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In this work, we explore time-resolved dynamics of non-equilibrium magnons in Rb2MnF4, a model two-dimensional square lattice Heisenberg antiferromagnet using a novel laser-neutron pump-probe technique. This technique uses a nanosecond pulsed laser to periodically excite magnons to out-of-equilibrium states and then probe the resulting dynamics using INS.
Neutron scattering science is leading to significant advances in our understanding of materials and will be key to solving many of the challenges that society is facing today. Improvements in scientific instruments are actually making it more difficult to analyze and interpret the results of experiments due to the vast increases in the volume and complexity of data being produced and the associated computational requirements for processing that data. New approaches to enable scientists to leverage computational resources are required, and Oak Ridge National Laboratory (ORNL) has been at the forefront of developing these technologies. We recently completed the design and initial implementation of a neutrons data interpretation platform that allows seamless access to the computational resources provided by ORNL. For the first time, we have demonstrated that this platform can be used for advanced data analysis of correlated quantum materials by utilizing the world's most powerful computer system, Frontier. In particular, we have shown the end-to-end execution of the DCA++ code to determine the dynamic magnetic spin susceptibility χ(q, ω) for a single-band Hubbard model with Coulomb repulsion U/t = 8 in units of the nearest-neighbor hopping amplitude t and an electron density of n = 0.65. The following work describes the architecture, design, and implementation of the platform and how we constructed a correlated quantum materials analysis workflow to demonstrate the viability of this system to produce scientific results.
This dataset contains simulations generated by Sunny.jl of the magnetic excitations on the NiPS3 lattice. The exchange parameters are varied over the system so these simulations can be used for AI model training.
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.
Traditional inelastic neutron scattering (INS) characterizes excitations—such as phonons and magnons—in condensed matter systems at thermodynamic equilibrium. However, the most intriguing and puzzling many-body effects in open quantum systems often emerge from dissipative dynamics that are inherently out of equilibrium. Here, we use a combination of laser pumping and INS to experimentally observe long-lived nonequilibrium magnons in a two-dimensional (2D) square-lattice Heisenberg antiferromagnet. These nonequilibrium magnons manifest themselves as a violation of detailed balance in the dynamic structure factor and reach steady states under periodic driving, analogous to nonequilibrium steady states in driven dissipative systems. Furthermore, we show that the violation of detailed balance reflects the quantum-mechanical nature of the underlying dynamical system, where out-of-time-ordered correlations of creation and annihilation operators do not satisfy commutation relations. The in operando INS technique developed here provides a new approach to studying nonequilibrium magnons in prototypical 2D quantum magnets and can be extended to other systems, including one-dimensional spin chains and topological many-body spin systems, where nonequilibrium effects are widespread and rich in discovery potential.
Provides raw neutron scattering data for all plots and analysis for single crystals of RuCl3 in the intermediate field regime. Fields are applied within honeycomb plane both parallel (IPTS 27539) and perpendicular to Ru bonds (IPTS 27353).
Advanced batteries require advanced characterization techniques, and neutron scattering is one of the most powerful experimental methods available for studying next-generation battery materials. Neutron scattering offers a non-destructive method to probe the complex structural and chemical processes occurring in batteries during operation in truly in situ/in operando measurements with a high sensitivity to battery-relevant elements such as lithium. Neutrons have energies comparable to the energies of excitations in materials and wavelengths comparable to atomic distances in the solid state, thus giving access to study structural and dynamical properties of materials on an atomic scale. In this review, a broad overview of selected neutron scattering techniques is presented to illustrate how neutron scattering can be used to gain invaluable information of solid-state battery materials, with a focus on in situ/in operando methods. These techniques span multiple decades of length and time scales to uncover the complex processes taking place fundamentally on the atomic scale and to determine how these processes impact the macroscale properties and performance of functional battery systems. This review serves the solid-state battery research community by examining how the unique capabilities of neutron scattering can be applied to answer critical and unresolved questions of materials research in this field. A thorough and broad perspective is provided with numerous practical examples showing these techniques in action for battery research.
The thermal neutron scattering law (TSL) sublibrary aims to describe the interaction of incident neutrons at thermal or sub-thermal energies with different compound materials such fuels, moderators and special-purpose materials. In ENDF/B-VIII.1 there was a large number of new and updated TSL evaluations, including traditional moderators (light water, Beryllium metal, Beryllium Oxide, Calcium Hydride, plastics (Polystyrene and Lucite), graphite (reactor-grade and crystalline), anhydrous Hydrogen Fluoride, and heavy paraffinic oil); exotic moderators (Beryllium Carbide, Zirconium Hydride, Yttrium Hydride, Lithium-7 Hydride and Deuteride), FLiBe molten salt, structural materials and cladding (Silicon Carbide, Silicon Dioxide, Zirconium Carbide), fuels (Plutonium Dioxide, Uranium Carbide, Uranium metal, Uranium Nitride, Uranium Dioxide, Uranium Hydride), and special purpose materials. In ENDF/B-VIII.1 we also distribute alongside the evaluated files, a comma-separated file (CSV), named TSL_MAT_numbers.csv, which lists all evaluated files in the current release and their corresponding unique MAT number.
The importance of actinides for science, technology, and medicine is widely recognized and does not require a lengthy introduction. However, the fundamental understanding of actinides and their chemical and physical properties lags behind the knowledge of most other elements in the periodic table. Most actinides (89 ≤ Z ≤ 103) are man-made and were produced in particle accelerators or nuclear reactors in the second half of the 20th century. Although trends in bonding and electronic structure are well characterized and documented across the periodic table, fundamental questions remain regarding the chemistry and physics of the actinides. This lack of knowledge is largely because most isotopes of actinides are intensely radioactive, which greatly increases the difficultly in handling them.
Measurements of the areal density (ρR) of inertially confined implosions are critical to evaluate their performance. On OMEGA, ρR is inferred from measurements of the scattered neutron spectrum via neutron-time-of-flight (nTOF) and magnetic recoil spectrometer detectors. The nTOF measurements, in particular, have the ability to measure a wide range of neutron energies and thus scattering angles, with high precision. However, the neutrons that are backscattered into the detector must transit through the entire dense fuel assembly, and as a result are subject to rescattering effects, which have been heretofore neglected in the interpretation of OMEGA neutron spectra. At the backscatter edge, neglecting rescattering on OMEGA can lead to a ~10 to 20% reduction of the apparent areal density and therefore must be included in the analysis. The low ρR s on OMEGA also mean that backgrounds from non-target physics effects, such as scattering in the target chamber or slow scintillator decays, can significantly alter the measured signal. Here, we discuss how the Monte Carlo neutron spectrum postprocessor IRIS is used to include second-order scattering effects in the interpretation of the scattered neutron spectrum in OMEGA implosion experiments, and how dedicated implosion experiments are used to measure nTOF backgrounds in order to infer backscattered areal densities on OMEGA.
An international group of researchers gathered for the “Symposium on Advancements in Simulating Neutron Scattering Instruments and Experiments” at Oak Ridge National Laboratory (ORNL) on October 29- 30, 2024. The symposium highlighted state-of-the-art advancements in neutron scattering instrument simulations and the development of digital twins for scattering instruments. This document summarizes the recurring themes from the 19 talks and discussions. A key focus was on the role of neutronics simulations in the design, analysis, and performance optimization of neutron instruments. Presentations featured the most widely used software packages, such as McStas, McVine, Vitess, and MCNP. Another major theme addressed the analysis and interpretation of experimental neutron data, where materials models and simulations play a critical role. Talks on relevant software tools, including NCrystal, OCLimax, and Paradyse, were delivered by their respective developers. During the symposium, both talks and breakout sessions explored strategies to enhance the interplay between neutronics simulations and materials models. A key question emerged: How can we develop a RealTime Explainable Digital Twin of a neutron scattering experiment? Discussions include the idea that the Digital Twin concept has implications for instrument control and testing. Through this symposium, we gained valuable insights into the challenges and requirements for developing a Real-Time Explainable Digital Twin of a neutron scattering experiment. The discussions and presentations paved the way for future innovations in this rapidly advancing field.
We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.
Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.
Inelastic neutron scattering (INS) experiments utilizing modern time-of-flight spectrometers enable the comprehensive mapping of the energy (E)- and momentum (Q)-resolved dynamical structure factor of single crystals, probing both the lattice and magnetic excitations. Yet, the large size and complexity of four-dimensional INS data are challenging current analysis workflows, often resulting in an underutilization of the measured information. To help address this issue, this paper introduces new software interfaced with the Mantid framework, pathSQE, designed to streamline the processing, analysis and interpretation of 4D single-crystal INS data. By automating key tasks such as 1D/2D slicing, symmetrization, Brillouin zone folding, data visualization, prioritization and filtering, and comparisons with simulations, pathSQE facilitates and accelerates INS data analysis workflows. Here, this paper outlines the features and implementation and provides several illustrations of the use of pathSQE on data collected on single crystals using direct-geometry time-of-flight spectrometers at the Spallation Neutron Source, including Ge, FeSi, MnO and SnS single-crystal measurements on the ARCS, HYSPEC and CNCS neutron spectrometers. Beyond streamlining post-experiment data processing, pathSQE establishes an automated and modular processing pipeline that could support future real-time experiment steering.
Here, a miniature sized end-loaded piston cylinder cell with radial side windows for neutron scattering experiments is described. The principle of the bicone-shaped cylinders used was first presented by McWhan in 1974. The present cell is of compact portable design yet significantly enlarges the scattering angles. Its small size allows neutron scattering experiments at low temperatures. The bicone-shaped cylinders are made from various ceramics or a highly neutron-transmissive Ni-free Cr–Mo–V steel. Successful neutron scattering experiments up to 5 GPa have been demonstrated on the CORELLI single-crystal diffractometer and the VISION vibrational spectrometer of the Spallation Neutron Source at the Oak Ridge National Laboratory.
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.
The 2-D position sensitive neutron detectors featuring a significantly improved count rate capacity and a sub-mm spatial resolution are in high demand by neutron scattering facilities, especially the next generation high-flux spallation neutron sources (SNSs). They are anticipated to play a crucial role in fully utilizing the unprecedentedly high neutron brightness offered by these sources. In this work, a high rate and high spatial resolution neutron Anger camera has been successfully developed based on a Ce-doped microcolumnar LiI scintillator film and the PETsys TOFPET2 ASIC readout electronics. The performance evaluation was conducted in a standard laboratory environment as well as the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) with regard to light yield, γ-ray sensitivity, neutron detection efficiency, count rate capability, spatial resolution, and position linearity. The LiI:Ce scintillator was found to have a higher light yield and a lower γ-ray sensitivity than GS20 (i.e., 11729 versus 6000 photons/n and 1.67 × 10 −5 versus on the order of 10 −4 ). The neutron detection efficiency was measured to be 63% at 4.2 Å. This camera demonstrated an exceptional count rate capability, up to at least 481 kHz without rate loss. The spatial resolution was as good as 0.47 mm. Here, the position linearity was also enhanced.
Here, we show the implementation of superconducting magnetic Wollaston prisms for spin echo small-angle neutron scattering. Two calibration methods for the spin echo length are presented: one utilizing spin echo modulated small-angle neutron scattering and the other based on the neutron refraction by quartz wedge crystals. Our experimental results with polystyrene nano-particle colloids showcase the system’s efficacy in measuring both dilute and concentrated colloidal systems. Additionally, investigations into the pore diameter and pitch of a nano-porous alumina membrane demonstrate its capability in analyzing nano-porous materials. Furthermore, we discuss potential optimizations to further extend the accessible spin echo length.