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DOE OSTI2018

Microstructure of titanium on complex deformation paths: Comparison of ECAP, KOBO and HE techniques

Highlights: • Method for producing CP titanium rods for medical implants is searched. • Three processing methods producing ultra-fine grain titanium are compared. • Microstructure and textures are examined and analysed. • Mechanical characteristics are determined based on microhardness and tensile tests. • Hydrostatic extrusion (HE) leads to the best properties of titanium rods for medical implants. - Abstract: In this work samples of commercial purity grade 2 titanium were severely deformed by three different extrusion techniques: equal-channel angular pressing (ECAP), extrusion through oscillating die (KOBO), and hydrostatic extrusion (HE). Resulting microstructures and mechanical properties of processed titanium samples are studied and compared with regard to potential application as a material for dental implants. The obtained results demonstrate the effect of different strain paths, involved by three applied deformation methods, on microstructure refinement, mechanical properties and textures of the studied material. Heterogeneous microstructures with bimodal grain size distributions are observed for all deformation techniques in the examined material, however differences in their internal structures and grain boundary distributions point to different grain refinement mechanisms. The fraction of ultra-fine grains is the highest in titanium deformed by HE. Also the internal grain fragmentation is the most important after HE deformation. This leads to the best mechanical and microstructural properties obtained in this type of deformation. Consequently, the HE process seems to be very interesting for production of material for medical implants.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Linking sintering stresses to nano modification in the microstructure of BaLa4Ti4O15 by transmission electron microscopy

Highlights: • by systematic HRTEM studies we link the microstructural changes in BLT ceramics to the external pressure applied during sintering; • we developed a mechanistic understanding of the role of stress in sintering; • external stresses during sintering affect the microstructural development at the nanoscale level, being responsible for the creation of higher defective bulk and grain boundary regions; • observation of high density of stacking faults (which generally arrises due to the Ti vacancy layers) indicates that the applied stress is modifying the stacking of AO{sub 3} layers of BLT which in turn creates Ti vacancy layer and stacking faults; • stress assisted sintering has, therefore, the potential to be used as a tool to design microstructures and achieve tailored properties, as suggested from our previous results in BLT and BNT. - Abstract: High quality factor and a temperature stable resonant frequency make BaLa{sub 4}Ti{sub 4}O{sub 15} (BLT) ceramics attractive materials for microwave applications. Aiming to exploit the effects of external stresses on the development of textured and anisotropic microstructures to optimise MW properties, the influence of applied external pressure during sintering of BLT ceramics is analysed. HRTEM and geometric phase analysis (GPA) showed that stresses applied during sintering, trigger the nucleation and growth of faults hypothesised to be due to the errors in the AO{sub 3} layer (basal plane) stacking sequence of the hexagonal perovskite structure. The results reveal a strong correlation between the high concentration of structural defects and the development of anisotropic microstructures, which tune the properties of BLT. Stresses applied during sintering are therefore a promising tool to design material properties.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Strengthening effects and thermal stability of the ultrafine grained microstructure of a nickel base superalloy at room and elevated temperatures

Highlights: • UFG Alloy 718-5 vol.%Y{sub 2}O{sub 3} alloy is fabricated from alloy machining chips. • The kind of oxide nanoparticles is identified in Nb-rich superalloys. • High thermal stable nanoparticles and UFG microstructure is achieved. • The GB strengthening effects at 25 °C and 650 °C of UFG alloy are calculated. - Abstract: An ultrafine grained (UFG) nickel base superalloy doped with 5 vol.%Y{sub 2}O{sub 3} nanoparticles, Alloy 718-5 vol.%Y{sub 2}O{sub 3}, was fabricated by a powder metallurgy route which combines high energy mechanical milling of Alloy 718 machining chips, spark plasma sintering, hot extrusion and heat treatment, and its microstructure and mechanical properties at room temperature and 650 °C were studied. The study showed that the Y{sub 2}O{sub 3} nanoparticles reacted with Al from the base alloy and transformed to Y{sub 4}Al{sub 2}O{sub 9} nanoparticles (average diameter: 12.5 nm) which were stable during heat treatment at 970 °C (0.78T{sub m}, where T{sub m} is the solidus temperature of the alloy in K). As a result of the high thermal stability of Y{sub 4}Al{sub 2}O{sub 9} nanoparticles and their effective pinning of the grain boundaries, the UFG microstructure (average grain size: 179 nm) of the alloy was stable during heat treatment. Grain boundary and nanoparticle strengthening rendered the heat treated Alloy 718-5 vol.%Y{sub 2}O{sub 3} alloy with a notable room temperature tensile yield strength of 1870 MPa. It was demonstrated that the grain boundary strengthening effect associated with the UFG microstructure was still significant at 650 °C, but clearly decreased from its level at room temperature. The grain boundary strengthening and nanoparticle strengthening effects which are likely to be independent of test temperature sustain a reasonably high tensile yield strength of 800 MPa at 650 °C, despite the absence of γ′ and γ″ precipitates in the UFG microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Evolution of microstructure and microtexture during hot deformation in an advanced P/M nickel base superalloy

Highlights: • Microstructural evolution of PM superalloy sensitive to temperature and strain rate. • Highest DRX with finer grained structure at higher temperatures and strain rates. • Dominance of DDRX showed by serrated grain boundaries and misorientation gradient. • Weak microtextural evolution inclined towards [110] fiber compression texture seen. In the present study, the effect of hot deformation parameters on the microstructural evolution is investigated for an experimental powder metallurgy nickel superalloy. The hot isostatically pressed (HIPed) alloy is isothermally hot compressed at constant true strain rate over wide temperatures (1000 °C, 1050 °C, 1100 °C, 1150 °C) and strain rates (0.001 s{sup −1}, 0.01 s{sup −1}, 0.1 s{sup −1}, 1 s{sup −1}) regimes. Electron Back-Scattered Diffraction (EBSD) characterization of the hot deformed samples is carried out to evaluate the microstructural evolution, grain boundary characteristics, and microtextural behaviour. The strong dependence of dynamic recrystallization characteristics on the hot deformation conditions is divulged through EBSD derived colour inverse pole figure maps endorsed by grain/twin boundary characteristics and misorientation gradient. Dynamic recrystallization (DRX) is maximized at higher deformation temperatures, whereas limited DRX is observed at lower deformation temperatures, especially at higher strain rates. The dominance of discontinuous dynamic recrystallization (DDRX) is manifested through bulged/serrated grain boundaries resulting in the formation of necklace microstructure corroborated by grain boundary cumulative misorientation gradient. Although random microtexture is revealed in both deformed and recrystallized microstructures, the tendency towards the formation of 110 fiber compression texture is apparently evident.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗

DOE OSTI2019

On the evolution of microstructure and defect control in 316L SS components fabricated via directed energy deposition

To identify the critical issues that affect the evolution of microstructure during additive manufacturing, we investigated the influence of process parameters on the evolution of the dimensional and surface quality, microstructure, internal defects, and mechanical properties in 316L stainless steel (SS) components fabricated using laser engineered net shaping (LENS®), a directed energy deposition (DED) additive manufacturing (AM) technique. The results show that the accumulation of un-melted powder particles on the side walls of deposited sections can be avoided by selecting a laser under-focused condition. Moreover, we report that the variation of melt pool width is more sensitive to laser power than to the depth of the melt pool. The formation of a so-called “hierarchical” microstructure with cellular morphology is attributable to a combination of layer deposition and rapid solidification, which are characteristics of AM. Finally, we discuss microstructure evolution and defect formation, particularly the formation of multiple interfaces and the presence of un-melted powder particles and pores, in light of the dynamic convective fluid flow and rapid solidification that occur in the melt pool. X-ray computed tomography (X-CT) was used to precisely map the spatial distribution of pores in the DED components. The evolution of microstructure during DED is discussed in the context of related thermal phenomena in an effort to provide fundamental insight into the mechanisms that govern defect formation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗

DOE OSTI2020

Implications of post-processing induced microstructural changes on the deformation and fracture response of additively manufactured Ti–6Al–4V

Ti–6Al–4V parts fabricated via electron beam melting (EBM) powder bed fusion are often subjected to hot isostatic pressing below the β-transus temperature to mitigate defects. During which the pressure aids in pore closure and the thermal exposure results in coarsening of α phase while retaining the columnar prior-β phase grain morphology present in the as-fabricated condition. The same post-processing treatment can also be carried out above β-transus temperature which is an effective way to modify both the grain morphology and the associated α textures. Here, the objective of this work is to correlate thermally induced microstructural changes to the deformation and fracture response of the EBM processed Ti–6Al–4V. To this end, we have carried out both sub-transus and super-transus heat-treatments of the as-fabricated material. The mechanical response of the as-fabricated and all heat-treated materials are characterized by in-situ tensile tests under a high-resolution digital optical microscope. This enabled us to capture large-scale panoramic images of the deforming microstructure, and overcome the trade-off between the image resolution and the field of view during in-situ experiments. The series of images captured throughout the imposed deformation are subsequently used to perform microstructure-based digital image correlation to measure microstructural-scale strains over a large area. The results of the in-situ tests together with detailed fractographic analyses are then used to elucidate how the heterogeneous deformation spanning over multiple microstructural length-scales, for example, at the scale of lamellae, colonies of lamellae and grain boundaries, affect the overall deformation and fracture response of the post-processed materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Design of a separate effects MiniFuel irradiation experiment investigating microstructure evolution in high burnup UO 2

The microstructural evolution of UO 2 fuel pellets during commercial operation in light water reactors (LWRs) is known to vary significantly across the pellet radius due to spatial variations in local temperature and burnup. The primary obstacle to extending LWR refueling cycles to 24-month intervals is the susceptibility of certain high burnup fuel microstructures to fuel fragmentation, relocation, and dispersal (FFRD) during a loss of coolant accident (LOCA). Although FFRD of the high burnup structure in the rim region of a pellet is well studied, the fine fragmentation that has been observed in a second region, near the midradius of the pellet (termed the “dark zone”) following mock LOCA testing of high burnup commercial fuel rods is less understood. This paper describes the design, analysis, and execution of a separate effects MiniFuel irradiation experiment that aims to identify the specific temperature and burnup regimes under which FFRD-susceptible dark zone microstructures form. The small disc specimens (3 mm diameter by ∼0.3 mm thick) enable more precise control of the relatively uniform temperature and burnup conditions. A total of 42 specimens were fabricated with typical LWR fuel densities (∼96%–98% of theoretical density) and grain sizes (∼12 μm) and are being irradiated over a range of temperatures (600°C–1000°C) and discharge burnups (50–72 MWd/kg-U) that bound the midradius region of high burnup LWR fuel. Fuel specimens with identical 235 U enrichments were inserted in two irradiation locations in the High Flux Isotope Reactor and are currently undergoing irradiation to further evaluate the impact of rate effects (fission rate, time at temperature) on the microstructural evolution. The fuel fabrication and the thermal and neutronic simulations used for designing the experiment are detailed in this paper. A secondary objective of the experiment is to observe fission gas release (FGR) under the various irradiation conditions, and this work provides first-order predictions of FGR from all fuel specimens. The insights gained from these experiments will inform future high burnup core designs that could minimize the formation of susceptible microstructures and ultimately enable 24-month refueling cycles while minimizing the fraction of the fuel susceptible to FFRD.

FFRD↗

DOE OSTI2021

Predicting material microstructure evolution via data-driven machine learning

The recent rapid rise in data-driven practices in the materials science domain has led to the development of efficient, generalizable, and accurate approaches for several applications, including: material property prediction, mining (micro)structure- property and (micro)structure-processing relationships, and characterization of material microstructures. Central to the materials science domain is linking microstructure to properties and performance, and critical to building such linkages is understanding how microstructures evolve as a function of environmental exposure or processing conditions (e.g., time, temperature, applied stress or strain, irradiation). This preview article summarizes recent work on the development of recurrent neural networks for predicting spatio-temporal microstructure evolution detailed by Yang et al in their manuscript entitled 'Self-supervised Learning and Prediction of Microstructure Evolution with Recurrent Neural Networks'.

machine learning (ML), materials characterization↗

DOE OSTI2022

Scaling CFB risers: Maintaining microstructure dynamics

Over the years there have been numerous approaches to develop a scaleup methodology for circulating fluidized beds. Many of these past approaches have relied on macroscopic definitions of similitude to define dimensionless groups such as Reynolds number, Froude number, density ratios, and dimensional ratios involving different length scales. These approaches have demonstrated various levels of success, but often fail when used outside the bounds of experimental datasets. The issue with these methods is that they rely on macroscopic similitude with the hopes that those conditions would provide microscopic similitude as it does in single phase systems where the Buckingham Pi techniques have given reasonable success. Two of the main reasons for failure are 1) changing fluidization regimes and 2) changing material properties that result in the material falling into a different Geldart group. Both are certain to change the microstructure (local instantaneous volume solids fraction) and changes to the microstructure affect the interphase transport properties of the reactor system, namely the mass transfer and heat transfer. Here, this work presents a new approach towards scaling based upon maintaining similitude at the microscale. It reviews a novel dimensionless flow regime map developed from analysis of the deterministic chaos parameters and higher order moments to ensure microstructure similitude. The work then examines four cases from the literature to assess the scaling approach used: (1) same particle-different scale risers for Geldart Group B particles, (2) Glicksman scaling of atmospheric circulating fluidized bed combustor, (3) same particle-different scale risers for Geldart Group A particles and (4) Glicksman scaling for pressurized gasification. General findings are that none of the scaling approaches produced directly applicable microstructure similar behavior based upon the chaotic and higher moment analysis. The positive take away is that the approach can define scale conditions that will provide similar microstructure that can be us to predict transport behavior.

42 ENGINEERING↗

DOE OSTI2022

Microstructural and nanomechanical studies of PVD Cr coatings on SiC for LWR fuel cladding applications

The microstructure and nanomechanical properties of pure Cr coatings deposited on SiC with various physical vapor deposition (PVD) methods have been investigated for the mitigation of hydrothermal corrosion of SiC-SiC f (SiC fiber-reinforced SiC matrix) composite fuel cladding in light water reactors (LWR). Cr coatings (4–7 μm thick) were deposited on unbiased SiC substrates using six variants of magnetron sputtering processes: (i) standard (S-DCMS), (ii) pulsed (P-DCMS), (iii) ion-assisted (I-DCMS), and (iv) pulsed ion-assisted direct current magnetron sputtering (PI-DCMS), (v) high-power impulse magnetron sputtering (HiPIMS), and (vi) bipolar HiPIMS (B-HiPIMS). Microstructural characterization and nanoindentation testing were used to evaluate effects of deposition technique on coating microstructure and nanomechanical properties. The application of positive reverse pulses to the sputter target induced coarsening of the columnar grain structure, while ion bombardment of substrates during deposition promoted densification of the coating microstructure. Both effects are exemplified in B-HiPIMS deposition, resulting in a high-density microstructure with compressive residual stress. Material pile-up around nano-indents and plastic work during nanoindentation were analyzed to understand deformation behavior of the coatings. Finally, the results suggest the B-HiPIMS process to be among the promising methods for the deposition of Cr coatings on SiC-SiC f for LWR cladding application.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Predicting Microstructural Void Nucleation in Discontinuous Fiber Composites through Coupled in-situ X-ray Tomography Experiments and Simulations

Composite materials have become widely used in engineering applications, in order to reduce the overall weight of structures while retaining their required strength. In this work, a composite material consisting of discontinuous glass fibers in a polypropylene matrix is studied at the microstructural level through coupled experiments and simulations, in order to uncover the mechanisms that cause damage to initiate in the microstructure under macroscopic tension. Specifically, we show how hydrostatic stresses in the matrix can be used as a metric to explain and predict the exact location of microvoid nucleation that occurs during damage initiation within the composite’s microstructure. Furthermore, this work provides evidence that hydrostatic stresses in the matrix can lead to coupled microvoid nucleation and early fiber breakage, and that small fragments of fibers can play an important role in the process of microvoid nucleation. These results significantly improve our understanding of the mechanics that drive the initiation of damage in the complex microstructures of discontinuous fiber reinforced thermoplastics, while also allowing scientists and engineers to predict the microstructural damage behavior of these composites at sub-fiber resolution and with high accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Machine learning-based microstructure prediction during laser sintering of alumina

Abstract Predicting material’s microstructure under new processing conditions is essential in advanced manufacturing and materials science. This is because the material’s microstructure hugely influences the material’s properties. We demonstrate an elegant machine learning algorithm that faithfully predicts the microstructure under new conditions, without the need of knowing the governing laws. We name this algorithm, RCWGAN-GP, which is regression-based conditional generative adversarial networks with Wasserstein loss function and gradient penalty. This algorithm was trained with experimental SEM micrographs from laser-sintered alumina under various laser powers. The RCWGAN-GP realistically regenerates the SEM micrographs under the trained laser powers. Impressively, it also faithfully predicts the alumina’s microstructure under unexplored laser powers. The predicted microstructure features, including the morphology of the sintered particles and the pores, match the experimental SEM micrographs very well. We further quantitatively examined the prediction accuracy of the RCWGAN-GP. We trained the algorithm with computer-created micrograph datasets of secondary-phase growth governed by the well-known Johnson–Mehl–Avrami (JMA) equation. The RCWGAN-GP accurately regenerates the micrographs at the trained time series, in terms of the grains’ shapes, sizes, and spatial distributions. More importantly, the predicted secondary phase fraction accurately follows the JMA curve.

08 HYDROGEN↗

DOE OSTI2026

Hierarchical microstructure of Yb-filled skutterudites through ultrasonically atomized spherical powders for enhanced thermoelectric performance

Hierarchical microstructures are widely explored as a strategy to reduce lattice thermal conductivity in thermoelectric materials while preserving favorable electronic transport. Here we demonstrate that ultrasonic atomization of precursor powders provides an intrinsic pathway to generate such architectures in n-type Yb0.3Co4Sb12 skutterudites. Materials were synthesized by both conventional sealed-ampoule and ultrasonic atomization routes, each yielding essentially single-phase skutterudite after densification. However, the atomized spherical powders undergo a distinct reaction-driven microstructural evolution during thermal treatment prior to densification. Electron microscopy reveals that the skutterudite phase within the particles induces swelling, cracking, and fragmentation of the droplets before consolidation. Multimodal structural and microstructural characterizations show that densification of these fragmented powders produces a hierarchical microstructure consisting of submicron grains, micrometer-scale faceted crystallites, and powder-derived domains separated by oxide-decorated boundaries. Comprehensive thermoelectric transport measurements evidence that this multiscale architecture lowers the lattice thermal conductivity while maintaining favorable electronic transport, leading to an average ~10% enhancement in the thermoelectric figure of merit. Complementary 121Sb Mössbauer spectroscopy further indicates lattice softening in the atomized material. These results demonstrate that ultrasonic atomization provides an effective route to engineer hierarchical microstructures in skutterudite thermoelectrics and offers a promising strategy for tailoring thermal transport in energy-conversion materials.

Bouteiller, Hugo [ORNL] (ORCID:0009000421322962)↗

DOE OSTI2021

Shock-reshock of zirconium to explore the effect of microstructure on the alpha-omega phase transformation

Phase transformations play an important role in the mechanical behavior of materials subjected to extreme loading conditions. A series of shock-reshock experiments were fielded to determine whether the phase transitions in materials are significantly enhanced or inhibited by preexisting microstructural features. Polycrystalline zirconium samples were shock loaded using gas-gun plate impact and soft recovered to examine microstructure using electron backscatter diffraction (EBSD). Drive conditions were varied to study the (hcp) alpha to (hexagonal) omega solidsolid phase transformation. Recovered samples were then subjected to a second shock loading event to determine the change in material behavior as a function of pre-shock microstructure. Crystallography of phase fragments in the final microstructure showed that prior twinning (formed during the shock to a peak stress below the transition threshold) appeared to suppress omega formation/retention after reshock. Conversely, when a material was initially shocked into the omega phase field, retained-omega was not found to have a large impact on subsequent omega formation during reshock. This suggests that nucleation and growth of omega phase are important processes, and the relative activity of nucleation vs. growth processes is modified by a pre-existing substructure. Additionally, orientation relationships reveal a reverse transformation pathway (omega to alpha) dominates the final microstructure, suggesting significant grain growth in the omega phase field is possible even for dynamic timescales.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FE meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.

36 MATERIALS SCIENCE↗