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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Deciphering the small-angle scattering of polydisperse hard spheres using deep learning

We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard sphere system. We use a variational autoencoder-based neural network to learn the bidirectional mapping between the scattering function and the system parameters, including the volume fraction and polydispersity. Such that the trained model serves both as a generator that produces a scattering function from the system parameters and an inferrer that extracts system parameters from the scattering function. We first generate a scattering dataset by carrying out molecular dynamics simulations of the polydisperse hard spheres modeled by the truncated-shifted Lennard-Jones model, then analyze the scattering function dataset using singular value decomposition to confirm the feasibility of dimensional compression. Then, we split the dataset into training and testing sets and train our neural network on the training set only. Our generator model produces a scattering function with significantly higher accuracy compared to the traditional Percus–Yevick approximation and β correction, and the inferrer model can extract the volume fraction and polydispersity with much higher accuracy than traditional model functions.

Ding, Lijie [ORNL] (ORCID:0000000227454606)↗
DOE OSTI2025

Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning

Here, we present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a Variational Autoencoder (VAE), and two converter networks establish a bidirectional mapping between the polymer parameters (bending modulus, stretching force, and steady shear) and the scattering functions. The training data are generated using off-lattice Monte Carlo simulations to avoid the orientational bias inherent in lattice models, ensuring robust sampling of polymer conformations. The feasibility of this bidirectional mapping is demonstrated by the organized distribution of polymer parameters in the latent space. By integrating the converter networks with the VAE, we obtain a generator that produces scattering functions from given polymer parameters and an inferrer that directly extracts polymer parameters from scattering data. While the generator can be utilized in a traditional least-squares fitting procedure, the inferrer produces comparable results in a single pass and operates 3 orders of magnitude faster. This approach offers a scalable automated tool for polymer scattering analysis and provides a promising foundation for extending the method to other scattering models, experimental validation, and the study of time-dependent scattering data.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

Machine learning inversion from scattering for mechanically driven polymers

A machine learning inversion method is developed for analyzing scattering functions of mechanically driven polymers and extracting the corresponding feature parameters, which include energy parameters and conformation variables. The polymer is modeled as a chain of fixed-length bonds constrained by bending energy, and it is subject to external forces such as stretching and shear. We generate a data set consisting of random combinations of energy parameters, including bending modulus, stretching and shear force, along with Monte Carlo-calculated scattering functions and conformation variables such as end-to-end distance, radius of gyration and off-diagonal component of the gyration tensor. The effects of the energy parameters on the polymer are captured by the scattering function, and principal component analysis ensures the feasibility of the machine learning inversion. Finally, we train a Gaussian process regressor using part of the data set as a training set and validate the trained regressor for inversion using the rest of the data. The regressor successfully extracts the feature parameters.

Gaussian process regressors↗
DOE OSTI2025

Femtosecond x-ray photon correlation spectroscopy enables direct observations of atomic-scale relaxations of glass forming liquids

Glass-forming liquids exhibit structural relaxation behaviors, reflecting underlying atomic rearrangements on a wide range of timescales and playing a crucial role in determining material properties. However, the relaxation processes on the atomic scale are not well-understood due to the experimental difficulties in directly characterizing the evolving correlations of atomic-scale order in disordered systems. Here, in this study, we harness the coherence and ultrashort pulse characteristics of an x-ray free electron laser to directly probe atomic-scale ultrafast relaxation dynamics in the model system Ge 15 Te 85 . We demonstrate an analysis strategy for determining the intermediate scattering function by extracting the contrast decay of summed scattering patterns from two rapidly successive, nearly identical femtosecond x-ray pulses generated by a split-delay system. The result indicates a full decorrelation of atomic-scale order on the sub-picosecond timescale, supporting the argument for a high-fluidity fragile state of liquid Ge 15 Te 85 above its dynamic crossover temperature. The demonstrated strategy opens an avenue for experimental studies of relaxation dynamics in liquids, glasses, and other highly disordered systems.

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

Alpha-relaxation by scattering and medium-range atomic correlation in simple liquids

The relaxation dynamics of liquid and glass can be studied by inelastic x-ray or neutron scattering through the intermediate scattering function F(Q, t), where Q is the momentum transfer of scattering. Because of the time-consuming nature of these measurements, F(Q, t) is usually measured only at the first peak of the structure function S(Q), and its principal decay time is referred to as the α-relaxation time τ α . τ α is generally considered to describe the relaxation time of the bulk, which is related to viscosity and is controlled by the atomic cage around an atom. Here, through simulations on metallic liquids, we show that the α-relaxation time determined by scattering experiments does not purely reflect viscosity but is influenced by changes in spatial cooperativity. We also demonstrate that atomic caging is not exerted by the nearest neighbors but involves more cooperative atomic dynamics of the atomic medium-range order.

Glass transitions↗
DOE OSTI2024

Direct observation of ultrafast cluster dynamics in supercritical carbon dioxide using X-ray Photon Correlation Spectroscopy

Supercritical fluids exhibit distinct thermodynamic and transport properties, making them of particular interest for a wide range of scientific and engineering applications. These anomalous properties emerge from structural heterogeneities due to the formation of molecular clusters at conditions above the critical point. While the static behavior of these clusters and their effects on the thermodynamic response functions have been recognized, the relation between the ultrafast cluster dynamics and transport properties remains elusive. By measuring the intermediate scattering function in carbon dioxide at conditions near the critical point with X-ray photon correlation spectroscopy, we directly capture the cross-over dynamics between 4 and 13 picoseconds, revealing the transition between ballistic and diffusive motion. Complementary analysis using large-scale molecular dynamics simulations reveals that this behavior arises from collisions between unbound molecules and clusters. This study provides direct evidence of the ultrafast momentum exchange between clusters, which has significant impact on transport properties, solvation processes, and reaction kinetics in supercritical fluids.

carbon capture and storage↗
DOE OSTI2025

Scattering-based structural inversion of soft materials via Kolmogorov–Arnold networks

Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov–Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions—two representative soft matter systems—we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Here, our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.

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

Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers

Here, we develop off-lattice simulations of semiflexible polymer chains subjected to applied mechanical forces by using Markov Chain Monte Carlo. Our approach models the polymer as a chain of fixed length bonds, with configurations updated through adaptive nonlocal Monte Carlo moves. This proposed method enables precise calculation of a polymer’s response to a wide range of mechanical forces, which traditional on-lattice models cannot achieve. Our approach has shown excellent agreement with theoretical predictions of persistence length and end-to-end distance in quiescent states as well as stretching distances under tension. Moreover, our model eliminates the orientational bias present in on-lattice models, which significantly impacts calculations such as the scattering function, a crucial technique for revealing the polymer conformation.

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

Understanding the superconductivity and charge density wave interaction through quasi-static lattice fluctuations

In unconventional superconductors, coupled charge and lattice degrees of freedom can manifest in ordered phases of matter that are intertwined. In the cuprate family, fluctuating short-range charge correlations can coalesce into a longer-range charge density wave (CDW) order which is thought to intertwine with superconductivity, yet the nature of the interaction is still poorly understood. Here, by measuring subtle lattice fluctuations in underdoped YBa 2 Cu 3 O 6+y on quasi-static timescales (thousands of seconds) through X-ray photon correlation spectroscopy, we report sensitivity to both superconductivity and CDW. The atomic lattice shows remarkably faster relaxational dynamics upon approaching the superconducting transition at T c ≈ 65 K. By tracking the momentum dependence, we show that the intermediate scattering function almost monotonically scales with the relaxation distance of atoms away from their average positions above T c and in the presence of the CDW state, while this peculiar trend is reversed for other temperatures. These observations are consistent with an incipient CDW stabilized by local strain. This work provides insights into the crucial role of relaxational atomic fluctuations for understanding the electronic physics cuprates, which are inherently disordered due to carrier doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Data Reproducibility of Spin-Echo Small-Angle Neutron Scattering Instruments

Spin-echo small-angle neutron scattering (SESANS) is a unique method to measure structures of materials in real space with length scales from ∼ 30 μm to ∼20 µm. As shown in Figure 1, the accessible length scale of SESANS is given by its ability to encode the momentum transfer into the Larmor phase, namely Φ = $\vec{𝛿}$ ⋅ $\vec{𝑄}$, where $\vec{𝑄}$ is the momentum transfer and $\vec{𝛿}$ is the encoding vector of the setup and its projection along Q (δQ) is called spin-echo length (SEL). The spin echo length, which is synonymous with the spatial correlation distance probed, is defined as the following 𝛿𝑄 ∝ 𝜆 2 𝐵𝐿cot𝜃 where 𝜆 is neutron wavelength, B is magnetic field, L is length of the parallelogram magnetic field region, and 𝜃 is the angle between the inclined magnetic field boundary and the beam direction, as shown in Figure 1. The result of the SESANS experiment is a Hankel transformation of the SANS scattering function I(Q), which yields the correlation function of the sample in real space.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Insights on carbon dioxide adsorption in a flexible 1-D coordination polymer from in situ X-ray scattering and density functional theory

A combination of in situ small-angle X-ray scattering (SAXS) microstructure characterization over scales ranging from 1 nm to 10 µm and powder X-ray diffraction (XRD) structure characterization under various gas/pressure/temperature conditions with density functional theory (DFT) calculations provides new insights for the CO2 sorption behavior of a one-dimensional porous coordination polymer: catena-bis­(di­benzoyl­methanato)(4,4′-bi­pyridyl)­nickel(II), denoted NiDBM-Bpy. The NiDBM-Bpy chains are held together by van der Waals forces, but the structure of guest-free NiDBM-Bpy is unsolved due to a lack of suitable crystals and high-quality powder XRD patterns. Nevertheless, SAXS and powder XRD can follow microstructural and structural changes as a function of gas pressure, composition and temperature. Both mixed-gas flow and static supercritical CO2 regimes are explored experimentally. DFT calculations are used to model the structural variation associated with XRD changes and hysteresis in the sorption isotherms. XRD and DFT calculations suggest that an orthorhombic Fddd structure with two CO2 per Ni emerges following a transition from the structure with lower molar volume and symmetry that exists without CO2 present.

Allen, Andrew J.↗
DOE OSTI2024

Light scattering by V 4 O 7 film across the metal–insulator transition

The experimental study of the angle-resolved hemispherical light scattering by V 4 O 7 film within a broad temperature range across metal–insulator transition reveals complex structural reorganization of the film deposited on the c-cut sapphire crystal. The bidirectional scattering distribution function and the surface autocorrelation function were obtained from scattering data to visualize statistics of the spatially resolved contributions of optical inhomogeneities in normal and lateral directions to the surface. The measurements reveal an anisotropic surface roughness distribution due to the twinned domain structure, with significant anisotropy changes across the phase transition. The V 4 O 7 film deposited on sapphire leads to a polydomain structure, minimizing elastic strain energy with distinct multiscale distributions of surface domains. Near T c , the material shows the lowest roughness but the highest lateral disorder of the surface.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Characterization of nuclear breakup as a function of hard-scattering kinematics using dijets measured by ATLAS in p+Pb collisions

This Letter analyzes the sensitivity of event geometry estimators to the initial-state kinematics of hard scattering in proton–lead collisions. This analysis uses dijets as a proxy for the parton–parton scattering configuration, correlating it with event geometry estimators, namely the energy deposited in the Zero-Degree Calorimeter and the transverse energy recorded in the Forward Calorimeter in the Pb-going direction. The analysis uses data recorded by the ATLAS detector at the Large Hadron Collider with a nucleon–nucleon center-of-mass energy of 8.16 TeV, corresponding to an integrated luminosity of 56 nb − 1 . The jets are measured within the pseudorapidity interval −2.8 < η < 4.5, where positive η values correspond to the direction of the proton beam. Results are presented as a function of the Bjorken-x of the parton originating from the proton, xp . Both event geometry estimators are found to be dependent on xp , with the energy deposited in the Zero-Degree Calorimeter about six times less sensitive to xp compared with the transverse energy deposited in the Forward Calorimeter.

Aad, G↗
DOE OSTI2026

Spectral deconvolution without the deconvolution: Extracting temperature from x-ray Thomson scattering spectra without the source-and-instrument function

X-ray Thomson scattering (XRTS) probes the dynamic structure factor of the system, but the measured spectrum is broadened by the combined source-and-instrument function (SIF) of the setup. In order to extract properties such as temperature from an XRTS spectrum, the broadening by the SIF needs to be removed. Recent work [Dornheim et al. Nat. Commun. 13 , 7911 (2022)] has suggested that the SIF may be deconvolved using the two-sided Laplace transform. However, the extracted information can depend strongly on the shape of the input SIF, and the SIF is in practice challenging to measure accurately. Here, we propose an alternative approach: we demonstrate that considering ratios of Laplace-transformed XRTS spectra collected at different scattering angles is equivalent to performing the deconvolution, but without the need for explicit knowledge of the SIF. From these ratios, it is possible to directly extract the temperature from the scattering spectra, when the system is in thermal equilibrium. We find the method to be generally robust to spectral noise and physical differences between the spectrometers, and we explore situations in which the method breaks down. Furthermore, the fact that consistent temperatures can be extracted for systems in thermal equilibrium indicates that non-equilibrium effects could be identified by inconsistent temperatures of a few eV between the ratios of three or more scattering angles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Scatter and Blur Corrections for High-Energy X-Ray Radiography

High-energy X-ray radiography is useful as a highly penetrating method for imaging through dense materials. However, the primary modes of interaction of X-rays at these energies involve scattering or the production of secondary high-energy photons, which can interfere with the image. In addition, detector blurring, often resulting from scatter within the detector, can reduce image sharpness. Both of these processes can be mitigated with the use of convolution kernels, with the main challenge being that the proper kernel to use is not known, particularly for the scatter contribution. By radiographing solid slabs of uniform attenuation, we show that point spread functions and material-specific point scatter functions can be determined to significantly reduce the effect of detector blurring and object scatter. Constraining the fits to the slabs and uniform transmission within the slabs is sufficient to recover these functions. A functional form that reproduces the angular distribution of high-energy bremsstrahlung X-rays is presented for recovering point scatter functions. In conclusion, the method is applied to radiographs of objects from bremsstrahlung X-ray sources operating at 4- and 7.5-MV endpoint energies and a significant increase in sharpness is observed.

Blind deconvolution↗
DOE OSTI2026

Heavy-quark contributions to the DIS structure functions F 4 and F 5 at NLO in the ACOT scheme

We compute the contributions of heavy quarks to the deep-inelastic scattering structure functions F 4 and F 5 at next-to-leading order of perturbative QCD in the ACOT scheme. Both analytic results including the details of the calculation as well as numerical results for the neutral and charged current cases are presented. Our study thus lays the groundwork for future measurements of these two structure functions in experiments such as the SHiP experiment.

deep inelastic scattering↗
DOE OSTI2025

Molecular beam scattering of neon from flat jets of cold salty water

Molecular beam scattering experiments are carried out to study collisions between Ne atoms (E i = 24.3 kJ mol-1) and the surface of a cold salty water (8 m LiBr(aq), 230 K) flat jet. Translational energy distributions are collected as a function of scattering angle using a rotatable mass spectrometer. Impulsive scattering and thermal desorption contribute to the overall scattering distributions, but impulsive scattering dominates at all three incidence angles explored. Highly super-specular scattering is observed in the impulsive scattering channel that is attributed to anisotropic momentum transfer to the liquid surface. The thermal desorption channel exhibits a cos θ angular distribution. Compared to Ne scattering from dodecane, fractional energy loss in the impulsive scattering channel is much larger across a wide range of deflection angles. A soft-sphere model is applied to investigate the kinematics of energy transfer between the scatterer and liquid surface. Fitting to this model yields an effective surface mass of 250-60 +100 amu and internal excitation of 11.8 ± 1.6 kJ mol-1, both of which are considerably larger than for Ne/dodecane. It thus appears that energy transfer to cold salty water is more efficient than to a dodecane liquid surface, a result attributed to the extensive hydrogen-bonded network of liquid water and roughness of the liquid surface.

Yang, Walt↗
DOE OSTI2026

Spin Diagnostics Using Mott Polarimeter for the EIC Pre-Injector

Polarization measurement and front-end commissioning are critical steps in the EIC preinjector program. We designed a spin-diagnostics beamline at around 4 MeV for front-end commissioning. This paper describes a high-energy Mott polarimeter, including Mott scattering, the Sherman function, and extrapolation toward single elastic scattering in finite-thickness foils. We summarize the key equations used to calculate essential design parameters, including detection time, effective Sherman function, differential cross section, and Mott polarimeter figure of merit. We also present the diagnostics beamline lattice design and kicker design for continuous spin-polarization monitoring. These notes provide concepts, formulas, and methods for diagnostic-beamline design and commissioning measurements.

43 PARTICLE ACCELERATORS↗