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At least 217 records · Page 12

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

Formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

The formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗

Influence of Microstructural Features on Austenite-Martensite Interfaces in NiTi Shape Memory Alloys

Shape memory alloys (SMAs) exhibit several unique thermomechanical properties due to a reversible martensitic phase transformation. A key aspect of this transformation is the austenite-martensite interface. Here we present a molecular dynamics (MD) simulation methodology to study the atomic-scale features of austenite-martensite interface migration under near-equilibrium conditions. In single crystals, the interfaces migrate rapidly with only a small thermodynamic driving force. In polycrystals, however, interface migration is significantly impeded due to the change in orientation relationship at grain boundaries and the stored elastic energy resulting from microstructural constraints. This behavior can be linked to several mechanisms associated with transformation width and hysteresis in SMAs, properties of great importance for applications involving actuation. Additionally, we will present preliminary MD simulation results on the influence of precipitates on the formation and migration of austenite-martensite interfaces.

Gabriel Plummer↗

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

Formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗

3D-ink-printing of monocrystalline YBCO superconductor

Single-crystal microstructure can bring high performance for many materials includingpiezoelectrics1, 2, semiconductors3, 4, and cuprate superconductors5. Unlike single-crystal metalsthat can be machined into complex components6, most single-crystal ceramics are limited to theshape of thin films or plates due to their brittleness. However, more designs of advanced devicesneed to break these geometric limitations. 3D-ink-printing can efficiently fabricate complex architectured ceramics, but the microstructure is polycrystals. Here, for the first time, we demonstrate a route to grow single-crystal on 3D printed ceramic-YBa2Cu3O7-x (YBCO)superconductors that can simultaneously have complex architectures and high critical currentdensity. An ink containing precursor powders was 3D extruded and sintered to obtain polycrystalYBCO micro-lattices. A single-crystal seed is then utilized to grow single crystal on 3D-printedmicro-lattices by melt growth method. We found that the geometric details of 3D printed microlatticecan survive after it went through liquid + solid phase region above its peritectic temperature.More complex YBCO single-crystal parts, such as horizontal and toroidal coils, were thensuccessfully fabricated. In addition, Origami can be implemented on our 3D printed sample to increase their complexity. This research provides a new way to develop superconducting devicessuch as undulators for synchrotron radiation and microwave cavities for dark-matter axion search7.We expect this new process will inspire more studies about 3D printing of single-crystal ceramics. For example, 3D printing of BaTiO3 can be developed to grow a single crystal8 for the applications of dielectric capacitors and transducers.

43 PARTICLE ACCELERATORS↗

Vacancy-mediated transport and segregation tendencies of solutes in FCC Ni under diffusional creep

Nickel-based alloys are known for their excellent corrosion resistance and high-temperature strength. However, at high temperatures, polycrystals experience grain boundary-stress-driven vacancy diffusion leading to diffusion-driven creep. Understanding the fundamentals of defect migration is essential to predict diffusion creep behavior. In this talk, we explore the Nabarro-Herring diffusion creep and the associated solute segregation that is likely to result from the different diffusivities of the solute and solvent elements. Density functional theory calculations are performed to determine the formation, migration and binding energies of the solute and vacancy defects in stress-free and stressed states. The dilute-limit transport coefficients are then calculated using the self-consistent mean field theory as implemented in the Kinetic Cluster Expansion (KineCluE) code. Predictions of diffusion creep strain rates and solute segregation are then presented for various solutes, stress and temperatures. This work opens research avenues for exploration of diffusion creep via characterization of elemental segregation to grain boundaries.

36 MATERIALS SCIENCE↗

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗

Understanding Fundamental Mechanisms Behind Anomalous Segregation Behavior at Grain Boundaries during Diffusional Creep

Recent experimental studies in a nickel (Ni)-rhenium (Re) alloy demonstrated anisotropic elemental segregation around grain boundaries (GBs) while under tensile strain. Some GBs showed Re enrichment, while others showed Re depletion. We hypothesize that differing vacancy fluxes to GBs, caused by the anisotropic elastic stresses generated within the polycrystal, results in anisotropic creep-induced segregation (CIS) and grain growth. Using molecular dynamics simulations, we developed a mechanistic understanding of CIS and determined the contribution of elastic stresses and grain growth in Ni-Re alloys. We find that the stress state of the GB significantly changes the segregation energy profile for Re atoms, leading to significant Re redistribution. Further, as the GB migrates, the segregation/desegregation tendency of Re leads to bands of Re enrichment/depletion. Our results have important consequences for the quantitative predictions of diffusion creep and for the design of high-temperature creep-resistant Ni alloys.

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↗

Simultaneous Optimization of Crystal Plasticity Hardening Parameters

Crystal plasticity models relate macroscopic deformation behavior to the evolution of slip systems strength, but their parameterization is often non-unique, with multiple parameter sets being able to describe the same macroscopic behavior. To address this issue, the present work adopts a Bayesian optimization framework for the parameterization of face-centered cubic plasticity models while simultaneously considering multiple experimental datasets from the literature. For single crystal Cu, parameter optimization was guided by the tensile stress–strain curves along several crystallographic orientations, with an adequate fit being found for five orientations at once. While additional parameters allowed for the consideration of more physical mechanisms, like different slip system interaction strengths or misorientations inherent to the experimental data, the extra dimensionality was found to limit the efficiency of the global minimization procedure. For polycrystalline Ni, multiple grain sizes were considered together in a representative polycrystalline model, with the optimization able to reconcile the model with the data for three grain sizes at once. As meaningful interpretation of parameters relies on the uniqueness of their values, incorporating multiple datasets into this discerning parameterization procedure enables more robust prediction and application of crystal plasticity models.

36 MATERIALS SCIENCE↗

Simulation of dynamic crystal plasticity with a Lagrangian discontinuous Galerkin hydrodynamic method

Here we present a new Lagrangian modal discontinuous Galerkin (DG) hydrodynamic method that supports a dynamic dislocation based crystal plasticity model for simulating the mechanical behavior of crystallographic materials, both single crystal and polycrystalline, under dynamic conditions. A modal DG approach is used to evolve fields relevant to conservation laws. These fields are approximated by Taylor series polynomials of varying degree. These polynomials describe macro-scale hydrodynamic behavior while their evolution is determined by evaluating the dynamic crystal plasticity model at material points within the element. The dynamic crystal plasticity model is sensitive to the time increment size, with too large of time increments leading to instability in the model. To mitigate this, the temporal evolution of the dynamic crystal plasticity model is achieved with the combination of a sub-incrementing scheme with Heun’s third-order time integration scheme, which is also used to temporally evolve the governing equations. The implementation of the dynamic crystal plasticity model within the DG framework is tested using a 2D approximation of the Taylor impact test with a single crystal material, using quadratic elements that have faces that can bend. In addition to the standard continuous material modeling, we propose a new simulation method that would represent the heterogeneous behavior of polycrystalline microstructures within an element by varying the position and material properties of the material points within the element. This method is demonstrated using random orientation distributions on materials points that are arranged in both structured and random configurations.

42 ENGINEERING↗

Machine learning based approach to predict ductile damage model parameters for polycrystalline metals

Damage models for ductile materials typically need to be parameterized, often with the appropriate parameters changing for a given material depending on the loading conditions. This can make parameterizing these models computationally expensive, since an inverse problem must be solved for each loading condition. Using standard inverse modeling techniques typically requires hundreds or thousands of high-fidelity computer simulations to estimate the optimal parameters. Additionally, the time of a human expert is required to set up the inverse model. Machine learning has recently emerged as an alternative approach to inverse modeling in these settings, where the machine learning model is trained in an offline manner and new parameters can be quickly generated on the fly, after training is complete. Here, this work utilizes such a workflow to enable the rapid parameterization of a ductile damage model called TEPLA with a machine learning inverse model. The machine learning model can efficiently estimate the model parameters much faster, as compared to previously employed methods, such as Bayesian calibration. The results demonstrate good accuracy on a synthetic test dataset and is validated against experimental data.

36 MATERIALS SCIENCE↗

Unraveling the implications of finite specimen size on the interpretation of dynamic experiments for polycrystalline aluminum through direct numerical simulations

Normal and Pressure-shear plate impact (NPI and PSPI) experiments are popular experimental techniques for studying the mean-field macroscopic behavior of polycrystalline metals under high-rate dynamic loading. However, since both configurations rely upon geometry for subjecting the specimen to high strain rates, these experiments often involve a limited specimen size. Moreover, because of the inherent heterogeneities present within polycrystalline metals, it is difficult to ascertain if the size of the specimen and/or regions where measurements are made are sufficiently large for making representative inferences about the mean-field macroscopic properties from single-point velocity measurements. In the present study, we quantify the expected measurement variability on observable point measurements in NPI and PSPI experiments by carrying out direct numerical simulations (DNS) of statistically representative polycrystalline microstructures subjected to dynamic compression and compression-shear loading. In particular, we consider the role of specific material heterogeneities (e.g. the grain-to-grain difference in size, crystallographic orientation) on dispersion in the normal and transverse particle velocity records and on local fluctuations in key state variables (e.g. velocity, accumulated plastic strain) by incorporating these effects directly into a representative synthetic microstructure geometry and crystalline description of pure polycrystalline aluminum. The form of the present study is a large parametric investigation, consisting of ten ensembles of one hundred simulations. Each of the thousand simulations reflects a randomly realized synthetic microstructure in one of five cases of decreasing average grain size for the two loading configurations. Our analysis of the DNS results demonstrates that for both of these experimental configurations, the grain size directly correlates with the coefficient of variation (CV) in simulated point measurements, showing a convergent decrease in CV to zero (i.e. particle velocity record approaches the mean-field value) with decreasing grain size. Remarkably, the magnitude of variations in the particle velocity record is shown to be largest where the deviatoric stresses are most significant. In the case of NPI, this occurs at the elastic and plastic wavefront, whereas, in the case of PSPI, the magnitude of fluctuations are approximately constant throughout the experimental window time. The reasoning for the scatter in particle velocity due to the heterogeneous microstructure is demonstrated to be dependent on the mechanisms for accommodating deformation and on the interaction of reflection waves generated at sites of heterogeneities occurring at the scale of grains. Lastly, we develop a power-law description for the magnitude of scattering versus characteristic length, which provides a statistical framework for assessing the required number of grains per characteristic specimen dimension for minimizing scatter within these two experimental configurations (NPI, PSPI).

36 MATERIALS SCIENCE↗

Survey of the mechanical and physical behaviors of yttria-stabilized zirconia from multiple dental laboratories

Background: When selecting zirconia for a dental restoration, laboratory prescriptions often refer to high strength and high translucency. In this survey, zirconia specimens were ordered from various dental laboratories for posterior (high strength) and anterior (high translucency) clinical indications. The specimens were then tested and evaluated for their mechanical and physical behaviors. Methods: In a double-blinded manner, 9 laboratories provided 32 specimens from 17 different zirconia blanks, which were tested in the American Dental Association laboratory. Flexural strength tests were performed on standard specimens, and fracture surfaces were examined using both optical and scanning electron microscopy. Chemical composition, Vickers hardness, and absolute transmittance measurements were also performed. Results: A large scatter in the strength values was observed. The zirconia intended for posterior applications displayed strengths (SD) from 195 through 783 MPa (490 [183] MPa), which overlapped greatly with the strengths (SD) of the zirconia intended for anterior applications, 320 through 768 MPa (581 [136] MPa). However, when the strength values were recalculated on the basis of yttria content, the strengths (SD) were 584 (158) MPa for 3 mol% yttria and 373 (104) MPa for 5 mol% yttria. Conclusions: When a prescription was given to dental laboratories to request zirconia on the basis of clinical requirements, there was a large scatter and no consistency in the resulting strength values partly because of mixed use of 3 mol% and 5 mol% yttria zirconia. The 3 mol% materials had much higher strength when the strength values were grouped according to yttria content. Strength was also highly dependent on processing and finishing at the dental laboratories.

3 mol% yttria-tetragonal zirconia polycrystal (3Y-↗

Learning macroscopic internal variables and history dependence from microscopic models

This paper concerns the study of history dependent phenomena in heterogeneous materials in a two-scale setting where the material is specified at a fine microscopic scale of heterogeneities that is much smaller than the coarse macroscopic scale of application. Here, we specifically study a polycrystalline medium where each grain is governed by crystal plasticity while the solid is subjected to macroscopic dynamic loads. The theory of homogenization allows us to solve the macroscale problem directly with a constitutive relation that is defined implicitly by the solution of the microscale problem. However, the homogenization leads to a highly complex history dependence at the macroscale, one that can be quite different from that at the microscale. In this paper, we examine the use of machine-learning, and especially deep neural networks, to harness data generated by repeatedly solving the finer scale model to: (i) gain insights into the history dependence and the macroscopic internal variables that govern the overall response; and (ii) to create a computationally efficient surrogate of its solution operator, that can directly be used at the coarser scale with no further modeling. We do so by introducing a recurrent neural operator (RNO), and show that: (i) the architecture and the learned internal variables can provide insight into the physics of the macroscopic problem; and (ii) that the RNO can provide multiscale, specifically FE 2 , accuracy at a cost comparable to a conventional empirical constitutive relation.

36 MATERIALS SCIENCE↗

Kinetics of the luminescence decay of Fe{sup 2+} impurity centres in polycrystalline ZnSe upon excitation by an electron beam

The kinetics of the decay of the luminescence of Fe{sup 2+} ions is measured at nitrogen temperature in polycrystalline ZnSe excited by a short pulse of accelerated electrons. The time dependence of the luminescence intensity differs from the exponential one, observed upon excitation of luminescence by a short light pulse. The obtained nonexponential dependence is theoretically described. The explanation is based on the quenching effect of the excited state of the Fe{sup 2+} ion by free electrons of the volume charge of the current of accelerated electrons in the sample (Auger effect). It was shown that the relaxation of the volume charge after the electron-accelerating voltage is removed makes a significant contribution to the decay kinetics of the impurity luminescence. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Experimental investigation of laser ablation of stone polycrystalline targets

We report the results of an experimental investigation of ablation of stone polycrystalline targets of complex multicomponent composition, which imitate the substance of asteroids. The targets were irradiated by nanosecond pulses of a neodymium laser at an energy density Φ{sub L} of up to 5 × 10{sup 4} J cm{sup −2}. The experiments demonstrated the existence of two ablation regimes, with the boundary between them lying at Φ{sub L} ≈ 4000 J cm{sup −2}. The regime change is characterised by a change in the form of the dependence of the surface mass density of removed target material on the laser energy density and by the appearance of a minimum in the dependence of specific energy of destruction on Φ{sub L}. This is supposedly related to the passage from a one-dimensional plasma plume expansion to the three-dimensional one and the corresponding decrease in the efficiency of energy transfer from the laser beam to the target due to a lowering of laser-produced plasma density. Our experiments also showed the existence of a maximum in impulse coupling coefficient C{sub m} as a function of laser energy density (C{sub m} ≈ 6.3 × 10{sup −5} N W{sup −1} for Φ{sub L} = Φ{sub opt} ≈ 25 J cm{sup −2}). Maxima were also recorded in the dependences of the ablation efficiency and average ablation flow velocity on Φ{sub L}. For Φ{sub L} > Φ{sub opt}, the decrease in the function C{sub m}(Φ{sub L}) turns out to be much steeper than for metals and polymer materials. The difference is supposedly due to the lower strength and lower plasticity of the polycrystalline stone targets. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗