In the quest for designing novel protocols for quantum information and quantum computation, an important goal is to achieve perfect quantum state transfer for systems beyond the well-known one- dimensional cases, such as 1D spin chains. Here, we use methods from fractal analysis and probability to find a new class of quantum spin chains on fractal-like graphs (known as diamond fractals) which support perfect quantum state transfer and which have a wide range of different Hausdorff and spectral dimensions. The resulting systems are spin networks combining Dyson hierarchical model structure with transverse permutation symmetries of varying order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Synthesis and pharmacological activity of a silicon—zinc—boron-containing glycerohydrogel

A new pharmacologically active nanostructured silicon—zinc—boron-containing glycerohydrogel was synthesized by the sol—gel method using silicon, zinc, and boron glycerolates as biocompatible precursors. The hydrogel composition and structural features were investigated by transmission electron microscopy, powder X-ray diffraction, IR spectroscopy, atomic emission spectrometry, and elemental analysis; a structural model was proposed. It was found that the 3D framework of the gel is formed by the products of hydrolysis and subsequent (co)condensation of silicon- and boron-containing precursors. Meanwhile, the major part of zinc monoglycerolate does not undergo hydrolytic transformations during gelation, being present in the 3D framework cells as amorphous nano-sized particles. The dispersion medium of the gel is an aqueous glycerol solution of silicon and boron glycerolates, products of their hydrolytic transformations, and water-soluble products of hydrolytic transformations of zinc monoglycerolate. The silicon—zinc—boron gel is nontoxic and possesses wound-healing and antimicrobial activities; it can be considered as a nanostructured dispersed system promising for biomedical applications, which is prepared in a simple and cost-effective way without using catalysts or toxic organic solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Dynamics of an epidemic model with delays and stage structure

In this paper, dynamics of a stage-structured epidemic model with delays and nonlinear incidence rate is analyzed. Local stability and existence of Hopf bifurcation is discussed by choosing possible combination of the delays as the bifurcation parameter. It is proved that the unique endemic equilibrium is locally asymptotically stable when the delay is suitably small and a bifurcating periodic solution will be caused once the delay passes through the corresponding critical value of the delay. We make use of the normal form theory and center manifold theorem to obtain the explicit formulas for determining the properties of the Hopf bifurcation. Numerical simulations supporting our obtained findings are carried out in the end.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry

Herein, protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the “early events” of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Portable interactive visualization of large-scale simulations in geotechnical engineering using Unity3D

Development in large-scale geotechnical engineering simulation places tremendous demand for efficient visualization of such simulation data. This study presents a lightweight software tool, i.e. Geotechnical Interactive Visualization (GIV), as a solution to this challenge, which achieves efficient interactive visualization of large-scale simulations data in geotechnical engineering. Visualization data flow and algorithms specifically optimized for common geotechnical engineering applications are implemented in GIV. GIV can visualize geotechnical structure models with time-varying attributes attached to mesh with fixed topology, and also models with time-varying mesh topologies but no attributes attached, the two most common visualization tasks in geotechnical engineering. Furthermore, challenges for large-scale simulation data visualization, including parallel simulation data redundancy, massive data size, dynamic user interaction, and portability are overcome via specifically designed algorithms for simulation data preprocessing and optimized visualization modules using the powerful 3D rendering and interactive game engine Unity3D. Comparison of GIV with several widely used visualization tools for the visualization of large-scale idealized datasets and realistic geotechnical simulations highlights the visualization efficiency, smooth interactivity, and lightweight features of GIV.

42 ENGINEERING↗
DOE OSTI2022

Hourly water-carbon interactions modulate decadal water-use efficiency trends inferred from ecosystem-scale measurements

Plant stomatal conductance regulates photosynthesis and transpiration. This physiological link affects ecosystem responses to microclimate and harmonizes carbon, energy, and water exchanges between the biosphere and atmosphere. The relationship between water losses via transpiration and carbon gains via photosynthesis can be quantified by plant water-use efficiency (WUE). While leaf- and ecosystem-scale observations both suggest rising WUE in recent decades, WUE trends inferred from the ecosystem scale are much larger than those inferred from the leaf scale or implied by theory. The unexpectedly large ecosystem-scale WUE trends complicate interpretation of ecophysiological responses to changing environmental conditions. Here, we analyze ecosystem-scale WUE inferred from 40 FLUXNET sites, each with at least 10 years of measurements. Furthermore, our results demonstrate that observed ecosystem-scale WUE trends are more sensitive to hourly weather conditions than longer-term changes in atmospheric carbon dioxide or vapor pressure deficit. Our analysis shows that Earth System Models participating in CMIP6 did not capture the observed WUE sensitivity to inter-site variability and microclimatic conditions. Collectively, our findings suggest that ecosystem-scale WUE trends reflect water-carbon interactions across multiple temporal scales, and disentangling factors contributing to emergent ecosystem responses is needed to infer ecophysiological relationships and model structures from observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Deep reinforcement learning for class imbalance fault diagnosis of equipment in nuclear power plants

In equipment fault diagnosis in nuclear power plants, there may be far more samples in one class (e.g., a health state) than in another class (e.g., a fault state). The distribution of data in each class is highly skewed. Most machine learning algorithms are suitable for balanced training datasets. When faced with imbalanced samples, these algorithms tend to provide good identification for the majority classes and bias for the minority classes. However, the misclassification of minority classes can lead to high costs. To address the above problem, this paper develops a deep reinforcement learning-based diagnosis method that models fault diagnosis as a sequential decision-making process. At each time step, the agent receives the state of the environment represented by the training samples and then takes a diagnosis action guided by a policy. If the action is correct/incorrect, the agent receives a positive/negative reward. The reward for minority classes is higher than that for majority classes. The agent’s goal is to obtain as many cumulative rewards as possible in the process, i.e., to identify the sample as correctly as possible. Six demonstration scenarios are constructed, depending on the selected fault datasets and the designed model structures. Experiments show that the proposed method achieves a higher weighted-averaged F1 score than the classical supervised learning method in most cases of class imbalance. Finally, the proposed method has potential applications in the field of class imbalance fault diagnosis of equipment in nuclear power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗