Search NASA⌕ Search

SEARCH · Search NASA

Results for “space structures”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probing Supercritical Phase Transition using Ultrafast X-ray Diagnostics (Final Technical Report)

Over recent years, several hypotheses have been put forward to elucidate supercritical transition states. Despite significant progress on the fundamental understanding of fluids at these supercritical conditions, important questions concerning the microstructure and dynamical processes remain. A particular research issue is hereby the fundamental understanding of the morphology of the molecular microstructure and its effect on the macroscopic behaviour and thermodynamic response functions. It is widely believed that the supercritical state is homogeneous without structural and dynamic observables to distinguish between a liquid and a vapor. However, recent investigations have identified regions of distinct liquid-like or vapor-like properties even under supercritical conditions. Specifically, it was shown that the transition between liquid-like and vapor-like states occurs across an extension to the coexistence line, marked by almost discontinuous changes in fluid properties. This transition was first identified experimentally by Nishikawa and Tanaka and stands in contrast to the classical presentation of the supercritical state space as a featureless, homogeneous domain. Structurally, the most important properties of supercritical fluids are the dynamic heterogeneities and local density fluctuations that are present within the fluid state at the microscopic level. These inhomogeneities are associated with the formation of molecular clusters of various sizes with liquid-like properties separated by voids of unbound gas-phase molecules which continuously restructure itself at picosecond timescales. By utilizing ultrafast X-ray Photon Correlation Spectroscopy (XPCS) at the Linac Coherent Light Source (LCLS) and X-ray synchrotron measurements as an experimental probe of these structural changes at the molecular level we seek to elucidate the higher-order phase transition from a liquid-like to a vapor-like state in the region extending the critical point. Open questions we seek to address particularly with XPCS are: (i) the underlying mechanisms responsible for the density fluctuations at supercritical conditions and how these dynamical processes at the molecular level affect the thermodynamic response functions and (ii) on what timescales do dynamical processes evolve that are associated with thermalization, molecular diffusion, and intermolecular cluster transfer.

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

Moments of axial-vector GPD from lattice QCD: quark helicity, orbital angular momentum, and spin-orbit correlation

In this work, we present a lattice QCD calculation of the Mellin moments of the twist-2 axial-vector generalized parton distribution (GPD), $\overset{\sim }{H}\left(x,\xi, t\right)$ , at zero skewness, ξ, with multiple values of the momentum transfer, t. Our analysis employs the short-distance factorization framework on ratio-scheme renormalized quasi-GPD matrix elements. The calculations are based on an N f = 2 + 1 + 1 twisted mass fermions ensemble with clover improvement, a lattice spacing of a = 0.093 fm, and a pion mass of m π = 260 MeV. We consider both the iso-vector and iso-scalar cases, utilizing next-to-leading-order perturbative matching while omitting the disconnected contributions and gluon mixing in the iso-scalar case. For the first time, we determine the Mellin moments of $\overset{\sim }{H}$ up to the fifth order. From these moments, we discuss the quark helicity and orbital angular momentum contributions to the nucleon spin, as well as the spin-orbit correlations of the quarks. Additionally, we perform a Fourier transform over the momentum transfer, which allows us to explore the spin structure in the impact-parameter space.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Realizing mechanical frustration at the nanoscale using DNA origami

Structural designs inspired by physical and biological systems have been previously utilized to develop mechanical metamaterials with enhanced properties based on clever geometric arrangement of constituent building blocks. Here, we use the DNA origami method to realize a nanoscale metastructure exhibiting mechanical frustration, a counterpart of the well-known phenomenon of magnetic frustration. By selectively actuating reconfigurable struts, it adopts either frustrated or non-frustrated states, each characterized by distinct free energy profiles. While the non-frustrated state distributes the strain homogeneously, the frustrated mode concentrates it at a specific location. Molecular dynamics simulations reconcile the contrasting behaviors and provide insights into underlying mechanics. We explore the design space further by tailoring responses through structural modifications. Our work combines programmable DNA self-assembly with mechanical design principles to overcome engineering limitations encountered at the macroscale to design dynamic, deformable nanostructures with potential applications in elastic energy storage, nanomechanical computation, and allosteric mechanisms in DNA-based nanomachinery.

DNA nanostructures↗
DOE OSTI2025

Structural, magnetic, optical, dielectric and electronic properties of R 2 NiIrO 6 (R = Pr and Nd): A comprehensive experimental and theoretical investigation

Double perovskites are highly promising materials capable of exhibiting a wide variety of phenomena. In this work, we perform a comprehensive experimental and theoretical study of polycrystalline R 2 NiIrO 6 (R = Pr and Nd) compounds. Both compounds were synthesised using the solid-state reaction method. Rietveld refinement confirmed a monoclinic structure with the P2 1 /n space group for both compounds. The scanning electron images showed the average grain sizes of 0.55 μm for R = Pr and 0.46 μm for R = Nd. Fourier transform infrared ra- diation spectra of the two compounds presented two intense bands at 470 cm -1 and 540 cm -1 . The optical measurements revealed that the band gaps of the compounds were in the visible absorption range. The field- cooled magnetisation - field hysteresis measurements indicated exchange bias properties in the synthesised compounds at low temperatures. Both temperature and frequency variation of dielectric constant and loss tangent measurements were conducted. The frequency-dependent ac conductivity measurements indicated that the conductivity increases with the increase of frequency as well as temperature. The Nd 2 NiIrO 6 compound showed lower ac conductivities compared to its isostructural Pr 2 NiIrO 6 compound. The atomic and electronic structures of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 were explored using the spin-polarised calculations performed within the DFT+U method. Our results suggested that the inclusion of on-site correlations and repulsions for the d-states of atoms was necessary in order to obtain finite band gaps of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Identifying Topological Defects in Lamellar Phases through Contour Analysis of Complex Wave Fields

Lamellar phases frequently contain structural imperfections that significantly affect their behaviors and properties. Our previous research successfully reconstructed real-space configurations of defective lamellar phases from diffuse scattering patterns, indicating the presence of phase vortices as a potential method for identifying topological defects disrupting the smectic ordering. Here, this report presents a mathematical framework using regularized wave fields to represent defective lamellar structures in real space. Phase singularities, resulting from the interference of random waves and indicating lamellar order disruption, are identified through a contour integral. These wave fields, derived from coherent scattering in reciprocal space, were validated via computational benchmarks analyzing small-angle neutron scattering data from AOT surfactant solutions, facilitating further statistical analysis of the defects. Our study highlights the potential to extract meaningful information about topological defects in lyotropic phases by inversely analyzing experimentally measured two-point static correlations. Our method allows for detailed structural analysis of various lyotropic phases, both particulate and nonparticulate, in their quiescent states and facilitates quantitative investigation of defects’ role in phase transitions. By integrating small-angle scattering, deep learning, and vortex tangle analysis, our comprehensive approach shows promise in addressing complex challenges in the structural analysis of soft matter systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Two Spacers, One Perovskite: Integrating Ruddlesden–Popper and Dion–Jacobson Halide Perovskites

Hybrid organic–inorganic perovskites are a rapidly developing class of materials due to their desirable properties for optoelectronic applications such as their ease of synthesis, solution-processable film formation, tunable band gap, strong photoluminescence, good charge carrier mobilities, and high defect tolerance. Here, we present a novel 2D perovskite motif that seamlessly integrates the structural elements from both Ruddlesden–Popper and Dion–Jacobson halide perovskites. We demonstrate the incorporation of two different organic spacer cations in an ordered manner in 5 novel 2D perovskite iodide materials. Both a cyclic diammonium cation 3-(aminomethyl)piperidinium (3AMP) and a linear alkyl monoammonium cation (Cn = C n H 2n+4 N, n = 4–8) are present in distinct alternating layers, making the new series (Cn) 2 (3AMP)[PbI 4 ] 2 . The crystallization of these materials was optimized through careful temperature control to obtain precise crystal structures via single-crystal X-ray diffraction (XRD) which confirmed the presence of the two cations in distinct layers. The influence of the two spacers on optical properties including the band gaps and photoluminescence spectra are found to more closely resemble (3AMP)PbI 4 than (Cn) 2 PbI 4 , which can be attributed to the amount of distortion imposed by the 3AMP spacer on the lead iodide layers. The findings are supported by density functional theory calculations. The strong photoelectric response of solution-processed thin films shows the potential of these materials in photodetectors or photovoltaics. This unprecedented amalgamation of RP–DJ in (Cn) 2 (3AMP)[PbI 4 ] 2 in a structurally ordered fashion suggests a potential vastly underexplored phase space of 2D perovskites in which there are chemically different spacers in distinct layers of the structure, providing an additional parameter to tune perovskite properties.

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

The distinctive mechanical and structural signatures of residual force enhancement in myofibers

In muscle, titin proteins connect myofilaments together and are thought to be critical for contraction, especially during residual force enhancement (RFE) when steady-state force is elevated after an active stretch. We investigated titin’s function during contraction using small-angle X-ray diffraction to track structural changes before and after 50% titin cleavage and in the RFE-deficient,mdmtitin mutant. We report that the RFE state is structurally distinct from pure isometric contractions, with increased thick filament strain and decreased lattice spacing, most likely caused by elevated titin-based forces. Furthermore, no RFE structural state was detected inmdmmuscle. We posit that decreased lattice spacing, increased thick filament stiffness, and increased non-cross-bridge forces are the major contributors to RFE. We conclude that titin directly contributes to RFE.

Science & Technology - Other Topics↗
DOE OSTI2026

Frustrated Magnetism in FeGe 3 O 4 with a Chiral Trillium Network

The discovery of new magnetic ground states in geometrically frustrated lattices remains a central challenge in materials science. Here, we report the synthesis, structural characterization, and frustrated magnetic properties of FeGe 3 O 4 , a newly identified compound that crystallizes in the noncentrosymmetric cubic space group P 2 1 3. In this structure, Fe atoms form an intricate double-trillium lattice with nearest-neighbor Fe−Fe distances of ∼4.2 Å, while Ge 2+ ions mediate magnetic interactions through Fe− Ge−Fe pathways. Field-dependent magnetization at 2 K shows a pronounced nonlinearity, reaching a maximum moment of 2.55(3) μ B /Fe 2+ at 70 kOe without evidence of saturation. Magnetic susceptibility, heat capacity, and neutron scattering collectively reveal the onset of short-range magnetic interactions near 5 K, with no longrange ordering detected down to 0.06 K. Specific heat measurements demonstrate strong frustration: only ∼34% of the expected magnetic entropy is recovered at 2.4 K. Taken together, these results establish FeGe 3 O 4 as a rare example of a geometrically frustrated trillium lattice magnet, offering a promising platform for exploring exotic quantum magnetic phenomena.

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

Resilient stellarator divertor characteristics in the Helically Symmetric eXperiment

Resilient divertor features connected to open chaotic edge structures in the Helically Symmetric eXperiment are investigated. For the first time, an expanded vessel wall was considered that would give space for implementation of a physical divertor target structure. The analysis was done for four different magnetic configurations with very different chaotic plasma edges. A resilient plasma wall interaction pattern was identified across all configurations. This manifests as qualitatively very similar footprint behavior across the different plasma equilibria. Overall, the resilient field lines of interest with high connection length L C lie within a helical band along the wall for all configurations. This resiliency can be used to identify the best location of a divertor. The details of the magnetic footprint’s resilient helical band is subject to specific field line structures which are linked to the penetration depth of field lines into the plasma and directly influence the heat and particle flux patterns. The differences arising from these details are characterized by introducing a new metric, the minimum radial connection min $(\delta_N)$ of a field line from the last closed flux surface. The relationship, namely the deviation from a scaling law, between min $(\delta_N)$ and L C of the field lines in the plasma edge field line behavior suggests that the field lines are associated with structures such as resonant islands, cantori, and turnstiles. This helps determine the relevant magnetic flux channels based on the radial location of these chaotic edge structures and the divertor target footprint. These details will need to be taken into account for resilient divertor design.

divertor↗
DOE OSTI2025

Shifting and tilting towards enhanced piezoelectricity in high-temperature ceramics: an average structure study of (1 − x )BiFe 2/8 Ti 3/8 Mg 3/8 O 3 – x PbTiO 3 through X-ray and neutron diffraction

A comprehensive report is provided of the average structure of a high Curie temperature ferroelectric ceramic, (1 − x)BiFe 2/8 Ti 3/8 Mg 3/8 O 3 –xPbTiO 3 (BFTM–xPT) when x = 0.25–0.375 at room temperature. Both neutron and synchrotron X-ray powder diffraction data were collected and combined Rietveld refinements were completed. These data revealed that, of the compositions studied, BFTM–xPT crystallizes as mixed phase material. At x = 0.25–0.275, the average structure of each phase is best described by space groups R3c and Cc. At 0.30 ≥ x ≥ 0.35, a morphotropic phase boundary is present and is best modelled by space groups P4mm and Cc, where space group Cc is the dominant phase. As the concentration of PbTiO 3 increases, the amount of octahedral tilting decreases and x = 0.375 exhibits a loss of octahedral tilting and crystallizes in space groups P4mm and Cm. In conclusion, an updated phase diagram at room temperature of this novel system is given and structural intricacies responsible for its piezoelectric properties are revealed.

high Curie temperature↗
DOE OSTI2024

Learning Functions Varying along a Central Subspace

Many functions of interest are in a high-dimensional space but exhibit low-dimensional structures. This paper studies regression of an s-Hölder function in $R^D$ which varies along a central subspace of dimension $d$ while $d \ll D$. A direct approximation of $f$ in $R^D$ with an accuracy $\varepsilon$ requires the number of samples in the order of $\varepsilon^{-(2s+D)/s}$. In this paper, we analyze the generalized contour regression (GCR) algorithm for the estimation of the central subspace and use piecewise polynomials for function approximation. GCR is among the best estimators for the central subspace, but its sample complexity is an open question. In this paper, we partially answer this questions by proving that if a variance quantity is exactly known, GCR leads to a mean squared estimation error of $O(n^{-1})$ for the central subspace. The estimation error of this variance quantity is also given in this paper. The mean squared regression error of $f$ is proved to be in the order of $(n/\log n)^{-\frac{2s}{2s+d}}$, where the exponent depends on the dimension of the central subspace instead of the ambient space . This result demonstrates that GCR is effective in learning the low-dimensional central subspace. We also propose a modified GCR with improved efficiency. Here, the convergence rate is validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Establishing coherent momentum-space electronic states in locally ordered materials

Rich momentum-dependent electronic structure naturally arises in solids with long-range crystalline symmetry. Reliable and scalable quantum technologies rely on materials that are either not perfect crystals or non-crystalline, breaking translational symmetry. This poses the fundamental questions of whether coherent momentum-dependent electronic states can arise without long-range order, and how they can be characterized. Here we investigate Bi 2 Se 3 , which exists in crystalline, nanocrystalline, and amorphous forms, allowing direct comparisons between varying degrees of spatial ordering. Through angle-resolved photoemission spectroscopy, we show for the first time momentum-dependent band structure with Fermi surface repetitions in an amorphous solid. The experimental data is complemented by a model that accurately reproduces the vertical, dispersive features as well as the replication at higher momenta in the amorphous form. These results reveal that well-defined real-space length scales are sufficient to produce dispersive band structures, and that photoemission can expose the imprint of these length scales on the electronic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Targeted Adaptive Design

Modern advanced manufacturing and advanced materials design often require searches of relatively high-dimensional process control parameter spaces for settings that result in optimal structure, property, and performance parameters. The mapping from the former to the latter must be determined from noisy experiments or from expensive simulations. Here, we abstract this problem to a mathematical framework in which an unknown function from a control space to a design space must be ascertained by means of expensive noisy measurements, which locate control settings generating desired design features within specified tolerances, with quantified uncertainty. We describe targeted adaptive design (TAD), a new algorithm that performs this sampling task efficiently. TAD creates a Gaussian process surrogate model of the unknown mapping at each iterative stage, proposing a new batch of control settings to sample experimentally and optimizing the updated expected log-predictive probability density of the target design. TAD either stops upon locating a solution with uncertainties that fit inside the tolerance box or uses a measure of expected future information to determine that the search space has been exhausted with no solution. TAD thus embodies the exploration-exploitation tension in a manner that recalls, but is essentially different from, Bayesian optimization and optimal experimental design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗
DOE OSTI2024

Integrating the full four-loop negative geometries and all-loop ladder-type negative geometries in ABJM theory

The decomposition of the four-point ABJM amplituhedron into negative geometries produces compact integrands of logarithmic of amplitudes such that the infrared divergence only comes from the last loop integration, from which we can compute the cusp anomalous dimension of the ABJM theory. In this note, we integrate L – 1 loop momenta of the L-loop negative geometries for all four-loop negative geometries and a special class of all-loop ladder-type negative geometries by a method based on Mellin transformation, and from these finite quantities we extract the corresponding contribution to the cusp anomalous dimension. We find that the infrared divergence of a box-type negative geometry at L = 4 is weaker than other negative geometries, then only tree-type negative geometries contribute to the cusp anomalous dimension at L = 4. For the all-loop ladder-type negative geometries, we prove and conjecture some recursive structures as integral equations in Mellin space and find that they cannot contribute zeta values like ζ 3 , ζ 5 to the cusp anomalous dimension.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2025

Recent trends in all-organic polymer dielectrics for high-temperature electrostatic energy storage capacitors

Electrostatic energy storage (EES) capacitors are critical for renewable energy and high-power systems, driving the search for dielectric materials that combine superior electrical insulation, mechanical flexibility, low density, cost-effectiveness, and processability. Polymer-based dielectrics have emerged as leading candidates, particularly for high electric field applications. However, conventional polymers often fail to meet the demands of high-temperature environments due to increased electrical conductivity and reduced discharged energy density at elevated temperatures, resulting in energy loss and reduced performance. High glass transition temperature (T g) polymers show promise but require further optimization to enhance their energy storage capabilities under thermal and electrical stress. This review provides a comprehensive update on recent advancements in high-T g polymer-based dielectrics for EES capacitors, focusing on both intrinsic polymers and all-organic composites. It outlines key design principles, critical performance parameters, and innovative strategies—such as nanofiller doping, layered architectures, physical blending, and chemical crosslinking—to improve electrical, thermal, and mechanical properties. The review also highlights emerging trends, including the integration of machine learning algorithms to explore novel polymer structures and expand the chemical design space. By bridging the gap between academic research and industrial application, this review aims to accelerate the development of next-generation dielectric materials capable of balancing multiple performance metrics for high-temperature EES capacitors.

Xie, Zongliang↗