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At least 415 records · Page 23

Multi-scale modeling of the electric field assisted sintering process

The electric field assisted sintering (EFAS) process involves tightly coupled physics that influence microstructural evolution in the particles being compacted. It is also an inherently multi-scale phenomenon, with the microstructure of the compact influencing the subsequent engineering-scale response of the sintering system. To improve understanding of how processing parameters influence microstructural evolution, we have developed a multi-scale modeling approach that couples a continuum-level model of the sintering system with a phase-field model for microstructural evolution of particles within the compact. The phase-field model couples the effect of chemical and electrical driving forces on microstructural evolution and includes the effect of charged defect segregation to surfaces and grain boundaries; this segregation leads to enhanced defect transport and heat generation at these interfaces in response to applied electric field. The effect of enhanced heat generation on particle neck growth and the influence of microstructural evolution on the engineering-scale model are demonstrated.

36 - MATERIALS SCIENCE↗

Development and Characterization of High Performance and Robust Mixed Conducting Cathodes Supportive of Lower Cost Solid Oxide Fuel Cells (Final Report)

The objective of the proposed research is to advance an existing partnership between the University of South Carolina (USC) and LG Fuel Cell Systems, Inc. (LGFCS) to research and develop mixed electronic and ionic conducting cathode materials for durable and robust low-cost solid oxide fuel cells (SOFCs). The first task is to develop mixed ionic and electronic conducting doped (Pr,Nd)NiO 4 (PNNO)-based cathodes. This task is built on a prior collaborative work with LG Fuel Cell System, which showed that doped PNNO could exhibit phase stability at high temperatures. The initial focus will be on investigating the durability and endurance of its electrochemical performance and the temporal evolution of microstructures. In-situ high temperature neutron diffraction and x-ray diffraction will be used to study the structures of these phase stable compounds. PNNO doped with Ca and transition metal elements will be synthesized. Physical properties of these materials with respect to coefficient of thermal expansion, electrical conductivity, diffusion coefficient, and nonstoichiometry will be measured. The benefits of dense versus porous barriers will be studied and the role of barrier layer will be identified and a guideline will be provided to choose the maximum porosity for durable and robust cathode performance with co-doped PNNO as the cathodes. LSCF6428 will be used to compare its power density with that of co-doped PNNO in the absence of Cr, but some studies comparing Cr tolerance will be performed towards the end of the project. The conditions at which preferred nickelate phases are stable will be defined, including sintering temperature, operating temperature, and composition range. The second task will focus on the investigation of the location of degradation by using differential relaxation time (DRT) analysis, coupled with least squares fitting and systematical post analyses. DRT analysis can provide (1) a direct access to the kinetic parameters of the underlying processes in both cathode and anode, and (2) a clearer picture of SOFC operation, which allows loss factors to the changes of microstructures or activities of either electrode to be distinguished, and a better target fuel cell development to be enabled. The third task aims at applying the accelerated testing protocol to investigate the microstructural evolution of the cathode candidates identified in this research. Technical approaches will be developed to mitigate and improve the durability of cathode materials by choosing the right chemistry and tuning cathode microstructures.

36 MATERIALS SCIENCE↗

Effects of build orientation and heat treatment on the evolution of microstructure and mechanical properties of alloy Mar-M-509 fabricated via laser powder bed fusion

We present the main results from an experimental investigation into the consequences of various microstructural features, created by laser powder bed fusion (LPBF) and subsequent heat treatments (HTs), in alloy Mar-M-509 on several aspects of plastic deformation including mechanical anisotropy and elongation-to-fracture (ETF). To ensure successful manufacturing of the alloy, porosity fraction and distribution are first characterized using micro X-ray computed tomography. Next, grain structure, crystallographic texture, and regions of recrystallization in the studied microstructures are measured using electron backscattered diffraction (EBSD). Lastly, chemistry, distribution, and morphological features of carbide phases are extracted using electron microscopy and X-ray diffraction. Strength in tension and compression are measured at room temperature for different initial microstructures created by variations in manufacturing conditions and sample orientations with respect to sample processing frame. While the strength of the alloy varies with sample orientation by approximately 30% in the as-built condition, the alloy is softer, more ductile, and approximately isotropic after HT. These results are discussed and critically compared with the data reported for the as-cast material. The alloy manufactured via LPBF is found to be significantly stronger and more ductile than the same alloy produced by casting. The interesting deformation behavior characteristics of the samples in different conditions are explained in terms of their microstructures. EBSD measurements reveal evolution from columnar grains along the build direction favoring a moderately strong <001> fiber texture in the as-built material to equiaxed grains favoring the {110}<001> Goss texture component after subsequent HTs. The major change in grain structure and texture is a result of recrystallization. While carbide phases precipitate primarily at dendrite and cellular interfaces in the as-built material, these phases are both intra-and inter-granular within the HT materials and coarsen with HT duration. These microstructural observations formed bases to rationalize the observed mechanical behavior of the alloy. With this being said, tailoring the alloy performance characteristics with HTs is reported on.

36 MATERIALS SCIENCE↗

C–S–H gel densification: The impact of the nanoscale on self-desiccation and sorption isotherms

The relationship between humidity and water content in a hydrating cement paste is largely controlled by the nanostructure of the C–S–H gel. Current hydration models do not describe this nanostructure, thus sorption isotherms and self-desiccation are given as constitutive inputs instead of being predicted from microstructural evolution. To address this limitation, this work combines a C–S–H gel description from nanoscale simulations with evolving capillary pore size distributions from a simple hydration model. Results show that a progressive densification of the C–S–H gel must be considered in order to explain the self-desiccation of low-alkali pastes. The impact of C–S–H densification on the evolution of microstructure and sorption isotherms is then discussed, including the effect of water-to-cement ratio, cement powder fineness, and curing temperature. Overall, this work identifies an area where nanoscale simulations can integrate larger-scale models of cement hydration and poromechanics.

36 MATERIALS SCIENCE↗

Microstructure study of U–35 wt.% Zr alloy after quick annealing at 650 °C

Uranium-35wt.%zirconium (U-35wt.%Zr) alloy was annealed for 1 hour and 24 hours at 650 ºC and characterized to understand the early stage microstructure evolution. Dendritic microstructure with fine (~300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-hour annealed sample. After 24-hour annealing 650 ºC, the α-U precipitates coarsened, and the dendritic microstructure disappeared due to microstructure homogenization. Furthermore, microchemical homogenization observed with Energy-Dispersive X-ray Spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-hour annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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↗

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↗

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↗

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↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

Impact of forging direction on the recrystallization behaviour of nickel base superalloy AD730 billet material at subsolvus temperatures

Highlights: • Large unrecrystallized grains present a fine distribution of intragranular γ′ precipitates; • Intragranular precipitates play a key role on strain distribution and subsequent recrystallization behaviour for AD730; • Continuous dynamic recrystallization (CDRX) promotes the gradual consumption of large unrecrystallized grains. • Undissolved secondary precipitates play a key role on the microstructural evolution of AD730 • No significant effect associated to the forging direction on the recrystallization behaviour of AD730 was found. AD730™ is a newly developed Ni-based superalloy for turbine disk applications produced by cast and wrought processes. Conventional ingot-to-billet conversion is an expensive and very complex operation. Because of the difficulties to achieve a uniform strain for recrystallization, large unrecrystallized grains are retained along this process. Heterogeneities of grain size have a negative impact on subsequent forging processes as well as ultrasonic inspectability of the destination part. The main aim of this work is to analyse the impact of both forging direction (billet, cogging) and strain (ε = 0.3–2) on the microstructural evolution of AD730 at subsolvus temperatures from a semi-finished product (billet) under conditions representative of both cogging and hot forging operations. Special attention to the presence of large unrecrystallized grains was paid. Double truncated cones (DTCs) were hot forged at subsolvus temperatures followed by air cooling. SEM and EBSD analysis were conducted in the as-received (billet) and the as-forged conditions. AD730 alloy presents a complex microstructure characterized by the presence of large unrecrystallized grains, aligned in the billet direction, with remarkable differences in γ′ precipitates distribution as compared to recrystallized structures. The fine distribution of primary γ′ precipitates (pinning effect) plays a key role on grain size control but also on the recrystallization behaviour. Continuous dynamic recrystallization (CDRX) mechanism was found to be operating in the large unrecrystallized grains, promoting the formation intragranular DRX grains and the gradual recrystallization of these grains. Strain presents a strong effect on the microstructural evolution of AD730, increasing the recrystallization fraction and refining the structure. By contrast, no significant effect associated to the forging direction was found. Conditions representative of cogging operations (ε ≤ 0.6) at subsolvus temperatures were translated into large fractions of unrecrystallized structures (strain accumulation).

36 MATERIALS SCIENCE↗