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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tuning of lattice oxygen reactivity and scaling relation to construct better oxygen evolution electrocatalyst

Developing efficient and low-cost electrocatalysts for oxygen evolution reaction is crucial in realizing practical energy systems for sustainable fuel production and energy storage from renewable energy sources. However, the inherent linear scaling relation for most catalytic materials imposes a theoretical overpotential ceiling, limiting the development of efficient electrocatalysts. Herein, using modeled Na x Mn 3 O 7 materials, we report an effective strategy to construct better oxygen evolution electrocatalyst through tuning both lattice oxygen reactivity and scaling relation via alkali metal ion mediation. Specifically, the number of Na + is linked with lattice oxygen reactivity, which is determined by the number of oxygen hole in oxygen lone-pair states formed by native Mn vacancies, governing the barrier symmetry between O–H bond cleavage and O–O bond formation. On the other hand, the presence of Na + could have specific noncovalent interaction with pendant oxygen in *OOH to overcome the limitation from linear scaling relation, reducing the overpotential ceiling. Combining in situ spectroscopy-based characterization with first-principles calculations, we demonstrate that an intermediate level of Na + mediation (NaMn 3 O 7 ) exhibits the optimum oxygen evolution activity. This work provides a new rational recipe to develop highly efficient catalyst towards water oxidation or other oxidative reactions through tuning lattice oxygen reactivity and scaling relation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co 3 Sn 2 S 2 , we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co 3 Sn 2 S 2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co 3 Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co 3 Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Constructing protein polyhedra via orthogonal chemical interactions

Many proteins exist naturally as symmetrical homooligomers or homopolymers. The emergent structural and functional properties of such protein assemblies have inspired extensive efforts in biomolecular design2–5. As synthesized by ribosomes, proteins are inherently asymmetric. Therefore, they must acquire multiple surface patches that selectively associate to generate the different symmetry elements needed to form higher-order architectures—a daunting task for protein design. Here we address this problem using an inorganic chemical approach, whereby multiple modes of protein–protein interactions and symmetry are simultaneously achieved by selective, ‘one-pot’ coordination of soft and hard metal ions. We show that a monomeric protein (protomer) appropriately modified with biologically inspired hydroxamate groups and zinc-binding motifs assembles through concurrent Fe 3+ and Zn 2+ coordination into discrete dodecameric and hexameric cages. Our cages closely resemble natural polyhedral protein architectures and are, to our knowledge, unique among designed systems in that they possess tightly packed shells devoid of large apertures. At the same time, they can assemble and disassemble in response to diverse stimuli, owing to their heterobimetallic construction on minimal interprotein-bonding footprints. With stoichiometries ranging from [2 Fe:9 Zn:6 protomers] to [8 Fe:21 Zn:12 protomers], these protein cages represent some of the compositionally most complex protein assemblies—or inorganic coordination complexes—obtained by design.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Impaired photosynthesis and increased leaf construction costs may induce floral stress during episodes of global warming over macroevolutionary timescales

Global warming events have coincided with turnover of plant species at intervals in Earth history. As mean global temperatures rise, the number, frequency and duration of heat-waves will increase. Ginkgo biloba was grown under controlled climatic conditions at two different day/night temperature regimes (25/20 °C and 35/30 °C) to investigate the impact of heat stress. Photosynthetic CO 2 -uptake and electron transport were reduced at the higher temperature, while rates of respiration were greater; suggesting that the carbon balance of the leaves was adversely affected. Stomatal conductance and the potential for evaporative cooling of the leaves was reduced at the higher temperature. Furthermore, the capacity of the leaves to dissipate excess energy was also reduced at 35/30 °C, indicating that photo-protective mechanisms were no longer functioning effectively. Leaf economics were adversely affected by heat stress, exhibiting an increase in leaf mass per area and leaf construction costs. This may be consistent with the selective pressures experienced by fossil Ginkgoales during intervals of global warming such as the Triassic - Jurassic boundary or Early Eocene Climatic Optimum. The physiological and morphological responses of the $G$. biloba leaves were closely interrelated; these relationships may be used to infer the leaf economics and photosynthetic/stress physiology of fossil plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Foundations and strategies of the construction of hybrid catalysts for optimized performances

Catalysts are generally classified into three categories: homogeneous, heterogeneous and enzyme, each evolved as an independent field. Efforts to bridge these fields are scarce but desirable. In this paper, we first describe how numerous classes of reactions can be achieved by all three categories of catalysts. Examples are given based on a selective survey of the literature. Next, a selection of important approaches, the benefits and challenges of constructing heterogeneous–homogeneous, heterogeneous–enzyme and homogeneous–enzyme hybrid catalysts are discussed based on published researches. Hybrid catalysts not only increase the performance, including activity, selectivity, lifetime and recyclability compared to one of the components, but also offer extra functions such as a microenvironment for different reaction pathways, and cascade catalysis for products that are challenging to produce. Finally, we expect future tailor-made hybrid catalysts will combine the advantages of the components and be optimized for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Two-in-one: construction of hydroxyl and imidazolium-bifunctionalized ionic networks in one-pot toward synergistic catalytic CO 2 fixation

Here, a succinct strategy was demonstrated for constructing a hydroxyl group and imidazolium-bifunctionalized ionic network via a onepot quaternization. Key to success lies in the rational design of multi-imidazole precursor and hydroxyl-containing counterpart. Unique properties of the resultant ionic network render its high catalytic efficiency toward CO 2 fixation under ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Alkaline salt-promoted construction of hydrophilic and nitrogen deficient graphitic carbon nitride with highly improved photocatalytic efficiency

Graphitic carbon nitride (g-C 3 N 4 ) possesses fascinating merits, but its practical applications are limited by the inferior properties of limited visible-light sorption, rapid recombination of photo-excited charge carriers and low electrical conductivity. Introduction of N-defects is an efficient approach to tune its optical properties, but strategies capable of creating abundant vacancies and simultaneously maintaining the highly crystalline architecture are still limited and highly desired. In this work, a facile construction methodology was demonstrated to afford g-C 3 N 4 with abundant N vacancies, high crystallinity, a hydrophilic surface structure, a small particle size, and an increased surface area under neat and mild conditions. Furthermore, the essence of our approach lies in the treatment of the bulk g-C 3 N 4 precursor with an alkaline salt (LiN(SiMe 3 ) 2 ) with a low melting point, moderate nucleophilicity, and easy removal procedures. The unique structural properties of the afforded ND-g-C 3 N 4 allow for a significantly redshifted absorption edge and enhanced charge carrier separation, leading to superior photocatalytic hydrogen evolution performance three times that obtained by pristine g-C 3 N 4 . The modification strategy developed herein sheds light on the fabrication of g-C 3 N 4 -based materials with improved photocatalytic efficiency via efficient introduction of N defects, variation of the surface structure, and retention of the high crystallinity.

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

Constructing “Li-rich Ni-rich” oxide cathodes for high-energy-density Li-ion batteries

The current exploration of high-energy-density cathode materials for Li-ion batteries is mainly concentrated on either so-called “Li-rich” or “Ni-rich” oxides. However, both are suffering from formidable practical challenges. Here, we combine these two concepts to obtain “Li-rich Ni-rich” oxides in pursuit of more practical high-energy-density cathodes. As a proof of concept, we synthesized an array of Li 1+y Ni( 3-5y)/3 Mo 2y/3 O 2 oxides, whose structures were identified to be the coexistence of LiNiO 2 -rich and Li 4 MoO 5 -rich domains with the aid of XRD, TEM, and NMR techniques. Such an intergrowth structure of 5–20 nm size enables excellent mechanical and structural reversibility for the layered rock-salt LiNiO 2 -rich domain upon cycling thanks to the robust cubic rock-salt Li 4 MoO 5 -rich domain enabling an “epitaxial stabilization” effect. As a result, we achieved high capacities (>220 mA h g -1 ) with Ni contents as low as 80%; the Li 1.09 Ni 0.85 Mo 0.06 O 2 member (y = 0.09) shows much improved cycling performances (91% capacity retention for 100 cycles at C/10) compared with pure LiNiO 2 . Further, this work validates the feasibility of constructing Li-rich Ni-rich compounds in the form of intergrowing domains and hence unlocks vast possibilities for future cathode design.

25 ENERGY STORAGE↗
DOE OSTI2026

Construction of generalized quasilinear diffusion coefficient using neural networks with physical restrictions

The quasilinear diffusion coefficient (D QL ) derived from our machine learning framework shows comparable trends with the ground truth D QL obtained from GENRAY-CQL3D simulations. Additionally, for the strong absorption cases, the radial current drive profiles generated using the D QL from our model exhibit consistent behavior with those obtained from the original simulation. These findings indicate the potential of our surrogate modeling approach with physical restrictions to replicate key wave–plasma interaction characteristics while reducing computational costs. Traditionally, calculating D QL for wave–particle interactions relies on computationally intensive wave simulations coupled with Fokker–Planck solvers. To address this challenge, we developed a machine learning-based surrogate model with physical restrictions derived from cold plasma theory and bounce-averaged damping effects. First, we establish the propagation domain of Lower Hybrid Waves in the (N∥, ρ) space by identifying the accessibility limit and determining the upper and lower bounds of N∥ using the Potential Power Deposition (PPD) method. Subsequently, leveraging a database constructed using Latin hypercube sampling alongside the underlying physical restrictions (e.g. PPD), machine learning methods including U-Net and Recurrent Neural Networks are employed to design a physics-restricted machine learning framework capable of reconstructing D QL .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Automated Approach for Construction of Long-Term, Data-Intensive Watershed Models

Watershed models such as the Hydrological Simulation Program in FORTRAN (HSPF) are frequently used to analyze large-scale water quantity and water quality issues. The construction of HSPF models is a difficult and time-consuming process, because it requires compilation of extensive quantities of data into formatted files followed by a simultaneous fitting of many uncertain parameters. Because of these complications, studies are often limited to calibration periods of only a few years even when analyzing long time-scale issues such as climate and land-use changes that are difficult or impossible to reproduce. High-level, open source programming languages provide an environment for automating the extraction and processing of various sources of data in addition to the calibration process required by HSPF. Recently developed software can be used to build HSPF input files, run simulations, and postprocess simulation results using the Python programming language. The combination of tools in Python, public data sets on the Internet, and software extensions enables rapid development of long-term, reproducible, and sophisticated models for new hydrologic insight. Herein, the utility of these tools is illustrated by developing an automated 30-year HSPF model with a Nash-Sutcliffe efficiency of 0.88 for monthly flows and 0.75 for daily flows in a simulation time of approximately 3h. The integration of HSPF with a high-level programming language creates opportunities to more rigorously explore model assumptions, calibration methods, and alternative data sets.

Lampert, Dave J↗
DOE OSTI2015

Construction of a magnetic bottle spectrometer and its application to pulse duration measurement of X-ray laser using a pump-probe method

To characterize the temporal evolution of ultrashort X-ray pulses emitted by laser plasmas using a pump-probe method, a magnetic bottle time-of-flight electron spectrometer is constructed. The design is determined by numerical calculations of a mirror magnetic field and of the electron trajectory in a flight tube. The performance of the spectrometer is characterized by measuring the electron spectra of xenon atoms irradiated with a laser-driven plasma X-ray pulse. In addition, two-color above-threshold ionization (ATI) experiment is conducted for measurement of the X-ray laser pulse duration, in which xenon atoms are simultaneously irradiated with an X-ray laser pump and an IR laser probe. The correlation in the intensity of the sideband spectra of the 4d inner-shell photoelectrons and in the time delay of the two laser pulses yields an X-ray pulse width of 5.7 ps, in good agreement with the value obtained using an X-ray streak camera.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Wigner functions for noncommutative quantum mechanics: A group representation based construction

This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group G{sub NC}, which is the three fold central extension of the Abelian group of ℝ{sup 4}. These representations have been exhaustively studied in earlier papers. The group G{sub NC} is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Constructing a folding model for protein S6 guided by native fluctuations deduced from NMR structures

The diversity in a set of protein nuclear magnetic resonance (NMR) structures provides an estimate of native state fluctuations that can be used to refine and enrich structure-based protein models (SBMs). Dynamics are an essential part of a protein’s functional native state. The dynamics in the native state are controlled by the same funneled energy landscape that guides the entire folding process. SBMs apply the principle of minimal frustration, drawn from energy landscape theory, to construct a funneled folding landscape for a given protein using only information from the native structure. On an energy landscape smoothed by evolution towards minimal frustration, geometrical constraints, imposed by the native structure, control the folding mechanism and shape the native dynamics revealed by the model. Native-state fluctuations can alternatively be estimated directly from the diversity in the set of NMR structures for a protein. Based on this information, we identify a highly flexible loop in the ribosomal protein S6 and modify the contact map in a SBM to accommodate the inferred dynamics. By taking into account the probable native state dynamics, the experimental transition state is recovered in the model, and the correct order of folding events is restored. Our study highlights how the shared energy landscape connects folding and function by showing that a better description of the native basin improves the prediction of the folding mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗