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At least 433 records · Page 24

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↗

Thermal stability of the microstructure of an aged Nb-Zr-C alloy

The effects of thermal aging with and without an applied stress on the microstructure of a Nb-Zr-C alloy containing 0.9 wt percent Zr and 0.06 wt percent C were studied. Chemical analysis, metallographic examination, energy dispersive x-ray spectra of the bulk material, and chemical and x-ray analyses of the phase-extracted residue were used to characterize the microstructure. The samples examined were from a creep strength study involving hot and cold working, and various combinations of exposure to temperatures ranging from 1350 to 1755 K with and without applied load for times as long as 34,000 plus hours. The results showed that the initial microstructure consisted primarily of orthorombic precipitates of Nb sub 2 C which were partially or completely transformed to face-centered cubic carbides of nb and Zr, (Zr, Nb)C, upon prolonged exposure to elevated temperatures. Furthermore, it was found that the microstructure of the alloy is extremely stable owing to the very finely distributed precipitates throughout its matrix and along the grain boundaries. The lattice parameters of the cubic carbides were determed to vary from 0.458 to 0.465 nm as the Zr/Nb ratio varied from 38/62 to 75/25.

Uz, Mehmet↗

Materials analysis by ultrasonics: Metals, ceramics, composites

Research results in analytical ultrasonics for characterizing structural materials from metals and ceramics to composites are presented. General topics covered by the conference included: status and advances in analytical ultrasonics for characterizing material microstructures and mechanical properties; status and prospects for ultrasonic measurements of microdamage, degradation, and underlying morphological factors; status and problems in precision measurements of frequency-dependent velocity and attenuation for materials analysis; procedures and requirements for automated, digital signal acquisition, processing, analysis, and interpretation; incentives for analytical ultrasonics in materials research and materials processing, testing, and inspection; and examples of progress in ultrasonics for interrelating microstructure, mechanical properties, and dynamic response.

Vary, Alex↗

In Situ Prediction of Microstructure and Mechanical Properties in Laser-Remelted Al-Si Alloys: Towards Enhanced Additive Manufacturing

Laser surface remelting of aluminum alloys has emerged as a promising technique to enhance mechanical properties through refined microstructures. This process involves rapid cooling rates ranging from 10 3 to 10 8 °C/s, which increase solid solubility within aluminum alloys, shifting their eutectic composition to a larger value of silicon content. Consequently, the resulting microstructure combines a strengthened aluminum matrix with silicon fibers. This study focuses on the laser scanning of Al-Si aluminum alloy to reduce the size of aluminum matrix spacings and transform fibrous silicon particles from micrometer to nanometer dimensions. Analysis revealed that the eutectic structure contained 17.55% silicon by weight, surpassing the equilibrium eutectic composition of 12.6% silicon. Microstructure dimensions within the molten zones, termed ‘melt pools’, were extensively examined using Scanning Electron Microscopy (SEM) at intervals of approximately 20 μm from the surface. A notable increase in hardness, exceeding 50% compared to the base plate, was observed in the melt pool regions. Thus, it is exemplified that laser surface remelting introduces a novel strengthening mechanism in the alloy. Moreover, this study develops an in situ method for predicting melt pool properties and dimensions. A predictive model is proposed, correlating energy density and spectral signals emitted during laser remelting with mechanical properties and melt pool dimensions. This method significantly reduces characterization time from days to seconds, offering a streamlined approach for future studies in additive manufacturing.

36 MATERIALS SCIENCE↗

Flow/Damage Surfaces for Fiber-Reinforced Metals Having Different Periodic Microstructures

Flow/damage surfaces can be defined in terms of stress, inelastic strain rate, and internal variables using a thermodynamics framework. A macroscale definition relevant to thermodynamics and usable in an experimental program is employed to map out surfaces of constant inelastic power in various stress planes. The inelastic flow of a model silicon carbide/ titanium composite system having rectangular, hexagonal, and square diagonal fiber packing arrays subjected to biaxial stresses is quantified by flow/damage surfaces that are determined numerically from micromechanics, using both finite element analysis and the generalized method of cells. Residual stresses from processing are explicitly included and damage in the form of fiber-matrix debonding under transverse tensile and/or shear loading is represented by a simple interface model. The influence of microstructural architecture is largest whenever fiber-matrix debonding is not an issue; for example in the presence of transverse compressive stresses. Additionally, as the fiber volume fraction increases, so does the effect of microstructural architecture. With regard to the micromechanics analysis, the overall inelastic flow predicted by the generalized method of cells is in excellent agreement with that predicted using a large number of displacement-based finite elements.

Lissenden, Cliff J.↗

Flow/Damage Surfaces for Fiber-Reinforced Metals having Different Periodic Microstructures

Flow/damage surfaces can be defined in terms of stress, inelastic strain rate, and internal variables using a thermodynamics framework. A macroscale definition relevant to thermodynamics and usable in an experimental program is employed to map out surfaces of constant inelastic power in various stress planes. The inelastic flow of a model silicon carbide/ titanium composite system having rectangular, hexagonal, and square diagonal fiber packing, arrays subjected to biaxial stresses is quantified by flow/damage surfaces that are determined numerically from micromechanics. using both finite element analysis and the generalized method of cells. Residual stresses from processing are explicitly included and damage in the form of fiber-matrix debonding under transverse tensile and/or shear loading is represented by a simple interface model. The influence of microstructural architecture is largest whenever fiber-matrix debonding is not an issue, for example in the presence of transverse compressive stresses. Additionally, as the fiber volume fraction increases, so does the effect of microstructural architecture. With regard to the micromechanics analysis, the overall inelastic flow predicted by the generalized method of cells is in excellent agreement with that predicted using a large number of displacement-based finite elements.

Lissenden, Cliff J.↗

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

Nondestructive evaluation of fatigue damage in aluminum 2024 by x-ray diffraction

Aluminum alloys are widely used in the automobile and aerospace industries. This is due to their attractive low density-high modulus and low density-high strength characteristics. Unfortunately, cyclic stress-strain deformations alter the microstructure of aluminum alloys when they are placed into service. These structural changes can lead to fatigue damage and ultimately service failure. Since x-ray diffraction analysis is known to be a sensitive nondestructive indicator of structural changes due to deformations, this technique is being used to evaluate changes in the microstructure of cycled aluminum 2024 commercial alloys. Line shapes, widths, and positions in an x-ray diffraction pattern depend on microstructural properties such as grain size, grain orientation, residual stress, microstrain, etc. Changes in the microstructure due to fatigue will appear as changes in the diffraction pattern. One parameter used to characterize a reflection in a diffraction pattern is the full width at half maximum (FWHM). Preliminary x-ray diffraction results on cycled Al 2024 indicate that the (111) and (222) reflections of the matrix phase do not show any variations in the FWHM due to an increase in the fatigue cycles. However, the FWHM of the (200) and (400) reflections of the same phase unexpectedly showed a dramatic decrease. These results can be interpreted as due to the relaxation of some initial nonuniform residual stresses in the matrix phase lattice. Further work is in progress to evaluate the FWHM of the second phase of the cycled alloys.

Ferguson, Milton W.↗

Stress localization investigation of additively manufactured GRCop-42 thin-wall structure

A full-field crystal plasticity (CP) framework is presented for the GRCop-42 alloy to study microscopic mechanical behavior and local stress heterogeneities. The microstructures of additively manufactured (AM) materials are often unique relative to conventionally processed materials, and the local thermal histories drive these differences during the build process. These thermal histories depend on the process parameters (laser power, scan speed, and scan strategy) and the part geometry. Prior research has shown that the mechanical properties of thin-walled structures can vary significantly with wall thickness due to changes in the thermal boundary conditions during manufacturing. It is, therefore, desirable to perform CP simulations based on the phenomenological constitutive model to predict the local mechanical responses induced by microstructural heterogeneities. This work generates representative microstructures based on experimentally collected grain information (i.e., texture) for grain scale stress analysis, and the material constitutive parameters are calibrated using the experimental mechanical testing data. Here, we specifically investigated the effect of crystallographic texture and grain morphologies on the size-dependent mechanical properties of AM GRCop-42. The selection of appropriate material properties for implementing an effective free surface boundary condition and the influence of adjacent buffer layers are also discussed. Analysis of local field results reveals a strong correlation between stress localization and the initial grain orientation. However, no significant relationship between the misorientation of the individual adjacent grains and the average misorientation is observed.

36 MATERIALS SCIENCE↗

Desmearing two-dimensional small-angle neutron scattering data by central moment expansions

Resolution smearing is a critical challenge in the quantitative analysis of two-dimensional small-angle neutron scattering (SANS) data, particularly in studies of soft-matter flow and deformation using SANS. Here, we present a central moment expansion technique to address smearing in anisotropic scattering spectra, offering a model-free desmearing methodology. By accounting for directional variations in resolution smearing and enhancing computational efficiency, this approach reconstructs desmeared intensity distributions from smeared experimental data. Computational benchmarks using interacting hard-sphere fluids and Gaussian chain models validate the accuracy of the method, while simulated noise analyses confirm its robustness under experimental conditions. Experimental validation using rheological SANS data from shear-induced micellar structures demonstrates the practicality and effectiveness of the proposed algorithm. The desmearing technique provides a powerful tool for advancing the quantitative analysis of anisotropic scattering patterns, enabling precise insights into the interplay between material microstructure and macroscopic flow behavior.

anisotropic scattering spectra↗

Embedded High-Temperature Sensors: Enhancing Thermoelectrical Performance with Refractory Composites Gradient Layers

To monitor the stability of various energy and manufacturing systems, sensors capable of operating at temperatures exceeding 1000 °C in diverse environments for extended durations are essential. However, under harsh conditions, degradation of sensing materials is a concern that can be controlled by embedding the sensors into refractory oxides. Doped-LaCrO3 based composites are excellent candidates for high-temperature sensing applications due to their good thermoelectrical properties. However, chemical reactivity between the conductive phase and the refractory oxides can decrease the performance of the sensors. In this work, it was devised gradient-type protective layers safeguarding conductive phases within embedded thermocouples, which were fabricated and characterized by X-Ray Diffraction for phase development analysis, Scanning Electron Microscopy and Energy-dispersive X-ray spectroscopy for microstructure and cationic interdiffusion kinetics, long-term thermoelectric testing was completed up to 1400 °C. The enhanced performance of these novel sensors addresses a critical limitation, rendering them viable for long-term high-temperature applications.

20 FOSSIL-FUELED POWER PLANTS↗

Approximating the stress field within the unit cell of a fabric reinforced composite using replacement elements

This report concerns the prediction of the elastic moduli and the internal stresses within the unit cell of a fabric reinforced composite. In the proposed analysis no restrictions or assumptions are necessary concerning yarn or tow cross-sectional shapes or paths through the unit cell but the unit cell itself must be a right hexagonal parallelepiped. All the unit cell dimensions are assumed to be small with respect to the thickness of the composite structure that it models. The finite element analysis of a unit cell is usually complicated by the mesh generation problems and the non-standard, adjacent-cell boundary conditions. This analysis avoids these problems through the use of preprogrammed boundary conditions and replacement materials (or elements). With replacement elements it is not necessary to match all the constitutional material interfaces with finite element boundaries. Simple brick-shaped elements can be used to model the unit cell structure. The analysis predicts the elastic constants and the average stresses within each constituent material of each brick element. The application and results of this analysis are demonstrated through several example problems which include a number of composite microstructures.

Foye, R. L.↗

The Effect Stacking Fault Segregation and Phase Transformations have on Creep Strength in Ni-based Superalloys

In this study, two commercially similar polycrystalline Ni-based disk superalloys (LSHR and ME3) were creep tested at 760C and 552MPa to approximately 0.3% plastic strain. LSHR consistently displayed superior creep properties at this stress/temperature regime even though the microstructural characteristics between the two alloys were comparable. High resolution structural and chemical analysis, however, revealed significant differences between the two alloys among active gamma prime shearing modes involving superlattice intrinsic and extrinsic stacking faults. In ME3, Co and Cr segregation and Ni and Al depletion were observed along the intrinsic faults - revealing a gamma prime -to- gamma phase transformation. Conversely in LSHR, an alloy with a higher W content, Co and W segregation was observed along the intrinsic faults. This observation combined with scanning transmission electron microscopy (STEM) simulations confirm a gamma prime-to-D019 phase transformation along the intrinsic faults in LSHR. Using experimental observations and density functional theory calculations, a novel local phase transformation strengthening mechanism is proposed that could be further utilized to improve the high temperature creep capabilities of Ni-base disk alloys.

Superalloy↗

Comprehensive new insights on the potential use of SiC as plasma-facing materials in future fusion reactors

Abstract The performance of silicon carbide as an alternative plasma facing material (PFM) was studied at various irradiation conditions relevant to ion energies and fluxes of a fusion reactor. This analysis involves detailed modeling of subsurface plasma/material interactions, sputtered particle transport above the surface and redeposition, and related changes in material composition and microstructure induced by steady-state and Edge Localized Mode ion fluxes. Transition of a crystalline SiC surface to semi-crystalline and amorphous phases was analyzed based on advanced modeling of DIII-D tokamak experiments where SiC was irradiated in single- and multiple- L-mode and H-mode discharges. This analysis shows that displacement damage, particle deposition/redeposition, and D accumulation on the SiC divertor surface can lead to significant microstructural changes that result in enhanced sputtering erosion in comparison with the original crystalline material. However, the resulting total net erosion rate for a full-coverage, advanced tokamak, SiC coated divertor may well be acceptably low. Moreover, the C sputtering yield from the evolved SiC surface can be seven times lower than from a pure graphite surface; this would imply significantly reduced tritium co-deposition rates in a D-T tokamak reactor, compared with a pure carbon surface. It was also determined that chemical sputtering of both C and Si should not result in any noticeable effect on the net erosion, for attached plasma regimes. Our results thus show encouraging results overall for use of SiC as a PFM in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

Crystallization Kinetics of a Solid Oxide Fuel Cell Seal Glass by Differential Thermal Analysis

Crystallization kinetics of a barium calcium aluminosilicate glass (BCAS), a sealant material for planar solid oxide fuel cells, have been investigated by differential thermal analysis (DTA). From variation of DTA peak maximum temperature with heating rate, the activation energy for glass crystallization was calculated to be 259 kJ/mol. Development of crystalline phases on thermal treatments of the glass at various temperatures has been followed by powder x-ray diffraction. Microstructure and chemical composition of the crystalline phases were investigated by scanning electron microscopy and energy dispersive spectroscopic (EDS) analysis. BaSiO3 and hexacelsian (BaAl2Si2O8) were the primary crystalline phases whereas monoclinic celsian (BaAl2Si2O8) and (Ba(x), Ca(y))SiO4 were also detected as minor phases. Needle-shaped BaSiO3 crystals are formed first, followed by the formation of other phases at longer times of heat treatments. The glass does not fully crystallize even after long term heat treatments at 750 to 900 C.

Bansal, Narottam P.↗

Microstructural origin of high‐strength Tyranno SA4 SiC fiber studied by comparative Raman spectroscopy #

Tyranno SA4 grade SiC fiber is an emerging continuous fiber with excellent mechanical properties. The origin of the fiber's high-performance was studied by comparative Raman spectroscopy of four different grades of SiC fibers and reference SiC monolith. Analysis of the Raman spectra of fiber cross-sections, surface and homogeneity, and fibers under stress, revealed how differences in microstructure, such as crystalline order, size, and the presence of critical flaws, dictate mechanical properties. In conclusion, this information can help optimize SiC fiber manufacturing.

36 MATERIALS SCIENCE↗

Correlations Among Microstructure, Morphology, Chemistry, and Isotopic Systematics of Hibonite in CM Chondrites

Introduction: Hibonite is a primary refractory phase occurring in many CAIs, typically with spinel and perovskite. Our microstructural studies of CAIs from carbonaceous chondrites reveal a range of stacking defect densities and correlated non-stoichiometry in hibonite. We also conducted a series of annealing experiments, demonstrating that the Mg-Al substitution stabilized the formation of defect-structured hibonite. Here, we continue a detailed TEM analysis of hibonite-bearing inclusions from CM chondrites that have been well-characterized isotopically. We examine possible correlations of microstructure, morphology, mineralogy, and chemical and isotopic systematics of CM hibonites in order to better understand the formation history of hibonite in the early solar nebula. Methods: Fifteen hibonite-bearing inclusions from the Paris CM chondrite were analyzed using a JEOL 7600F SEM and a JEOL 8530F electron microprobe. In addition to three hibonite-bearing inclusions from the Murchison CM chondrite previously reported, we selected three inclusions from Paris, Pmt1-6, 1-9, and 1-10, representing a range of 26Al/27Al ratios and minor element concentrations for a detailed TEM study. We extracted TEM sections from hibonite grains using a FEI Quanta 3D field emission gun SEM/FIB. The sections were then examined using a JEOL 2500SE field-emission scanning TEM equipped with a Thermo-Noran thin window EDX spectrometer. Results and Discussion: A total of six hibonite-bearing inclusions, including two platy hibonite crystals (PLACs) and four spinel-hibonite inclusions (SHIBs), were studied. There are notable differences in chemical and isotopic compositions between the inclusions (Table 1), indicative of their different formation environment or timing. Our TEM observations show perfectly-ordered, stoichiometric hibonite crystals without stacking defects in two PLACs, 2-7-1 and 2-8-2, and in three SHIBs, Pmt1-6, 1-9, and 1-10. In contrast, SHIB 1-9-5 hibonite grains contain a low density of stacking defects linked to an increase in MgO contents, indicating complex, disordered intergrowths of stoichiometric and MgO-enriched hibonites. From the data collected to date, we find no clear correlation between the microstructures of hibonite and its morphological and mineralogical types that reflect distinct chemical and isotopic systematics [6-8,10]. Interestingly, the presence of no or few stacking defects in hibonite from the PLACs and SHIBs are in contrast to our experimental studies that produced very high densities of stacking defects in hibonite [3-5]. Unlike our experi-ments, electron microprobe data from the PLACs and SHIBs hibonite grains show a strong correlation between (Ti4++Si4+) and Mg2+ cations, suggesting that coupled substitutions of (Ti4++Mg2+) and (Si4++Mg2+) for 2Al3+ inhibit the formation of defect-structured hibonite. However, our experimental studies suggest that kinetics (e.g., cooling rate) or other thermal effects also exert a strong control on the microstructures and chemical compositions of hibonite. In Pmt1-6, elongated perovskite grains present at the hibonite grain boundaries display (121) twinning, indicative of a fast cooling (>50degC/min) after high-temperature events. Therefore, the nebular microstructural characteristics of hibonite, at least in this inclusion, would not have destroyed by subsequent high-temperature annealing. Conclusions: Our TEM observations thus far show no clear correlation in microstructures, morphological and mineralogical characteristics, and chemical and isotopic systematics of hibonites from CM chondrites. The observed variation in stacking defect densities in the hibonites may be controlled by thermal processes in the early solar nebula. A detailed TEM analysis of additional CM hibonite samples is underway to evaluate this hypothesis.

Han, J.↗