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DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Anion exchange membranes based on (3-acrylamidopropyl) trimethylammonium chloride (APTA) and phenyl Acrylate: Impact of crosslinker and crosslinker content on physiochemical properties and transport behavior of acetate and formate

CO 2 reduction cells are innovative devices that convert CO 2 into valuable chemicals, such as formate (OFm - ) and acetate (OAc - ), at the cathode. One of the key challenges in these devices is the development of ion exchange membranes that enable the transport of charge carriers between electrodes while minimizing the transfer of CO 2 reduction products. This study focuses on the preparation and characterization of crosslinked anion exchange membranes (AEMs) made of phenyl acrylate (PA) and (3-acrylamidopropyl) trimethylammonium chloride (APTA), crosslinked with either poly(ethylene glycol) diacrylate (PEGDA) or N,N’-methylenebisacrylamide (MBAA). Here, the membranes are characterized to understand their physiochemical properties and corresponding transport behavior through characterization of water volume fraction, mechanical properties, ionic conductivity, ion exchange capacity, water contact angle, glass transition temperature as well as their permeability and solubility to formate and acetate. MBAA crosslinked membranes exhibit higher Young’s modulus and lower strain at break compared to PEGDA-crosslinked membranes, which is attributed to their shorter chain length. Within a series of membranes of varied comonomer content, for either PEGDA or MBAA as crosslinker, permeabilities generally follow free volume theory (increasing permeability with increasing water content where water content increases with decreasing crosslinker content). Interestingly, for membranes with different crosslinkers but analogous water volume fraction significant differences (∼2 orders of magnitude) in permeability are observed which we attribute to differences in chain mobility as characterized through the glass transition temperature.

25 ENERGY STORAGE↗

DOE OSTI2024

Strain phase equilibria and phase‐field method of ferroelectric polydomain: A case study of monoclinic K x Na 1 − x NbO 3 thin films

Abstract Knowledge of the thermodynamic equilibria and domain structures of ferroelectrics is critical to establishing their structure–property relationships that underpin their applications from piezoelectric devices to nonlinear optics. Here, we establish the strain condition for strain phase separation and polydomain formation and analytically predict the corresponding domain volume fractions and wall orientations of, relatively low symmetry and theoretically more challenging, monoclinic ferroelectric thin films by integrating thermodynamics of ferroelectrics, strain phase equilibria theory, microelasticity, and phase‐field method. Using monoclinic K x Na 1 − x NbO 3 (0.5 < x < 1.0) thin films as a model system, we establish the polydomain strain–strain phase diagrams, from which we identify two types of monoclinic polydomain structures. The analytically predicted strain conditions of formation, domain volume fractions, and domain wall orientations for the two polydomain structures are consistent with phase‐field simulations and in good agreement with experimental results in the literature. The present study demonstrates a general, powerful analytical theoretical framework to predict the strain phase equilibria and domain wall orientations of polydomain structures applicable to both high‐ and low‐symmetry ferroelectrics and provide fundamental insights into the equilibrium domain structures of ferroelectric K x Na 1 − x NbO 3 thin films that are of technology relevance for lead‐free dielectric and piezoelectric applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.

25 ENERGY STORAGE↗

DOE OSTI2025

Deciphering the small-angle scattering of polydisperse hard spheres using deep learning

We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard sphere system. We use a variational autoencoder-based neural network to learn the bidirectional mapping between the scattering function and the system parameters, including the volume fraction and polydispersity. Such that the trained model serves both as a generator that produces a scattering function from the system parameters and an inferrer that extracts system parameters from the scattering function. We first generate a scattering dataset by carrying out molecular dynamics simulations of the polydisperse hard spheres modeled by the truncated-shifted Lennard-Jones model, then analyze the scattering function dataset using singular value decomposition to confirm the feasibility of dimensional compression. Then, we split the dataset into training and testing sets and train our neural network on the training set only. Our generator model produces a scattering function with significantly higher accuracy compared to the traditional Percus–Yevick approximation and β correction, and the inferrer model can extract the volume fraction and polydispersity with much higher accuracy than traditional model functions.

Ding, Lijie [ORNL] (ORCID:0000000227454606)↗

DOE OSTI2024

Bulk high-temperature superconductivity in pressurized tetragonal La 2 PrNi 2 O 7

The Ruddlesden–Popper (R–P) bilayer nickelate, La 3 Ni 2 O 7 , was recently found to show signatures of high-temperature superconductivity (HTSC) at pressures above 14 GPa . Subsequent investigations achieved zero resistance in single-crystalline and polycrystalline samples under hydrostatic pressure conditions. Yet, obviousdiamagnetic signals, the other hallmark of superconductors, are still lacking owing to the flamentary nature with low superconducting volume fraction. The presence of a new 1313 polymorph and competing R–P phases obscured proper identification of the phase for HTSC. Thus, achieving bulk HTSC and identifying the phase at play are the most prominent tasks. Here we address these issues in the praseodymium (Pr)-doped La 2 PrNi 2 O 7 polycrystalline samples. We find that substitutions of Pr for La efectively inhibit the intergrowth of diferent R–P phases, resulting in a nearly pure bilayer structure. For La 2 PrNi 2 O 7 , pressure-induced orthorhombic to tetragonalstructural transition takes place at P c ≈ 11 GPa, above which HTSC emerges gradually on further compression. The superconducting transition temperatures at 18–20 GPa reach $T$ $^{onset}_{c}$ = $82.5$ $K$ and $T$ $^{zero}_{c}$ = $60$ $K$, which are the highest values, to our knowledge, among known nickelate superconductors. Importantly, bulk HTSC was testified by detecting clear diamagnetic signals below about 75 K with appreciable superconducting shielding volume fractions at a pressure of above 15 GPa. Further, our results not only resolve the existing controversies but also provide directions for exploring bulk HTSC in the bilayer nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗

DOE OSTI2025

Analysis of the weighted shifted boundary method for the Poisson and Stokes problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L2-error estimates can also be derived.

Approximate domain boundaries↗

DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗

DOE OSTI2025

Porosity, swelling, and composition evolution in high-burnup monolithic U-Mo fuel

The microstructural progression of very high-burnup (>8 × 10 21 fissions/cm 3 ) monolithic uranium-molybdenum (U-10wt.%Mo) was analyzed, providing crucial insights into the behavior of post-recrystallized nuclear fuel, where scant data exists. Three focused ion beam cuboids sourced from a fuel plate with varying local burnups of 8.86 × 10 21 , 9.05 × 10 21 , and 9.36 × 10 21 fissions/cm 3 were characterized. The porosity and composition of the samples were evaluated to characterize the evolution of the microstructure as a function of fission density and different locations on the fuel plate, while simultaneously isolating plate-specific parameters such as Zr diffusion barrier thickness, hot-isostatic-pressing conditions, enrichment, and reactor conditions. The porosity was segmented, and the three-dimensional distribution of the porosity was extrapolated from the two-dimensional segmentation. The composition was assessed and quantified using energy-dispersive X-ray spectroscopy areal mapping. The porosity fraction increased as a function of the burnup from 27.77±0.51, 35.12±1.54, and 37.71±0.44 % for 8.86 × 10 21 , 9.05 × 10 21 , and 9.36 × 10 21 fissions/cm 3 , respectively. When compared to literature, the porosity volume fraction plateaus at burnups greater than 6 × 10 21 fissions/cm 3 , while the pore size grows linearly as a function of fission density. The number of large pores increased in number density as a function of burnup, while the smallest pores (<0.3 µm) increased up to 9.05 × 10 21 fissions/cm 3 , followed by a decrease at 9.36 × 10 21 fissions/cm 3 . The delamination and cracking in the fuel plate propagated through an interconnected porosity sublayer identified ∼5 µm from the diffusion barrier. The local swelling of the specimens was within or near the prediction bounds of the Robinson-Williams model for local swelling. The fission products, strontium, barium, cerium, and cesium, precipitated into the pores, while neodymium accumulated adjacent to the pores. Furthermore, these findings have direct implications for the development of fuel performance codes and the accurate documentation of the microstructure evolution in high burnup U-Mo, thus enhancing the safety and efficiency of nuclear fuel usage.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Influence of Rigidity–Hydration Coupling on Size-Dependent Diffusion in Hydrated Polymer Membranes

Selective ion transport in polymer membranes depends critically on how penetrant motion couples to polymer dynamics and hydration. Yet, the mechanistic interplay between polymer rigidity, water content, and penetrant size remains poorly understood, especially in the regime where the penetrant diameter, polymer Kuhn length, and correlation length are comparable. Here, we employ coarse-grained molecular dynamics simulations to systematically investigate penetrant diffusion in hydrated polymer networks across a broad range of water volume fractions, chain rigidities, and penetrant sizes. The results reveal a transition from a decoupled regime, where small penetrants diffuse nearly independently of polymer relaxation, to a coupled regime in which large penetrants require cooperative polymer motion for transport. Increasing polymer rigidity amplifies the sensitivity of diffusivity to hydration, particularly at low water content, leading to pronounced deviations from Stokes−Einstein scaling. Comparison with scaling theories and free-volume models shows that classical nanoparticle-based frameworks fail to capture this intermediate regime. To address this gap, we extend the Yasuda model to incorporate polymer rigidity through a single parameter that quantifies the dynamic contribution of chain stiffness to free-volume fluctuations. The resulting model collapses diffusivity data across all sizes, water contents, and rigidities, providing a unified description of penetrant transport in hydrated polymer matrices. Furthermore, these findings establish polymer rigidity as a key, tunable determinant of diffusion and offer a framework for interpreting size-dependent transport in ion-selective membranes.

diffusion↗

DOE OSTI2025

Soot formation and precursor chemistry in Counterflow flames of aviation fuel surrogates

To meet market demands, the aviation sector is interested in utilizing drop-in Synthetic Aviation Turbine Fuels (SATF), either as neat fuels or in blends with conventional Jet A. SATF currently approved in standard specifications may have lower aromatic content with significant fractions of normal, branched, and cyclo-alkanes. Fundamental studies on soot formation from aviation fuels (Jet A, SATF) and their surrogate components are essential to understand how fuel composition influences soot and soot precursor formation. Here, this study reports new measurements of polycyclic aromatic hydrocarbons (PAH) and soot in counterflow diffusion flames (CDFs) of aviation fuel surrogates. Both intrusive and non-intrusive diagnostics are employed to determine the profiles of temperature, gas phase species, PAHs (up to C16), and soot volume fraction (SVF) in CDFs of iso-octane and surrogate mixtures. These measurements shed light on the transition of soot precursors to primary soot particles. In addition to serving as a common surrogate component in Jet A surrogate mixtures, iso-octane is a template species for larger, less volatile branched alkanes found in SATF mixtures. The newly developed Lawrence Livermore National Laboratory (LLNL) PAH and soot model successfully captures temperature, precursor species, and SVF profiles for the mixtures and conditions discussed in this work. Finally, a high-fidelity surrogate for Jet A is proposed that matches targeted physical and chemical properties well, while leveraging the wide range of candidate fuel molecules available in the LLNL detailed chemical model. The proposed surrogate formulation is validated against newly acquired measurements of the surrogate and literature measurements of Jet A. These new experiments and simulations provide critical insights into the PAH and soot formation from aviation fuels. Reaction pathways which require further investigation are highlighted, such that future work may bridge the remaining quantitative gaps in predicting soot formation from aviation fuel surrogates and surrogate components.

Aviation fuels↗

DOE OSTI2025

The effect on soot and its gas precursors of doping ethylene with 2,2,4,6,6-pentamethyl-heptane in the nitrogen-fuel stream of a laminar non-premixed Planar Mixing Layer Flame (PMLF)

Synthetic Aviation Turbine Fuels (SATFs) are promising for reducing soot emissions from the aviation sector and diversifying Jet Fuel (JF) sources. Accurately predicting the combustion and emissions behavior of SATFs (and other JFs) necessitates robust experimental databases to elucidate the chemistry of long-chain iso-paraffins, which can compose up to two-thirds of SATF blends and whose behavior is considered to be well-represented by that of iso-dodecane isomers. Here, this study characterizes two laminar non-premixed Planar Mixing Layer Flames (PMLFs) with mild soot loads fueled by nitrogen-diluted ethylene, pure and doped with 2,2,4,6,6-pentamethyl-heptane, respectively. The two PMLFs have the same stoichiometric mixture fraction and total hydrocarbon mole fraction in the fuel stream (X F,F =X C2H4,F +X C12H26,F = 0.260), resulting in nearly the same maximum temperature (T max ≈1800 K) and simple identification of the effects of doping. Importantly, any horizontal PMLF cross-section has a self-similar structure that can be modeled as an equivalent One-Dimensional Counterflow Flame (1D-CF) with vanishingly small strain rate (a). The cross-section at a Height Above the Burner (HAB) of 50 mm is characterized in terms of C 0 -C 18 gas species using capillary sampling followed by GC-MS analyses. Laser-Induced Emission Spectroscopy (LIES) quantifies the soot volume fraction (ƒ v ) profiles at HAB=25 and 50 mm where Elastic Laser Light Scattering (E-LLS) is performed to determine the a of the equivalent 1D-CFs and the profile of the E-LLS equivalent diameter ( d 6,3 ) of soot. The substitution of 1500 ppm of ethylene with 2,2,4,6,6-pentamethyl-heptane causes an increase of ≈1.5 in the concentrations of several polycyclic aromatic hydrocarbons and fv. Concurrently, the measured d 6,3 doubles in the oxidizer stream, yet remains the same in the fuel stream, at HAB=50 mm. Instead, at HAB= 25 mm, the iso-dodecane doping does not affect the d 6,3 profile in either stream. The experimental results partially validate the chemical reactions and soot formation kinetic model developed at Lawrence Livermore National Laboratory and provide directions to further improve its predictions.

Iso-dodecane (2,2,4,6,6-Pentamethyl-Heptane)↗

DOE OSTI2024

Crystallization of Bottlebrush Statistical Copolymers of Polystyrene and Poly(ethylene oxide)

Here, bottlebrush statistical copolymers (BSCPs) with poly(ethylene oxide) (PEO) and polystyrene (PS) side chains grafted to a polynorbornene (PNB) backbone were synthesized by ring-opening metathesis polymerization (ROMP). The impact of the glassy PS side chains on the crystallization of the PEO side chains as a function of the backbone length, grafting densities, and fraction of the PS and PEO side chains is described. The bottlebrush architecture, where the side chains are anchored to the backbone, inherently constrains the mobility of PEO. Compared with the bulk crystallization temperature of PEO, the higher glass transition temperature of PS places further constraints on PEO crystallization. The limited mobility of PEO leads to cold crystallization behavior during heating. Reduced grafting densities, in turn, reduce side-chain crowding, leading to less extended pendant structures. The degree of crystallinity of PEO was found to decrease at lower grafting densities to a point where crystallization was not observed. The average distance between bottlebrush backbones increased linearly with the backbone length, suggesting that the backbone forms a distinct mesodomain. For BSCPs with asymmetric volume fractions of PS and PEO side chains, the degree of crystallinity of PEO increases with a change from cold crystallization to normal nucleation and growth during cooling, as a result of reduced constraints on PEO mobility by the glassy PS side chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗

DOE OSTI2024

Effect of Heat Treatment on Microstructure and Mechanical Property of 316L Stainless Steel Produced by Laser Powder Bed Fusion

The advanced non-light water reactor designs (Gen IV reactors), including molten salt/ very high temperature/ sodium-cooled and lead-cooled fast reactors, typically operate at higher temperatures and more extreme radiation conditions than light water reactors. An intrinsic part of the deployment and progress of Gen IV reactor designs is selecting the most suitable structural material for a specific application. Additive manufacturing (AM), a fairly new process of making physical, three-dimensional objects from a computer design file, is going to completely change the way of design, build and certify nuclear systems. It offers a range of opportunities to produce complex geometries from existing materials, offers new routes for processing of previously difficult to process materials, allows for design of new high-performance materials, and finally facilitates hybridization of dissimilar materials. This emerging technology has successfully produced cars, wind turbine blade molds and even live cells. It could also open up big opportunities for the nuclear industry to quickly deploy technologies at a fraction of the cost. So far, AM techniques have been preliminarily applied in the field of nuclear reactors, including the classical parts such as the pressure vessel of a small reactor with 508-III steel, the bottom nozzle of a fuel assembly with 304L steel, the fuel cladding with zirconium alloy and the integrated impeller of a pump and the multi-channel valve body with 316L steel [6,7]. The AM applications for operating nuclear reactors started in auxiliary plant components and have slowly migrated to metallic reactors and core components, but many of these are not safety critical components. Although many parts used for nuclear reactors have been fabricated by AM techniques, practical applications in engineering are still a long way off due to the uncertainty factors focused on the processing, material properties, analysis methods and application standards, which feeds the safety and life-cycle of the nuclear reactor. Due to rapid, repeated heating and cooling during production, a high dislocation density was present in the AM material. This microstructure feature is unstable at elevated temperature while high temperature is one of the typical operation environments for nuclear reactors. Thus, it is important to understand the thermal effect on the microstructure of AM material. The objectives of this study are to investigate the effect of heat treatment on the microstructure and mechanical properties of 316L stainless steel produced by laser powder bed fusion additive manufacturing, and to determine an appropriate heat treatment practice that will be applied to the lightweight AM lattice-structured material with the same chemistry. The heat treatment study consisted of annealing the samples at a temperature range of 800 to 1200 oC with a 50 oC increment for different times (1-24 hours), followed by vacuum or air cooling. Microstructural characterization was carried out by Scanning Electron Microscope (SEM). Grain size and crystallographic orientation were investigated by Electron Backscatter Diffraction (EBSD). Vickers hardness tests with a 0.5 kg load were employed to determine the hardness of samples after different heat treatments. After heat treatment, the random crystallographic orientation was preserved, and the volume fraction of high-angle grain boundaries (grain boundary misorientation =15 oC) remained the same. The dislocation density decreased with annealing temperature due to recovery. The fine subgrain structures in the as-printed specimen were quite stable up to 1200 oC. Minimal recrystallization was observed up to 1200 oC. Recrystallization initiated only after 8.5 hours at 1200 oC. The SEM images did not show obvious dependence of microstructure on cooling rate. The hardness of the specimens decreased with increasing annealing temperature as a result of the decrease in dislocation density. It is interesting to note that the AM material showed very similar hardness to the wrought material when annealing at similar temperature, although the microstructures are very different. Annealing at 1050 oC for 1 hour followed by air cooling was selected as the heat treatment procedure for the lattice designed lightweight AM 316L material.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Structural Phase Separation and Enhanced Superconductivity in La 1.875 Ba 0.125 CuO 4 Under Uniaxial Strain

Strain engineering has attracted significant attention in recent years due to its capability in tuning lattice and electronic structures of quantum materials. Using moderate uniaxial compressive strain, structural phase separation is induced in the low-temperature phase of x = 1/8 La 2-x Ba x CuO 4 (LBCO) single crystals. These structures are low temperature tetragonal (LTT), low temperature less orthorhombic (LTLO), and a plastically deformed nano-domain structure (PDNS), comprised of few-nanometer-sized orthorhombic domains within an amorphous matrix. These three structures exhibit distinct superconducting behaviors. The volume fraction of the LTT structure is suppressed with increasing strain, while its superconducting transition temperature increases and broadens. The LTLO structure exhibits a sharp superconducting transition above 32 K, which increases up to ≈ 36 K at maximum strain. The PDNS phase exhibits a very broad superconducting transition and persists even after removing the strain. This study illustrates the sensitivity of superconductivity to the structure of the LBCO sample near its stripe instability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗