Elucidating the porous structure of aluminum adjuvants via in-situ small-angle scattering technique
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Rinee, Khaleda C.↗
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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)↗
Model2SAS: software for small-angle scattering data calculation from custom shapes
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Li, Mu↗
Precision Small Scattering Angle Measurements of Proton–Proton and Proton–Nucleus Analyzing Powers at the RHIC Hydrogen Jet Polarimeter
At RHIC, the hydrogen jet target polarimeter (HJET) is used to measure proton beam polarization with accuracy $σ^{syst}_{P}$ / $P$ ≲ 0.5% by counting low energy (1–10 MeV) recoil protons in left-right symmetric detectors. The HJET performance also allowed us to precisely measure $pp$ and $pA$ (where $A$ is any ion stored at RHIC) analyzing powers in the CNI region. The results of the measurements are discussed.
43 PARTICLE ACCELERATORS↗
A Small Angle Scattering Sensor System for the Characterization of Combustion Generated Particulate
One of the critical issues for the US space program is fire safety of the space station and future launch vehicles. A detailed understanding of the scattering signatures of particulate is essential for the development of a false alarm free fire detection system. This paper describes advanced optical instrumentation developed and applied for fire detection. The system is being designed to determine four important physical properties of disperse fractal aggregates and particulates including size distribution, number density, refractive indices, and fractal dimension. Combustion generated particulate are the primary detection target; however, in order to discriminate from other particulate, non-combustion generated particles should also be characterized. The angular scattering signature is measured and analyzed using two photon optical laser scattering. The Rayleigh-Debye-Gans (R-D-G) scattering theory for disperse fractal aggregates is utilized. The system consists of a pulsed laser module, detection module and data acquisition system and software to analyze the signals. The theory and applications are described.
Feikema, Douglas A.↗
An algebraic convolution formulation for multiple-scattering correction in small-angle neutron scattering
Multiple scattering in small-angle neutron scattering (SANS) redistributes spectral weight and distorts structural interpretation, particularly for thick or strongly scattering samples. We develop a finite-dimensional spectral desmearing framework that corrects multiple scattering without resorting to integral transforms or model-dependent extrapolation. The primary intensity is expanded in an orthonormal basis adapted to the isotropic transverse-momentum measure, under which convolution reduces to a recursive tensor contraction, allowing the Poisson-weighted multiple-scattering series to be evaluated directly in a finite-dimensional basis representation. This formulation yields a stable forward–inverse mapping between apparent and primary spectra. Numerical tests demonstrate convergence under repeated convolution and accurate recovery of the single-scattering intensity. Application to SANS measurements collected at multiple neutron facilities, including the Spallation Neutron Source, the High Flux Isotope Reactor, and the Institut Laue-Langevin, shows the quantitative reconstruction of the underlying primary spectrum across a wide range of transmission conditions, including strongly attenuating samples. Here, the method provides a stable, model-agnostic framework for multiple-scattering correction in SANS and enables consistent structural interpretation across instruments and scattering regimes.
Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
A machine learning inversion scheme for determining interaction from scattering
Small angle scattering techniques have now been routinely used to quantitatively determine the potential of mean force in colloidal suspensions. However the numerical accuracy of data interpretation is often compounded by the approximations adopted by liquid state analytical theories. To circumvent this long standing issue, here we outline a machine learning strategy for determining the effective interaction in the condensed phases of matter using scattering. Via a case study of colloidal suspensions, we show that the effective potential can be probabilistically inferred from the scattering spectra without any restriction imposed by model assumptions. Comparisons to existing parametric approaches demonstrate the superior performance of this method in accuracy, efficiency, and applicability. This method can effectively enable quantification of interaction in highly correlated systems using scattering and diffraction experiments.
74 ATOMIC AND MOLECULAR PHYSICS↗
Small Angle Neutron Scattering Shows Nanoscale PMMA Distribution in Transparent Wood Biocomposites
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99 GENERAL AND MISCELLANEOUS↗
Unlocking hidden information in sparse small-angle neutron scattering measurements
Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.
Small angle neutron scattering↗
Nanocomplex made up of antimicrobial metallo-supramolecules and model biomembranes – characterization and enhanced fluorescence
Antimicrobial pentatopic 2,2':6',2"-terpyridines that form 3-D supramolecular hexagonal prisms with Cd 2+ through coordination driven self-assembly can be entrapped by lipid discoidal bicelles, composed of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine, 1,2-dihexanoyl-sn-glycero-3-phosphocholine and 1,2-dipalmitoyl-sn-glycero-3-phospho-(1'-rac-glycerol) lipid, forming a well-defined nanocomplex. Structural characterization performed by very small angle neutron scattering, small angle X-ray scattering and transmission electron microscopy suggests that the hexagonal prisms are preferably located at the rim of bicellar discs with the hexagonal face in parallel with the bilayers, instead of face-to-face stacking. Such a configuration reduces the π–π interaction and consequently enhances the fluorescence emission. Since novel supramolecules were reported to have antibiotic functions, in this work we provide insight into the interactions of antimicrobial supermolecules with lipid membranes, leading to potential theranostic applications.
36 MATERIALS SCIENCE↗
A science-driven approach to optimize the design for a biological small-angle neutron scattering instrument
Biological small-angle neutron scattering (SANS) instruments facilitate critical analysis of the structure and dynamics of complex biological systems. However, with the growth of experimental demands and the advances in optical systems design, a new neutron optical concept is necessary to overcome the limitations of current instruments. This work presents an approach to include experimental objectives ( i.e. the science to be supported by a specific neutron scattering instrument) in the optimization of the neutron optical concept. The approach for a proposed SANS instrument at the Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory, USA, is presented here. Further, the instrument is simulated with the McStas software package. The optimization process is driven by an evolutionary algorithm using McStas output data, which are processed to calculate an objective function designed to quantify the expected performance of the simulated neutron optical configuration for the intended purpose. Each McStas simulation covers the complete instrument, from source to detector, including realistic sample scattering functions. This approach effectively navigates a high-dimensional parameter space that is otherwise intractable; it allows the design of next-generation SANS instruments to address specific scientific cases and has the potential to increase instrument performance compared with traditional design approaches.
47 OTHER INSTRUMENTATION↗
X-ray microscopy and talbot imaging with the matter in extreme conditions X-ray imager at LCLS
The last decade has shown the great potential that X-ray Free Electron Lasers (FEL) have to study High Energy Density (HED) physics. Experiments at FELs have made significant breakthroughs in Shock Physics and Dynamic Diffraction, Dense Plasma Physics and Warm Dense Matter Science, using techniques such as isochoric heating, inelastic scattering, small angle scattering and X-ray diffraction. In addition, and complementary to these techniques, the coherent properties of the FEL beam can be used to image HED samples with high fidelity. We present new imaging diagnostics and techniques developed at the Matter in Extreme Conditions (MEC) instrument at Linac Coherent Light Source (LCLS) over the last few years. We show results in Phase Contrast Imaging geometry, where the X-ray beam propagates from the target to a camera revealing its phase, as well as in Direct Imaging geometry, where a real image of the sample plane is produced in the camera with a spatial resolution down to 200 nm. Last, we show an implementation of the Talbot Imaging method allowing both X-ray phase and intensity measurements change introduced by a target with sub-micron resolution.
47 OTHER INSTRUMENTATION↗
Resolving the organization of CO 2 molecules confined in silica nanopores using in situ small-angle neutron scattering and molecular dynamics simulations
This work quantifies the core–shell structure of nano-confined CO 2 molecules under pressure in silica pores using in operando small-angle neutron scattering (SANS) measurements and molecular dynamics simulations.
Mohammed, Sohaib↗
PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology
PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.
59 BASIC BIOLOGICAL SCIENCES↗
Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering
Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.
Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
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↗
Small-Angle Neutron Scattering for Studying Lipid Bilayer Membranes
Small-angle neutron scattering (SANS) is a powerful tool for studying biological membranes and model lipid bilayer membranes. The length scales probed by SANS, being from 1 nm to over 100 nm, are well-matched to the relevant length scales of the bilayer, particularly when it is in the form of a vesicle. However, it is the ability of SANS to differentiate between isotopes of hydrogen as well as the availability of deuterium labeled lipids that truly enable SANS to reveal details of membranes that are not accessible with the use of other techniques, such as small-angle X-ray scattering. In this work, an overview of the use of SANS for studying unilamellar lipid bilayer vesicles is presented. The technique is briefly presented, and the power of selective deuteration and contrast variation methods is discussed. Approaches to modeling SANS data from unilamellar lipid bilayer vesicles are presented. Finally, recent examples are discussed. While the emphasis is on studies of unilamellar vesicles, examples of the use of SANS to study intact cells are also presented.
59 BASIC BIOLOGICAL SCIENCES↗
Particle dynamics of nanoplastics suspended in water with soil microparticles: insights from small angle neutron scattering (SANS) and ultra-SANS
Small-angle neutron scattering (SANS) and ultra-SANS (USANS) were employed to understand the aggregation behavior and observe the size reduction for nanoplastics (NPs) formed from a biodegradable mulch film, and microparticles of vermiculite (V), an artificial soil, suspended in water in the presence of low convective shear (ex situ stirring) prior to measurements. Neutron contrast matching was employed to minimize the signal of V (by 100-fold) and thereby isolate the signal due to NPs in the neutron beam, as the contrast match point (CMP) for V (67 vol% deuteration of water) differed from that of NPs by more than 20%. The original NPs' size distribution was bimodal: <200 nm and 500–1200 nm, referred to as small and large NPs, i.e., SNPs and LNPs, respectively. In the absence of V, SNPs formed homoaggregates at higher concentrations that decreased with stirring time, while the size of LNPs remained unchanged. The presence of V at 2-fold lower concentration than NPs did not change the size of SNPs but reduced the size of LNPs by nearly 2-fold as stirring time increased. Because the size of SNPs and LNPs did not differ substantially between CMP and 100% D 2 O solvents, it is evident that SNPs and LNPs are mainly composed of NPs and not V. In conclusion, the results suggest that LNPs are susceptible to size reduction through collisions with soil microparticles via convection, yielding SNPs near soil–water interfaces within vadose zones.
Nanoplastics↗