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At least 973 records · Page 54

Recent progress on the mesoscale modeling of architected thin-films via phase-field formulations of physical vapor deposition

Thin-film coatings can be found everywhere in modern technological applications due to desirable electrical, mechanical, chemical, and optical properties. These properties directly depend upon the thin-film’s microstructural features, which are themselves influenced by the materials and vapor-deposition processing conditions used for fabrication. As such, understanding processing-microstructure relationships is essential to designing thin-films with optimized properties, and discovering new processing conditions that allow for novel thin-films with multifunctional microstructures. Here, a short review is presented on recent developments that utilize the phase-field method to simultaneously model the vapor-deposition process and corresponding microstructure formation at the mesoscale. Also phase-field-based vapor-deposition models that simulate thin-film growth of immiscible alloy and polycrystalline systems are highlighted in addition to machine-learning-based surrogate models that can facilitate accelerated high-fidelity simulations along with materials design and exploration studies.

36 MATERIALS SCIENCE↗

High-temperature ordered intermetallic alloys III; Proceedings of the Third Symposium, Boston, MA, Nov. 29-Dec. 1, 1988

The present conference on high-temperature ordered intermetallic alloys discusses alloy theory and phase stability, defects and microstructures, mechanical behavior, alloy design and material processing, multiphase and composite materials, nickel aluminides, titanium aluminides, and other ordered intermetallics. Attention is given to compositional effects on processing and properties of nickel aluminides, dynamic compaction and hot-isostatic-pressing of nickel aluminides, improvement of elevated-temperature material properties in Ni3Al, the effect of microalloying B on the high-temperature mechanical properties of Ti3Al, the effects of structure on creep of Ti-53.4 mol pct Al intermetallics, the deformation microstructure in Ni3Si polycrystals strained over the range of temperature of flow stress anomaly, and the microstructure and mechanical properties of dual phase alloys consisting of the intermetallic phases.

Liu, C. T.↗

GRCop-42: Comparison between laser powder bed fusion and laser powder direct energy deposition

This study involves a comparative analysis of additively manufactured GRCop-42 specimens produced using two processes: laser-powder bed fusion (L-PBF) and laser powder direct energy deposition (LP-DED). The investigation characterizes a range of material attributes, including surface topography, internal defects, microstructural features, quasi-static mechanical properties, and fractographic characteristics. The findings demonstrate that, despite the specimens being fabricated with the same base material, the resulting material properties vary significantly between the two additive manufacturing processes. As such, material properties cannot be presumed to be uniform across different manufacturing methods. Consequently, material characterization must be conducted for individual manufacturing processes based on specific parameters.

36 MATERIALS SCIENCE↗

Nanoindentation mapping defects filtration for heterogeneous materials using generative adversarial networks

Advanced composite materials with multiple phases and heterogeneous microstructure necessitate spatial mapping characterization of elastic modulus to develop constitutive relations and overall mechanical response. Such modulus mapping can be obtained using the nanoindentation technique, where the indenter tip raster over the selected microstructure region. Typically, a surface preparation procedure is done in the specimens to ensure proper contact between the indenter tip and sample surface. However, a near-perfect surface finish is unachievable in heterogeneous materials, primarily with ceramic reinforcements, due to the differential material removal rate during polishing. Thus, the nanoindenter records localized erroneous measurements due to differences in surface roughness and corresponding force response. This study establishes a novel deep learning-based strategy to rectify incorrect experimental spatial measurements acquire during nanoindentation modulus mapping. Here, the integrated bicubic interpolation and generative adversarial networks (GANs) model was trained using 14 ceramic and 18 metallic data sets, each comprising 65,536 measurements. The developed algorithm was validated against experimental measurements on four unknown specimens. The standard deviation in measured elastic modulus reduces by ~50% in ceramics and ~72% in metallic samples. This computational framework proposes a novel approach to reducing uncertainty in materials’ properties using state-of-the-art computer vision techniques.

36 MATERIALS SCIENCE↗

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↗

Quantum Dots Microstructured Optical Fiber for X-Ray Detection

Microstructured optical fibers containing quantum dots scintillation material comprised of zinc sulfide nanocrystals doped with magnesium sulfide are presented. These quantum dots are applied inside the microstructured optical fibers using capillary action. The x-ray photon counts of these fibers are compared to the output of a collimated CdTe solid state detector over an energy range from 10 to 40 keV. The results of the fiber light output and associated effects of an acrylate coating and the quantum dot application technique are discussed.

DeHaven, Stan↗

Quantum Dots Microstructured Optical Fiber for X-Ray Detection

A novel concept for the detection of x-rays with microstructured optical fibers containing quantum dots scintillation material comprised of zinc sulfide nanocrystals doped with magnesium sulfide is presented. These quantum dots are applied inside the microstructured optical fibers using capillary action. The x-ray photon counts of these fibers are compared to the output of a collimated CdTe solid state detector over an energy range from 10 to 40 keV. The results of the fiber light output and associated effects of an acrylate coating and the quantum dots application technique are discussed.

DeHaven, S. L.↗

Irradiation Testing of Additively Manufactured Materials for LWR Applications: Alloy 718 and 316L Stainless Steel

The objective of this NSUF Project is to assess the changes in irradiated additively manufactured (AM) material properties as compared to non-irradiated material. Type 316L stainless steel and Alloy 718 samples were produced using Direct Metal Laser Melting (DMLM) fabrication. Materials produced from this fabrication method have several potential applications within the nuclear industry as reactor internal repair parts, fuel debris resistant filters, or fuel spacers within existing light water reactors (LWRs). AM materials have been shown to achieve equivalent mechanical behavior in simulated reactor environments as compared to wrought materials, but have significantly more flexibility when it comes to unique design features. The increased component design flexibility makes these AM materials an attractive choice for both current LWR applications as well as for small modular reactor (SMR) designs. Prior to use of these materials in reactor fleet operation, the industry as a whole must evaluate the effects of irradiation on their material properties. Standard 0.4 inch thick Compact Tension specimens and SSJ3 type tensile bars were neutron irradiated at the Advanced Test Reactor to ~1 dpa for the purpose of performing a variety of mechanical tests in a range of simulated environments applicable to LWRs. For the ductile austenitic Type 316L stainless steel, the irradiated data will be used to confirm that the AM process produces materials with properties that are equivalent to wrought materials under testing conditions applicable to LWR operation. Transmission electron microscopy analysis was also performed in order to understand microstructural and microchemical changes induced in each material in response to neutron irradiation. If possible, data collected from these AM 316L samples will be used to remove fluence limits from specifications of ASME code cases for this alloy, which will give vendors much more flexibility in building future components.

36 - MATERIALS SCIENCE↗

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.

36 MATERIALS SCIENCE↗

Correlating microstructure and mechanical properties of harvested high dose Zorita light water reactor internals

Here, in this study, microstructural studies and micro-mechanical testing of an ex-plant material harvested from the decommissioned pressurized water reactor (PWR) is carried out. Irradiated 304 stainless steel (SS) components were harvested by the Electric Power Research Institute, U.S. Nuclear Regulatory Commission, and members of the José Cabrera Nuclear Power Station (Zorita) in Spain. The bi-crystalline micro-tensile specimens, atom probe tomography (APT) tips, and transmission electron microscopy (TEM) lamellae were fabricated from the baffle plate materials irradiated to 0.05, 15 and 50 dpa to elucidate microstructural, microchemical, and local mechanical properties changes as a function of dose. TEM and APT studies reveal radiation induced Ni, Cr, and Si rich precipitates in the 15 dpa sample that become smaller and partially redissolve into the matrix of the 50 dpa sample (decreasing size and number density). Dislocation loop and cavity number density and size were quantified as a function of dose as well as swelling. Intergranular Ni and Si enrichments with concomitant Fe and Cr depletion were observed in the 15 dpa sample and were more pronounced in the 50 dpa sample. Micro-tensile testing performed in the scanning electron microscope (SEM) at room temperature and 300 °C shows that the material's local yield strength and ultimate tensile strength decreases with increased dose and elevated test temperature and provides further insights via localized strain mapping. Current and previous mechanical data was compared with calculated values using the dispersed barrier hardening model with inputs of dislocation loops, precipitates, and cavities from microstructural characterization.

36 MATERIALS SCIENCE↗

Critical impact of experimentally-driven strut level anisotropic material models in advanced stress analysis of additively manufactured lattice structures

The rapid acceleration in materials discovery may overshadow the importance of thoroughly understanding the mechanical performance of newly developed materials in demanding environments. The recent interest in combining parametric studies with machine learning techniques to explore how changes in specific processing parameters or model inputs affect the overall behavior of a material system can only be truly beneficial if the governing constitutive relations describing material behavior are accurately established. In this study, we demonstrate the critical impact of accurately representing strut-level anisotropic material behavior in advanced stress analysis of additively manufactured lattice structures (AMLS). We introduce a systematic experimental and modeling approach for developing strut-level anisotropic elastoplastic material models that account for the influence of microstructural features such as porosity, texture, and surface roughness on the development of local anisotropic mechanical properties, which vary with strut orientation relative to the build direction (BD). As a result the presented material model captures and relates the statistics of spatially varying struts’ microstructural features to the local stress distribution. Our findings suggest that incorporating strut-level anisotropic material behavior into unit cell analysis significantly influences the load distribution and evolution of local stresses within the structure. Therefore, accounting for this anisotropy is critical for developing an understanding of unit cell behavior and performance, including subsequent topology/component design optimization based on this analysis.

Sahoo, Subhadip [University of Arizona]↗

High temperature annealing of irradiated nuclear grade graphite

Previous work has shown that the material properties of nuclear grade graphite are substantially affected by the atomic and microstructural changes that occur during neutron-irradiation. The parameters that play a role in these changes are irradiation dose, temperature, graphite composition and the initial microstructure of the graphite. Understanding the details of how these material changes occur and exactly what the changes consists of will enable the prediction of the material property changes as a function of these variables. Other work has shown these atomic level and microstructural changes can be healed or annealed out by raising the irradiated graphite above its irradiation temperature. Here in this work, experiments were carried out to investigate how the properties of irradiated graphite recover when heated. By showing property recovery as a function of annealing temperature or energy, insight is provided into the type of damage that occurred during neutron-irradiation. The data presented here shows recovery of thermal diffusivity, coefficient of thermal expansion, Young's modulus and electrical resistivity between annealing temperatures of 500 °C and 2380 °C. Graphite grades NBG-18, IG-110 and PCEA are considered that were both stressed and unstressed during irradiation.

36 MATERIALS SCIENCE↗

An automated procedure built on MTEX for reconstructing deformation twin hierarchies from electron backscattered diffraction datasets of heavily twinned microstructures

Here we present a set of algorithms built on the MTEX and MATLAB graph toolboxes for automatic reconstruction of deformation twin hierarchies from Electron Backscatter Diffraction (EBSD) datasets with a focus on developing methods for heavily twinned microstructures (twin fractions >0.5). The algorithms address key issues arising at large strains, mainly: missing twin relationships, grouping of heavily deformed grain fragments into families of similar orientation originating from a single initial grain, identification of parent fragments for large twin volume fractions, and classification of families having twin relationships with multiple families. To facilitate the development of these algorithms, large-grained ultra-high purity α-Ti deformed in compression along two directions is investigated. Graphs are utilized to handle non-local geometric merging and to represent relationships throughout the reconstruction process. When determining if a grain fragment is from the undeformed microstructure, the combined metrics of the fragment's orientation volume fraction in the initial texture and the directed graph centrality measure of out-closeness (the number of nodes reached in a graph from a given node) are essential. To address automation in reconstructing the sequence of twinning and relating fragments originating from a single grain in the initial microstructure, the twin family tree is formulated as a minimum spanning tree emanating from the initial grain family. A scheme constructing the distances associated with twin relationship comprising the spanning tree is developed, and a novel quasi-directional Prim spanning tree algorithm is used to determine the twin family tree. The procedure is demonstrated to significantly improve the level of automation in reconstructing twin hierarchies in heavily twinned microstructure compared to other methodologies in literature. The procedure can readily be applied to analyses of twinning in metals, as well as provide an approach for routinely extracting twin statistics at larger deformation levels than previously possible. Significantly, the procedure is demonstrated to be capable of identifying third generation twinning in α-Ti microstructures.

36 MATERIALS SCIENCE↗

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys.

Bayuzick, Robert J.↗

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilatometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.

Bayuzick, R. J.↗

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods [1-6]. Dilitometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics [7]. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov [8]. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.

Bayuzick, Robert J.↗