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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Phase-Field Modeling of Thermally-Grown Oxide and the Induced Damage Evolution in Environmental Barrier Coatings

The advent of next-generation hydrogen-based engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the critical role of thermally grown oxides (TGO) in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and microstructural evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

Cheng, Tianle↗
DOE OSTI2020

Decarburization and Carburization Behavior of Grade 91 Steel in Sodium Environments

Two heats of G91 steel have been investigated in sodium at 550-650°C to understand its corrosion behaviour, microstructural evolution, and tensile properties. Sodium exposure tests of subsized tensile and coupon specimens of G91 base metal and weldment were conducted in Argonne’s forced convection sodium materials testing loops. Maximum exposure times of ~39,000 h at 550°C, ~37,000 h at 600°C, and ~20,000 h at 650°C have been achieved, respectively. Thermal aging experiments of G91 steel were conducted in parallel, and the data of the sodium-exposed specimens were compared with the thermal aging data of the same heat to isolate the thermal aging effect from the effect of sodium exposure. It was found that the tensile strength of G91 steel can be reduced by more than 50% after sodium exposures at 650°C. The effect of a sodium environment on tensile properties is largely dependent on the carburization/decarburization behavior of G91 steel exposed to sodium. The carbon concentrations in sodium in Argonne’s SMT-1 and SMT-2 loops were determined by the equilibration method. The carbon activity in sodium was established by equilibrating high-purity nickel in sodium, analyzing the material for carbon, and using the reported data on the carbon solubility for this material. The carbon activity results were combined with the carbon solubility data in sodium to establish the carbon concentration in sodium. The carbon concentrations in the SMT-1 and SMT-2 loop were estimated to be 1.23 and 0.25 ppm, respectively. With this initial success, we will continue to monitor the carbon contents in the two loops to correlate the microstructural and mechanical property changes with the sodium purity. Future experiments will also consider sodium exposure tests in controlled carbon activities. Online monitoring and control of carbon contents in sodium in nuclear reactors would also be of interest. Thermodynamic analysis was conducted to understand the carburization-decarburization behavior of G91 steel exposed to sodium in the SMT-1 and SMT-2 loops. The equilibrium carbon activity in the alloy was evaluated by the thermodynamics of M 23 C 6 carbides. The calculated carburization-decarburization boundary showed that G91 would undergo decarburization at 650°C in the SMT-1 loop and carburization at 600°C in the SMT-2 loop, which is consistent with our findings from the sodium exposure tests. Future work will include thermodynamic analysis of the carbon concentration – activity relationship including the effect of carbide-forming elements, vanadium and niobium in G91 steel. Kinetics of carbon diffusion and the effect on microstructure and mechanical performance under various service conditions will also be investigated. The ultimate goal is to understand the mechanisms and the kinetics of carbon transfer in the sodium-steel system and to provide a basis for predicting the effect of long-term decarburization-carburization process on the integrity of reactor components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Platform-Independent X-ray Diffraction Diagnostic for Phase Transition Kinetics in Traditional and Synthetic Microstructure Materials (LDRD Project 213088 Final Report)

Pulsed-power generators using the magnetic loading technique are able to produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects such as dislocations. Here, we present a cost effective, compact X-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically-driven ramp compression of materials with single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials community. The success in fielding this new XRD diagnostic dramatically improves our predictive capability and understanding of rate-dependent behavior at or near phase transition. As Sandia plans the next-generation pulse-power driver platform, a key element needed to deliver new state-of-the-art experiments will be having the necessary diagnostic tools to probe new regimes and phenomena. These diagnostics need to be as versatile, compact, and portable as they are powerful. The development of a platform-independent XRD diagnostic gives Sandia researchers a new window to study the microstructure and phase dynamics of materials under load. This project has paved the way for phase transition research in a variety of materials with mission interest.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Regulating Gas Transport in Molecularly Engineered Polymer Membranes (Final Technical Report)

Energy-efficient separation processes are essential for a wide range of applications ranging from clean fuels (e.g., hydrogen purification) and petroleum refining (e.g., natural gas processing) to water purification and carbon capture. Membrane-mediated separations have shown tremendous promise in providing high productivity and high separation efficiency at significantly lower energy consumption, e.g., up to 90% less energy cost than traditional thermally driven processes such as distillation. Polymeric membranes–the dominant separation membrane materials–have yet to reach their full potential due to their limitations in long-term durability (e.g., productivity loss over the period of their lifetime due to physical aging) or insufficient stability under harsh conditions (e.g., high temperature, chemically complex feeds). This research seeks to establish a new paradigm in polymer membrane material design by harnessing crosslinked model networks with well-defined yet finely tailorable microstructure to facilitate fast and selective gas transport and simultaneously enhance membrane stability. Unlike traditional randomly crosslinked polymers, which suffer from structural inconsistencies and consequently suboptimal gas separation performance, crosslinked model network membranes prepared via a precisely controlled end-linking process enables the creation of previously unattainable microstructure tunability, which, in turn, results in versatile crosslinked membranes with high separation performance that meet the needs of various challenging gas separations. Using model network framework as a fundamental tool by applying this concept in diverse polymer categories, this work has led to the development of various innovative crosslinked membrane structures such as unimodal, bimodal and clustered model networks. These advanced crosslinked polymer membranes not only demonstrate exceptional gas separation performance that significantly outperform existing randomly crosslinked membranes, but also possess excellent long-term durability and robust stability under complex operating conditions. From a fundamental perspective, results from this research provide critical mechanistic insights into gas separation in crosslinked polymer membranes, addressing key knowledge gaps and opening new avenues for membrane design to meet various separation needs. The new membrane materials produced from this research enable the use of polymeric membranes for high temperature gas separations, offering substantial energy and cost savings by eliminating the need for repeated cooling-heating cycles in industrial processes.

02 PETROLEUM↗
DOE OSTI2025

Synergistic Tuning of Microstructure and Morphology in Carbon Molecular Sieve Hollow Fibers for Propylene/Propane Separation

Abstract Asymmetric carbon molecular sieve (CMS) hollow fiber membranes with tunable micro‐ and macro‐structural morphologies for energy efficient propylene‐propane separation are reported here. A sub‐glass transition temperature (sub‐Tg) thermal oxidative crosslinking strategy enables simultaneous optimization of the intrinsic molecular sieving properties while also reducing the thickness of the CMS “skin” derived from the 6FDA : BPDA/DAM polyimide precursors. Such synergistic tuning of CMS microstructure and macroscopic morphology of CMS hollow fibers enables significantly increased propylene permeance (reaching 186.5 GPU) while maintaining an appealing propylene/propane selectivity of 13.3 for 50/50 propylene/propane mixed gas feeds. Our findings reveal a more refined and versatile tool than available with previous O 2 ‐doping pretreatments. The advanced approach here should be broadly useful to other polyimide precursors and diverse gas pairs.

Liu, Zhongyun [School of Chemical &amp, Biomolecul↗
DOE OSTI2021

Deep-freeze graph training for latent learning

Scientific and engineering advances are primarily driven by multi-tier conceptual constructs and conditional theoretical frameworks. The theories allow predictions of hypothetical system responses, given a set of approximate conditions (ranges of applicability) imposed on latent parameters that cannot be measured directly. Learning to estimate the latent variables (Latent Learning) helps to pinpoint the anticipated range-edge anomalies and improves the confidence in interpretation, interpolation and extrapolation of limited experimental data. Due to high dimensionality and extreme non-linearity of the materials science problems, very large datasets are typically required for conventional data-driven model development. The vital experimental data collection, particularly on microstructural phases, is very challenging, which makes it difficult to compile a high-quality database. Incorporation of the domain knowledge into the computational graph structure, initialization and optimization processes presents a viable mechanism for developing accurate models, with limited datasets. Furthermore, this study successfully utilized the approach to build the Deep Freeze Graph (DeepFreG) by mapping known causality relationships and by digitizing empirical domain knowledge for Latent Learning (LL), with specific applications in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Friction stir processing on a strontium modified, thin-wall, vacuum-assisted high-pressure die-cast Aural-5 alloy to improve tensile and fatigue performance

Here, this study explores the application of friction stir processing (FSP) to enhance the material properties of Sr-modified Aural-5 alloy, with a focus on improved tensile and fatigue properties. Aural-5 is a well-known vacuum-assisted high-pressure die-cast (HPDC) Al-Si7-Mg alloy used in the automotive industry to reduce vehicle weight, enhance fuel efficiency, and lower carbon emissions. This alloy modifies its material chemistry with Sr for fine fibrous networks of eutectic silicon and manganese (Mn) to reduce die soldering. It has significantly less iron (Fe) content resulting in the elimination of detrimental needle-shaped Fe-bearing ß-phase intermetallic and improving ductility. The initial microstructure of as-received HPDC Aural-5 exhibits shrinkage porosity in the middle section, a dendritic microstructure with fibrous Al-Si eutectic colonies, a shear-band structure beneath the die-wall, large dendritic externally solidified crystals (ESCs), needle-shaped Mg 2 Si phase and significant second-phase particulates. Some of those microstructural features, such as porosity, ESCs, needle-shaped Mg 2 Si phase, and large second-phase particles, serve as initiation sites for cracks under mechanical loading, resulting in adverse effects on tensile properties, particularly ductility. FSP effectively transforms the microstructure into a wrought configuration with uniform particle distribution by eliminating porosity and disintegrating dendrites, eutectic colonies, ESCs, second-phase particles, and shear-band structures. FSP-driven microstructure modification enhances yield strength and tensile ductility by ~30% and ~35%, respectively. The fatigue life of the material in a bending mode configuration (stress ratio R = 0.1) after FSP exhibits enhancements ranging from 2.0 to 3.9 times that of the original HPDC Aural-5 alloy, depending on the applied stress level.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrated TBC/EBC for SiC Fiber Reinforced SiC Matrix Composites for Next Generation Gas Turbines (Final Report)

In this ambitious project, a significant challenge preventing widespread use of ceramic matrix composites in hot section components of gas power generating turbines was addressed. Hot section components made from SiC fiber reinforced SiC matrix composites (SiC/SiC composites), have the potential to achieve a combined cycle energy efficiency of above 65%. To achieve this efficiency, the temperature of the combustion gases on the turbine component surface is expected to reach as high as ~1700ºC (3100ºF). However, SiC/SiC composites suffer from volatilization at high temperature under high velocity steam environment – typical in a turbine hot chamber. This integrated collaborative project, between two research groups at Clemson University and a team of engineers and scientists at GE Gas Power, focused on design, fabrication and evaluation of a new graded environmental barrier coating. Using the excellent compositional tailorability of polymer derived ceramics (PDCs), we developed an integrated EBC/BC that smoothly transitions from bottom SiC/SiC bond interface to hermetic sesquioxide (Y 2 O 3 ) top surface. This smooth compositional transition avoided the sharp CTE mismatch at interfaces to greatly reduce the thermal stress. The developed EBC is compatible with and bonds well with the bond coat that GE uses. The top hermetic oxide surface ensures low oxygen transportation and volatilization rates under the high velocity steam environment. The graded microstructure with increasing sesquioxide concentration also decreases the amount of Si and C elements near the top hermetic sesquioxide layer. Coatings made using a process suitable for manufacturing – atmospheric plasma spraying was demonstrated. The microstructure of coatings made using this process were fully characterized. Finally, the performance of these coatings was investigated under the most demanding conditions for this application. Specifically, high temperature, high velocity steam exposure; thermal shock test; and thermal cycling tests. The graded coatings performed exceptionally well in all these tests. Specific suggestions for future development in this area have also been identified. In addition to the excellent technical progress, this project helped initiate a robust collaboration between the research groups at Clemson and GE Gas Power. It also provided a high-quality learning and mentoring opportunity for the three post-doctoral research associates and two UG students at Clemson University who worked on this project. All proposed tasks, sub-tasks were completed, and all milestones achieved.

03 NATURAL GAS↗
DOE OSTI2023

Grain Structure Evolution in Fe-6Si During Directed Energy Deposition

The purpose of this study is to explore the effect of additive manufacturing (AM) process variables on the grain structure of Fe-6Si, a soft-magnetic alloy used in electrical machine and grid applications. Samples were fabricated with laser engineered net shaping (LENS) with varying inter-pass timing and numbers of unidirectional passes. Here the results show that the grain structure was affected by both solidification and solid-state grain growth mechanisms. A model of the LENS process suggests that, although shorter inter-pass times encourage greater nucleation of new grains and therefore grain refinement during solidification, these conditions also help maintain high solid-state temperatures that allow for grain boundary motion to keep pace with the build rate. Grains formed under these conditions may span multiple layers, and the high-temperature gradient promotes directional growth. This new understanding of these microstructure evolution mechanisms will aid in using process conditions to control the competition between solidification and solid-state grain growth to create grain structures that may not be possible with conventional processing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanoscale Engineering of Polymorphism in Cu 2 Se-Based Composites

Crystal polymorphism selection during synthesis is extremely challenging. However, promoting the formation of a specific metastable polymorph enables modulation of the functional properties of phase-change materials through alteration of the relative abundance of various polymorphs. Here, we demonstrate the stabilization of the superionic β-Cu 2 Se phase under ambient conditions and the direct control over the relative ratio between the α-Cu 2 Se and β-Cu 2 Se polymorphs in (x)CuGaSe 2 /(1-x)Cu 2 Se composites using CuGaSe 2 nanoseeds. Here, we found that the small lattice mismatch between β-Cu 2 Se (cubic) and the ab plane of tetragonal CuGaSe 2 nanoseeds promotes the formation of low-energy coherent CuGaSe 2 /β-Cu 2 Se interfaces leading to preferential stabilization of β-Cu 2 Se. Astonishingly, the hierarchical microstructure of the resulting composites enables a remarkable decoupling of charge and heat transport, which is manifested by a breakdown of the Wiedemann-Franz law

36 MATERIALS SCIENCE↗
DOE OSTI2026

Part-scale evolution of fine-scale microstructural heterogeneity in solid-state additive manufacturing

Current solid-state additive manufacturing methods, refined through costly and time-consuming trial and error, have spurred interest in computational models that replicate material behavior under typical thermomechanical conditions (e.g., strain-rate ~ 102 s−1). These models, however, struggle to capture time-dependent microstructural evolution. In this work, Additive Friction-Stir Deposition (AFSD) is used as a representative case study for part-scale quantification of microstructure evolution at a fine spatial resolution (200 μm) by examining a liquid-nitrogen-cooled stop-action build via energy-dispersive X-ray diffraction coupled with a multi-channel detector. These results inform modeling efforts by linking process asymmetry to stored plastic strain, residual elastic strain, and texture development, and unlike current state-of-the-art characterization methods (e.g., EBSD or neutron diffraction), this approach provides both the spatial resolution and collection efficiency necessary to quantify fine-scale microstructural heterogeneity over large component volumes. As such, this technique provides essential validation data for computational models, e.g., crystal plasticity, enabling future prediction of heterogeneous behavior in AFSD and other additive manufacturing processes.

Franz, Cole [ORNL] (ORCID:0000000213465881)↗
DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗
DOE OSTI2021

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Progress on the evolution of the pilot scale manufacturing plant and initial results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Construction of the pilot scale manufacturing plant has been completed and results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Genetic programming for interpretable, data-driven continuum damage models.

The damage mechanisms that lead to failure in engineering alloys have been studied extensively, but converting this knowledge into constitutive models that are suitable for engineering-scale analysis remains a challenge. Evolution laws for continuum damage have been developed in the past and have proven effective but suffer from many non-physical assumptions that inhibit the overall accuracy of the model. Further, the assumptions inherent in these existing models prevent them from being applicable to a broad class of materials. At the same time, computational models of fine-scale damage mechanisms continue to advance making it tractable to generate large training data sets through computer simulation. Data-driven machine learning approaches can leverage these data sets to avoid making limiting assumptions, and instead produce models directly from the results of microstructural simulations and/or experiments. Many of these machine learning approaches are rapid and accurate, but they offer little to no insight into the underlying relationships among state variables being discovered. Conversely, genetic programming symbolic regression (GPSR) is a machine learning method that produces analytic expressions relating the state variables, allowing maximal insight and interpretability. To that end, we propose using GPSR as a data-driven method of obtaining microstructurally informed continuum damage models. Data is generated using microstructural simulations of damage evolution, parameterized over microstructural statistics (i.e., pore shape) and nominally applied deformations. Analytic expressions for damage evolution are obtained from the data using GPSR, and these expressions are then utilized within a continuum constitutive model. Overall, this approach is a promising method of automatically obtaining analytic relations describing constitutive phenomena in a material.

Buche, Michael Robert↗
DOE OSTI2025

Unpacking model inadequacy: The quantification of silver release from TRISO fuel by considering empirical and mechanistic approaches

Increasing adoption of the proposed tristructural isotropic (TRISO) particle fuel for both advanced and existing reactors makes it critical to assess and address any uncertainties and inadequacies of TRISO fission product release models. Model inadequacy stems from simplifications made to the computational model when compared to the experiments. The modeling and simulation efforts conducted using the BISON fuel performance code, along with the experimental campaigns carried out under the Advanced Gas Reactor Fuel Development and Qualification Program, afford a unique opportunity to conduct a rigorous modeling inadequacy assessment within the Bayesian uncertainty quantification (UQ) framework. Here, this study compares the standard Bayesian framework against the Kennedy-O'Hagan (KOH) framework, which explicitly represents modeling inadequacy, in regard to UQ for TRISO silver release models. For this purpose, both the traditional Arrhenius equation fitted to experimental data and the more advanced lower-length-scale (LLS)-informed model, which considers microstructure information, are independently considered. Applying the inverse UQ process on the AGR-2 and -3/4 datasets revealed modeling inadequacy to be the most dominant source of uncertainty. Experimental noise uncertainty is also significant; however, model parameter uncertainty can be considered negligible. Interestingly, both the Arrhenius equation and the LLS-informed model demonstrated similar levels of modeling inadequacy. For the forward predictive UQ, the KOH framework improved both the accuracy and quality of quantified uncertainties in comparison to the standard Bayesian framework. This is true for both the Arrhenius equation and the LLS-informed model. In comparing these modeling approaches, both demonstrated similar performance at the engineering scale, while the LLS-informed model expectedly outperformed the Arrhenius equation at the mesoscale. These conclusions highlight the importance of explicitly accounting for modeling inadequacy in the UQ process, and reinforce the need for continuous refinement of physics-based models in order to address the modeling inadequacy.

Advanced reactors↗
DOE OSTI2023

An innovative and alternative approach toward gear fabrication

In this paper, we present the first demonstration of single-step gear manufacturing via an innovative in-situ friction stir forging approach. This novel process is a natural extension to the friction stir processing technique and relies on shear and normal stresses to form the complex shapes. Friction stir welding pin tool with shoulder is plunged at high revolutions per minute (rpm) into the sample to heat it to the desired temperature and enable plastic flow. Then, the tool is forged at high plunge rate to form the desired structurally-sound and defect free complex shapes. To better visualize the process the experiments are complemented by a 3D thermomechanically coupled, smoothed particle hydrodynamics (SPH) model to understand the material flow pattern both radially and through thickness in the gear teeth, plastic strain distribution, and temperature profile. We have demonstrated application of I-FSF to inherently poor formable AZ31 Mg, AA 7075-T6, and AA5083–10 vol% TiB 2 composite and fabricated 14-tooth spur gears from these materials with minimal farther machining. In conclusion, microstructure of the forged gears exhibited a directional material flow pattern due to the normal forging action and refinement of grains to 6–13 μm through dynamically recrystallization across the radial, through-thickness direction, which is in good agreement with the corresponding SPH simulation results.

42 ENGINEERING↗
DOE OSTI2020

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

This report summarizes the current state of modeling and simulation methods for predicting the initial structure and properties of material in components assembled using advanced manufacturing technologies (AMTs). The report is the first volume in a two-volume series. This first volume focuses on predicting initial microstructures of AM material. The second volume discusses predicting material properties given the initial microstructure. The focus is on technologies of particular relevance to the design and manufacture of nuclear reactor components. The purpose of the report is to help develop the technical knowledge base to support regulatory decisions that will be needed to assess nuclear components manufactured with AMTs as these components are installed at nuclear power plants (NPPs). The report develops a list of AMTs of particular interest to the NRC and summarizes the key microstructural features and corresponding processing parameters relevant to each technology. Further sections describe available physically-based and data-driven prediction methods and survey widely available software tools. The report concludes with a summary of gaps that may be of particular interest to the NRC when evaluating modeling and simulation methods for AMTs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗