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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthetic β-sheets mimicking fibrillar and oligomeric structures for evaluation of spectral X-ray scattering technique for biomarker quantification

Archetypical cross-β spines sharpen the boundary between functional and pathological proteins including β-amyloid, tau, α-synuclein and transthyretin are linked to many debilitating human neurodegenerative and non-neurodegenerative amyloidoses. An increased focus on development of pathogenic β-sheet specific fluid and imaging structural biomarkers and conformation-specific monoclonal antibodies in targeted therapies has been recently observed. Identification and quantification of pathogenic oligomers remain challenging for existing neuroimaging modalities. We propose two artificial β-sheets which can mimic the nanoscopic structural characteristics of pathogenic oligomers and fibrils for evaluating the performance of a label free, X-ray based biomarker detection and quantification technique. Highly similar structure with elliptical cross-section and parallel cross-β motif is observed among recombinant α-synuclein fibril, Aβ-42 fibril and artificial β-sheet fibrils. We then use these β-sheet models to assess the performance of spectral small angle X-ray scattering (sSAXS) technique for detecting β-sheet structures. sSAXS showed quantitatively accurate detection of antiparallel, cross-β artificial oligomers from a tissue mimicking environment and significant distinction between different oligomer packing densities such as diffuse and dense packings. The proposed synthetic β-sheet models mimicked the nanoscopic structural characteristics of β-sheets of fibrillar and oligomeric states of Aβ and α-synuclein based on the ATR-FTIR and SAXS data. The tunability of β-sheet proportions and shapes of structural motifs, and the low-cost of these β-sheet models can become useful test materials for evaluating β-sheet or amyloid specific biomarkers in a wide range of neurological diseases. By using the proposed synthetic β-sheet models, our study indicates that the sSAXS has potential to evaluate different stages of β-sheet-enriched structures including oligomers of pathogenic proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A cross-sectional aeroelastic analysis and structural optimization tool for slender composite structures

A fully open-source available framework for the parametric cross-sectional analysis and design optimization of slender composite structures, such as helicopter or wind turbine blades, is presented. The framework—Structural Optimization and Aeroelastic Analysis (SONATA)—incorporates two structural solvers, the commercial tool VABS, and the novel open-source code ANBA4. SONATA also parameterizes the design inputs, postprocesses and visualizes the results, and generates the structural inputs to a variety of aeroelastic analysis tools. It is linked to the optimization library OpenMDAO. This work presents the methodology and explains the fundamental approaches of SONATA. Structural characteristics were successfully verified for both VABS and ANBA4 using box beam examples from literature, thereby verifying the parametric approach to generating the topology and mesh in a cross section as well as the solver integration. The framework was furthermore exercised by analyzing and evaluating a fully resolved highly flexible wind turbine blade. Computed structural characteristics correlated between VABS and ANBA4, including off-diagonal terms. Stresses, strains, and deformations were recovered from loads derived through coupling with aeroelastic analysis. The framework, therefore, proves effective in accurately analyzing and optimizing slender composite structures on a high-fidelity level that is close to a three-dimensional finite element model.

42 ENGINEERING↗
DOE OSTI2021

Machine learning-enabled prediction of chemical durability of A 2 B 2 O 7 pyrochlore and fluorite

Pyrochlore-structure type and its derivative in a general formula A 2 B 2 O 7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste form materials capable of immobilizing actinides and fission products. It is essential to understand these materials’ chemical durability and element release of radionuclides in order to evaluate their performance in near-field environment. However, it is a formidable grand technological challenge to experimentally perform durability testing across hundreds of thousands of possibilities resulting from their extreme compositional complexities due to cation substitutions at both A and B-sites. In this work, we demonstrate a machine learning approach to determine the key materials parameters and structural characteristics governing the leaching behaviors from a small set of selected compositions as model systems, enabling a science-based prediction of their chemical durability that can be extended to a wide range of chemical compositions. The combination of four key structural characteristics and materials parameters, including ionic radius size difference , ionic potential difference , electronegativity difference , and lattice parameter , creates features an optimized prediction of the chemical durability. Two machine learning models, linear regression and Kernel ridge regression models, are trained on the randomly-split training dataset derived from the experimentally-determined elemental release rates, and subsequently tested on the testing dataset. The predicted leaching rates from both machine learning models show an excellent agreement with the experimental data, demonstrating the feasibility of rapidly evaluating the material properties of new compositions. These results highlight the immense potential of synergizing informatics through machine learning-based models and well-controlled experiments of selected model systems to accelerate materials design and discovery with optimized compositions and performance of promising materials for effective nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Resolving local structural motifs across the phase evolution of zinc titanates with computational x-ray absorption spectroscopy

Resolving the local structure motifs that characterize phase evolution as a function of composition is a key challenge in structure characterization of complex materials. Here, in this study, we combine first-principles simulations and x-ray absorption near-edge structures (XANES) analysis to gain insights into the structure evolution revealed by measurements across a combinatorial zinc titanate thin film, which was grown with smoothly varying composition over a wide range of the Ti:Zn ratio. Specifically, we propose a cluster blind-signal-separation (cBSS) method for XANES spectral analysis based on a library of the structures and spectra of representative local motifs. In addition to motifs from zinc titanate crystals, two types of Ti-defect models constructed in this study are key to the understanding of the structure characteristics in the Zn-rich region. The cBSS method makes use of both spectral clustering of the simulated site-XANES spectra library and the BSS procedure to construct high-fidelity spectral basis functions from an experimental spectral sequence. The method provides a rigorous measure of the spectral sensitivity and basis completeness. The results of the XANES analysis are corroborated with other experimental modalities, including x-ray diffraction and spectroscopic ellipsometry, to validate the cBSS method. The calculated motif weights resulting from fitting the XANES spectra with the cBSS basis probe the atomic structure characteristics of both crystalline and amorphous phases as a function of the Ti/Zn composition. The insights of the local structure motif evolution are pivotal to the understanding of the nonmonotonic trend in the optical gap, which may lead to potential applications through tuning the optical properties of zinc titanate. The workflow of the XANES spectral analysis developed in this work can be generalized to construct the structure-property relationship in a broad material space.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterizing leaf-scale fluorescence with spectral invariants

Sun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R 2 ) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm -2 µm -1 sr -1 , respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. Further, the leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory

Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaqvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient ($β_p$), lidar scattering ratio (SR), and aerosol particulate depolarization ratio ($δ_p$) profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structural Complexity and Tuned Thermoelectric Properties of a Polymorph of the Zintl Phase Ca 2 CdSb 2 with a Non-centrosymmetric Monoclinic Structure

The Zintl phase Ca 2 CdSb 2 was found to be dimorphic. Besides the orthorhombic Ca 2 CdSb 2 (-o), here we report on the synthesis, the structural characterization, and the thermoelectric transport properties of its monoclinic form, Ca 2 CdSb 2 (-m), and its Lu-doped variant Ca 2–x Lu x CdSb 2 (x ≈ 0.02). The monoclinic structure exhibits complex structural characteristics and constitutes a new structure type with the non-centrosymmetric space group Cm (Z = 30). The electrical resistivity ρ(T) measured on single crystals of both phases portrays a transition from a semiconductor to a degenerate p-type semiconductor upon doping with Lu and with an attendant change in the Hall carrier concentration nH from 7.15 × 10 18 to 2.30 × 10 19 cm –3 at 300 K. The Seebeck coefficient S(T) of both phases are comparable and indicate a hole-dominated carrier transport mechanism with magnitudes of 133 and 116 μV/K at 600 K for Ca 2 CdSb 2 (-m) and Ca 2–x Lu x CdSb 2 , respectively. The convoluted atomic bonding with an attendant large unit cell volume of ~4365 Å 3 drives a putative low thermal conductivity in these materials resulting in a power factor PF of 1.63 μW/cm K 2 and an estimated thermoelectric figure of merit zT of ~0.5 for Ca 2–x Lu x CdSb 2 at 600 K. Furthermore, differential scanning calorimetry results reveal the stability of these phases up to about 960 K, making them candidates for moderate temperature thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Harnessing structural stochasticity in the computational discovery and design of microstructures

This paper presents a deep generative model-based design methodology for tailoring the structural stochasticity of microstructures. Although numerous methods have been established for designing deterministic (periodic) or stochastic microstructures, a systematic design approach that allows the unified treatment of both deterministic and stochastic microstructure design domains has yet to be created. The proposed methodology resolves this issue by learning a unified feature space that embodies diverse structural patterns with continuously varying stochasticity levels. A highly diverse microstructure database is established to incorporate various types of deterministic and stochastic microstructure patterns. A property-aware deep generative model is proposed to learn a unified feature space of the structural characteristics, as well as the relationship between structure features and properties of interest. Autoencoder (AE), Variational Autoencoder (VAE), and Adversarial Autoencoder (AAE) are compared to understand their relative merits in the property-aware learning of the unified feature space. Microstructural designs with tailorable stochasticity and properties are obtained by searching the unified feature space. Multiple design cases are presented to demonstrate the capability of designing microstructures for structural stochasticity and properties. Furthermore, the proposed method is employed to create stochastically graded structures, which manipulate the mechanical behaviors by varying the local stochasticity of the structure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Heavy boron doping in superconducting carbon materials

Here we examine physical properties of heavily boron-doped sp 3 -hybridized carbon allotropes: cubic diamond, hexagonal diamond, and body centered tetragonal C 4 . The structural similarity between cubic diamond and hexagonal diamond leads to similar responses to substitutional boron doping. On the other hand, body centered tetragonal C 4 exhibits distinct structural and electronic properties because of its characteristic structure. Our study also shows that the superconducting transition temperatures up to 60 K are possible in heavily doped carbon materials despite their various atomistic structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing

The field of metal–organic framework (MOF)-based biomimetic catalysts has achieved great progress but is still in its infancy. The systematic investigation of the tailored construction of MOF-based biomimetic catalysts is required for further development. Herein, two iron-based MOFs, namely, [(Fe 3 O) 2 (H 2 O) 4 (HCOO)(L) 2 ] n (HUST-5: H 6 L = hexakis(4-formylphenoxy) cyclotriphosphazene; HUST = Huazhong University of Science and Technology) and [(Fe 3 O)(H 2 O) 3 (L)] n (HUST-7) have been fabricated through the assembly of different iron clusters and hexa-carboxylate ligand under the control of the added acid species. The two MOFs exhibit distinct secondary building units (SBUs) and topological structures, which could be used as biomimetic catalysts for the systematic comparisons of structural characteristics and the catalytic activity. Both MOFs possess catalytic activity similar to that of natural peroxidases towards the catalysis of the oxidation of a variety of substrates. Significantly, HUST-5 and HUST-7 can effectively catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H 2 O 2 accompanied by significant colorimetric biosensing. With same compositions, different catalytic performances were obtained due to differences in the porous structures and characteristics of SBUs in two Fe-MOFs, which was also validated by theoretical calculation results. Furthermore, the phenomenon of colorimetric biosensing could be significantly suppressed by the addition of ascorbic acid (AA) during the oxidation process of TMB. It was observed from these findings that a facile colorimetric biosensing platform for detecting H 2 O 2 and ascorbic acid has been successfully explored. Therefore, this work provides another unique perspective for the tailor-made preparation of stable MOF-based peroxidase mimics with excellent catalytic performance and colorimetric biosensing.

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

Single-Step Direct Laser Writing of Multimetal Oxygen Evolution Catalysts from Liquid Precursors

We investigate a laser direct-write method to synthesize and deposit metastable, mixed transition metal oxides and evaluate their performance as oxygen evolution reaction catalysts. This laser processing method enabled the rapid synthesis of diverse heterogeneous alloy and oxide catalysts directly from cost-effective solution precursors, including catalysts with a high density of nanocrystalline metal alloy inclusions within an amorphous oxide matrix. The nanoscale heterogenous structures of the synthesized catalysts were consistent with reactive force-field Monte Carlo calculations. By evaluating the impact of varying transition metal oxide composition ratios, we created a stable Fe 0.63 Co 0.19 Ni 0.18 O x /C catalyst with a Tafel slope of 38.23 mV dec -1 and overpotential of 247 mV, a performance similar to that of IrO 2 . Synthesized Fe 0.63 Co 0.19 Ni 0.18 O x /C and Fe 0.14 Co 0.46 Ni 0.40 O x /C catalysts were experimentally compared in terms of catalytic performance and structural characteristics to determine that higher iron content and a less crystalline structure in the secondary matrix decreases the charge transfer resistance and thus is beneficial for electrocatalytic activity. Furthermore, this conclusion is supported by density-functional theory calculations showing distorted active sites in ternary metal catalysts are key for lowering overpotentials for the oxygen evolution reaction.

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

Convergent behavior of extended stalk regions from staphylococcal surface proteins with widely divergent sequence patterns

Staphylococcus epidermidis and Staphylococcus aureus are highly problematic bacteria in hospital settings. A major challenge is their ability to form biofilms on abiotic or biotic surfaces. Biofilms are well-organized, multicellular bacterial aggregates that resist antibiotic treatment and often lead to recurrent infections. Bacterial cell wall-anchored (CWA) proteins are important players in biofilm formation and infection. Many have putative stalk-like regions or regions of low complexity near the cell wall-anchoring motif. Recent work demonstrated the strong propensity of the stalk region of S. epidermidis accumulation-associated protein (Aap) to remain highly extended under solution conditions that typically induce compaction. This behavior is consistent with the expected function of a stalk-like region that is covalently attached to the cell wall peptidoglycan and projects the adhesive domains of Aap away from the cell surface. In this study, we evaluate whether the ability to resist compaction is a common theme among stalk regions from various staphylococcal CWA proteins. Circular dichroism spectroscopy was used to examine secondary structure changes as a function of temperature and cosolvents along with sedimentation velocity analytical ultracentrifugation, size-exclusion chromatography, and SAXS to characterize structural characteristics in solution. All stalk regions tested are intrinsically disordered, lacking secondary structure beyond random coil and polyproline type II helix, and they all sample highly extended conformations. Remarkably, the Ser-Asp dipeptide repeat region of SdrC exhibited nearly identical behavior in solution when compared to the Aap Pro/Gly-rich region, despite highly divergent sequence patterns, indicating conservation of function by various distinct staphylococcal CWA protein stalk regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Repetitive proteins that undergo large conformational changes evade structural prediction algorithms

Protein structure prediction algorithms, such as AlphaFold, have accelerated protein design and advanced the understanding of the relationship between amino acid sequence and protein structure. However, these algorithms are limited in their ability to predict the structures of conformationally dynamic, intrinsically disordered, and stimuli-responsive proteins. To evaluate sequence-to-structure predictions of such challenging proteins, we explored a class of conformationally dynamic, repeats-in-toxin (RTX) proteins. RTX proteins adopt intrinsically disordered conformations in the absence of calcium and undergo reversible folding into β-roll structures upon binding to calcium. RTX proteins are characterized by tandem repeats of the sequence GGXGXDXUX, in which X can be any amino acid and U is an aliphatic amino acid. We designed RTX sequence variants with global substitutions of nonconserved amino acids, tandem repeats of consensus sequences GGAGXDTLY, and tandem repeats of scrambled sequences GGAGXDTYL. AlphaFold2 and AlphaFold3 predicted that all of these RTX variants adopt β-roll structures, characteristic of wild-type RTX bound to calcium. However, modeling the predicted structures with molecular dynamics simulations and characterizing the protein variants with circular dichroism spectroscopy, small-angle x-ray scattering, and x-ray crystallography revealed that variants adopt diverse, sequence-dependent structures in the absence and presence of calcium. To better design proteins for applications in biotechnology and sustainability, it is critical to build predictive tools that consider intrinsically disordered protein states and validate these tools with multi-mode, multi-scale experimental data.

Chang, Marina P. [Stanford Univ., CA (United State↗
DOE OSTI2021

Analysis of plant ABCB organic acid transporters (Final Report)

Functional Analysis and Genetic Manipulation of Plant ABCB Organic Ion Transporters- The project explores how ABC transporters export hydrophobic aromatics, identifies structural characteristics that regulate lateral positioning, and uses nanodisc technology to create platforms for structural studies of ABC plasma membrane transport proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Characterization of MoS 2 films via simultaneous grazing incidence X-ray diffraction and grazing incidence X-ray fluorescence (GIXRD/GIXRF)

Physical vapor deposited (PVD) molybdenum disulfide (nominal composition MoS 2 ) is employed as a thin film solid lubricant for extreme environments where liquid lubricants are not viable. The tribological properties of MoS 2 are highly dependent on morphological attributes such as film thickness, orientation, crystallinity, film density, and stoichiometry. These structural characteristics are controlled by tuning the PVD process parameters, yet undesirable alterations in the structure often occur due to process variations between deposition runs. Nondestructive film diagnostics can enable improved yield and serve as a means of tuning a deposition process, thus enabling quality control and materials exploration. Grazing incidence X-ray diffraction (GIXRD) for MoS 2 film characterization provides valuable information about film density and grain orientation (texture). However, the determination of film stoichiometry can only be indirectly inferred via GIXRD. The combination of density and microstructure via GIXRD with chemical composition via grazing incidence X-ray fluorescence (GIXRF) enables the isolation and decoupling of film density, composition, and microstructure and their ultimate impact on film layer thickness, thereby improving coating thickness predictions via X-ray fluorescence. We have augmented an existing GIXRD instrument with an additional X-ray detector for the simultaneous measurement of energy-dispersive X-ray fluorescence spectra during the GIXRD analysis. This combined GIXRD/GIXRF analysis has proven synergetic for correlating chemical composition to the structural aspects of MoS 2 films provided by GIXRD. We present the usefulness of the combined diagnostic technique via exemplar MoS 2 film samples and provide a discussion regarding data extraction techniques of grazing angle series measurements.

MoS2↗
DOE OSTI2022

Structural transitions in the GTP cap visualized by cryo-electron microscopy of catalytically inactive microtubules

Microtubules (MTs) are nonequilibrium polymers that switch between states of growth and shrinkage. This property is critical for their function and is a consequence of GTP hydrolysis in the MT. The structure of the stable GTP part of the MT (the GTP cap) has previously been inferred from MTs polymerized with nonhydrolyzable GTP analogs. Here, we report high-resolution structures of MTs truly containing GTP, polymerized from mutated, hydrolysis-deficient tubulins. We find that GTP-MTs have an “expanded lattice” and a “closed seam,” structural characteristics possibly responsible for stabilizing the GTP cap. These results provide insight into the structural transitions at growing MT ends, furthering our understanding of the bistable nature of MTs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

In-situ observation of single-phase compositionally-complex oxide formation during high-pressure and high-temperature synthesis

Compositionally-complex oxides (CCOs) with equal or non-equal atomic ratios of multi-principal cations are single-phase solid solutions and possess unique structural characteristics and correlated possibilities for tailorable and exceptional functionalities. However, breakdown of single-phase structure and phase separation impair widespread adoption of CCOs under in-service environments. Here, in-situ phase transformation during high-pressure and high-temperature synthesis of an exemplary CCO (CeZrHf) 0.852 (YbY) 0.148 O 2-δ is for the first time clarified by using synchrotron X-ray energy dispersive diffraction. During synthesizing at ~4.5 GPa inside a large-volume press, ZrO 2 and HfO 2 gradually initiate lattice diffusion as monoclinic (022) and (220) peaks collapse and merge completely at 973 K; CeO 2 starts diffusing as the dramatic intensity change of cubic (220) peak above 1073 K, causing a metastable phase formation; single-phase solid solution ultimately forms at 1673 K. Importantly, the results revealed provide in-depth understanding of phase transformation dynamics and insights for novel design paradigm of CCOs.

36 MATERIALS SCIENCE↗