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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microstructure, Thermal, and Mechanical Properties Relationships in U and UZr Alloys (Final Report)

Uranium-zirconium (U-Zr) alloys are candidate fuel systems for transmutation based reactors that can be used to burn long-lived minor actinides and fission products in fast spectrum reactors. Metallic fuels have also been gaining more recent attention for applications as accident tolerant fuels, as well as for use in small modular reactors. This research focused on a “science-based” approach to capture the connections between U and U-Zr alloys’ three-dimensional (3-D) microstructure, thermal properties, and mechanical properties through closely coordinated experiments and modeling efforts from the unirradiated to the irradiated fuels. Advanced characterization and modeling techniques were used to understand irradiation-induced microstructural evolution and its direct impact on the thermal and mechanical properties of U and U-Zr fuel. Closely coordinated experiments and modeling were performed to provide crucial data that does not currently exist. Overall, this research spanned multiple length and time scales within the models and experiments. The scope of the research encompassed the understanding of the irradiation effects in U and various U-Zr alloys with particular attention paid to three task areas: (1) microstructural evolution, (2) in-situ/ex-situ thermal and mechanical properties, and (3) multiscale modeling connections to microstructure, thermal, and mechanical properties. This research resulted in (1) the 3-D characterization of neutron irradiated U-Zr fuel in multiple phase regions to better understand fission gas swelling and constituent redistribution, (2) development of a microstructural model linking thermal and mechanical properties via in situ Raman and nanoindentation, (3) and mesoscale phase field modeling was coupled with the AEH method in the MOOSE framework was used to calculate the effective thermal conductivities of U-Zr fuels consisting of α-U and δ-UZr 2 heterogeneous microstructures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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 OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2019

Prediction of Probabilistic Detonation Threshold via Millimeter-Scale Microstructure-Explicit and Void-Explicit Simulations

We present an approach and relevant models for predicting the probabilistic shoc-to-detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure-explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro-1,3,5,7-tetranitro-1,2,3,5-tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical-thermal-chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank-ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run-distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Multilayered microstructures with shape memory effects for vertical deployment

This paper presents a fabrication and characterization of multilayered microstructures with shape memory effects enabling large vertical deployment under electro-thermal actuation. Our previous research demonstrated vertical deployment of such microstructures by the effect of thermal mismatch. Development of equiatomic NiTi layers in the multilayered microstructure is investigated further for shape memory effects. Multilayered microstructures are built by sputtered NiTi layers and a lift-off process. Negative photoresist ma-N1420 enables clean lift-off of 500 nm thick NiTi layers by forming a significant undercut profile after development. The parametric study on co-sputter powers for Ti and Ni 50 Ti 50 targets suggests that 100 W RF on Ti target and 200 W DC on Ni 50 Ti 50 target can deposit Ni 49.62 Ti 50.38 layers. X-Ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were used to study the crystal structures and surface topography of NiTi layers. XRD results of post-annealed Ni 49.62 Ti 50.38 layers show coexistence of austenite and martensitic phases at room temperature, suggesting that the transformation temperature of such NiTi layers should be approximate 20 °C. The surface topography of Ni 49.62 Ti 50.38 layers reveals substantial increase of surface roughness at ambient conditions after the annealing. Experimental verification of the multilayered microstructure for vertical deployment was carried out by Signatone Probe Station and Dual Scanning Electron Microscope/Focused Ion Beam (SEM/FIB) system. Finally, a vertical deployment of the two-dimensional (2D) multilayered microstructures for three-dimensional (3D) can be detected by applying a constant voltage of 0.04 V, and the expected 3D deployment displacement is enlarged from 2 μm to 10 μm by introducing the shape memory effect.

42 ENGINEERING↗
DOE OSTI2020

Microstructural development in DED stainless steels: applying welding models to elucidate the impact of processing and alloy composition

Austenitic stainless steel microstructures produced by directed energy deposition (DED)are analogous to those developed during welding, particularly high energy density welding. To better understand microstructural development during DED, theories of microstructural evolution,which have been established to contextualize weld microstructures, are applied in this study to microstructural development in DED austenitic stainless steels. Phenomenological welding models that describe the development of oxide inclusions, compositional microsegregation, ferrite,matrix austenite grains, and dislocation substructures are utilized to clarify microstructural evolution during deposition of austenitic stainless steels. Two different alloys, 304L and 316L, arecompared to demonstrate the broad applicability of this framework for understanding microstmctural development during the DED process. Despite differences in grain morphology and solidification mode for these two alloys (which can be attributed to compositional differences),similar tensile properties are achieved. It is the fine-scale compositional segregation and dislocation structures that ultimately determine the strength of these materials. The evolution of microsegregation and dislocation structures is shown to be dependent on the rapid solidification and thermomechanical history of the DED processing method and not the composition of the starting material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Boundary characterization using 3D mapping of geometrically necessary dislocations in AM Ta microstructure

Additive manufacturing (AM) of high strength metallic materials produces microstructures and defects that deviate substantially from those created through conventional manufacturing methods. It has recently been demonstrated that with application of extreme energy densities, a high-temperature refractory metal, tantalum (Ta), can be printed to a fully dense state with exceptionally low porosity. Here we employ a combination of three-dimensional electron backscattered diffraction (EBSD) TriBeam technology and crystallographic geometrically necessary dislocation (GND) theory to characterize the microstructure and defect boundaries of this unusual AM product. Two-dimensional (2D) EBSD and these three-dimensional (3D) measurements indicate that the microstructure of AM Ta is highly oriented <111> along the build direction, yet at the same time contains large crystallographic orientation gradients that span mm’s across the build. Crystallographic GND density analysis of the 3D microstructure reveals that highly misoriented subboundaries exist within this strongly textured microstructure that have large dislocation densities of 1×10 16 m –2 , just as large as those comprising the high-angle grain boundaries (HAGBs) in the same material. The 3D crystallographic GND density mapping reveals these subboundaries are part of a complex, finely spaced network that extends throughout the entire microstructure. Here, the orientation of these boundaries can be related to the scan strategy used during printing. TEM measurements corroborate an extremely high dislocation density at the microscale and indicate a cell-like dislocation network structure existing in the AM Ta at the sub-μm scale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructural Development in Inconel 718 Nickel-Based Superalloy Additively Manufactured by Laser Powder Bed Fusion

Excellent weldability and high temperature stability make Inconel 718 (IN718) one of the most popular alloys to be produced by additive manufacturing. Here in this study, we investigated the effects of laser powder bed fusion (LPBF) parameters on the microstructure and relative density of IN718. The samples were fabricated with independently varied laser power (125 - 350W), laser scan speed (200 - 2200 mm/s), and laser scan rotation (0° - 90°). Archimedes’ method, optical microscopy, and scanning electron microscopy were employed to assess the influence of LPBF parameters on the relative density and microstructure. Optimal processing windows were identified for a wide range of processing parameters and relative density greater than 99.5% was achieved using volumetric energy density between 50 and 100 J/mm3. Microstructural features including melt pool geometry, lack of fusion defect, keyhole porosity, and sub-grain cellular microstructure were examined and quantified to correlate to LPBF parameters. A simple empirical model was postulated to relate relative sample density and LPBF volumetric energy density. Melt pool dimensions were quantitatively measured and compared to estimations based on Rosenthal solution, which yielded a good agreement with the width, but underestimated the depth, particularly at high energy input, due to lack of consideration for keyhole mode. In addition, the sub-grain cellular-dendritic microstructure in the as-built samples was observed to decrease with increasing laser scan speed. Quantification of the sub-micron cellular-dendritic microstructure yielded estimated cooling rate in the order of 10 5 – 10 7 K/s.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data-Driven Surrogate Modeling with Microstructure-Sensitivity of Viscoplastic Creep in Grade 91 Steel

Abstract To support the development of advanced steel alloys tailored to withstand extreme conditions, it is imperative to account for the mechanical performance of components, while considering the influence of local microstructure on the macroscopic response. To this end, this study focuses on the development of microstructure-sensitive constitutive models for the mechanical response of Grade 91 steel exposed to extreme thermo-mechanical environments. Polynomial chaos expansion (PCE) surrogates are used to emulate high-fidelity polycrystal simulations of the viscoplastic response of Grade 91 steel as a function of the microstructure fingerprint (e.g., dislocations and precipitates). To cover a wide temperature–stress domain, two separate PCE surrogates—one that captures softening and the other that captures hardening behavior—are combined using another (sparse) Gaussian process regression model. The resulting constitutive creep surrogate model is integrated within the MOOSE finite element framework to simulate the intricate effects of microstructure, in particular MX-phase precipitates, on a component with a graded microstructure. Surrogate sensitivity analysis is applied to quantify the relevant impact of spatially varying microstructure on the creep response in a test-case involving a Grade 91 alloy with a prototypical weld.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microstructural changes and mass transport in cement-based materials: A modeling approach

Highlights: • Concept to relate microstructural changes, mass transport, and chemical reactions in cement-based materials is presented. • Multi-physics modeling approach utilizing an extended version of the PNP equation and the geochemical code IPHREEQC. • Case studies indicate significant changes in mass transport properties due to alterations in the microstructure. • Microstructural changes depend on exposure and interactions between chemical reactions, pore structure, and mass transport. A generic modeling framework is presented to relate microstructural changes, i.e. changes in the pore volume distribution and phase assemblage, and mass transport in cement-based materials. The modeling framework accounts for mass transport and chemical equilibrium between ions in the pore solution and solid hydrates by means of an extended version of the Poisson-Nernst-Planck equation, in which the chemical equilibrium is solved by the external geochemical code IPHREEQC. Results of numerical studies concerning carbonation and leaching of a cement-based material indicate significant changes in mass transport properties due to chemical reactions leading to alterations in the microstructure. The resulting highly non-linear (both spatial and temporal) microstructural changes are thereby depending on the exposure and indicate that interactions between chemical reactions, pore structure changes, and mass transport have to be accounted for as a whole.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of cementation on the yield surface of rocks numerically determined from digital microstructures

Digital Rock Physics has reached a level of maturity on the characterisation of primary properties that depend on the microstructure – such as porosity, permeability or elastic moduli – by numerically solving field equations on μCT scan images of rock. After small deformations or at depth though, most rocks eventually reach their limit of elasticity and the complementary plastic properties are needed to describe the full mechanical behaviour. Currently, determination of a rock’s yield surface from its microstructure is often restricted to semi-analytical criteria derived by limit analysis or numerical simulations performed on idealised geometries. Such simplification lacks representativeness, particularly for processes that affect directly the pore-grain interface such as the cementation phenomenon, happening during diagenesis. Eventually, only direct numerical simulation of elasto-plasticity performed on digitalised microstructures can be used to assess the strength of different cemented materials and its evolution with the alteration of the microstructure. In this study, we provide a comprehensive parametric study on the impact of cementation on rock strength for real microstructures of cemented granular materials. Compared to most previous studies, the whole yield surface is determined numerically (using Finite Element Method) in order to assess the influence of cementation for different stress-paths. The previously known tendency of rock to strengthen with increasing cementation volume is verified. New results on the influence of cement property namely Young’s modulus, friction and cohesion on the rock’s yield surface are explored. The envelopes obtained are compared to the ones obtained by experimental data and existing models. Finally, the framework presented in this study showcases the wider possibility of determining any rock’s or porous material’s yield surface from its microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impacts of annealing treatment on the microstructure of U-Mo monolithic fuel plates

The objective of this paper is to analyze the effect of different heat treatments on the fuel microstructure and texture in laboratory scale monolithic U-Mo fuel plates. Such analyses are relevant as they could possibly inform future fabrication methods for the optimization of microstructure and of material properties to ultimately improve fuel performance during irradiation. For this reason, detail characterization including Energy x-ray dispersive spectroscopy (EDS) and electron backscattered diffraction (EBSD) techniques were applied on U-Mo plates fabricated with different heat treatments to understand the influence of fabrication on fuel microstructure. Here, U-Mo fresh fuel specimens with or without annealing treatments (homogenization and stress release annealing) after rolling were analyzed in this work. In this study for the first time EBSD was systematically used to analyze the heat treatments influence on texture present in fresh fuel monolithic U-Mo fuel plates. Such changes were connected to other known microstructural and chemical changes. In this work minimization of molybdenum concentration variation and gamma phase decomposition of the U-Mo fuel core after homogenization was observed. Also, an increase in the interaction layer of the U-Mo fuel core with the Zr interlayer diffusion barrier was observed with the UZr 2 growing up to 1 µm in thickness. Such microstructural changes were aligned to the changes in texture and grain structure. Indeed, common texture observed in body-centered cubic (BCC) metal after cold rolling (e.g., α, ξ, γ fibers) were minimized by the annealing/homogenization process. Moreover, grain structure was influenced by the fabrication route with elongated grains formed in the rolled sample and equiaxed grains found after annealing. Such features are relevant since the formation of microstructural features formed during fuel fabrication can impact fuel performance in reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Strengthening mechanisms for microstructures containing unimodal and bimodal γ' precipitates in ATI 718Plus

Here, the influence of γ' precipitate size distribution on the deformation mechanisms under tensile loading in ATI 718Plus was studied. A set of aging treatments within the temperature range of 720 °C–900 °C was performed on solution-treated samples to obtain various γ' precipitate size distributions. Unimodal and bimodal γ' precipitate size distributions were achieved through single-step and two-step aging sequences, respectively, and such microstructures were tensile tested to failure to assess their yield strength, ultimate tensile strength, and elongation-to-failure. Some of the tensile samples were interrupted after achieving 3–4 % plastic strain, and the deformed microstructures were examined using transmission electron microscopy to investigate the γ' precipitate-dislocation interactions. For the unimodal γ' precipitate size distribution samples with the smaller γ' precipitates (radius ~ 7 nm), dislocations sheared through the precipitates. Both dislocation loops and paired dislocations were observed for the microstructures containing larger γ' precipitates (radius ~ 24 nm). The microstructure containing a bimodal γ' precipitate size distribution, which included average γ' precipitate radii of ~6 nm and ~28 nm, exhibited shearing as the dominant deformation mechanism, and this microstructure exhibited the highest strength values. The experimental observations were rationalized based on the theoretically-calculated critical resolved shear stress values for shearing and looping and a modified model for predicting the yield strength for bimodal microstructures was introduced.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Three-dimensional microstructure-explicit and void-explicit mesoscale simulations of detonation of HMX at millimeter sample size scale

Fully three-dimensional (3D) microstructure-explicit and void-explicit mesoscale simulations of the shock-to-detonation (SDT) process of pressed granular HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) are performed. The overall size scale of the models is up to 3 × 3 × 15 mm3, with ∼30 000 grains and 206 265 voids. The models account for the heterogeneous material microstructure, constituent distribution, constituent morphology, and voids. Loading conditions considered involve piston velocities in the range of 600–1200 m/s or pressures in the range of 4–8 GPa. The focus is on analyzing the SDT process and the effects of microstructure and voids on the run-to-detonation distance (RDD). Companion two-dimensional (2D) simulations are also carried out to assess the differences between 2D and 3D. Statistically equivalent microstructure sample sets (SEMSSs) are generated and used for both 2D and 3D, allowing the prediction of the statistical and probabilistic Pop plots (PPs). The predictions are in general agreement with trends in available experimental data in the literature. It is found that both the microstructure (heterogeneous grain size, morphology, and size distribution) and voids significantly affect the RDD and the PPs. These effects are systematically delineated and quantified via the use of SEMSSs with different combinations of attributes. A recently developed probabilistic formulation for the PPs is used to characterize the results, allowing uncertainties in the relations between the shock pressure and RDD arising from material heterogeneities to be quantified. The probabilistic formulation is further used to quantify the confidence levels in the ranked order of influences of different combinations of microstructure and voids on the PPs.

Miller, Christopher (ORCID:0000000206844381)↗
DOE OSTI2026

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗
DOE OSTI2021

Microstructural Evolution During a Solid State Tube Pinch Weld of Type 304l Stainless Steel

Microstructure development is examined for a specialized spot weld that is used as a solid-state closure process for austenitic stainless steel tubing, referred to as pinch welding. In order to elucidate the microstructural evolution of the weld, a series of test welds were made at nominal conditions using tubing and production like components. These pinch welds normally terminate after twelve cycles of a 60 Hz AC weld process. In this study, production tubes were welded from one to twelve cycles and the microstructure and weld variables after each individual weld cycle number were characterized using radiography and optical metallography. Two electrochemical etchants were used to highlight different microstructural features. The study revealed that: (1) this type pinch weld is largely complete after about six cycles of 60 Hz AC current, half the weld time utilized; (2) the resistance, deformation, and closure length approach “steady-state” conditions after six cycles; and (3) both oxalic and nitric acid electrolytic etchants are useful for highlighting specific microstructural attributes of type 304 L stainless steel. Finally, two distinct microstructural regions can be identified for these welds: the edge of the weld, which is driven by concentrated deformation, recrystallization, and grain growth, and the center region, which is more typical of forge welding and micro-asperity breakdown followed by diffusion and grain-growth.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗