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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

On the contribution of Pair Distribution Function (PDF) to the characterization of nanocrystalline MOFs: The case of M-MOF-74

Nanoporous Metal-Organic Frameworks (MOFs) have a great potential in so many industrial applications including heterogeneous catalysis and gas storage/capture/separation. MOF-74 is one of the most interesting MOFs in an academic context, as it contains open metal sites, possesses high versatility in metal nature, and can be prepared with so small crystal size. As a consequence, the catalytic activity of these nanocrystalline materials is superior to that given by their conventional counterparts. However, their characterization by conventional X-ray diffraction (XRD) is insufficient. Here, we present a joint study of XRD and Pair Distribution Function (PDF) -both acquired under synchrotron radiation- of a series of nanocrystalline M-MOF-74 materials (M = Mg, Co, Ni, Cu or Zn) prepared at room temperature. Whereas the XRD continues being lacking for an adequate structural characterization, PDF provides key structural information at medium and short range and, therefore, is ideal for studying such nano-domains. It was confirmed that these materials are exclusively composed by MOF-74 phase and that their poor ability to diffract is due solely to their eminent nanocrystallinity, which resulted to be even more pronounced than it has been previously estimated. Beyond Scherrer-like approaches, PDF can give direct information about the range of crystal size in nanocrystalline materials. Moreover, the technique is also able to detect slight structural deviations in short-range environments, just like it is made clear in the case of Cu-MOF-74 compared with the rest of M-MOF-74 materials, which possesses a marked Jahn-Teller effect in the octahedral coordination of Cu.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cryogenic “Iodide-Tagging” Photoelectron Spectroscopy: A Sensitive Probe for Specific Binding Sites of Amino Acids

This work showcases cryogenic and temperature-dependent “iodide-tagging” photoelectron spectroscopy to probe specific binding sites of amino acids using the glycine-iodide complex (Gly?I-) as a case study. Multiple Gly?I- isomers were generated from ambient electrospray ionization and kinetically isolated in a cryogenic ion trap. These structures were characterized with temperature-dependent “iodide-tagging” negative ion photoelectron spectroscopy (NIPES) where iodide was used as the “messenger” to interpret electronic energetics and structural information of various Gly?I- isomers. Accompanied by theoretical computations and Franck-Condon simulations, a total of five cluster structures have been identified along with their various binding motifs. This work demonstrates that “iodide-tagging” NIPES is a powerful general means for probing specific binding interactions in biological molecules of interest.

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

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Determination of the dehydration pathway in a flexible metal–organic framework by dynamic in situ x-ray diffraction

Understanding guest exchange processes in metal–organic frameworks is an important step toward the rational design of functional materials with tailor-made properties. The dehydration of the flexible metal-organic framework [Co(AIP)(bpy)0.5(H2O)]•2H2O was studied by novel in situ dynamic x-ray diffraction techniques. The complex mechanism of dehydration, along with the as-yet unreported metastable structures, was determined. The structural information obtained by the application of these techniques helps to elucidate the important guest–host interactions involved in shaping the structural landscape of the framework lattice and to highlight the importance of utilizing this technique in the characterization of functional framework materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1978

Seismic structure of the lunar mantle - An overview

The direct P and S wave arrival times from natural lunar seismic events are the most complete and reliable data set for determining the structure of the lunar mantle. A total of 40 events provide sufficiently well-observed arrivals to permit the extraction of structural information. Using this arrival time data set, the average velocities in a two-layered mantle with an assumed crustal structure (from Toksoz et al., 1974) have been obtained. Reflected phases arriving after direct S are then used to calculate the depth of the boundary between the two mantle layers, and to demonstrate that it is probably a complex transition zone approximately 80 km thick between 400 and 480 km depth. To determine velocity gradients in the upper mantle it is required that the model explain the pronounced decrease in shear wave amplitudes and accompanying delay in shear wave arrival times beyond a distance of about 90 deg. The final model is well-constrained.

Goins, N. R.↗
DOE OSTI2020

Operating Procedure Extender For Novel Systems

Operating procedures that are used in nuclear power plants are primarily paper. These paper documents are functional for normal operations, but the process has remained relatively unchanged for thirty years. This neglects the digital technology advancements that have been made in that time. There are objectively more efficient ways to present a procedure to an operator using a digital interface. These digital interfaces require structured information to be able to function. This tool takes the procedure that has been written and converts it into the structured from required by the presentation system. This is accomplished through a reliable four phase compilation algorithm.

Lehmer, Jacob P↗
DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗
DOE OSTI2022

Characterization of biological materials with soft X-ray scattering

The complex structure of biological assemblies is crucial for function yet challenging to discern given the chemical similarities between constituent components. Hard X-ray techniques, for example, rely on small density differences between domains that lead to modest scattering intensities. Resonant soft X-ray scattering (RSoXS) uses X-rays below 2 keV to access absorption edges of low-Z elements. In this way, RSoXS can enhance scattering contrast between domains of different chemical compositions or bonding motifs, thus providing structural information about specific chemical motifs. RSoXS is emerging as a technique applicable for biological systems, having been used to characterize protein structure in solution and polysaccharide organization in plant cell walls. Sample environment instrumentation, however, is challenging in the current state of the art, particularly with liquid samples. Here, this chapter contains a brief introduction to RSoXS and current beamline capabilities, and provides methods to prepare, store, and mount biological samples for RSoXS characterization. Furthermore, key details during RSoXS and X-ray absorption data acquisition are highlighted and some future opportunities in RSoXS instrumentation for biological systems are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

ALS mutations disrupt self-association between the ubiquilin STI1 hydrophobic groove and internal placeholder sequences

Ubiquilins are molecular chaperones that play multifaceted roles in proteostasis, with point mutations in UBQLN2 leading to altered phase-separation properties and amyotrophic lateral sclerosis (ALS). Our mechanistic understanding of this essential process has been hindered by a lack of structural information on the STI1 domain, which is essential for ubiquilin chaperone activity and phase separation. Here, we present the first crystal structure of a ubiquilin-family STI1 domain bound to a transmembrane domain (TMD), and show that ALS mutations disrupt the STI1-TMD interaction. We further demonstrate that ubiquilins contain multiple conserved internal sequences that bind to the STI1 domain, including the PXX-repeat region that is a hotspot for ALS mutations. We propose that these placeholder sequences prevent solvent exposure of the STI1 hydrophobic groove and contribute to the multivalency that drives ubiquilin phase-separation. Together, this work provides a new paradigm for understanding how STI1 domains modulate ubiquilin chaperone activity and phase separation, and offers insights into the molecular basis of ALS pathogenesis.

Onwunma, Joan [Univ. of Toledo, OH (United States)↗
NASA NTRS2007

Quantifiable Assessment of SWNT Dispersion in Polymer Composites

NASA LaRC has established a new protocol for visualizing the nanomaterials in structural polymer matrix resins. Using this new technique and reconstructing the 3D distribution of the nanomaterials allows us to compare this distribution against a theoretically perfect distribution. Additional tertiary structural information can now be obtained and quantified with the electron tomography studies. These tools will be necessary to establish the structural-functional relationships between the nano and the bulk. This will also help define the critical length scales needed for functional properties. Field ready tool development and calibration can begin by using these same samples and comparing the response. i.e. gold standards of good and bad dispersion.

Park, Cheol↗
DOE OSTI2022

Visualizing Light-Induced Microstrain and Phase Transition in Lead-Free Perovskites Using Time-Resolved X-Ray Diffraction

Metal halide perovskites have emerged as promising materials for optoelectronic applications in the last decade. A large amount of effort has been made to investigate the interplay between the crystalline lattice and photoexcited charge carriers as it is vital to their optoelectronic performance. Among them, ultrafast laser spectroscopy has been intensively utilized to explore the charge carrier dynamics of perovskites, from which the local structural information can only be extracted indirectly. Here, we have applied a time-resolved X-ray diffraction technique to investigate the structural dynamics of prototypical two-dimensional lead-free halide perovskite Cs 3 Bi 2 Br 9 nanoparticles across temporal scales from 80 ps to microseconds. We observed a quick recoverable (a few ns) photoinduced microstrain up to 0.15% and a long existing lattice expansion (~a few hundred nanoseconds) at mild laser fluence. Once the laser flux exceeds 1.4 mJ/cm 2 , the microstrain saturates and the crystalline phase partially transfers into a disordered phase. This photoinduced transient structural change can recover within the nanosecond time scale. Furthermore, these results indicate that photoexcitation of charge carriers couples with lattice distortion, which fundamentally affects the dielectric environment and charge carrier transport.

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

Electrosome assembly: Structural insights from high voltage-activated calcium channel (CaV)–chaperone interactions

Ion channels are multicomponent complexes (termed here as“electrosomes”) that conduct the bioelectrical signals required for life. It has been appreciated for decades that assembly is critical for proper channel function, but knowledge of the factors that undergird this important process has been lacking. Although there are now exemplar structures of representatives of most major ion channel classes, there has been no direct structural information to inform how these complicated, multipart complexes are put together or whether they interact with chaperone proteins that aid in their assembly. Recent structural characterization of a complex of the endoplasmic membrane protein complex (EMC) chaperone and a voltage-gated calcium channel (CaV) assembly intermediate comprising the pore-forming CaVα1 and cytoplasmic CaVβ subunits offers the first structural view into the assembly of a member of the largest ion channel class, the voltagegated ion channel (VGIC) superfamily. The structure shows how the EMC remodels the CaVα1/CaVβ complex through a set of rigid body movements for handoff to the extracellular CaVα2δ subunit to complete channel assembly in a process that involves intersubunit coordination of a divalent cation and ordering of CaVα1 elements. These findings set a new framework for deciphering the structural underpinnings of ion channel biogenesis that has implications for understanding channel function, how drugs and disease mutations act, and for investigating how other membrane proteins may engage the ubiquitous EMC chaperone.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Improving Building Footprint Extraction Using NAIP and 3DEP Lidar Derived Features with Deep Learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Liu, Jung Kuan [United States Geological Survey (U↗
NASA NTRS1993

Isotopic composition and concentration of sulfur in carbonaceous chondrites

New sulfur isotopic ratio measurements are reported for seven carbonaceous chondrites. Newly developed procedures permit measurement of delta S-33, delta S-34, and delta S-36 at precisions significantly greater than previously reported. A search for S-36 nucleosynthetic anomalies coproduced with anomalies in, for example, Ti-50 and Ca-48 was negative. The high endemic sulfur concentration probably dilutes any S-36 anomaly, and separation of individual sulfur phases may be needed to identify S-36 carrier phases. Large internal isotopic variations are observed, deriving from parent body and possibly nebular processes. Chondrule separates from Allende demonstrate isotopic compositions which vary as a function of diameter. High-temperature gas-solid exchange and a two-component mixing model may account for the observations. High-resolution isotopic data and structural information are reported for organic sulfur compounds separated by chemical extractions. The insoluble organics appear to be of either aliphatic or alicyclic structure and are dominant phases.

Gao, Xia↗
NASA NTRS1970

Computerized management information systems and organizational structures

The computerized management of information systems and organizational structures is discussed. The subjects presented are: (1) critical factors favoring centralization and decentralization of organizations, (2) classification of organizations by relative structure, (3) attempts to measure change in organization structure, and (4) impact of information technology developments on organizational structure changes.

Zannetos, Z. S.↗
DOE OSTI2023

Structure of VanS from vancomycin-resistant enterococci: A sensor kinase with weak ATP binding

The VanRS two-component system regulates the resistance phenotype of vancomycin-resistant enterococci. VanS is a sensor histidine kinase that responds to the presence of vancomycin by autophosphorylating and subsequently transferring the phosphoryl group to the response regulator, VanR. The phosphotransfer activates VanR as a transcription factor, which initiates the expression of resistance genes. Structural information about VanS proteins has remained elusive, hindering the molecular-level understanding of their function. Here, we present X-ray crystal structures for the catalytic and ATP-binding (CA) domains of two VanS proteins, derived from vancomycin-resistant enterococci types A and C. Both proteins adopt the canonical Bergerat fold that has been observed for CA domains of other prokaryotic histidine kinases. We attempted to determine structures for the nucleotide-bound forms of both proteins; however, despite repeated efforts, these forms could not be crystallized, prompting us to measure the proteins' binding affinities for ATP. Unexpectedly, both CA domains displayed low affinities for the nucleotide, with K D values in the low millimolar range. Since these K D values are comparable to intracellular ATP concentrations, this weak substrate binding could reflect a way of regulating expression of the resistance phenotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structure of the Extracellular Region of the Bacterial Type VIIb Secretion System Subunit EsaA

Gram-positive bacteria use type VII secretion systems (T7SSs) to export effector proteins that manipulate the physiology of nearby prokaryotic and eukaryotic cells. Several mycobacterial T7SSs have established roles in virulence. By contrast, the genetically distinct T7SSb pathway found in Firmicutes bacteria more often functions to mediate bacterial competition. A lack of structural information on the T7SSb has limited the understanding of effector export by this protein secretion apparatus. Here, we present the 2.4 angstrom crystal structure of the extracellular region of the T7SSb subunit EsaA from Streptococcus gallolyticus. Our structure reveals that homodimeric EsaA is an elongated, arrow-shaped protein with a surface-accessible "tip", which in some species of bacteria serves as a receptor for lytic bacteriophages. Because it is the only T7SSb subunit large enough to traverse the peptidoglycan layer of Firmicutes, we propose that EsaA plays a critical role in transporting effectors across the entirety of the Gram-positive cell envelope.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling

Abstract Metabolite identification in non-targeted mass spectrometry-based metabolomics remains a major challenge due to limited spectral library coverage and difficulties in predicting metabolite fragmentation patterns. Here, we introduce Multiplexed Chemical Metabolomics (MCheM), which employs orthogonal post-column derivatization reactions integrated into a unified mass spectrometry data framework. MCheM generates orthogonal structural information that substantially improves metabolite annotation through in silico spectrum matching and open-modification searches, offering a powerful new toolbox for the structure elucidation of unknown metabolites at scale.

Science & Technology - Other Topics↗