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DOE OSTI2024

Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

Archibald, Rick [ORNL] (ORCID:0000000245389780)↗

DOE OSTI2025

Fast and Accurate Pixel Calibration of Tof Neutron Diffractometers with Machine Learning

At a spallation neutron source, neutron pulses of varying energies are generated, and the detection of neutrons by instrument detectors is recorded as time-of-flight from the emission of the neutron pulse to its arrival at specific detector pixels with high time resolution. The flight path of neutrons from the moderator to the sample and then to the detector must be precisely calibrated at the detector-pixel level using standard powders, so the neutron events from all pixels can be time-focused to produce high-resolution diffraction patterns. Modern time-of-flight neutron diffractometers at spallation neutron sources are equipped with two-dimensional detectors with millimeter-scale pixelations. The number of pixels in a diffraction instrument can reach millions, which makes a single-pixel-level calibration process time-consuming or even impossible with conventional refinement or fitting approaches. Here we present a machine-learning-aided calibration process using a train-and-predict approach, in which machine learning models are trained on the relationship between an individual pixel time-of-flight diffraction pattern and its diffraction constant. These models use a portion of the available pixels for training, and a good model then predicts the diffraction constants precisely and rapidly for large sets of pixel diffraction patterns.

detector pixel calibration↗

DOE OSTI2024

Design improvements to the SNS ion source and diagnostics

The U.S. Spallation Neutron Source (SNS) is a state-of-the-art neutron scattering facility delivering the world's most intense pulsed-neutron beams to a wide array of instruments which are used to conduct investigations in many fields of science and engineering. The accelerator system is fed by an RF-driven, multicusp, H - ion source which nominally provides pulsed beam currents of 50-60 mA (1ms, 60Hz). This report provides a discussion of ongoing design improvements to the SNS ion source and Low Energy Beam Transport (LEBT) as well as diagnostic upgrades undertaken since the previous ICIS conference. These improvements include (i) simple mechanical modifications to the source outlet aperture which resulted in dramatically increased extracted beam current and comparable or lower emittance at similar beam currents, (ii) design improvements to the LEBT chopper target which will enable full power beam-dumping during physics studies, (iii) refinement of the SNS Allison emittance scanner that has enabled the first reliable LEBT beam measurements at full beam power (65kV, 50-100mA, 1ms, 60Hz) on the SNS ion source test stand and (iv) the implementation of a thermal imaging camera for the monitoring the LEBT electrode temperatures. (v) The design of an advanced Cs system, capable of more efficient Cs utilization with significantly lower Cs losses from the source is also presented. Mechanical details, computational simulations and experimental results are discussed within the context of these improvements.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Laser beam pointing stabilization using analog position-sensitive diodes

Laser wire scanners have been used for ion beam profile and emittance measurements at the Spallation Neutron Source linear accelerator. Due to propagation distances exceeding 100 m, reliable measurements require laser beam stabilization, previously accomplished with a feedback control loop using a digital camera as a position sensor [Hardin et al., Opt. Express 19, 2874 (2011)]. Here, this paper presents an upgraded pointing stabilization system utilizing analog position-sensitive diodes (PSDs) as the position detector, optimized with an optical diffuser. The new system significantly surpasses the previous system by offering an order-of-magnitude improvement in radiation tolerance and a bandwidth limited only by the burst repetition rate of the laser beam. Operating with a 60-Hz burst mode laser, the new system effectively suppresses laser beam drifts up to 30 Hz, compared to the previous system’s 4 Hz limit. In addition, the amplitude of spectral components below 0.1 Hz was reduced by a factor of more than 100, which is over seven times greater than was achieved by the previous system.

Data acquisition↗

DOE OSTI2025

Neutron Scattering in High Magnetic Fields: Community Recommendations to Seize the Moment for Scientific Breakthroughs

Oak Ridge National Laboratory (ORNL) operates the world’s two most powerful neutron sources: the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS). These form a national user facility that provides neutron scattering instruments to probe and image static and dynamic properties of materials down to the atomic scale. Because the neutron carries a magnetic moment and the energies and wavelengths of neutrons match energy and length scales associated with magnetic materials, these facilities provide unique sensitivity to magnetism.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Gallium oxide (Ga 2 O 3 ) energy dependent scintillation response to fast neutrons and flash gamma-rays

Gallium oxide is a newly emerged ultrawide bandgap (4.9 eV) semiconductor that is suitable as a combined electronics and radiation detection platform. We have experimentally demonstrated fast neutron and gamma-ray scintillation from Czochralski-grown β-Ga 2 O 3 in a recent series (October 2023) of experiments at the unmoderated pulsed neutron spallation source located at the Los Alamos Neutron Science Center. Using the neutron time-of-flight (TOF) technique and a fast-gated intensified CCD camera, we observed energy-dependent neutron scintillation for neutron energies ranging from 1 to 400 MeV, including the 14.1 MeV neutron energy relevant to D–T fusion. Neutron flux is quantified and calibrated by cascading the scintillator after the fission chamber, enabling a detailed analysis of temporal and energy-dependent characteristics of the scintillation events. Further, a pronounced scintillation signal from the spallation gamma flash with a temporal full width of half maximum of ~4 ns is indicative of the material’s rapid response. Neutron energy dependent scintillation is observed using the TOF method at a 22.6-m distance from the neutron source. These results highlight the possibility of developing a Ga 2 O 3 based fusion neutron diagnostic platform integrated with both scintillation and electronics functions on the integrated chip scale.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

New generation bunch shape monitor for ion accelerators

Measuring longitudinal beam parameters is important for operation and development of high intensity linear accelerators, but it is notoriously difficult for proton and ion beams at non-relativistic energies. The Bunch Shape Monitor (BSM) is a device used for measuring the longitudinal bunch distribution in ion linacs. The existing BSM models have poor electron collection efficiency from the wire and are limited to one-dimensional measurements of the phase coordinate. In response to this problem, we have developed a new generation BSM with improved performance. The proposed design incorporates three major innovations: First, the collection efficiency was improved by adding a focusing field between the wire and the entrance slit, which will also allow measurements over a much wider dynamic range. Second, an improvement in the measurement speed was achieved by sampling longitudinal profiles of multiple energy slices simultaneously, where the BSM wire is placed at the exit of an ion spectrometer so that ions with different energies hit the wire at different horizontal coordinates along the wire. Finally, the design incorporates a motion system that can shift the wire and deflecting cavity together, enabling transverse profile measurements like a wire scanner. Here, in this paper, we will provide the design of the new BSM and report on its beam test results at the Spallation Neutron Source facility in Oak Ridge National Laboratory.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Virtual to Physical: Reinforcement Learning to Optimize SNS Particle Accelerator Controls

Complex accelerators must have control systems that can handle dynamic nonlinear environments. This makes traditional control methods unsuitable as they can struggle to adapt to these uncertainties. This provides an ideal environment for reinforcement learning algorithms as they are adaptable and generalizable. We present a reinforcement learning pipeline that can effectively handle the dynamics of a complex accelerator. We test and prove our pipelines capabilities on multiple environments including the Spallation Neutron Source (SNS) and the Beam Test Facility (BTF) at Oakridge National Lab (ORNL). Due to the limited time available to train an online algorithm like reinforcement learning on a real accelerator, we utilize a virtual twin accelerator (VIRAC) developed by ORNL to pretrain the policy and show its ability to converge in the virtual environment. We then test the adaptability of the pretrained RL model by applying it on the real accelerator and comparing the results. Utilizing our Scientific Optimization and Controls Toolkit (SOCT) and open-source standards such as Gymnasium we create and solve for a MEBT orbit correction problem in the SNS and an emittance maximization problem in the BTF. We show how Twin Delayed Deep Deterministic Policy Gradient (TD3) can solve this optimization environment in the virtual accelerator and transfer this policy onto the real accelerator for inference and model retraining. We show how reinforcement learning can be utilized as a control system for complex accelerators and provide a model pipeline for how an implementation performs and can be adapted to new accelerator control problems.

Kasparian, Armen [Thomas Jefferson National Accele↗

DOE OSTI2025

Inelastic Neutron Scattering Data for Ba₃Zn(Ru₀.₁Sb₁.₉)O₉

This dataset contains inelastic neutron scattering measurements on the magnetically dilute compound Ba₃Zn(Ru₀.₁Sb₁.₉)O₉, collected at the Spallation Neutron Source using the Cold Neutron Chopper Spectrometer (CNCS) and the SEQUOIA Fine-Resolution Fermi Chopper Spectrometer. The sample consists of nominally 5% magnetic Ru⁵⁺ ions (S = 3/2) randomly substituted into a diamagnetic Sb⁵⁺ matrix. Measurements were performed at base temperature (2–5 K) and 300 K using multiple incident energies (1.00, 3.32, 12.0, and 100 meV) to resolve magnetic excitations from isolated monomers and small Ru clusters (dimers, trimers, etc.). The dataset includes raw event-mode files, momentum- and energy-resolved spectra, and supporting metadata for instrument configuration, sample environment, and reduction parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Impact of post-irradiation annealing on mechanical performance of irradiated 718 alloy

Here, the effect of post-irradiation annealing on solution-annealed 718 alloy was investigated using advanced mechanical testing, fractography, scanning electron microscopy, and transmission electron microscopy. Specimens were extracted from a proton beam window operated at the Spallation Neutron Source, irradiated with 940 MeV protons to a maximum dose of approximately 9.7 displacements per atom (dpa) at a calculated temperature not exceeding 110 °C while in service. Helium and hydrogen concentrations reached about 1700 and 6900 atomic parts per million (appm), respectively. Despite irradiation and high tensile strength (yield stress over 1 GPa), the material exhibited significant ductility. Annealing at 500 °C, 700 °C, and 900 °C for 30 min resulted in an appreciable decrease in yield strength and an increase in ductility for annealing treatments at 500 °C and 900 °C relative to the strength and ductility of the as-irradiated material. The presence of helium and hydrogen led to cavity formation and cleavage-like brittle features on fractured surfaces; however, high-magnification imaging revealed the presence of small-scale ductile dimples, indicating that the fracture mechanism remained mixed. The annealed specimens retained total elongation levels of 14–33 %, and there was no sudden drop in ductility after heat treatments. The ductility level in the irradiated and annealed material is notable despite the presence of helium and hydrogen.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments

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.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Record of Decision: H - LEBT Design Modifications

The LAMP Conceptual Design (LCD) is described in the LAMP Conceptual Design Report. The proposed new configuration of the LAMP H - LEBT encompasses multiple changes to the LCD. The new configuration makes use of a single H - source to supply beam to all LANSCE user stations except IPF; this eliminates one of the H - sources in the LCD, and the associated pulsed merger magnet the use of two such sources required. The source current from the sole H - source is gated on a macropulse-by-macropulse basis using techniques demonstrated at SNS (Spallation Neutron Source), specifically, changes to the RF plasma drive power. A pulsed electrode system is used to match the beam into the LEBT transport line, variable on a macropulse-by-macropulse basis to match the source beam current.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Analysis of Second Target Station Target Removal Dose Rates

The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.

Transmutation↗

DOE OSTI2025

Supporting Data for "Constraints on magnetism and correlations in RuO2 from lattice dynamics and Mössbauer spectroscopy"

Contents of this DOI are data for the research paper "Constraints on magnetism and correlations in RuO2 from lattice dynamics and Mossbauer spectroscopy" by the authors: George Yumnam, et. al. The dataset contains data from inelastic x-ray scattering measurements of RuO2 single crystals performed at the Advanced Photon Source in Argonne National Lab. This dataset also contains data from inelastic neutron scattering experiments of RuO2 powder performed at the ARCS spectrometer at Spallation Neutron Source at ORNL. Supporting theoretical calculations based on density functional theory with r2SCAN and DFT+U methods is also included in this dataset. Please see the README.txt files for more information of the dataset and file contents. For comments and questions, please contact: George Yumnam (yumnamg@ornl.gov) and/or Raphael P Hermann (hermannrp@ornl.gov)

density functional theory↗

DOE OSTI2026

BM3DORNL

BM3DORNL is a high-performance, open-source library for removing streak and ring artifacts from computed-tomography (CT) data, developed for neutron imaging at Oak Ridge National Laboratory's Spallation Neutron Source (VENUS beamline) and applicable to X-ray CT as well. Ring artifacts — concentric rings in reconstructed slices caused by detector pixel-to-pixel response non-uniformities — appear as vertical streaks in the sinogram and degrade both image quality and quantitative analysis. BM3DORNL operates in the sinogram domain using an adaptation of the BM3D (block-matching and 3D collaborative filtering) algorithm (Dabov et al., 2007). It provides a dedicated streak-removal mode, a true multi-scale BM3D variant (after Mäkinen et al., 2021) that suppresses wide streaks single-scale methods miss, and an alternative Fourier–SVD method (~2.6× faster) combining FFT-based energy detection with rank-1 SVD. The computationally intensive core is implemented in Rust with parallel (Rayon) block matching, integral-image pre-screening, and optimized transforms, and is exposed through a simple Python API (with an optional GUI) so it integrates directly into existing tomography reconstruction pipelines. It processes both 2D sinograms and 3D sinogram stacks, is pip-installable for Linux and macOS, and is documented at https://bm3dornl.readthedocs.io.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗

DOE OSTI2026

Prospects for exploring non-standard neutrino properties with argon-based CEvNS experiments

Coherent elastic neutrino-nucleus scattering (CEvNS) provides a powerful frame-work for testing the Standard Model (SM) and searching for new physics at low energies. In this work, we examine the prospects for argon-based CEvNS experiments at stopped-pion sources to perform precision measurements of weak interactions and probe non-standard neutrino properties. Our study focused on the CENNS-10 and CENNS-750 detectors at the Spallation Neutron Source at Oak Ridge National Laboratory, the Coherent Captain Mills (CCM) detector at Los Alamos National Laboratory, and the proposed PIP2-BD detector at Fermilab’s Facility for Dark Matter Discovery (F2D2). Using realistic neutrino fluxes and detector configurations corresponding to these facilities, we evaluate event rates and sensitivities to a range of observables. Within the SM, argon-based CEvNS detectors enable precision tests of electroweak parameters, including the weak mixing angle, at momentum transfers well below the electroweak scale. We also investigate the sensitivity of these experiments to neutrino electromagnetic properties, such as the magnetic moment and effective charge radius, as well as to possible non-standard neutrino interactions with quarks. Together, these studies highlight the potential of argon-based CEvNS experiments as a clean and versatile platform for precision exploration of non-standard neutrino properties.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗

DOE OSTI2026

rustpix

rustpix is a high-performance, open-source Rust library with first-class Python bindings (via PyO3) for processing pixel-detector data in neutron imaging. It targets time-stamping detectors such as Timepix3 (TPX3) at ORNL's Spallation Neutron Source (VENUS beamline), where each detected neutron deposits charge across a cluster of pixels within a very high-rate event stream (96M+ hits/sec). rustpix parses TPX3 event data in parallel using memory-mapped I/O, offers four interchangeable clustering algorithms (ABS adjacency-based search, DBSCAN, graph/union-find connected components, and a parallel grid method), and extracts weighted, super-resolved centroids to produce neutron-event lists. A streaming architecture lets it process files larger than available memory. rustpix is distributed as a pip-installable Python package (with NumPy integration), Rust crates, a command-line tool, and an interactive GUI; it writes HDF5, Apache Arrow, and CSV; and it is designed to extend to TPX4 and other detector types. Released as open-source under the MIT License.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗