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NASA NTRS2021

Synthesis and Characterization of Fe(III)-Fe(II)- Mg- Al Smectite Solid Solutions and Implications for Planetary Science

This study demonstrates the synergies and limits of multiple measurement types for the detection of smectite chemistry and oxidation state on planetary surfaces to infer past geochemical conditions. Smectite clay minerals are common products of water-rock interactions throughout the solar system, and their detection and characterization provides important clues about geochemical conditions and past environments if sufficient information about their composition can be discerned. Here, we synthesize and report on the spectroscopic properties of a suite of smectite samples that span the intermediate compositional range between Fe(II), Fe(III), Mg, and Al end-member species using bulk chemical analyses, X-ray diffraction, Vis/IR reflectance spectroscopy, UV and green-laser Raman spectroscopy, and Mössbauer spectroscopy. Our data show that smectite composition and the oxidation state of octahedral Fe can be reliably identified in the near infrared on the basis of combination and fundamental metal-OH stretching modes between 2.1–2.9 μm, which vary systematically with chemistry. Smectites dominated by Mg or Fe(III) have spectrally distinct fundamental and combination stretches, whereas Al-rich and Fe(II)-rich smectites have similar fundamental minima near 2.76 μm, but have distinct combination M-OH features between 2.24 and 2.36 μm. We show that with expanded spectral libraries that include intermediate composition smectites and both Fe(III) and Fe(II) oxidation states, more refined characterization of smectites from MIR data is now possible, as the position of the 450 cm–1 absorption shifts systematically with octahedral Fe content, although detailed analysis is best accomplished in concert with other characterization methods. Our data also provide the first Raman spectral libraries of smectite clays as a function of chemistry, and we demonstrate that Raman spectroscopy at multiple excitation wavelengths can qualitatively distinguish smectite clays of different structures and can enhance interpretation by other types of analyses. Our sample set demonstrates how X-ray diffraction can distinguish between dioctahedral and trioctahedral smectites using either the (02,11) or (06,33) peaks, but auxiliary information about chemistry and oxidation state aids in specific identifications. Finally, the temperature-dependent isomer shift and quadrupole splitting in Mössbauer data are insensitive to changes in Fe content but reliability differentiates Fe within the smectite mineral structure.

Valerie K Fox↗
NASA NTRSDate not supplied

Using Anharmonic PAH Vibrational Spectra to Simulate Fully Anharmonic Cascade Emission Spectra

In recent years, we have developed vibrational second-order perturbation theory (VPT2) approaches that can be applied to very large molecules, such as polycyclic aromatic hydrocarbon (PAH) molecules. One of the main difficulties in applying standard VPT2 methods to PAHs is the large number of Fermi resonances that occur, especially in the C-H stretching region of the infrared spectrum. In order to properly account for these resonances, it is necessary to set up resonance polyads for each irreducible representation of the symmetry point group to which the molecule belongs, and for specific wavenumber regions, such as the C-H stretching region. Diagonalization of the polyads allows us to determine vibrational band positions, the intensity sharing due to the resonances, and hence there will be many more vibrational bands present than there are C-H bonds. Using these data, a library of fully anharmonic temperature-dependent spectra, with proper treatment of polyad resonances, can be determined and subsequently used to model the cascade emission spectra of PAH molecules – the type of spectra directly observed by astronomers. The theoretical approach will be described, with comparison to experiment where possible, and the latest fully anharmonic PAH cascade emission spectra will be discussed.

Timothy J Lee↗
NASA NTRS2022

Reduction of Raman Spectroscopy Data for H2-CO2-Air Tubular Flame Measurements

An approach of reducing spontaneous Raman spectroscopy data, based on the matrix inversion method which logically removes undesired sources of the Raman scattering signals including cross-talk due to the signals from other species, is discussed. The approach contains extensive calibration of temperature-dependent system response. The Raman spectra of several cold and hot calibration flames and their resulting calibration matrix are elaborated. The structure of H2-CO2-air tubular flames, in terms of major species (CO2, O2, N2, H2O, and H2) concentrations and temperature, was successfully measured with the optical technique. The Raman spectra data used in this study are taken from a uniquely designed experimental apparatus – a tubular burner and Raman spectroscopy system at Vanderbilt University. The characteristic uncertainties for chemical species are approximately ±2% by mole fraction for hot products and ±0.5% for room temperature reactants. The approach described here for hydrogen/air tubular flames may be adapted to hydrocarbon/air tubular flames when other necessary major species, for example, CH4 and CO for methane/air tubular flame, are considered in the whole process.

Raman Spectroscopy↗
NASA NTRSDate not supplied

Maturation of Additive Manufactured Aerospace Alloys and Development of Mechanical and Thermophysical Properties for Space Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts have focused on the understanding of AM processes through design optimization, component fabrication, material characterization, testing, standards development, and infusion into propulsion development for flight applications. NASA and partners have matured commonly used aerospace alloys from various alloy families (Nickel, Steel, Iron, Aluminum, and Titanium) and AM processes. An extensive effort has been ongoing between NASA, industry partners, and academia to complete detailed AM process and heat treatment characterization, in addition to generating temperature-dependent mechanical and thermophysical properties. This presentation highlights the characterization and property results using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes among various alloys. In addition to commonly used alloys, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are launch vehicles, liquid rocket engines, advanced propulsion systems, advanced power systems, and in-space propulsion with high heat fluxes, high pressure, and that utilize propellants such as hydrogen, which can degrade alloys. This presentation will also discuss some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, and C-103. The results from these processes have demonstrated that AM can enable rapid development and new AM optimized alloys can yield higher performance. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, and microstructure characterization and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, can enable the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. This presentation provides a background and overview of these various common and AM-enabled alloys and processing developments including the initial effort related to metallurgical, mechanical, and thermophysical property studies. It also covers the latest advancement in the parallel component development, hot-fire testing, and future developments for these alloys.

Additive Manufacturing↗
NASA NTRSDate not supplied

Novel Test and Analysis Methodology for the Assessment of Joint under Re-entry Environment

Spacecraft thermal protection systems require unique approaches for design verification due to the extreme environments seen during space travel and atmospheric re-entry. In this work, unique considerations for design, analysis, and verification of a tiled heatshield design with material nonlinearity, material property temperature-dependency, material property rate-dependency, and geometric stress concentrations are presented. Such designs require a thorough application of the building block approach to derive appropriate material property datasets, and a novel application of analysis models to aid in the structural verification with testing. The custom application of material rate-dependency in finite element analysis software is presented as a means of leveraging the rate-dependent test data for the material property dataset. Because bonded tile heatshields contain so many design considerations and nonlinearities which often preclude the ability to easily achieve the requisite test factors in qualification testing, a novel sub-element test was developed that amplifies the stress singularity beyond flight conditions. The test achieves an over-test over flight stress conditions. The approach for sub-element coupon design can be extended to other bonded joint designs and can be used in aiding a qualification program.

Pavel Babuska↗
NASA NTRS2023

Temperature Effect on Silicate Melt-Sulfide-Metal Trace Element Partitioning in the Presence of Sulfur Under Reduced Conditions

The reduced nature of Mercury, enstatite chondrites, and the aubrite parent bodies (APB) have raised many questions regarding the geochemical behavior of typically lithophile, heat-producing, and rare-earth elements (REE) in magmas at low oxygen fugacity (fO2). Due to decreasing O availability at these low fO2, and an abundance of S(sup 2(-)), sulfur (S) acts as an important anion that changes the partitioning behavior of many elements and modifies the physical properties of silicate melts. Preliminary observations suggest that major and minor elements exhibit different geochemical affinities in highly reduced, S-rich systems compared to terrestrial rocks. The speciation and bonding environment of S, dictated by P/T/fO2 conditions, may strongly influence the degree to which S affects partitioning behavior. Here we investigate the partitioning behavior of major, minor, and trace elements between silicate melt, sulfide melt, and metal as well as the coordination chemistry of S in highly reduced silicate melts. Our work is focused on investigating solely the entropy-dependent temperature effect on partitioning of elements for which we currently have MESSENGER data (K, Na, Th, U, Si, Mg, Fe, Ti, Ca, Al, Cr, Mn, S, Cl) as well as a host of geochemically relevant trace elements such as REEs (P, Co, Ni, Mo, Ce, Nd, Sm, Eu, Gd, Dy, Yb). Previous studies in which temperature, pressure, and fO2 were co-varied found that as fO2 decreases, heat-producing elements U and Th become more chalcophile, while K becomes less chalcophile. Concurrently, nominally lithophile elements Mg and Ca become more chalcophile and were observed as minor elements in exsolved sulfides and bonded with S species in silicate melt. These studies, however, could not disentangle entropic effects from changes in the fO2. New temperature-dependent partitioning data from our work will be used to determine which elements are most likely to retain their lithophile character and hence be incorporated into silicates, and which elements are likely contained within the sulfide (chalcophile) and metal core (siderophile), setting the stage for the thermal and magmatic evolution of reduced planetary bodies.

B A Anzures↗
NASA NTRSDate not supplied

Fractionation of Iron and Titanium Isotopes By Ilmenite and the Isotopic Compositions of Lunar Magma Ocean Cumulates

Basaltic volcanism on the Moon produced low- and high-Ti mare basalt suites that are also distinct with respect to their iron, titanium, and magnesium iso- topic compositions. Here, the equilibrium fractionation of Fe and Ti isotopes between ilmenite and melt was experimentally investigated in order to evaluate the role of ilmenite in generating the isotopic compositional variability among the lunar mare basalts. Ilmenite crystallization experiments were conducted using two bulk compositions: an ilmenite-saturated basaltic andesite and an ilmenite-saturated Apollo 14 black glass, and the Fe and Ti isotopic compo- sitions of the experimental ilmenites and glass (quenched melt) were analyzed using solution MC-ICPMS after hand-picking. Additionally, Nuclear Resonant Inelastic X-ray Scattering (NRIXS) measurements on synthetic ilmenite were conducted and compared to previous NRIXS measurements on synthetic lunar glasses in order to derive temperature-dependent equilibrium ilmenite-melt Fe isotopic fractionations. Experimentally determined ilmenite-melt fractionations were then incorporated into a lunar magma ocean crystallization model that tracks the major element and isotopic compositional evolution of lunar magma ocean cumulates and residual liquid. There is good agreement between the Fe equilibrium isotopic fractionation measured by NRIXS and the laboratory equili- bration experiments, and we find that the isotopic fractionation is sensitive to il- menite compositional differences (0 vs. 10% Fe3+). Further, the light Ti isotopic composition of ilmenite relative to the melt (∆49Ti ilmenite-melt = −0.09 ± 0.03h at 1100°C) is consistent with the higher coordination of Ti in ilmenite relative to melts and results of previous studies. The modeled Ti isotopic compositions for lunar magma ocean cumulates display Ti isotopic variability sufficient to explain the low- and high-Ti mare basalt sources. However, the difference in Fe isotopic composition between the low- and high-Ti mare basalts cannot be attributed solely to ilmenite fractionation. Instead, Fe isotopic fractionation by additional products of lunar magma ocean crystallization, such as clinopy- roxene, is required to generate the inferred Fe and Mg isotopic variability in the lunar mantle. Alternatively, the Fe and Mg isotopic compositions of the lunar mare basalts may indicate Fe-Mg interdiffusion has occurred in the Ti- rich component of the mare basalt source regions via reaction between ilmenite cumulates and the olivine- and pyroxene-rich lunar mantle.

Kelsey Prissel↗
NASA NTRS2024

Exploring Standing and Reflected Slow-mode Waves in Flaring Coronal Loops: A Parametric Study Using 2.5D MHD Modeling

Abstract Recent observations of reflected propagating and standing slow-mode waves in hot flaring coronal loops have spurred our investigation into their underlying excitation and damping mechanisms. To understand these processes, we conduct 2.5D magnetohydrodynamic (MHD) simulations using an arcade active region model that includes a hot and dense loop. Our simulations allow for in-depth parametric investigations complementing and expanding our previous 3D MHD modeling results. We excite these waves using a large-amplitude, flow pulse applied at one footpoint of the loop in two distinct models as motivated by observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA). The first model (Model 1) incorporates classical compressive viscosity coefficient, while the second model (Model 2) adopts a 10-times enhanced viscosity coefficient. We obtain the following major results: (1) Our 2.5D MHD simulations reinforce previous conclusions derived from 1D and 3D MHD models that significantly enhanced viscosity is crucial for the rapid excitation of standing slow waves with damping times consistent with observations by Wang et al. (2015). (2)We uncover that nonlinearity in Model 1 delays the conversion of a reflected propagating wave into a standing wave. In contrast, Model 2 exhibits a much weak influence of nonlinearity on the excitation time of standing waves, thanks to the suppression of these effects by enhanced viscosity. (3) Our results reveal that the transverse temperature structure holds more influence on wave behavior than the density structure. In Model 1, increased loop temperature contrast significantly enhances wave trapping within the structure, mitigating the impact of temperature-dependent viscous damping. Conversely, in Model 2, the impact of temperature structure on wave behavior weakens in comparison to the effect of viscosity. (4) Model 1 displays evident nonlinear coupling to the fast and kink magnetoacoustic waves and pronounced wave leakage into the corona. Model 2 exhibits significantly weaker effects in this regard. Analyzing three observed wave events by SDO/AIA aligns with Model 2 predictions, providing further support for the substantial viscosity increase. Our 2.5D study unravels the complex interplay of wave-flow phenomena and nonlinear processes in coronal loops, extending our previous 1D modeling results to incorporate more realistic loop geometry. This provides insights into scenarios where 3D effects may be neglected, thereby enhancing our understanding of the intricate dynamics of the solar corona.

Tongjiang Wang↗
NASA NTRSDate not supplied

Thermoplastic Space Point Design (TSPD) Tall Tower Lunar Thermal Analysis

The Thermoplastics Development for Exploration Applications (TDEA) project seeks to advance NASA’s thermoplastic composites capabilities by developing structurally efficient joining solutions for large-scale space structures to support NASA’s future exploration missions. A key objective is to develop and understand advanced thermoplastic joining techniques relevant to space environments and applicable to unitized and/or reconfigurable composite structures. The TDEA project uses NASA Langley’s Tall Lunar Tower (TLT) concept as a target application for the design and development of in-space assembled thermoplastic composites. TLT is a 50-meter-tall tower constructed on the lunar surface near the south pole. The tower’s height at this location on the moon allows for extended durations of incident solar flux which can be used to generate power via photovoltaic arrays. The thermal environment present on lunar south pole represents a challenging environment for any space-based asset. This study provides an overview of the analysis techniques used to determine the temperature extremes, gradients, and timelines of a tall composite tower over a one-year duration at the Shackleton Connecting Ridge. The developed thermal model includes tower and lunar surface elements with anisotropic and temperature-dependent material properties and incorporates a solar vector orbit with time-varying solar flux. Study topics include: a comparison between the effects of simplified lunar surface topologies on thermal results, prediction of surface temperature values versus Lunar Reconnaissance Orbiter (LRO) flight data, and tower structural-thermal deformation.

Lunar↗
NASA NTRS2026

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics↗
DOE OSTI2024

Embedding Neural Thermal Scattering (NeTS) Modules in SERPENT for Higher Fidelity Advanced Reactor Analysis

When a neutron born in fission thermalizes to the order of $k$ $B$ $T$, it’s de-Broglie wavelength and energy approach the order of inter-atomic spacing and elementary lattice oscillations, respectively. $S$($a,β,t$) or the scattering law, uuantify these temperature-dependent crystallographic contributions to total cross section (or reaction rate). In a Monte Carlo analysis, cumulative distribution functions (CDFs) of $S$($a,β,t$) are loaded to memory from “A Compact ENDF” (ACE) files for stochastically selecting thermal scattered neutron trajectories. In this work, novel neural thermal scattering (NeTS) modules for $S$($a,β,t$) CDFs are designed, trained, serialized and embedded within SERPENT using Python’s limited C-API for on-the-fly deployment of crystalline graphite $S$($a,β,t$) sampling. Torchscript tracing and Numba just-in-time (JIT) compilation streamline neural inference on NVIDIA GPUs with CUDA libraries. Demonstrations of bare sphere thermalization of fast and thermal sources show excellent agreement between embedded NeTS in SERPENT and MCNP. With an explicit model of the reactor, NeTS can predict on-the-fly changes in TREAT neutron spectra as a function of local temperature, which can serve to improve transient and accident predictions in a multiphysics analysis framework. This framework can be further extended to account on-the-fly for changes in local graphitic microstructure to scattering cross sections, and outlines a novel coupling of modern machine learning with state-of-the-art reactor physics methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗
DOE OSTI2024

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage

Industrial process heating (IPH) accounts for approximately 70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately 1500 TWht (approximately 60%) of IPH demand is in the temperature range of 100-300. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. TES development has historically been dominated by technologies suitable for deployment with concentrating solar power (CSP). State-of-the-art thermal storage deployed commercially with power tower CSP plants uses a 60%/40% NaNO3/KNO3 molten salt and operates between temperatures of approximately 280 degrees Celsius and 570 degrees Celsius using a two-tank configuration. However, these nitrate salts are unsuitable for operation outside of this temperature range due to a high freezing point of approximately 220 degrees Celsius, and limits on high-temperature salt stability and corrosion resistance of containment alloys. Other materials being investigated for TES include those based on: (1) sensible energy storage (various molten salt compositions, inert solid particles, rocks or pebble beds, sulfur, water, concrete, graphite, etc.), (2) latent energy storage in materials that undergo solid-liquid phase change at relevant temperatures (organic materials for low-temperature applications, inorganic salts and/or metals for high-temperature applications), or (3) thermochemical energy storage (hydrides, hydroxides, carbonates, metal oxides, etc.). The application temperature and challenges pertaining to storage material and/or containment cost, energy density, long-term thermal and cyclic stability, and charge/discharge heat transfer effectiveness drive material selection for a given IPH or electricity generation application. Sulfur is a cheap commodity at $80/ton compared to $1100 - 1300/ton for conventional salts. When using a metric of storage cost per kWh, sulfur costs around 2-3 $/kWh. Previous sulfur TES development focused on high temperature (>600 degrees) concentrated solar power applications with sulfur encapsulated in pipes and flow of gaseous HTF (air) in the shell side. However, for lower-temperature IPH applications in the range of approximately 100-300 degrees Celsius Element 16 adopted a compact and scalable TES design with molten sulfur in the shell and HTF pipes submerged in the molten sulfur bath. The low-cost molten sulfur TES for dispatchable IPH has deployment potential for broad applications. The spatial and temporal evolution of the HTF and sulfur temperature is critical to the TES system performance, and thus detailed modeling can improve understanding of the performance and facilitate design improvements. Using high performance computing and computational fluid dynamics (CFD) a low-cost molten sulfur thermal energy storage (TES) system for industrial process heating (IPH) applications was developed. The unique challenges in CFD modeling of sulfur TES are the sharp property changes of sulfur relevant to the working temperatures. Above 159, liquid sulfur undergoes polymerization, and the viscosity of sulfur rapidly increases by several orders of magnitude between 159 degrees Celsius and 188 degrees Celsius, followed by a decrease in viscosity beyond 188 degrees Celsius due to thermal bound dissociation. In addition, various concentrations of H2S impurities can also modify sulfur viscosity. This numerical challenge is especially relevant to transient simulation of the sulfur TES charging and discharging processes as the extreme property variations limit the applicability of traditional heat transfer correlations. Transient CFD simulations including the temperature-dependent sulfur properties and geometric complexity of the TES design were used to predict the effect of natural convection during charging and discharging on the heat transfer process, sulfur temperature uniformity, charge/discharge rates, and performance of the storage devices. The CFD model was validated with experimental results for a full charge and discharge cycle. The work will show 3D and 2D simulation comparisons aimed to facilitate rapid design iterations and a machine learning based design optimization approach.

CFD↗
DOE OSTI2025

Developing a Nuclear Quality Assurance Compliant Design Methodology for Neutronic Analysis of Xe-100 Design

The primary objective of this work is to develop a design methodology compliant with nuclear quality assurance standards for the Xe-100 neutronic design verification studies. To achieve this, a Monte Carlo model of the Xe-100 reactor was constructed using the exclusion principle, transformation technique, and universe-based level specification following Idaho National Laboratory (INL) NQA level-1 compliant standards and an NQA-1 compliant version of MCNP6. The model encompasses the entire reactor core structures, including the upper plenum, core region, and lower plenum sections, along with all sub-components. The active core section was represented using the spectral regions, each comprising a particular fuel composition and temperature averaged over the considered zone, calculated by X-energy using Very Superior Old Programs (VSOP). Additionally, a component-wise temperature map was implemented into the model, not only for the core region but also for the structural components. Temperature-dependent cross-section libraries, along with thermal scattering law libraries, generated using INL NQA-1 compliant version of NJOY21, were utilized for each isotope in the burnt fuel and the structural materials. Furthermore, the volume of each modeled component was estimated using a stochastic approach with the ray tracing method in MCNP and criticality calculations were performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗
DOE OSTI2025

Investigating Radiation-Induced Actinide Species in Solution

Used nuclear fuel (UNF) separation techniques that strive to separate radiotoxic americium (Am) from trivalent lanthanide fission products through oxidation state control have increased research efforts surrounding Am(V) and Am(VI). However, equivalent knowledge of the tetravalent state, Am(IV), has remained elusive, particularly in conditions more representative of UNF reprocessing, i.e., in concentrated nitric acid (HNO3). With this in mind, we have used electron pulse radiolysis to study the radiation-induced redox reaction of Am(III) with the oxidizing nitrate radical (NO3?) in 6 M HNO3: Am(III) + NO3? ? Am(IV) + NO3? . These experiments enabled us to observe the growth and decay of Am(IV) in a concentrated acidic solution for the first time. The transient Am(IV) species was found to have a lifetime of ~16 µs?sufficiently long-lived to play a critical mechanistic role in UNF reprocessing systems. Additionally, we performed the first-ever temperature-dependent kinetics study of an actinide element, elucidating unprecedented Arrhenius and Eyring activation parameters for the reaction of Am(III) with NO3?. This new knowledge provides much-needed molecular-level insights into the radiation-induced behavior of Am.

actinide↗
DOE OSTI2025

Ceramography and Thermal Modelling of Irradiated TRISO Particles using BISON

This study presents a comprehensive analysis of irradiated TRISO fuel particles from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program conducted at the Advanced Test Reactor (ATR) as part of my internship. Failure Analysis using high-resolution microscopy was performed to characterize mechanisms in TRISO particle layers, including the kernel, buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) coatings. Failure modes were systematically classified. Thermal conductivity properties of each TRISO layer were evaluated through experimental measurements and computational models for use in BISON finite element code. Experimental thermal conductivity values ranged from 0.5 W/m·K for the buffer layer to 168 W/m·K for SiC, while BISON simulations provided averaged values of 0.57 W/m·K (buffer), 4.0 W/m·K (PyC layers), and 15.95 W/m·K (SiC). Temperature-dependent correlations from PARFUME were implemented for kernel thermal properties.

BISON↗
DOE OSTI2025

Minimization of thermal deformation in crystal optics for high repetition-rate FEL

Minimizing thermal deformation in X-ray crystal optics is crucial for preserving coherence and wavefront in high-repetition-rate free-electron lasers (FELs). This study presents two approaches to reduce pulse-by-pulse transient thermal deformation in diamond crystals used in cavity-based X-ray FELs (CBXFELs): (1) cryogenic cooling with liquid nitrogen (LN₂), and (2) second-order correction via focusing optics. We revisit the temperature-dependent thermal-mechanical properties of diamond and silicon, implement a finite-element analysis (FEA) method to accelerate convergence to a quasisteady-state regime. Results show that LN₂-cooled diamond crystals meet the stringent deformation requirement of less than 15 pm RMS for the pulse at mJ scale at 1 MHz repetition frequency, and up to 1.5 mJ for 100 kHz. Second-order correction by using focusing elements within the cavity can reduce the impact of thermal deformation for both liquid nitrogen and water cooling.

free electron laser↗