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At least 937 records · Page 52

Direct observation of C 3 S particle dissolution using fast nano X-ray computed tomography

Tricalcium silicate (C 3 S) occupies 50 % to 70 % of ordinary portland cement (OPC) by mass and it is an important component affecting the hydration of OPC [1], [2], [3], [4], [5], [6], [7]. Generally, the hydration of C 3 S is described by two processes: the dissolution of C 3 S particles and the precipitation of hydration products. While it is understood that the dissolution rates of C 3 S vary with time, more precise measurements are needed to understand this process. Many mechanisms have been proposed to explain the time-evolving dissolution rates of C 3 S [2]. The metastable barrier hypothesis suggests that a thin metastable layer of hydrates forms around the C 3 S particle surface and prohibits the access of grains to the aqueous solution [8], [9], [10], [11], [12]. The slow dissolution step hypothesis suggests that the increased ion concentration from the initial reaction delays the C 3 S dissolution [2], [13], [14], [15], [16], [17]. More recent publications suggest that C 3 S may react differently depending on the existence of crystallographic defects [18], [19], [20]. Etch pits are thought to open on the particle surface during the initial reaction and this contributes to the C 3 S dissolution [21], [22]. As hydrates precipitate and cover these highly reactive surfaces, hydration slows down and the induction period starts [18], [23], [24], [25], [26]. Many experiments have been conducted to test the aforementioned mechanisms. Some hydration studies utilize bulk measurements, such as isothermal calorimetry [27], [28], [29], pore solution analysis [30], quasi-elastic neutron scattering [31], and nuclear magnetic resonance spectroscopy [32], [33]. One limitation of these measurements is that they do not provide direct and detailed information on the individual C 3 S particles. Some other studies utilize imaging techniques, such as scanning electron microscopy (SEM) [34], [35], [36] and transmission electron microscopy (TEM) [37]. However, SEM/TEM cannot track the evolution of individual particles throughout hydration [34], [35], [38], [39], [40] and they do not give insights into the microstructure of materials before hydration [34], [35], [39]. This makes it challenging to draw strong conclusions from only SEM or TEM observations. Synchrotron X-ray tomography techniques have been used more broadly in recent years to study cement hydration. They are not only non-destructive but also able to image a sample in full 3D with resolutions that can reach from micron to nanoscale. Nano computed tomography (nCT) is one technique that has been applied to study cement hydration at the nanoscale [26], [41]. A typical nCT can reach a pixel size from 15 to 65 nm, providing enough detail for observing features <1 μm. However, nCT often takes >0.5 h to finish one scan. This makes the application of this technique on continuous scans for in-situ observations challenging. Fast X-ray computerized tomography (fCT) is another technique that has shown success in studying the time-evolving cement microstructures [20], [42], [43], [44], [45], [46], [47], [48], [49]. Due to the high flux of the X-ray beam from the synchrotron ring, fCT allows a scan to be captured within 1 min at a pixel size of 1 μm. This allows a paste sample to be continuously scanned during the hydration process. However, the micron-sized resolutions limit does not provide detailed insights for particles <5 μm [20], [49]. Fortunately, the combination of nCT and fCT has allowed the development of fast nano X-ray computed tomography (fnCT). fnCT can capture a 3D data set in <2 min at a pixel size of 50 nm. This makes this procedure an exciting method to evaluate hydrating pastes. fnCT collects multiple X-ray radiographs at various rotation angles and generates a 3D model of the scanned sample, which is also referred to as a 3D tomography [50], [51]. In one tomography, the X-ray absorptions of different components (e.g., C 3 S and hydrates) differ as functions of density and chemistry [52], [53]. These X-ray absorption contrasts can be used to extract detailed information about the 3D microstructure [26], [54], [55]. In this paper, fnCT is used to collect time-lapse tomographs of hydrating C 3 S paste from 18 min after mixing to 7 h of hydration. The bulk measurements of anhydrous C 3 S, as well as the microstructural changes of individual C 3 S particles, are directly observed, quantified, and discussed. The dissolution behavior of C 3 S particles at various size scales is systematically analyzed and compared. This work aims to find the relationship between the size of C 3 S particle sizes and their dissolution rates. This provides significant insights into the early-age hydration of C 3 S on length and time scales not previously possible. Because of the magnitude of the data and the substantial amount of observations, this work will solely focus on the change in the anhydrous particles. Changes in the hydration products will be reported in future work.

42 ENGINEERING↗

Thermal radiation model for solid rocket booster plumes

The Monte Carlo method is used to model the thermal radiation field of the plumes for the dual solid rocket boosters astride the Space Shuttle launch configuration. The model accounts for axial and radial variations in radiative properties of the plumes. The plumes are considered to be composed of a dispersion of aluminum oxide (Al2O3) particles immersed in the gaseous products of combustion. The principal emitting gases are taken to be CO, CO2, H2O, and HCl. The thermal model is based on local thermodynamic equilibrium. Scattering of radiant energy by Al2O3 particles may be treated as isotropic or anisotropic. Sample radiant heating rates to the base region of the Space Shuttle are shown. Space Shuttle geometries are simulated as combinations of quadric surfaces.

Watson, G. H.↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Measurements of ϒ states production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ = 500 GeV with STAR: Cross sections, ratios, and multiplicity dependence

We report measurements of ϒ⁡(1⁢𝑆), ϒ⁡(2⁢𝑆) and ϒ⁡(3⁢𝑆) production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ =500 GeV by the STAR experiment in year 2011, corresponding to an integrated luminosity ℒ int = 13 pb −1 . The results provide precise cross sections, transverse momentum (𝑝 T ) and rapidity (𝑦) spectra, as well as cross section ratios for 𝑝 T < 10 GeV/c and |𝑦| < 1. The dependence of the ϒ yield on charged particle multiplicity has also been measured, offering new insights into the mechanisms of quarkonium production. The data are compared to various theoretical models: the color evaporation model (CEM) accurately describes the ϒ⁡(1⁢𝑆) production, while the color glass condensate+nonrelativistic quantum chromodynamics (CGC+NRQCD) model overestimates the data, particularly at low 𝑝 T . Conversely, the color singlet model (CSM) underestimates the rapidity dependence. These discrepancies highlight the need for further development in understanding the production dynamics of heavy quarkonia in high-energy hadronic collisions. The trend in the multiplicity dependence is consistent with CGC/saturation and string percolation models or ϒ production happening in multiple parton interactions modeled by PYTHIA 8.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Theoretical shell-model signatures in heavy-ion, coherent pion production

A comprehensive summary of a many-body, microscopic, particle-hole formalism is presented that describes coherent, subthreshold, pion production in peripheral, heavy-ion collisions. The formalism uses a new separable model transition interaction that produces Delta-hole states in either the projectile or target nucleus. Shell-model states described by harmonic oscillator functions are used in the calculation of Delta formation and decay and Lorentz-contraction effects of the nucleus not at rest are included. An analytical expression to lowest multipole order for the differential cross section is examined. The sensitivity of the theoretical results to the shell-model states is determined with preliminary shape results compared with data. The effects of higher multipoles are examined with attention paid to the second-order multipole value.

Maung, Khin M.↗

Four α correlations in nuclear fragmentation: a game of resonances *

Abstract Heavy ion collisions near the Fermi energy produce a ‘freezout’ region where fragments appear and later decay, emitting mainly neutrons, protons, alpha particles, and gamma rays. These decay products carry information about the decaying nuclei. Fragmentation events may result in high yields of boson particles, especially alpha particles, and may carry important information about the nuclear Bose Einstein condensate (BEC). We study ‘in medium’ four α correlations and link them to the ‘fission’ of 16 O in two 8 Be in the ground state or 12 C * (Hoyle state)+ α . Using novel techniques for the correlation functions, we confirm the resonance of 16 O at 15.2 MeV excitation energy, and the possibility of a lower resonance, close to 14.72 MeV. The latter resonance is the result of all α particles having 92 keV relative kinetic energies.

Physics↗

Quality Control Methods for Measurement of UCO Kernel Composition and SiC Microstructure

Quality control (QC) is critically important to tristructural-isotropic (TRISO) particle fuels owing to the complexity of and reliance on the fuel form to contain fission products during irradiation. Characterization methods for particle fuel QC have decades of history and have continued to develop as new insights into fuel performance inform revised fuel specifications and as advances in underlying technologies expand the possibilities of what may be characterized. Two relatively new methods for characterization of TRISO fuels have been published in open literature: optical microscopy image analysis for mixed uranium carbide/uranium oxide (UCO) kernel composition analysis and automated grain boundary detection in backscattered electron (BSE) images of the silicon carbide (SiC) layer in TRISO particles for grain size characterization. Suggestions and guidelines for the application of these methods to TRISO fuel qualification are provided in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterizing the Electromagnetic Response of the NOvA Detectors

The NOvA Test Beam Program was commissioned to complement the full-scale NOvA experiment in its goal of measuring neutrino oscillations. The NOvA Experiment consists of a 300-ton Near Detector and a 14-kton Far Detector, both exposed to the same beam, which can be operated in neutrino or antineutrino mode from Fermilab at an off-axis angle of 14.6~mrad. These detectors can discriminate between $\nu_\mu$-CC and $\nu_e$-CC neutrino (or corresponding antineutrino) events, enabling appearance and disappearance measurements of these flavors across the \SI{810}{\kilo\meter} near-to-far detector baseline. From these measurements, the underlying parameters of the three-flavor PMNS oscillations framework are measured. The NOvA Test Beam uses identical technology to the full-scale detectors, but scaled down to 30~tons. It is exposed to a beam of charged particles closely matched to the daughter products of NOvA (anti)neutrino interactions in both energy and species. An instrumented beamline determines both particle momentum and species upstream of the NOvA detector, allowing for a crisp measurement of the NOvA detector response to these known inputs. This dissertation presents an analysis of the electromagnetic response of the NOvA hardware and establishes a framework for incorporating these results to enhance the physics reach of the experiment. Prior to this work, the electromagnetic energy response of the NOvA detector relied primarily on simulation-driven calibration together with a globally applied energy scale uncertainty. The measurements presented here provide direct test beam constraints on the detector response, enabling particle-dependent and potentially energy-dependent uncertainty models derived from controlled electromagnetic inputs.

Myers, Dalton Grant [U. Texas, Austin (main)] (ORC↗

3D-Reconstruction of Tau Neutrinos in LArTPC Detectors

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment currently under construction. DUNE will consist of two high-resolution neutrino interaction imaging detectors exposed to the world’s most intense neutrino beam, with the Near Detector at Fermilab and the Far Detector 1,300 km away in the Sanford Underground Research Facility in South Dakota, US. The high statistics and excellent resolution capabilities of DUNE's $^{40}$Ar detector will allow us to make precision studies of oscillation parameters capable of searching for CP violation in the lepton sector, testing interaction models, and studying phenomena that have until now, seemed too complex to measure, like $\nu_\tau$ detection and therefore, providing the completion of the 3-flavor neutrino paradigm. Knowledge of the $\nu_\tau$ detection can impact a broad spectrum of open questions. These include searching for non-standard neutrino interactions, constraining the unitarity of the PMNS matrix, searching for sterile neutrinos, and studying neutrino interactions. In the case of LArTPC data, the detector hits can be considered nodes in a graph, and the edges represent the spatial and temporal relationships between them. By using graph neural networks, it is possible to exploit these relationships and improve the accuracy of particle identification and reconstruction. During my presentation and specifically for tau neutrino reconstruction, I will show the effectiveness and reliability of our in-house developed graph neural network (GNN), NuGraph. This GNN classifies detector hits based on the particle type responsible for their production, assuring that the system accurately identifies and categorizes information based on its unique characteristics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fluidized-Bed Particles Scavenge Silicon Fines

Waste reduced, and silicon production rate improved. In new process silicon formed by thermal decomposition of SiH4. Part of silicon formed on silicon seed particles as result of surface chemical reaction. However, silicon formed by homogeneous reaction in gas phase tends to form aggregates of silicon atoms, which appear as fine particles (like dust). Believed that scavenging action of seed particles enables large fraction fines to be incorporated onto seed surface. This mode of growth confirmed by electron microscopy photographs.

Hsu, G. C.↗

Enhanced Catalytic Dechlorination of Polyvinyl Chloride (PVC) and H2 Production Enabled by Synergistic Gaδ+/Ga0 Active Sites in Liquid Metal Particles

Polyvinyl chloride (PVC) is ubiquitous yet challenging to recycle due to its tendency to thermally decompose above 250 °C, releasing toxic, corrosive chlorinated compounds, and its inability to melt. Here, we report a catalytic strategy for PVC upcycling at 160 °C using gallium liquid metal particles (Ga-LMP) featuring a dynamic Ga-GaOOH core–shell architecture. These catalysts enable concurrent dechlorination and hydrogen evolution, yielding up to 7% H2 (based on initial hydrogen atoms in PVC) along with a highly dechlorinated (>95%) carbonaceous solid and aqueous HCl. Mechanistic investigations combining X-ray photoelectron spectroscopy, infrared spectroscopy, solid-state NMR, inelastic neutron scattering, and ab initio molecular dynamics reveal a synergistic interplay between Gaδ+ sites in the GaOOH shell and metallic Ga0 in the core. Cationic Ga initiates C–Cl bond activation and HCl formation, while progressive reduction of the shell exposes Ga0 sites that promote C–H activation and H2 evolution. Control experiments with a Ga salt and bulk Ga liquid metal confirmed that neither oxidation state alone can achieve both transformations efficiently. This work establishes a dynamic dual-site paradigm for liquid metal catalysis, in which the in situ evolution and coexistence of oxidized and metallic species enable sequential and cooperative bond activation pathways. These findings provide a general design principle for novel liquid metal catalysts that target challenging polymer transformations under mild conditions.

Zingg, Benjamin [ORNL] (ORCID:0009000914530153)↗

Electrostatic Particle-In-Cell Code For Hypercube Computer

Code simulates two-dimensional motions of plasma particles in self-consistent electrostatic field and externally applied magnetic field developed for execution on Mark IIIfp hypercube computer. Based on generalization of one-dimensional particle-in-cell algorithm applicable to many different parallel computing architectures. Intermediate product of continuing effort to speed particle-in-cell computations by taking advantage of distributed-memory parallel computers like those of hypercube class.

Ferraro, Robert D.↗

A Model for Formation of Dust, Soil and Rock Coatings on Mars: Physical and Chemical Processes on the Martian Surface

This model is one of many possible scenarios to explain the generation of the current surface material on Mars using chemical, magnetic and spectroscopic data From Mars and geologic analogs from terrestrial sites. One basic premise of this model is that the dust/soil units are not derived exclusively from local rocks, but are rather a product of global, and possibly remote, weathering processes. Another assumption in this model is that there are physical and chemical interactions of the atmospheric dust particles and that these two processes create distinctly different results on the surface. Physical processes distribute dust particles on rocks and drift units, forming physically-aggregated layers; these are reversible processes. Chemical reactions of the dust/soil particles create alteration rinds on rock surfaces and cohesive, crusted surface units between rocks, both of which are relatively permanent materials. According to this model the dominant components of the dust/soil particles are derived from alteration of volcanic ash and tephra, and contain primarily nanophase and poorly crystalline ferric oxides/oxyhydroxide phases as well as silicates. These phases are the alteration products that formed in a low moisture environment. These dust/soil particles also contain a smaller amount of material that was exposed to more water and contains crystalline ferric oxides/oxyhydroxides, sulfates and clay silicates. These components could have formed through hydrothermal alteration at steam vents or fumeroles, thermal fluids, or through evaporite deposits. Wet/dry cycling experiments are presented here on mixtures containing poorly crystalline and crystalline ferric oxides/oxyhydroxides, sulfates and silicates that range in size from nanophase to 1-2 pm diameter particles. Cemented products of these soil mixtures are formed in these experiments and variation in the surface texture was observed for samples containing smectites, non-hydrated silicates or sulfates. Reflectance spectra were measured of the initial particulate mixtures, the cemented products and ground versions of the cemented material. The spectral contrast in the visible/near-infrared and mid-infrared regions is significantly reduced for the cemented material compared to the initial soil, and somewhat reduced for the ground, cemented soil compared to the initial soil. The results of this study suggest that diurnal and seasonal cycling on Mars will have a profound effect on the texture and spectral properties of the dust/soil particles on the surface. The model developed in this study provides an explanation for the generation of cemented or crusted soil units and rock coatings on Mars and may explain albedo variations on the surface observed near large rocks or crater rims.

Bishop, Janice↗

Exotic particles at the DUNE near detector from charged pion scattering

Fixed-target proton-beam experiments produce a multitude of charged pions that rescatter in the beam dump. These charged pion scattering events can be an additional irreducible source of exotic particles which couple to photons or hadrons. We analyze the sensitivity of the DUNE near detector complex to millicharged particles (MCPs) and heavy axionlike particles (ALPs) with low-energy couplings to gluons. Using the framework of chiral perturbation theory, we demonstrate regimes of parameter space where the charged pion production channel dominates over previously considered production mechanisms for both MCPs and ALPs, thereby improving the sensitivity of DUNE to these new particles compared to previous studies. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗