Multiphonon orbit-lattice relaxation in LaBr sub 3, LaCl sub 3, and LaF sub 3.
Multiphonon orbit-lattice relaxation rates in lanthanum bromide, lanthanum chloride and lanthanum fluoride determined using transition energy gap
Moos, H. W.↗
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New Scintillator Materials (K2CeBr5) and (Cs2CeBr5)
Cesium cerium bromide (Cs2CeBr5) and potassium cerium bromide (K2CeBr5) are new scintillator materials for X-ray and gamma ray detector applications. Recently halide scintillator materials, such as Ce doped lanthanum bromide has been proved to be very important material for the same purpose. These materials are highly hygroscopic; a search for high light yield non-hygroscopic materials was highly desirable to advance the scintillator technology. In this paper, we are reporting the crystal growth of novel scintillator materials, cesium cerium bromide (Cs2CeBr5) and potassium cerium bromide (K2CeBr5). Crystals were successfully grown from the melt using the vertical Bridgman-Stockbarger technique, in a comparison with the high performance LaBr3 or LaCl3 crystals, cerium based alkali halides crystals, (Cs2CeBr5) and (K2CeBr5) have similar scintillation properties, while being much less hygroscopic. Furthermore, cesium based compounds will not suffer from the self-activity present in potassium and lanthanum compounds. However the Cs2CeBr5 crystals did not grow properly probably due to non-congruent melting or to some phase transition during cooling. Keywords." Scintillator materials; Ce3+; Energy resolution; Light yield; K2CeBr5
Hawrami, R.↗
Fast-neutron response of LaBr 3 (Ce) and LaCl 3 (Ce) scintillators
The response of LaBr 3 (Ce) and LaCl 3 (Ce) scintillators to fast neutrons is investigated. Neutron-induced charged-particle reactions are observed in both materials when exposed to the fast neutrons produced by an AmBe source, with pulse-shape discrimination used to separate channels. LaBr 3 (Ce) is found to have the best separation between reaction channels, while LaCl 3 (Ce) has a significantly higher efficiency.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
The Mu2e experiment — Searching for charged lepton flavor violation
The Mu2e experiment will search for a Standard Model violating rate of neutrinoless conversion of a muon into an electron in the presence of an aluminum nucleus. Observation of this charged lepton flavor violating process would be an unambiguous sign of new physics. Mu2e will improve upon previous searches for this process by four orders of magnitude. This requires the world’s highest-intensity muon beam, a detector system capable of efficiently reconstructing the 105 MeV/c conversion electron signal, and minimizing sensitivity to background events. A pulsed 8 GeV proton beam strikes a target, producing pions that decay into muons. Beam outside the pulse must be suppressed to < 1 0 – 10 to reduce beam-related backgrounds. The muon beam is guided from the production target along the transport system and onto the aluminum stopping target. Conversion electrons leave the stopping target and propagate inside a solenoidal magnetic field to the tracker and electromagnetic calorimeter. The tracker is a system of straw tube panels filled with Ar/CO 2 at 1 atm that tracks particles inside of a solenoidal B-field and measures their momenta with ~ 100 keV/c resolution to resolve signal events from decay-in-orbit backgrounds. The CsI calorimeter provides E / p and is used to seed the track reconstruction algorithm with σ E / E ~ 10 % and σ t < 500 ps . Additionally, a novel cosmic ray veto with greater than 99.99% efficiency brings the expected number of background events to fewer than one over three years of running. Finally, to normalize the experiment, the stopping target monitor measures the rate of capture photons from muons incident on the stopping target by using a system of high-purity germanium and lanthanum bromide scintillators.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Sim-to-real supervised domain adaptation for radioisotope identification
Machine learning has the potential to improve the speed and reliability of radioisotope identification using gamma spectroscopy. However, meticulously labeling an experimental dataset for training is often prohibitively expensive, while training models purely on synthetic data is risky due to the domain gap between simulated and experimental measurements. In this research, we demonstrate that supervised domain adaptation can substantially improve the performance of radioisotope identification models by transferring knowledge between synthetic and experimental data domains. We consider two domain adaptation scenarios: (1) a simulation-to-simulation adaptation, where we perform multi-label proportion estimation using simulated high-purity germanium detectors, and (2) a simulation-to-experimental adaptation, where we perform multi-class, single-label classification using measured spectra from handheld lanthanum bromide (LaBr) and sodium iodide (NaI) detectors. We begin by pretraining a spectral classifier on synthetic data using a custom transformer-based neural network. After subsequent fine-tuning on just 64 labeled experimental spectra, we achieve a test accuracy of 96% in the sim-to-real scenario with a LaBr detector, far surpassing a synthetic-only baseline model (75%) and a model trained from scratch (80%) on the same 64 spectra. Furthermore, we demonstrate that domain-adapted models learn more human-interpretable features than experiment-only baseline models. Overall, our results highlight the potential for supervised domain adaptation techniques to bridge the sim-to-real gap in radioisotope identification, enabling the development of accurate and explainable classifiers even in real-world scenarios where access to experimental data is limited.
Lalor, Peter W.↗
Background studies and normalization of signal events in the Mu2e experiment
The Mu2e experiment is currently being constructed at Fermilab to search for the neutrino-less conversion of negative muons into electrons in the field of an aluminum nucleus. The experiment aims at a sensitivity of four orders of magnitude higher than previous related experiments, which implies highly demanding accuracy requirements both in the design and during the operation. To achieve such a goal, two important tasks should be accomplished. First, it is essential to estimate precisely the particle yields and all the backgrounds that could mimic the monoenergetic conversion electron signal. Second, it is necessary to normalize the signal events accurately. The normalization of the signal events is planned to be done using a detector system made of an HPGe detector and a Lanthanum Bromide detector, which will measure the rate of muons stopped on the aluminum target by looking at the emitted characteristic X-and γ-rays of energies up to 1809 keV. Therefore, it is essential to evaluate the detector system's performance before the start of the actual experiment. In this study, the first task was addressed by an extensive campaign of Monte Carlo simulations to investigate the relevant parameters and their impact on the experiment's sensitivity. The second task was handled by taking advantage of the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) pulsed Bremsstrahlung photon beam at the ELBE facility. The detector system was tested at the ELBE facility under timing and background conditions similar to the ones expected at the Mu2e experiment. The study presents and discusses the simulation results and the detector system testing campaign.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
FRAM v.7.1
Fixed-energy Response-function Analysis with Multiple efficiency (FRAM) is a software code designed primarily for plutonium and uranium isotopic analysis. It is widely used in both the domestic and international safeguards community. FRAM can quickly and accurately determine the isotopic compositions of plutonium, uranium, and mixed oxides (MOX) when measuring with a high-purity germanium (HPGe), cadmium zinc telluride (CZT), or lanthanum bromide (LaBr3) detector. The capabilities of FRAM have been enhanced to analyze the data of the pixelated CZT detector (made by H3D) and to measure the mass of plutonium, uranium, and MOX. Both the isotopic composition and mass of the item can be quickly determined with one measurement using a gamma detector with FRAM v.7.1.
07 ISOTOPE AND RADIATION SOURCES↗
24.1.3.4 Upgraded Fixed Energy Response Function Analysis with Multiple Efficiencies (FRAM) Software for U/Pu/MOX Mass Measurements
Fixed-energy Response-function Analysis with Multiple efficiency (FRAM) is a software code designed primarily for plutonium and uranium isotopic analysis. It is widely used in both the domestic and international safeguards community. FRAM can quickly and accurately determine the isotopic compositions of plutonium, uranium, and mixed oxides (MOX) when measuring with a high-purity germanium (HPGe), cadmium zinc telluride (CZT), or lanthanum bromide (LaBr 3 ) detector. The capabilities of FRAM have been enhanced to analyze the data of the pixelated CZT detector (made by H3D) and to measure the mass of plutonium, uranium, and MOX. Both the isotopic composition and mass of the item can be quickly determined with one measurement using a gamma detector with FRAM v.7.1.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Fast and bright scintillators for ultrafast materials dynamics using 4th generation synchrotron
We present recent advances in fast and bright scintillators for ultrafast X-ray phase contrast imaging of dynamic materials experiments at the upgraded Advanced Photon Source (APS-U), a fourth generation synchrotron. APS-U enables hard X-ray imaging at frame rates of at least 13 MHz (corresponding to 77 ns or shorter interframe intervals), creating a new need for scintillators with faster response and higher light output than lutetium yttrium oxyorthosilicate (LYSO). For indirect imaging and diffraction with ultrafast cameras, commercial lanthanum bromide (LaBr3) and cerium bromide (CeBr3) are promising candidates. These materials exhibit decay times approximately a factor of two shorter than LYSO (around 40 ns) and lutetium oxyorthosilicate (LSO), while maintaining comparable light yield per incident X-ray photon. However, their implementation at APS-U requires addressing several challenges, including material limitations due to hygroscopicity, efficient optical coupling to imaging systems, and high quantum efficiency for conversion of scintillation light, predominantly at wavelengths below 400 nm, into detectable electronic signals. We report results from material characterization, detector integration and packaging, and beamline experiments of materials with impact. In addition, emerging scintillator classes, including perovskites and high-entropy materials, are discussed as potential alternatives for next-generation ultrafast X-ray diagnostics.
Wang, Zhehui [Los Alamos] (ORCID:0000000178264063)↗
Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199
The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)
07 ISOTOPE AND RADIATION SOURCES↗
Radiant energy to electric energy converter
Radiant energy is converted into electric energy by irradiating a capacitor including an ionic dielectric. The dielectric is a sintered crystal superionic conductor, e.g., lanthanum trifluoride, lanthanum trichloride, or silver bromide, so that a multiplicity of crystallites exist between electrodes of the capacitor. The radiant energy cyclically irradiates the dielectric so that the dielectric exhibits a cyclic photocapacitive like effect. Adjacent crystallites have abutting surfaces that enable the crystallites to effectively form a multiplicity of series capacitor elements between the electrodes. Each of the capacitor elements has a dipole layer only on or near its surface. The capacitor is initially charged to a voltage just below the dielectric breakdown voltage by connecting it across a DC source causing a current to flow through a charging resistor to the dielectric. The device can be utilized as a radiant energy detector or as a solar energy cell.
Sher, Arden↗
Linearity for Ca 2+ -Doped CeBr 3 Scintillating Materials [Slides]
This project seeks to develop low-cost, high-resolution gamma scintillators based on new fracture-resistant alloys of cerium bromide. These alloys will eliminate limitations imposed by self-activity and fracture of currently available lanthanum-based scintillators.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Stoichiometric metal nitration based novel green synthesis of mesoporous metal oxides and their enhanced heterogeneity
Here, in this work, a general and novel method for the green synthesis of mesoporous metal oxides via stoichiometric metal nitration has been demonstrated. Pluronic surfactants and their effect on synthesis procedures in terms of surface area have been experimentally studied in detail. Contrary to the traditional synthesis procedure, water has been utilized as the solvent and in several cases, such as tin oxide, manganese oxide, aluminum oxide, antimony oxide, zinc oxide, cobalt oxide, copper oxide, yttrium oxide, lanthanum oxide, and silver either the highest or comparable surface areas have been successfully synthesized. Through XRD, and TEM, all materials were observed to be crystalline except silver and magnesium oxide. SEM shows that with an increase in surfactant molar mass agglomeration decreases. Ammonia chemisorption on acidic materials gives quantitative amounts of ammonia chemical bonding with catalysts, whereas carbon dioxide chemisorption gives a quantitative value of CO 2 chemical binding with basic sites. As high as 1901.8 μmol/g and 994.6 μmol/g ammonia chemisorption values for oxides of vanadium and tin were achieved. Amphoteric materials give both acidic and basic enhanced adsorption. Finally, all synthesized materials are studied under organic catalytic transformations. Benzyl bromide is theoretically more active compared with benzylamine and benzyl alcohol which was also experimentally shown through the conversion.
36 MATERIALS SCIENCE↗