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At least 127 records · Page 7

Analytic Chromaticity Formulas for the Muon g -2 experiment at fermilab

The Muon g-2 Experiment (E989) at Fermilab measured the muon anomalous magnetic moment aμ with unprecedented precision of 127 ppb using a storage ring. The experiment pushed the limits in terms of accuracy and systematic errors. Achieving the 78-ppb total systematic uncertainty required precise beam dynamics modeling and corrections for effects on the measured muon precession frequency. Here, we derived the first analytic aberration formulas up to the second order for the muon g-2 storage ring’s combined-function electrostatic quadrupoles (superimposed magnetic dipole and electric quadrupole fields) using an order-by-order perturbation method. From these, we obtained the exact chromaticity formulas for three ring models of different granularity and validated them against numerical calculations using COSY INFINITY, achieving analytic-numerical agreement to ⁠$\mathscr{O}(10^{-10})$. This work resolved discrepancies between previous approximate derivations and provided essential beam dynamics results for Runs 4-6 analyses. We also calculated nonlinear chromaticities up to ninth order. The experiment completed its final Run 6 in July 2023, collecting 21 times more data than the previous muon g-2 experiment at Brookhaven National Laboratory, with the final result announced in June 2025.

aberrations

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES

Selection and Ranking of Experiments from the Halden Database in support of Multiscale Model Validation

Validating fuel performance codes, such as BISON, requires an extensive amount of experiments covering a wide range of operating conditions and fuel types. Within the light-water reactor (LWR) space, there have been several international experimental programs that have contributed to the wealth of available experimental data available for use. One of those international programs, the Halden Reactor Project (HRP), began in 1958 and utilized the Halden Boiling Water Reactor to conduct many highly instrumented experiments until the reactor closed in 2018. Idaho National Laboratory, through the U.S. Department of Energy, has utilized several Halden experiments to perform the initial validation of the BISON code based upon their inclusion in international modeling and simulation benchmarks. Recently, the HRP has provided member organizations a complete copy of all available data, reports, and presentations since the HRP began. This report provides an initial exploration of the data available in the database for use in validating the multiscale models under development in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for LWR applications. Ranking tables that identify potential validation cases are provided for the high priority models of interest. It was found that some of the recommended high priority experiments correspond to additional rods in existing assemblies already available in the BISON validation suite. It is expected that several of these cases will be incorporated into future NEAMS milestones in the fuels technical area for increased validation of BISON.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

AGC Experiment Status

AGC Experiment Status to include: History and status of the AGC-4, Review of the AGC experiment, AGC graphite grades and samples, The AGC-4 capsule and specimens, and HDG-1 and HDG-2. Description of the Experiment, AGC graphite grades and samples, AGC-1 Test Train, AGC-1 Test Train Design Features, New AGC Irradiation Schedule (2018) and update in schedule, Irradiation and disassembly history, present and future status, and shipment and initial PIE. Initial PIE strategy, recovered specimens, PIE results, and status of experiments.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Effect of Sample Mass, Confinement, and Preheating Time on the Thermal Response of LLM‐105: Experiments and Kinetic Analysis

Various small-scale experiments were performed to provide data for developing a model to predict the thermal response of LLM-105 over a wide range of conditions. The thermal decomposition of LLM-105 was studied as a function of sample mass, confinement of volatile products, and preheating time in both isothermal and ramped heating experiments. The thermal decomposition of LLM-105 is a two-step process, as shown by the two exothermic peaks in the heat flow profiles, which were fitted to two nth-order autocatalytic reaction models with a similar activation energy of ∼289 kJ/mol. The magnitude and shape of these peaks varied with sample mass and confinement. Increasing sample mass enhanced the second exotherm with respect to the first one, while increasing the level of confinement promoted a transition from a sublimation-dominated regime towards thermal decomposition. The effect of LLM-105 particle size on the rate of weight loss was evident for open-pan experiments, where bigger particles sublimed at lower temperatures than smaller particles. Thermal response and solid residue composition of LLM-105 samples were analyzed following preheating for different durations. Longer preheating times caused a shift of the second exotherm to lower temperatures and a decrease in the reaction enthalpy, confirming that LLM-105 decay is a consecutive reaction mechanism, probably autocatalytic. In conclusion, the kinetic model derived from ramped experiments was validated against the measured LLM-105 fraction remaining and the enthalpy remaining of the solid residue as a function of preheating times and showed good agreement.

Chemistry - Chemical explosives

Filling the gap: hunting for vector bosons at the MUonE experiment with displaced decay signature

The upcoming MUonE experiment aims to precisely measure the running of the fine structure constant via elastic muon-electron scattering, to shed light on the current tension in the muon’s anomalous magnetic moment. In addition to its primary function as a precision experiment, MUonE also offers a unique testing ground to probe long-lived vector bosons. Such vector bosons can be produced via μe → μeV or μN → μNV scattering and decay into an electron/positron pair a few centimeters away from the interaction point. With its high-resolution tracking system and unique geometric design, MUonE is well-suited to reconstruct displaced vertices close to the target, allowing it to probe parameter space previously unattainable at colliders and longer-baseline beam dump experiments. We present a comprehensive study of the discovery potential of BSM vector boson mediators at the MUonE experiment. We show that MUonE can fill the long-standing gap in the parameter space of vector boson mediators with masses up to around 100 MeV.

Models for Dark Matter

Design of a separate effects MiniFuel irradiation experiment investigating microstructure evolution in high burnup UO 2

The microstructural evolution of UO 2 fuel pellets during commercial operation in light water reactors (LWRs) is known to vary significantly across the pellet radius due to spatial variations in local temperature and burnup. The primary obstacle to extending LWR refueling cycles to 24-month intervals is the susceptibility of certain high burnup fuel microstructures to fuel fragmentation, relocation, and dispersal (FFRD) during a loss of coolant accident (LOCA). Although FFRD of the high burnup structure in the rim region of a pellet is well studied, the fine fragmentation that has been observed in a second region, near the midradius of the pellet (termed the “dark zone”) following mock LOCA testing of high burnup commercial fuel rods is less understood. This paper describes the design, analysis, and execution of a separate effects MiniFuel irradiation experiment that aims to identify the specific temperature and burnup regimes under which FFRD-susceptible dark zone microstructures form. The small disc specimens (3 mm diameter by ∼0.3 mm thick) enable more precise control of the relatively uniform temperature and burnup conditions. A total of 42 specimens were fabricated with typical LWR fuel densities (∼96%–98% of theoretical density) and grain sizes (∼12 μm) and are being irradiated over a range of temperatures (600°C–1000°C) and discharge burnups (50–72 MWd/kg-U) that bound the midradius region of high burnup LWR fuel. Fuel specimens with identical 235 U enrichments were inserted in two irradiation locations in the High Flux Isotope Reactor and are currently undergoing irradiation to further evaluate the impact of rate effects (fission rate, time at temperature) on the microstructural evolution. The fuel fabrication and the thermal and neutronic simulations used for designing the experiment are detailed in this paper. A secondary objective of the experiment is to observe fission gas release (FGR) under the various irradiation conditions, and this work provides first-order predictions of FGR from all fuel specimens. The insights gained from these experiments will inform future high burnup core designs that could minimize the formation of susceptible microstructures and ultimately enable 24-month refueling cycles while minimizing the fraction of the fuel susceptible to FFRD.

FFRD

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption

Control Mechanisms for Self‐Sealing in Activated Clay‐Rich Faults Through Controlled Hydraulic Injection Experiment

Abstract In a high‐pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi‐weekly for a year revealed the gradual return of fault transmissivity to its initial state. The study utilized fluid pressure decay analysis, optical fiber monitoring, continuous active source seismic measurements and borehole displacement sensors for measuring fault displacements. The fault zone exhibited a dilation of approximately 1.4 mm, associated with both normal and tangential movements during activation, resulting in a sudden transmissivity increase from 1 × 10 −12 to 3.2 × 10 −7 m 2 /s. Early post‐activation, transient compaction and the subsequent slow compaction were observed, transitioning to an extension regime. The pressure pulse tests demonstrated a rapid transmissivity drop by more than two orders of magnitude within the first 10 days, followed by a gradual and less pronounced decrease. Plastic shear and compaction dominated the transmissivity evolution until 70 days after injection ended, followed by a period where additional factors, such as clay mineral swelling, influenced the behavior. Extrapolation suggested a sealing process taking at least 50 years after the initial activation. Plain Language Summary A field‐scale fault activation experiment offers valuable insights into the elasto‐plastic processes governing the sealing of shale faults. The experiment reveals a rapid increase in the fault's transmissivity by approximately five orders of magnitude during activation. Subsequent observations show a gradual transmissivity decrease by about three orders of magnitude post‐activation, with slow long‐term plastic shear and compaction of the fault competing against secondary processes, notably clay mineral swelling. All conceptual models employed to interpret these field data converge on the estimation that the fault's return to its initial low transmissivity state would require a minimum of 50 years. Key Points High‐pressure injection fault activation experiment at the Mont Terri underground research laboratory Continuous transmissivity measurements record self‐sealing inside a clay‐rich fault zone Transmissivity undergoes a phase of domination by slow plastic compaction and shearing during the initial post‐activation period, with mineral swelling exerting its influence over the long term

Guglielmi, Yves

The detection of marine microseismic activity with the CUORE tonne-scale cryogenic experiment

Vibrations from experimental setups and the environment are a persistent source of noise for low-temperature calorimeters searching for rare events, including neutrinoless double beta ( 0νββ ) decay or dark matter interactions. Such noise can significantly limit experimental sensitivity to the physics case under investigation. Here, we report the detection of marine microseismic vibrations using mK-scale calorimeters. This study employs a multi-device analysis correlating data from CUORE, the leading experiment in the search for 0νββ decay with mK-scale calorimeters, and the Copernicus Earth Observation program, revealing the seasonal impact of Mediterranean Sea activity on CUORE’s energy thresholds, resolution, and sensitivity over four years. The detection of marine microseisms underscores the need to address faint environmental noise in ultra-sensitive experiments. Understanding how such noise couples to the detector and developing mitigation strategies is essential for next-generation experiments. We demonstrate one such strategy: a noise decorrelation algorithm implemented in CUORE using auxiliary sensors, which reduces vibrational noise and improves detector performance. Enhancing sensitivity to 0νββ decay and to rare events with low-energy signatures requires identifying unresolved noise sources, advancing noise reduction methods, and improving vibration suppression systems, all of which inform the design of next-generation rare event experiments.

experimental nuclear physics

Radiation drive designed to extend the pressure ranges measured in Gbar equation of state experiments at the National Ignition Facility

We present the design and demonstration of a Shock-Strengthening hohlraum radiation temperature drive in the Gbar experimental platform at the National Ignition Facility intended to increase the pressure range measured in a single experiment. Previously published experiments by Döppner et al. measured the equation of state in polystyrene from 25 to 60 Mbar. Recent experimental data of the Shock-Strengthening drive initially demonstrated a much larger pressure range from 15 to 110 Mbar using the same peak radiation temperature and experimental platform. The Shock-Strengthening drive starts with a low temperature foot that launches a weak shock into the sample and is followed by a continuous increase in radiation temperature to strengthen the leading shock. The additional strengthening increases the pressure within the sample beyond what is achievable by convergence alone. Design features of the Shock-Strengthening drive and accompanying radiation hydrodynamics simulations are used to illustrate the method by which the pressure range is increased from previous experiments. This method of modifying the radiation temperature drive can be used on the Gbar platform to significantly increase the range for equation of state data collected in a single experiment for many materials.

Physics - Plasma physics

The next-generation particle x-ray temporal diagnostic for simultaneous time-resolved measurements of nuclear-burn and x-ray emission histories in support of basic-science and inertial confinement fusion experiments at OMEGA

The next-generation Particle X-ray Temporal Diagnostic (PXTD) has been implemented for simultaneous measurements of x-ray, charged particle, and neutron emission histories from a wide range of inertial confinement fusion and high energy density plasma experiments, demonstrating excellent timing accuracy and greatly improved experimental flexibility. The key changes to the previously fielded system are a redesigned set of thin foil filters in front of the scintillators and individual neutral density filters for each region of the detector. The fully implemented PXTD system can provide unique information about the evolution of ion and electron temperatures in multi-ion and kinetic-physics experiments, proton radiography experiments, and DT experiments executed at the OMEGA facility. The system has 35 ps time resolution and negligible relative timing uncertainty between measured emission history signals. The first use of the upgraded four-channel PXTD system during a set of D 3 He-filled silica-glass implosions on OMEGA captured electron temperatures with a minimum uncertainty of 0.5 keV and resolved both the relative timings and widths of neutron, proton, and x-ray peaks within a single recorded image.

Evans, T. E. [Massachusetts Inst. of Technology (M

Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing

The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.

97 MATHEMATICS AND COMPUTING

Demonstration of x-ray fluorescence spectroscopy as a sensitive temperature diagnostic for high-energy-density physics experiments

We present the use of x-ray fluorescence spectroscopy (XFS) to a sensitive temperature diagnostic in shocked foams at temperatures of 30–75 eV. Cobalt-doped foams were shock compressed using a planar drive at the OMEGA laser facility and photo-pumped with a Zn He⁢𝛼 x-ray source. Analysis of the resulting cobalt 𝐾⁢𝛽 x-ray fluorescence spectra using collisional radiative codes allows the temperature to be determined in the shocked foams. Furthermore, this method provides a sensitive and robust technique to determine temperatures in high-energy-density physics experiments in the tens of electronvolts temperature range. In these experiments, we find that radiation hydrodynamic simulations predict a lower temperature in the shocked foams compared to analysis of the XFS data using collisional radiative models. Although additional experiments with an independent temperature diagnostic to absolutely calibrate XFS spectra for these conditions will be required to resolve this discrepancy, these results demonstrate the excellent temperature sensitivity of XFS spectra for high-energy-density physics experiments.

Atomic spectra

Modern version of the uncited 1938 experiment that first observed DT fusion

Experiments are described, and results are provided, for the duplication of the first-ever triton-deuterium (colloquially referred to as DT) fusion experiment accidentally performed by A.J. Ruhlig in 1938, but forgotten in the published scientific literature. Here, we find that Ruhlig overestimated the ratio of the triton-deuterium over deuteron-deuterium neutron yields in his secondary reaction (Reaction-in-Flight) experiment compared to modern theoretical calculations and our duplication of his experiment using modern neutron detection methods. Nevertheless, Ruhlig’s observation provided the motivation for the application of DT fusion after World War II and its more recent importance in peaceful energy production at DT fusion facilities around the world. Additionally, the experimental technique used in the present work provides a novel approach for checking on low-energy triton stopping powers in deuterium containing compounds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

pdas-experiments

SAND2025-04589O pdas-experiments automates computational experiments of fluid flow simulations. It uses the pressio-demoapps-schwarz package as a basis to break down complex simulations into smaller, manageable parts. This application is an extension of the Sandia Pressio software which uses domain decomposition to work with complex simulations more efficiently. Users can test different simulation setups, while keeping a detailed record of their experiments so they can be reproduced later. The software includes a C++ program that runs individual experiments based on user-defined settings in a YAML file, as well as a Python script that can manage multiple simulations at once. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tezaur, Irina [Sandia National Lab. (SNL-CA), Live

IER 499 Thermal Epithermal eXperiments with Highly Enriched Uranium and Chlorine (TEX-Cl) CED-3B

The Thermal Epithermal eXperiments (TEX) with highly enriched uranium (HEU) and chlorine (TEX Cl) experiment, IER 499, was executed at the National Criticality Experiments Research Center (NCERC) in July - August 2024 by the following members of the Advanced Nuclear Technology Group at Los Alamos National Laboratory: Theresa Cutler, Peter Brain, Travis Grove, Rene Sanchez, Alex McSpaden, Kristin Stolte, Zach Lemke, Kenny Valdez, Charlie Kiehne. The experiment was born out of necessity for nuclear criticality safety validation of the capture cross section of 35 Cl. This cross section plays an important role in nuclear criticality safety at both Los Alamos National Laboratory (LANL) and the Y-12 National Security Complex. This work sought to validate the Cl capture cross section through the construction and measurement of three separate critical configurations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA