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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Grain size and structure distortion characterization of α-MgAgSb thermoelectric material by powder diffraction

Nanostructuring, structure distortion and/or disorder are the main manipulation techniques to reduce the lattice thermal conductivity and improve the figure of merit of thermoelectric materials. A single-phase α-MgAgSb sample, MgAg 0.97 Sb 0.99 , with high thermoelectric performance in near room temperature region was synthesized through a high-energy ball milling with a hot-pressing method. In this work, we report the average grain size of 24-28 nm and the accurate structure distortion, which are characterized by high-resolution neutron diffraction and synchrotron X-ray diffraction with Rietveld refinement data analysis. Both the small grain size and the structure distortion have a contribution to the low lattice thermal conductivity in MgAg 0.97 Sb 0.99 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-Level Structural Damage Characterization Using Sparse Acoustic Sensor Networks and Knowledge Transferred Deep Learning

Standard structural health monitoring techniques face well-known difficulties for comprehensive defect diagnosis in real-world structures that have structural, material, or geometric complexity. This motivates the exploration of machine-learning-based structural health monitoring methods in complex structures. However, creating sufficient training data sets with various defects is an ongoing challenge for data-driven machine (deep) learning algorithms. The ability to transfer the knowledge of a trained neural network from one component to another or to other sections of the same component would drastically reduce the required training data set. Also, it would facilitate computationally inexpensive machine learning based inspection systems. In this work, a machine-learning-based multi-level damage characterization is demonstrated with the ability to transfer trained knowledge within the sparse sensor network. A novel network spatial assistance and an adaptive convolution technique are proposed for efficient knowledge transfer within the deep learning algorithm. Proposed structural health monitoring method is experimentally evaluated on an aluminum plate with artificially induced defects. It was observed that the method improves the performance of knowledge transferred damage characterization by 50% during localization and 24% during severity assessment. Further, experiments using time windows with and without multiple edge reflections are studied. Results reveal that multiply scattered waves contain rich and deterministic defect signatures that can be mined using deep learning neural networks, improving the accuracy of both identification and quantification. In the case of a fixed sensor network, using multiply scattered waves shows 100% prediction accuracy at all levels of damage characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advances in Multimodal Characterization of Structural Materials

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermally stable manganese(Ⅲ) peroxido complexes with hindered N3 tripodal ligands: Structures and their physicochemical properties

Mononuclear manganese(III) peroxido complexes are candidates for the reaction intermediates in manganese containing proteins, such as manganese superoxide dismutase (Mn-SOD) etc. In this study, manganese(III) peroxido complexes [Mn(O 2 )(L3)] and [Mn(O 2 )(L10)] ligated by anionic N3 type ligands with sterically hindered substituents, hydrotris(3-tertiary butyl-5-isopropyl-1-pyrazolyl)borate (L3 - ) and hydrotris(3-adamantyl-5-isopropyl-1-pyrazolyl)borate (L10 - ), respectively, were structurally characterized. These complexes are the first examples of structurally characterized five-coordinate manganese(III) peroxido complexes. Their characteristic ν(O—O) and ν(Mn—O) stretchings were determined by using H 2 18 O 2 for the first time. Theoretical calculations were performed to obtain further insight into their structural parameters. The decomposed products were obtained as [{Mn III (μ-O)(L3)} 2 Mn IV ] and [Mn III (OH){L10(O)}] from [Mn(O 2 )(L3)] and [Mn(O 2 )(L10)], respectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO 3 ) 3 dissolved in acetonitrile with a terpyridine ligand (terpyNO 2 ), and Nd(NO 3 ) 3 dissolved in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO 3 ) 3 (terpyNO 2 ) and Nd(NO 3 )(acetonitrile) 3 , with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Transport of metformin metabolites by guanidinium exporters of the small multidrug resistance family

Proteins from the small multidrug resistance (SMR) family are frequently associated with horizontally transferred multidrug resistance gene arrays found in bacteria from wastewater and the human-adjacent biosphere. Recent studies suggest that a subset of SMR transporters might participate in the metabolism of the common pharmaceutical metformin by bacterial consortia. Here, we show that both genomic and plasmid-associated transporters of the SMRGdx functional subtype export byproducts of microbial metformin metabolism, with particularly high export efficiency for guanylurea. We use solid-supported membrane electrophysiology to evaluate the transport kinetics for guanylurea and native substrate guanidinium by four representative SMRGdx homologs. Using an internal reference to normalize independent electrophysiology experiments, we show that transport rates are comparable for genomic and plasmid-associated SMRGdx homologs, and using a proteoliposome-based transport assay, we show that 2 proton:1 substrate transport stoichiometry is maintained. Additional characterization of guanidinium and guanylurea export properties focuses on the structurally characterized homolog, Gdx-Clo, for which we examined the pH dependence and thermodynamics of substrate binding and solved an x-ray crystal structure with guanylurea bound. Together, these experiments contribute in two main ways. By providing the first detailed kinetic examination of the structurally characterized SMRGdx homolog Gdx-Clo, they provide a functional framework that will inform future mechanistic studies of this model transport protein. Second, this study casts light on a potential role for SMRGdx transporters in microbial handling of metformin and its microbial metabolic byproducts, providing insight into how native transport physiologies are co-opted to contend with new selective pressures.

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

Structure, electronic and magnetic characterization, and calculated electronic structures of two oxyhalide hexagonal perovskites

Herein we report the crystal structures, initial magnetic and charge transport characterization, and calculated electronic structures of the hexagonal oxyhalide perovskites, Ba 7 Ru 4 O 15 Cl 2 and Ba 7 Ru 4 O 15 Br 2 . The experimental information is obtained through the study of single crystals. Face-sharing Ru O 6 octahedra form Ru 2 O 9 dimers in a layered triangular geometry in these materials; minor amounts of off-magnetic-site structural disorder are present in our crystals. Both are magnetically isotropic, with 2.5 μB/mol-Ru, Curie-Weiss theta –185 K, and 2.9 μB/mol-Ru, Curie-Weiss theta –168 K, respectively. Broad features in the magnetic susceptibility and heat capacity associated with magnetic ordering (at 35 and 37 K, respectively) are observed. The charge transport band gaps are 0.03 eV for the oxychloride and 0.006 eV for the oxybromide. There is no gap at the Fermi level for either of these compounds in density-functional theory electronic structure calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sputter-Deposited Mo Thin Films: Multimodal Characterization of Structure, Surface Morphology, Density, Residual Stress, Electrical Resistivity, and Mechanical Response

Multimodal datasets of materials are rich sources of information which can be leveraged for expedited discovery of process–structure–property relationships and for designing materials with targeted structures and/or properties. For this data descriptor article, we provide a multimodal dataset of magnetron sputter-deposited molybdenum (Mo) thin films, which are used in a variety of industries including high temperature coatings, photovoltaics, and microelectronics. In this dataset we explored a process space consisting of 27 unique combinations of sputter power and Ar deposition pressure. Here, the phase, structure, surface morphology, and composition of the Mo thin films were characterized by x-ray diffraction, scanning electron microscopy, atomic force microscopy, and Rutherford backscattering spectrometry. Physical properties—namely, thickness, film stress and sheet resistance—were also measured to provide additional film characteristics and behaviors. Additionally, nanoindentation was utilized to obtain mechanical load-displacement data. The entire dataset consists of 2072 measurements including scalar values (e.g., film stress values), 2D linescans (e.g., x-ray diffractograms), and 3D imagery (e.g., atomic force microscopy images). An additional 1889 quantities, including film hardness, modulus, electrical resistivity, density, and surface roughness, were derived from the experimental datasets using traditional methods. Minimal analysis and discussion of the results are provided in this data descriptor article to limit the authors’ preconceived interpretations of the data. Overall, the data modalities are consistent with previous reports of refractory metal thin films, ensuring that a high-quality dataset was generated. The entirety of this data is committed to a public repository in the Materials Data Facility.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of Water Extraction on Malonamide Aggregation: A Molecular Dynamics and Graph Theoretic Approach

Solution structure in liquid-liquid extraction affects the efficacy of separation; however, even for simplified organic phases, structural characterization and attribution of aggregation to intermolecular interactions are fundamental challenges. We investigate water uptake into organic phases for two malonamides commonly applied to actinide and lanthanide separations. Extracted water induces reorganization of the amphiphilic extractant molecules, although we find this rearrangement is not strongly manifested in small-angle X-ray scattering making it challenging to probe without methods such as atomistic simulation. Using a graph theoretic approach to define hydrogen bonded water/malonamide aggregates from molecular dynamics simulations, we find evidence of a characteristic aggregate size by water number that results from geometric accommodation of the surrounding malonamide molecules. Furthermore, this implies a degree of size selectivity inherent to these water-in-oil aggregates. Conversely, we find no evidence of a characteristic size of the aggregates with respect to their malonamide number. By defining a separate graphical representation of self-association of the amphiphilic malonamides, we quantify how water affects the local and nonlocal topology of the malonamide network, providing a basis for characterization of the structure and impact of polar solutes in increasingly complex organic phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Molecular Origins of Temperature-Dependent X-ray Absorption in YAG:Dy

The absorption and emission of X-rays in dysprosium-doped yttrium aluminum garnet (YAG:Dy) has produced unexpected thermographic behavior, which is investigated using a combination of finite temperature ab initio molecular dynamic simulations, structural characterization, and electronic structure calculations of X-ray characteristics. Calculated average peak X-ray absorption spectra (XAS) from simulations between 300 and 600 K result in peak intensity loss due to thermalization effects, matching experimentally measured behavior of YAG:Dy. Here, investigation of atomic snapshots indicates structural factors that correlated with the X-ray behavior, with the first Y–O coordination sphere identified as the primary structural feature unique to high XAS intensity as calculated by radial and pair distribution functions.

Ab initio molecular dynamics↗
DOE OSTI2021

Effects of Al:Si and (Al+Na):Si Ratios on the Properties of the International Simple Glass, Part II: Structure

High-alumina containing high-level waste (HLW) will be vitrified at the Waste Treatment Plant at the Hanford Site. The resulting glasses, high in alumina, will have distinct composition-structure-property (C-S-P) relationships compared to previously studied HLW glasses. These C-S-P relationships determine the processability and product durability of glasses and therefore must be understood. The main purpose of this study is to understand the detailed structural changes caused by Al:Si and (Al+Na):Si substitutions in a simplified nuclear waste model glass (ISG, International Simple Glass) by combining experimental structural characterizations and molecular dynamics (MD) simulations. The structures of these two series of glasses were characterized by neutron total scattering and 27Al, 23Na, 29Si, and 11B solid-state nuclear magnetic resonance (NMR) spectroscopy. Additionally, MD simulations were used to generate atomistic structural models of the borosilicate glasses and simulation results were validated by the experimental structural data. Short-range (e.g., bond distance, coordination number, etc.) and medium-range (e.g., oxygen speciation, network connectivity, polyhedral linkages) structural features of the borosilicate glasses were systematically investigated as a function of the degree of substitution. The results show that bond distance and coordination number of the cation-oxygen pairs are relatively insensitive to Al:Si and (Al+Na):Si substitutions with the exception of the B-O pair. Additionally, the Al:Si substitution results in an increase of tri-bridging oxygen species, while (Al+Na):Si substitution creates non-bridging oxygen species. Charge compensator preferences were found for Si-[NBO] (Na+), [3]B-[NBO] (Na+), [4]B (mostly Ca2+), [4]Al (nearly equally split Na+ and Ca2+), and [6]Zr (mostly Ca2+). The network former-BO-network former linkages preferences were also tabulated; Si-O-Al and Al-O-Al were preferred at the expense of lower Si-O-[3]B and [3]B-O-[3]B linkages. These results provide insights on the structural origins of property changes such as glass transition temperature caused by the substitutions, providing a basis for future improvements of theoretical and computer simulation models.

Lu, Xiaonan↗
DOE OSTI2022

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rational design of a uranyl metal-organic framework for the capture and colorimetric detection of organic dyes

A new uranyl containing metal-organic framework, RPL-1: [(UO2)2(C28H18O8)] · H2O (RPL for Radiochemical Processing Laboratory), was prepared, structurally characterized, and the solid-state photoluminescence properties explored. The single crystal X-ray diffraction data reveal the structure of RPL-1 consists of two crystallographically unique three dimensional, interpenetrating nets with a 4,3-connected tbo topology. Each net contains large pores with an average width of 22.8 Å and is formed from monomeric, hexagonal bipyramidal uranyl nodes that are linked via 1,2,4,5-tetrakis(4-carboxyphenyl)benzene (TCPB) linkers. The thermal and photophysical properties of RPL-1 were investigated using thermogravimetric analysis and absorbance, fluorescence, and lifetime spectroscopies. The material displays excellent thermal stability and temperature dependent uranyl and TCBP luminescence. The framework is stable in aqueous media and due to the large void space (constituting 76% of the unit cell by volume) can sequester organic dyes, the uptake of which induces a visible change to the color of the material.

Surbella, Robert G.↗
DOE OSTI2021

Functional Characterization and Structural Insights Into Stereoselectivity of Pulegone Reductase in Menthol Biosynthesis

Monoterpenoids are the main components of plant essential oils and the active components of some traditional Chinese medicinal herbs like Mentha haplocalyx Briq ., Nepeta tenuifolia Briq ., Perilla frutescens (L.) Britt and Pogostemin cablin (Blanco) Benth. Pulegone reductase is the key enzyme in the biosynthesis of menthol and is required for the stereoselective reduction of the Δ 2,8 double bond of pulegone to produce the major intermediate menthone, thus determining the stereochemistry of menthol. However, the structural basis and mechanism underlying the stereoselectivity of pulegone reductase remain poorly understood. In this study, we characterized a novel (-)-pulegone reductase from Nepeta tenuifolia ( Nt PR), which can catalyze (-)-pulegone to (+)-menthone and (-)-isomenthone through our RNA-seq, bioinformatic analysis in combination with in vitro enzyme activity assay, and determined the structure of (+)-pulegone reductase from ( Mp PR) by using X-ray crystallography, molecular modeling and docking, site-directed mutagenesis, molecular dynamics simulations, and biochemical analysis. We identified and validated the critical residues in the crystal structure of Mp PR involved in the binding of the substrate pulegone. We also further identified that residues Leu56, Val282, and Val284 determine the stereoselectivity of the substrate pulegone, and mainly contributes to the product stereoselectivity. This work not only provides a starting point for the understanding of stereoselectivity of pulegone reductases, but also offers a basis for the engineering of menthone/menthol biosynthetic enzymes to achieve high-titer, industrial-scale production of enantiomerically pure products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Characterization and structure of the human lysine-2-oxoglutarate reductase domain, a novel therapeutic target for treatment of glutaric aciduria type 1

In humans, a single enzyme 2-aminoadipic semialdehyde synthase (AASS) catalyses the initial two critical reactions in the lysine degradation pathway. This enzyme evolved to be a bifunctional enzyme with both lysine-2-oxoglutarate reductase (LOR) and saccharopine dehydrogenase domains (SDH). Moreover, AASS is a unique drug target for inborn errors of metabolism such as glutaric aciduria type 1 that arise from deficiencies downstream in the lysine degradation pathway. While work has been done to elucidate the SDH domain structurally and to develop inhibitors, neither has been done for the LOR domain. Here, we purify and characterize LOR and show that it is activated by alkylation of cysteine 414 by N-ethylmaleimide. We also provide evidence that AASS is rate-limiting upon high lysine exposure of mice. Finally, we present the crystal structure of the human LOR domain. Our combined work should enable future efforts to identify inhibitors of this novel drug target.

59 BASIC BIOLOGICAL SCIENCES↗