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DOE OSTI2021

Background identification in cryogenic calorimeters through $\alpha -\alpha$ delayed coincidences

Localization and modeling of radioactive contaminations is a challenge that ultra-low background experiments are constantly facing. These are fundamental steps both to extract scientific results and to further reduce the background of the detectors. Here we present an innovative technique based on the analysis of $\alpha -\alpha$ delayed coincidences in 232 Th and 238 U decay chains, developed to investigate the contaminations of the ZnSe crystals in the CUPID-0 experiment. This method allows to disentangle surface and bulk contaminations of the detectors relying on the different probability to tag delayed coincidences as function of the $\alpha$ decay position.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Two datasets are better than one: method of double moments for 3D reconstruction in cryo-EM

Cryo-electron microscopy is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic projection images of randomly oriented particles. We introduce a new data fusion framework, termed the method of double moments, which reconstructs molecular structures from two instances of the second-order moment of projection images obtained under distinct orientation distributions: one uniform, the other non-uniform and unknown. We prove that these moments generically uniquely determine the underlying structure, up to a global rotation and reflection, and we develop a convex-relaxation-based algorithm that achieves accurate recovery using only second-order statistics. Our results demonstrate the advantage of collecting and modeling multiple datasets under different experimental conditions, illustrating that leveraging dataset diversity can substantially enhance reconstruction quality in computational imaging tasks.

Kam’s method↗

DOE OSTI2015

Development of nanosecond time-resolved infrared detection at the LEAF pulse radiolysis facility

When coupled with transient absorption spectroscopy, pulse radiolysis, which utilizes high-energy electron pulses from an accelerator, is a powerful tool for investigating the kinetics and thermodynamics of a wide range of radiation-induced redox and electron transfer processes. The majority of these investigations detect transient species in the UV, visible, or near-IR spectral regions. Unfortunately, the often-broad and featureless absorption bands in these regions can make the definitive identification of intermediates difficult. Time-resolved vibrational spectroscopy would offer much improved structural characterization, but has received only limited application in pulse radiolysis. In this paper, we describe in detail the development of a unique nanosecond time-resolved infrared (TRIR) detection capability for condensed-phase pulse radiolysis on a new beam line at the LEAF facility of Brookhaven National Laboratory. The system makes use of a suite of high-power, continuous wave external-cavity quantum cascade lasers as the IR probe source, with coverage from 2330-1051 cm⁻¹. The response time of the TRIR detection setup is ~40 ns, with a typical sensitivity of ~100 µOD after 4-8 signal averages using a dual-beam probe/reference normalization detection scheme. As a result, this new detection method has enabled mechanistic investigations of a range of radiation-induced chemical processes, some of which are highlighted here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Fluorescence Imaging of Single-Molecule Retention Trajectories in Reversed-Phase Chromatographic Particles

Due to its high specific surface area and chemical stability, porous silica is used as a support structure in numerous applications, including heterogeneous catalysis, biomolecule immobilization, sensors, and liquid chromatography. Reversed-phase liquid chromatography (RPLC), which uses porous silica support particles, has become an indispensable separations tool in quality control, pharmaceutics, and environmental analysis requiring identification of compounds in mixtures. For complex samples, the need for higher resolution separations requires an understanding of the time scale of processes responsible for analyte retention in the stationary phase. In the present work, single-molecule fluorescence imaging is used to observe transport of individual molecules within RPLC porous silica particles. This technique allows direct measurement of intraparticle molecular residence times, intraparticle diffusion rates, and the spatial distribution of molecules within the particle. On the basis of the localization uncertainty and characteristic measured diffusion rates, statistical criteria were developed to resolve the frame-to-frame behavior of molecules into moving and stuck events. The measured diffusion coefficient of moving molecules was used in a Monte Carlo simulation of a random-walk model within the cylindrical geometry of the particle diameter and microscope depth-of-field. Furthermore, the simulated molecular transport is in good agreement with the experimental data, indicating transport of moving molecules in the porous particle is described by a random-walk. Histograms of stuck-molecule event times, locations, and their contributions to intraparticle residence times were also characterized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Understanding the High Energy Higgs Sector with the CMS Experiment and Artificial Intelligence

This dissertation describes efforts towards understanding the Higgs boson at the highest energies humanly accessible, using the CMS experiment at the Large Hadron Collider and advances in artificial intelligence (AI) and machine learning (ML). We present searches for resonant and nonresonant Higgs-boson (H) pair production in the all-hadronic two beauty-quark and two vector boson (V) final state, using a novel strategy to measure the quartic HHVV coupling and search for new Higgs-like bosons. By targeting highly Lorentz-boosted Higgs pairs, we probe effects of potential new physics in the high energy Higgs sector, which could hold answers to fundamental mysteries of nature such as baryon asymmetry. To enable these and future searches, we introduce as well significant developments in AI/ML, including in the identification of boosted H$\rightarrow$VV decays with deep transformer networks and advances in AI-accelerated fast simulations of the CMS detector. The latter notably includes the development of the first, highly performant generative models for point-cloud data in high energy physics, which have the potential to improve CMS' computational efficiency by up to three orders of magnitude. We also highlight novel solutions to the important and challenging problems of calibrating and validating these ML techniques. Finally, we present new approaches to search for new physics in a model-agnostic manner, using physics-informed ML methods equivariant to Lorentz transformations. The quartic HHVV coupling is observed (expected) to be constrained to $[-0.04, 2.05]$ ($[0.05, 1.98]$) at the 95% confidence level relative to the standard model prediction, representing the second-most sensitive measurement of this coupling by CMS to date. Exclusion limits on the production cross section of new heavy resonances decaying to two Higgs-like bosons are expected to be as low as 0.3 fb for high resonance masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2012

Molecular-Level Design of Heterogeneous Chiral Catalysis

The following is a proposal to continue our multi-institutional research on heterogeneous chiral catalysis. Our team combines the use of surface-sensitive analytical techniques for the characterization of model systems with quantum and statistical mechanical calculations to interpret experimental data and guide the design of future research. Our investigation focuses on the interrelation among the three main mechanisms by which enantioselectivity can be bestowed to heterogeneous catalysts, namely: (1) by templating chirality via the adsorption of chiral supramolecular assemblies, (2) by using chiral modifiers capable of forming chiral complexes with the reactant and force enantioselective surface reactions, and (3) by forming naturally chiral surfaces using imprinting chiral agents. Individually, the members of our team are leaders in these various aspects of chiral catalysis, but the present program provides the vehicle to generate and exploit the synergies necessary to address the problem in a comprehensive manner. Our initial work has advanced the methodology needed for these studies, including an enantioselective titration procedure to identify surface chiral sites, infrared spectroscopy in situ at the interface between gases or liquids and solids to mimic realistic catalytic conditions, and DFT and Monte Carlo algorithms to simulate and understand chirality on surfaces. The next step, to be funded by the monies requested in this proposal, is to apply those methods to specific problems in chiral catalysis, including the identification of the requirements for the formation of supramolecular surface structures with enantioselective behavior, the search for better molecules to probe the chiral nature of the modified surfaces, the exploration of the transition from supramolecular to one-to-one chiral modification, the correlation of the adsorption characteristics of one-to-one chiral modifiers with their physical properties, in particular with their configuration, and the development of ways to imprint chiral centers on achiral solid surfaces. Chiral catalysis is not only a problem of great importance in its own right, but also the ultimate test of how to control selectivity in catalysis. The time is ripe for fundamental work in heterogeneous chiral catalysis to provide the U.S. with a leadership role in developing the next generation of catalytic processes for medicinal and agrochemical manufacturing. Our team provides the required expertise for a synergistic and comprehensive integration of physical and chemical experimentation with solid state and molecular reactivity theories to solve this problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Searches for a sterile-neutrino admixture in detecting tritium decays in a proportional counter: New possibilities

An experiment aimed at searches for an admixture of a sterile neutrino whosemass is 1 to 8 keV via detecting electrons from tritium decay in a proportional counter is proposed. The admixture in question can be discovered by a specific distortion of the energy spectrum of these electrons. For the above masses, the distortion extends over the whole spectrum; therefore, use can bemade of detectors that have a relatively low energy resolution (about 10 to 15%). A classic proportional counter is a simple and natural choice of detector for the decays of a gaseous tritium. The approach that we propose is novel in two respects. On one hand, the proportional counter used is made as a discrete unit in the form of a fully fused quartz tube. This permits a readout of current signals directly from the anode filament and ensures a high stability in the case of long-term measurements. At the same time, the application of state-of-the-art digital data-acquisition methods will make it possible to perform measurements under conditions of high counting rates—up to 10{sup 6} Hz. As a result, the energy spectrum of electrons from tritium decays that is formed by 10{sup 12} counts could be accumulated within about a month. This data sample would make it possible to set an upper limit in the range of 10{sup −3}–10{sup −5} on a sterile-neutrino admixture at a confidence level of three standard deviations (3σ) for m{sub s} in the range of 1–8 keV, this being one to two orders of magnitude more stringent than present-day limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2012

Energy weighting for the upgrade of the CMS HCAL

In these simulation studies an energy weighting method is applied to the signals of the CMS hadronic calorimeter readout with a longitudinal segmentation for a possible future upgrade. Tabulated weighting factors are used to compensate for the different response of hadronic and electromagnetic energy depositions of simulated pion showers in the hadronic calorimeter. The weighting improves the relative energy resolution: ( Greek-Small-Letter-Sigma {sub E}/E){sup 2} = [((92.2 {+-} 0.6)%/{radical}E){sup 2} + ((6.5 {+-} 01)%{sup 2}] (before weighting), (( Greek-Small-Letter-Sigma {sub E,weight}/E){sup 2} = [((85.4 {+-} 0.5)%/{radical}E){sup 2} + ((4.4 {+-} 0.1)%{sup 2}] (after weighting), where E in the square root has units of GeV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration - FY2018 Final Report

High-value R2R processing is used to support a wide range of products in applications which span many industrial business sectors. The overall R2R process technology can be considered as “mature” as the process methodology and has been in use for decades. This continuous processing technique traditionally involves deposition of material(s) onto moving webs or carriers or other continuous R2R, belt-fed, or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Current process technologies, which typify “roll to roll”, include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multi-layer technologies can be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, a means must be available to enable manufacture of these products in a cost-competitive manner that is affordable by the general consumer. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches.Within the DOE EERE AMO, it was recognized that establishment of a program supported at the DOE National Laboratories, along with their immense design of materials and equipment modelling capabilities enabled with use of high-performance computing, could take advantage of available R2R infrastructure to manufacture new technologies. In FY 2016, a R2R Consortium was established and provided with initial “seed” funding to take an approach that was envisioned to be supportable by advanced manufacturing R2R processes. This collaborative approach was designed to foster identification and development of materials and processes related to R2R for clean-energy product development. Using computational and experimental capabilities by acknowledged subject matter experts within the supported National Laboratory system, this collaborative project would leverage the capabilities and expertise at each of four laboratories to further the development of an enabling high-volume cost-competitive platform technology. The collaboration team that is comprised of ORNL, ANL, NREL and LBNL, coordinating with EPB and other selected industry partners, was formed in April 2016 to initially address enhancing battery electrode performance and R2R manufacturing challenges. The research efforts were to predict and measure changes and results in electrode morphology and performance based on process condition changes; to evaluate mixed, active, particle size deposition and drying for novel electrode materials; to model various process condition changes and the resulting morphology and electrode performance; and to develop and validate NDE techniques for in-line measurement of battery electrode material properties. These efforts carried through FY 2017 and completed at the end of FY 2018.The approach was to look at compositions of materials with different particle sizes to make electrode samples using a R2R manufacturing process. The shape, size, and morphology of the materials, the chemistry of the formulation, the nature of slurries, their coating rate, the rate of drying all play a role in determining the final coating architecture, quality, and performance. A commercial cathode material was selected to make a series of cathodes and anodes by single pass, dual pass and slot die methods. Analysis of all the compiled results for this battery electrode development were that the best performing cathodes included: dual-pass electrode with large particles near the foil, mixed small and large particles, and small particles only. Whereas, the best performing anodes were with a mix of small and large graphite particles. An additional core project was added in FY 2017 to conduct studies of fuel cell materials that can be produced using R2R processes. The goal of this project is to explore, understand and optimize material and process parameters to support increased throughput, increased quality, and reduced cost for high volume production of gas-diffusion electrodes (GDEs) for PEMFCs. Project work in FY 2018 were to use a R2R process to fabricate electrodes without ionomer overlayer that can produce the equivalent mass activity as spray-coated electrodes with an ionomer overlayer. Oxygen-limiting current measurements were utilized to optimize oxygen mass transport. Alcohol-rich solvents were investigated, and results were that the alcohol and water ratio can be tuned to control ionomer distribution. Water-rich solvents produce a more dispersed ink which results in better high-current density performance.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Detailed analysis of excited-state systematics in a lattice QCD calculation of 𝑔 𝐴

Excited state contamination remains one of the most challenging sources of systematic uncertainty to control in lattice QCD calculations of nucleon matrix elements and form factors: early time separations are contaminated by excited states and late times suffer from an exponentially bad signal-to-noise problem. High-statistics calculations at large time separations ≳ 1 fm are commonly used to combat these issues. In this work, focusing on g A , we explore the alternative strategy of utilizing a large number of relatively low-statistics calculations at short to medium time separations (0.2–1 fm), combined with a multistate analysis. On an ensemble with a pion mass of approximately 310 MeV and a lattice spacing of approximately 0.09 fm, we find this provides a more robust and economical method of quantifying and controlling the excited state systematic uncertainty. A quantitative separation of various types of excited states enables the identification of the transition matrix elements as the dominant contamination. The excited state contamination of the Feynman-Hellmann correlation function is found to reduce to the 1% level at approximately 1 fm while, for the more standard three-point functions, this does not occur until after 2 fm. Critical to our findings is the use of a global minimization, rather than fixing the spectrum from the two-point functions and using them as input to the three-point analysis. We find that the ground state parameters determined in such a global analysis are stable against variations in the excited state model, the number of excited states, and the truncation of early-time or late-time numerical data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Advanced Validation Risk-Informed Approach for the Flooding Tool Based Upon Smooth Particle Hydrodynamics: Validation and Development Status of NEUTRINO

Risk-Informed validation is to focus advanced validation on high-priority and critical elements of the RISMC methods and tools that can best be addressed by this targeted approach to validation. Initial validation focus will be on the RISMC flooding analysis computer software based upon Smoothed Particle Hydrodynamics (SPH), NEUTRINO. The NEUTRINO code is a SPH-based CFD software adopted as one of the RISMC modeling tools for external hazards analysis. This document discusses the validation and development activities of NEUTRINO, especially in relation to its simulation capability for flooding hazards analysis. In order to draw meaningful conclusions from the discussion, we first analyzed the potential risks to nuclear power plants in flooding scenarios (e.g., hazard modes, industry/regulatory concerns, etc.). Then, an initial high-level PIRT was proposed to define the key phenomena relevant to the analysis of flooding hazards. Finally, based on the framework of this PIRT analysis, the validation and development efforts that have been conducted to date for NEUTRINO were discussed. This analysis helped to determine the sufficiency, efficiency, and adequacy of the current code development and validation efforts for NEUTRINO.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration (FY2020 Final Report)

R2R processing is used to manufacture a wide range of products for various applications which span many industrial business sectors. The overall R2R methodology has been in use for decades and this continuous technique traditionally involves deposition of material(s) onto moving webs, carriers or other continuous belt-fed or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Established methods that typify R2R processing include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating, and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier and membrane materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multilayer technologies have the potential to be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, the means must be available to enable manufacture of these products in a cost-competitive manner that is affordable. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches. However, more early-stage research is needed to solve the challenge of linking the materials (particles, polymers, solvents, additives) used in ink and slurry formulations and the coating and drying processes to the ultimate performance of the final R2R product, especially for a process that uses multiple layers of deposition to achieve the end product. To solve the problems associated with these challenges, the R2R Collaboration is executing a research program with outcomes that will ultimately link modeling, processing, metrology and defect detection tools, thereby directly relating the properties of constituent particles and processing conditions to the performance of final devices. This collaborative approach was designed to foster identification and development of materials and processes related to R2R for clean-energy materials development. Using computational and experimental capabilities by acknowledged subject matter experts within the supported National Laboratory system, this project leverages the capabilities and expertise at each of five National Laboratories to further the development of multilayer technologies that will enable high-volume, cost-competitive platforms. A typical R2R process has three steps: (1) mixing of particles and various constituents in a slurry, (2) coating of the ink/slurry mixture on a substrate, and (3) drying/curing and processing of the coating. Final performance of devices made via R2R processes is dependent on the active materials (e.g., electrochemical particles in battery or fuel cell electrodes) and the device structure that stems from the governing component interactions within the various steps. However, a fundamental understanding of the underlying mechanisms and phenomena is still lacking, which is why industrial-scale R2R process development and manufacturing is still largely empirical in nature. The FY 2019 through FY 2021 program addresses aspects of the following two targets from the AMO Multi-Year Program Plan: (1) Target 8.1 Develop technologies to reduce the cost per manufactured throughput of continuous R2R manufacturing processes. (A) Increasing throughput of R2R processes by 5 times for batteries (to 50 square feet per minute (50 ft 2 /min)) and capacitors and 10 times for printed electronics and the manufacture of other substrates and MEs used in support of these products. (B) Developing resolution capabilities to enable registration and alignment that will detect, align, and co-deposit multiple layers of coatings and print < 1-micron (1 µm) features using continuous process scalable for commercial production. (C) Developing scalable and reliable R2R processes for solution deposition of ultra-thin (<10 nm) films for active and passive materials. (D) Develop in-line multilayer coating technology on thin films with yields greater than 95%. (2) Target 8.2 Develop in-line instrumentation tools that will evaluate the quality of single and multilayer materials in-process. (A) Developing in-line QC technologies and methodologies for real-time identification of defects and expected product properties “in-use/application” during continuous processing at all size-scales with a focus on the “micro” and “nano” scale traces, lines, and devices, i.e., <1 μm at 300 ft./min for R2R processing in air and <10 nm at 20 ft./min for vacuum (B) Developing technologies to increase the measurement frequency of surface rheology without significant cost increases with a goal of a 10-nanometer in-line profilometry at a production rate of 100,000 square millimeters per minute (100,000 mm 2 /min).

42 ENGINEERING↗

DOE OSTI2015

Barrel calorimeter of the CMD-3 detector

The structure of the barrel calorimeter of the CMD-3 detector is presented in this work. The procedure of energy calibration of the calorimeter and the method of photon energy restoration are described. The distinctive feature of this barrel calorimeter is its combined structure; it is composed of two coaxial subsystems: a liquid xenon calorimeter and a crystalline CsI calorimeter. The calorimeter spatial resolution of the photon conversion point is about 2 mm, which corresponds to an angular resolution of ∼6 mrad. The energy resolution of the calorimeter is about 8% for photons with energy of 200 MeV and 4% for photons with energy of 1 GeV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2011

Modeling the tagged-neutron UXO identification technique using the Geant4 toolkit

It is proposed to use 14 MeV neutrons tagged by the associated particle neutron time-of-flight technique (APnTOF) to identify the fillers of unexploded ordnances (UXO) by characterizing their carbon, nitrogen and oxygen contents. To facilitate the design and construction of a prototype system, a preliminary simulation model was developed, using the Geant4 toolkit. This work established the toolkit environment for (a) generating tagged neutrons, (b) their transport and interactions within a sample to induce emission and detection of characteristic gamma-rays, and (c) 2D and 3D-image reconstruction of the interrogated object using the neutron and gamma-ray time-of-flight information. Using the modeling, this article demonstrates the novelty of the tagged-neutron approach for extracting useful signals with high signal-to-background discrimination of an object-of-interest from that of its environment. Simulations indicated that an UXO filled with the RDX explosive, hexogen (C{sub 3}H{sub 6}O{sub 6}N{sub 6}), can be identified to a depth of 20 cm when buried in soil.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Fast-neutron/gamma-ray radiography using a broad-energy neutron source

Transmission radiography is a well-established nondestructive examination technique with widespread application to fields ranging from medicine to security. Traditionally, inspection is performed using a single particle type (such as x-rays). However, the information available using a single probe for traditional radiography is limited. The present work evaluates material discrimination via transmission radiography using the attenuation ratio of monoenergetic gamma rays to a broad spectrum of fast neutrons. Here, the method was assessed using an 241 Am/Be radioisotope source that provides both 4.4 MeV gamma rays and a spectrum of fast neutrons up to 12 MeV. A total of 14 object configurations were measured: seven different materials each with two thicknesses (2.5 cm and 5 cm). The ability to distinguish materials was evaluated and shows more significant variation among atomic numbers than for high-energy x-rays alone, making it easier to distinguish between classes such as low-, mid-, and high-Z materials. These results suggest that superior material discrimination is also possible using a combination of monoenergetic gamma rays and broad-spectrum fast neutrons from a variety of nuclear reactions, such as 11 B(d,nγ) 12 C, that could be implemented in future inspection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2013

Mid-infrared Study of Stones from the Sutters Mill Meteorite

The Sutter's Mill meteorite fell in northern California on April 22, 2012, and numerous pieces have been recovered and studied with several analytical techniques [1]. We present a Fourier-transform infrared (FTIR) spectroscopy analysis of fragments from several stones of the meteorite. Methods and analysis: Infrared spectra of samples SM2 and SM12 were recorded with a Nicolet iN10 MX FTIR microscope in the mid-IR range (4000-650/cm; spectral resolution 4/cm), while samples SM20 and SM30 were analyzed with a synchrotron-based Nicolet Continuum IR microscope in the same range. Samples were deposited on a clean glass slide, crushed with either a stainless steel roller tool or between 2 slides, and placed directly on the focal plane of the microscopes. Results: IR spectra of non-fusion crust samples show several absorption features associated with minerals such as olivines, phyllosilicates, carbonates (calcite and dolomite), and pyroxenes, as well as organics [2]. The carbonates display a main, broad band centered at 1433/cm, with additional bands at 2515/cm, 1797/cm, 882/cm, and 715/cm. Features associated with phyllosilicates include a symmetric Si-O stretching mode band centered at 1011/cm and several O-H stretching mode bands―a broad band centered at 3415/cm that is probably due to adsorbed H2O, and occasionally a much weaker, narrower feature centered near 3680/cm due to structural O-H. Features observed in the 2985-2855/cm range suggest the presence of aliphatic -CH3 and -CH2- groups. However, some of these bands show unusual relative intensities, mainly because of carbonate overtone bands that fall in the same spectral range, which can make the identification of C-H stretching bands problematic. The positions and relative strengths of the aliphatic -CH2- and -CH3 features, where they can be distinguished from overlapping carbonate bands, are consistent with those in interplanetary dust particles (IDPs) and Murchison. Finally, the absence of a strong C=O absorption feature near 1700/cm distinguishes the organics in the Sutter's Mill meteorite from that in most IDPs and in Murchison, but is consistent with the organic matter in Tagish Lake.

mid-infrared study↗

DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗

DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗