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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

TEMHD Effects on Solidification Under Microgravity Conditions

An unexplored potential exists to control microstructure evolution through the use of external DC magnetic fields. Thermoelectric currents form during solidification and interact with this external field to drive microscopic fluid dynamics within the inter-dendritic region. The convective heat and mass transport can lead to profound changes on the dendritic structure. In this paper the effect of high magnetic fields is demonstrated through the use of both 3-dimensional and 2-dimensional numerical models. The results show that the application of a magnetic field causes significant disruption to the dendritic morphology. Investigation into the underlying mechanism gives initial indicators of how external magnetic fields can either lead to unexpected growth behaviour, or alternatively can be used to control the evolution of microstructure in undercooled melts as encountered in levitated droplet solidification.

Kao, Andrew↗
DOE OSTI2020

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗
DOE OSTI2017

TA [B] Predicting Microstructure-Creep Resistance Correlation in High Temperature Alloys over Multiple Time Scales

DoE-NETL partnered with Purdue University to predict the creep and associated microstructure evolution of tungsten-based refractory alloys. Researchers use grain boundary (GB) diagrams, a new concept, to establish time-dependent creep resistance and associated microstructure evolution of grain boundaries/intergranular films GB/IGF controlled creep as a function of load, environment, and temperature. The goal was to conduct a systematic study that includes the development of a theoretical framework, multiscale modeling, and experimental validation using W-based body-centered-cubic alloys, doped/alloyed with one or two of the following elements: nickel, palladium, cobalt, iron, and copper—typical refractory alloys. Prior work has already established and validated a basic theory for W-based binary and ternary alloys; the study conducted under this project extended this proven work. Based on interface diagrams phase field models were developed to predict long term microstructural evolution. In order to validate the models nanoindentation creep data was used to elucidate the role played by the interface properties in predicting long term creep strength and microstructure evolution.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of Precipitation-Strengthening Heat-Resistant Austenitic Stainless Steels for Life-Prediction Modeling

In this study, the role of minor alloying additions in 347H stainless steels (UNS34709, ASTM A240/240M) on creep-rupture properties at 650-750°C and microstructure evolution during isothermal exposure at 750°C has been investigated, aiming to provide the experimental dataset as boundary conditions of physics-based modeling for material/component life prediction. Four different 347H heats containing various amounts of boron and nitrogen additions were prepared and evaluated. The combined additions of B and N are found to stabilize the strengthening secondary M23C6 carbides and retarding the transition from M23C6 to sigma phase precipitates during thermal exposure. The observed kinetics of microstructure evolution reasonably explains the improvement of creep-rupture properties of 347H stainless steels with the B and N additions.

Yamamoto, Yukinori↗
DOE OSTI2021

A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V

The elasto-plastic material behavior, material strength and failure modes of metals fabricated by additive manufacturing technologies are significantly determined by the underlying process-specific microstructure evolution. In this work a novel physics-based and data-supported phenomenological microstructure model for Ti-6Al-4V is proposed that is suitable for the part-scale simulation of laser powder bed fusion processes. The model predicts spatially homogenized phase fractions of the most relevant microstructural species, namely the stable β-phase, the stable α s -phase as well as the metastable Martensite α m -phase, in a physically consistent manner. In particular, the modeled microstructure evolution, in form of diffusion-based and non-diffusional transformations, is a pure consequence of energy and mobility competitions among the different species, without the need for heuristic transformation criteria as often applied in existing models. The mathematically consistent formulation of the evolution equations in rate form renders the model suitable for the practically relevant scenario of temperature- or time-dependent diffusion coefficients, arbitrary temperature profiles, and multiple coexisting phases. Due to its physically motivated foundation, the proposed model requires only a minimal number of free parameters, which are determined in an inverse identification process considering a broad experimental data basis in form of time-temperature transformation diagrams. Subsequently, the predictive ability of the model is demonstrated by means of continuous cooling transformation diagrams, showing that experimentally observed characteristics such as critical cooling rates emerge naturally from the proposed microstructure model, instead of being enforced as heuristic transformation criteria. Eventually, the proposed model is exploited to predict the microstructure evolution for a realistic selective laser melting application scenario and for the cooling/quenching process of a Ti-6Al-4V cube of practically relevant size. Numerical results confirm experimental observations that Martensite is the dominating microstructure species in regimes of high cooling rates, e.g., due to highly localized heat sources or in near-surface domains, while a proper manipulation of the temperature field, e.g., by preheating the base-plate in selective laser melting, can suppress the formation of this metastable phase.

Inverse parameter identification↗
NASA NTRS2010

Microstructure Modeling of Third Generation Disk Alloys

The objective of this program was to model, validate, and predict the precipitation microstructure evolution, using PrecipiCalc (QuesTek Innovations LLC) software, for 3rd generation Ni-based gas turbine disc superalloys during processing and service, with a set of logical and consistent experiments and characterizations. Furthermore, within this program, the originally research-oriented microstructure simulation tool was to be further improved and implemented to be a useful and user-friendly engineering tool. In this report, the key accomplishments achieved during the third year (2009) of the program are summarized. The activities of this year included: Further development of multistep precipitation simulation framework for gamma prime microstructure evolution during heat treatment; Calibration and validation of gamma prime microstructure modeling with supersolvus heat treated LSHR; Modeling of the microstructure evolution of the minor phases, particularly carbides, during isothermal aging, representing the long term microstructure stability during thermal exposure; and the implementation of software tools. During the research and development efforts to extend the precipitation microstructure modeling and prediction capability in this 3-year program, we identified a hurdle, related to slow gamma prime coarsening rate, with no satisfactory scientific explanation currently available. It is desirable to raise this issue to the Ni-based superalloys research community, with hope that in future there will be a mechanistic understanding and physics-based treatment to overcome the hurdle. In the mean time, an empirical correction factor was developed in this modeling effort to capture the experimental observations.

Jou, Herng-Jeng↗
DOE OSTI2022

Comprehensive characterization of irradiation induced defects in ceria: Impact of point defects on vibrational and optical properties

Validation of multiscale microstructure evolution models can be improved when standard microstructure characterization tools are coupled with methods sensitive to individual point defects. We demonstrate how electronic and vibrational properties of defects revealed by optical absorption and Raman spectroscopies can be used to compliment transmission electron microscopy (TEM) and x-ray diffraction (XRD) in the characterization of microstructure evolution in ceria under non-equilibrium conditions. Experimental manifestation of non-equilibrium conditions was realized by exposing cerium dioxide (CeO2) to energetic protons at elevated temperature. Two sintered polycrystalline CeO2 samples were bombarded with protons accelerated to a few MeVs. These irradiation conditions produced a microstructure with resolvable extended defects and a significant concentration of point defects. A rate theory (RT) model was parametrized using the results of TEM, XRD, and thermal conductivity measurements to infer point defect concentrations. An abundance of cerium sublattice defects suggested by the RT model is supported by Raman spectroscopy measurements, which show peak shift and broadening of the intrinsic T2g peak and emergence of new defect peaks. Additionally, spectroscopic ellipsometry measurements performed in lieu of optical absorption reveals the presence of Ce3+ ions associated with oxygen vacancies. This work lays the foundation for a coupled approach that considers a multimodal characterization of microstructures to guide and validate complex defect evolution models.

Chauhan, Vinay S.↗
DOE OSTI2019

A Systematic Study on the Dynamic Softening Behavior of a Heat-Resistant Alloy Considering Thermal and Microstructural Effects

Deep understanding of the relationships among flow softening behaviors, microstructure evolution and process parameters is an essential issue due to the varied strain rate and temperature in industrial hot working schedules. In this research, substantial hot compression tests of a SNCrW heat-resistant alloy were conducted to quantitatively investigate the extrinsic dynamic flow softening behaviors and intrinsic grain size evolution. The thermal softening ratio (TSR) and microstructural softening ratio (MSR) were introduced to, respectively, characterize the degree of deformation heating-induced thermal softening and dynamic recrystallization-induced microstructural softening, respectively. To obtain more accurate results, the TSR was calculated with an improved algorithm that considered strain effects. Additionally, a 3D TSR map and MSR map of the SNCrW heat-resistant alloy were constructed to study the response relationships between thermal softening or microstructural softening and the deformation parameters. In addition, a superimposed contour map of the average grain size on the MSR map was developed to reveal the relationships between microstructural evolution and the macromechanical response. The results show that the grain size of the SNCrW heat-resistant alloy exhibits an inverse correlation with the MSR and is slightly correlated with thermal softening.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effect of strain level on the evolution of microstructure in a recently developed AD730 nickel based superalloy during hot forging

Highlights: • Hot forging of AD730 led to formation of large non-recrystallized grains. • Similarity in chemical compositions of the non-recrystallized zones and the matrix. • Increase in strain level promoted recrystallization. - Abstract: Design and control of microstructure of engineering parts made from nickel based superalloys with superior mechanical properties for high temperature applications, require the parts to be subjected to certain thermo-mechanical processing during forging. This often includes sequential straining and annealing at elevated temperatures followed by subsequent aging heat treatments at lower temperatures. In this study, the effect of strain magnitude on the evolution of microstructure during hot forging of a recently developed AD730 nickel based superalloy has been investigated. Microstructural heterogeneity was observed in a forged material manifested in a form of large non-recrystallized grains within the recrystallized matrix that is observed to be dependent on the level of deformation (i.e. strain magnitude). Analyses of microstructure indicated significant reduction in the fraction of low-angle grain boundaries and sub-structures with an increase in the applied strain, suggesting higher fraction of recrystallization with higher levels of strains. It was concluded that the lower strain levels were insufficient to provide enough driving force for complete recrystallization throughout the entire microstructure of the forged material.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microstructure, texture, and mechanical properties of friction stir welded commercial brass alloy

Microstructural evolution during friction stir welding of single-phase brass and corresponding mechanical properties were investigated. For this purpose, 2 mm thick brass plate was friction stir welded at a rotational speed of 450 rpm and traverse speed of 100 mm/min. The microstructure of the joint was studied using optical microscopy, scanning electron microscopy equipped with electron back scattered diffraction system, and scanning transmission electron microscopy. The mechanical properties were measured using hardness and tensile tests. The formation of subgrains and their transformation into new grains in conjunction with existence of A{sub 1}{sup ⁎}, A{sub 2}{sup ⁎} and C texture components revealed that the continuous dynamic recrystallization plays a dominant role in the microstructural evolution. However, grain boundary bulging, along with the formation of twin boundaries, and presence of the G texture component showed that the discontinues dynamic recrystallization may participate in the new grain formation. Furthermore, the different strengthening mechanisms, which caused the higher strength of the joint, were discussed. - Highlights: •Microstructural evolution during FSW of a single phase brass was investigated. •CDRX and DDRX were the main mechanisms of the grain structure formation during FSW. •GDRX and SRX were not contributed in grain structure formation. •The lamellas TBs were formed in the SZ of the joints. •Grain boundary, dislocation, and texture effects resulted in higher strength.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Evolution of microstructure and residual stress during annealing of austenitic and ferritic steels

In this work the recovery and recrystallization processes occurring in ferritic and austenitic steels were studied. To determine the evolution of residual stresses during material annealing the nonlinear sin{sup 2}ψ diffraction method was used and an important relaxation of the macrostresses as well as the microstresses was found in the cold rolled samples subjected to heat treatment. Such relaxation occurs at the beginning of recovery, when any changes of microstructure cannot be detected using other experimental techniques. Stress evolution in the annealed steel samples was correlated with the progress of recovery process, which significantly depends on the value of stacking fault energy. - Highlights: • X-ray diffraction was used to determine the first order and second order stresses. • Diffraction data were analyzed using scale transition elastoplastic models model. • Stress relaxation in annealed ferritic and austenitic steels was correlated with evolution of microstructure. • Influence of stacking fault energy on thermally induced processes was discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2018

A novel approach to quantifying the kinetics of point defect absorption at dislocations

We report that microstructure evolution under creep loading and/or irradiation is largely affected by the two-way coupling between dislocation induced plasticity and point defect diffusion as mediated by the internal elastic strain field within the medium. The magnitude of this effect has been quantified only in idealized, simplified environments such that estimates of absorption rates of point defects to dislocations ignore the collective effects on capture rates arising from particular distribution of dislocations in a given network, the interaction of point defects with the internal strain, or in many cases both. To quantify these effects, we advance a novel methodology to determine point defect capture rates locally within a spatially resolved finite difference solution to the diffusion problem for arbitrarily directed dislocations and the corresponding strain fields. In addition to examining the effects of these couplings on local and effective absorption rates of dislocation networks, the potential consequences of these interactions on other microstructure evolution phenomena are examined using void swelling under irradiation as an example. Our study indicates that local rates of defect mediated microstructural changes such as cavity growth can vary strongly as a consequence of the arrangement of the dislocation network and the corresponding strain state. Lastly, the heterogeneous aspects of the resultant defect populations are shown to provide mechanisms for microstructural evolution under irradiation that are not available in the conventional homogeneous theory.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Evolution of microstructure and grain boundary character distribution of a tin bronze annealed at different temperatures

Specimens cut from a rolled tin bronze sheet were annealed at 400–800 °C for 1 h and evolution of their microstructures was then characterized in details by electron channeling contrast imaging and electron backscatter diffraction techniques. Particularly, statistics on special boundaries (SBs) with Σ ≤ 29 and network connectivity of random high angle boundaries (HABs) in the annealed specimens were examined to probe optimization potentials of grain boundary character distribution (GBCD) for this material. Results show that the deformed microstructure in the as-received material begins to be recrystallized when the annealing temperature increase to 500 °C and average grain sizes surge with further increasing temperatures. As a result of the recrystallization, a large number of annealing twins (with Σ3 misorientation) are produced, leading to remarkably increased fractions of SBs (f{sub SBs}). Thanks to preexisting dense low angle boundaries, the majority of SBs in the 500 °C specimen with only partial recrystallization are Σ3{sub ic} (incoherent) boundaries, which effectively disrupt connectivity of random HABs network. Although the f{sub SBs} can be further increased (up to 72.5%) in specimens with full recrystallization (at higher temperatures), the Σ3{sub ic} boundaries would be replaced to some extent by Σ3{sub c} (coherent) boundaries which do not contribute directly to optimizing the GBCD. This work should be able to provide clear suggestions on applying the concept of grain boundary engineering to tin bronze alloys. - Highlights: • The rolled tin bronze begins to be recrystallized as temperature increases to 500 °C. • A lot of SBs are produced after recrystallization and the highest f{sub SBs} is 72.5%. • Partially recrystallized specimen has the optimum GBCD due to more Σ3{sub ic} boundaries. • The Σ3{sub ic} boundaries are replaced by Σ3{sub c} boundaries after full recrystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding grain refinement and intergranular gas bubble evolution in U-10Mo fuel using phase-field modeling

Monolithic U-10Mo fuel undergoes significant microstructural changes in the form of grain refinement and gas bubble formation during burnup, which degrades its mechanical properties. In this talk, I present a phase-field model for microstructure evolution in U-10Mo developed using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Simulations demonstrate that grain refinement initiates at pre-existing grain boundaries (GBs) to eliminate the lattice distortion energy caused by the accumulation of self-interstitial loops. By employing an equation of state for xenon gas, we simulate the evolution of gas bubbles in the polycrystal microstructure. Large, interconnected bubbles are found to form along the triple junctions. The effects of defect production rate, diffusivities and GB mobility on the microstructure evolution are systematically studied. Homogenization is employed on the microstructures to obtain effective elastic constants and diffusivity as a function of fission density. The simulations provide critical insights on microstructure and property degradation in U-10Mo fuel.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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↗