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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Electron beam melting of Inconel 718: Effects of processing and post-processing

This study reports the effect of process temperature on microstructure evolution of electron beam melted Inconel 718. Samples fabricated at 915°C had fine grain boundary δ (∼200 nm) along with coarse intragranular δ spanning through the length of the grains. On the other hand, samples fabricated at 990°C, only had grain boundary δ along with secondary carbides. During hot isostatic pressing, the distribution of carbides governs the grain growth vs. lack of it. The samples fabricated at 990°C having grain boundary carbides had no grain growth owing to the pinning effect of carbides. In contrast, the sample processed at 915°C had significant grain growth owing to dissolution of grain boundary δ phase and absence of grain boundary carbides.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Creep deformation mechanism mapping in nickel base disk superalloys

We investigated the creep deformation mechanisms at intermediate temperature in ME3, a modern Ni-based disk superalloy, using diffraction contrast imaging. Both conventional transmission electron microscopy (TEM) and scanning TEM were utilised. Distinctly different deformation mechanisms become operative during creep at temperatures between 677-815 °C and at stresses ranging from 274 to 724 MPa. Both polycrystalline and single-crystal creep tests were conducted. The single-crystal tests provide new insight into grain orientation effects on creep response and deformation mechanisms. Creep at lower temperatures (≤760 °C) resulted in the thermally activated shearing modes such as microtwinning, stacking fault ribbons and isolated superlattice extrinsic stacking faults. In contrast, these faulting modes occurred much less frequently during creep at 815 °C under lower applied stresses. Instead, the principal deformation mode was dislocation climb bypass. In addition to the difference in creep behaviour and creep deformation mechanisms as a function of stress and temperature, it was also observed that microstructural evolution occurs during creep at 760 °C and above, where the secondary coarsened and the tertiary precipitates dissolved. Based on this work, a creep deformation mechanism map is proposed, emphasising the influence of stress and temperature on the underlying creep mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effects of electron–phonon coupling on damage accumulation in molecular dynamics simulations of irradiated nickel

The role of the electronic system in high energy displacement cascades is explored. The energy exchange between the electronic and the atomic subsystem is described by the electron–phonon coupling. The electronic effects on the damage accumulation due to 100 keV Ni ion cascades in nickel, a prototype system to a large group of nickel-based high entropy alloys, are investigated for overlapping cascades. It is shown that the energy exchange between the two subsystems affects microstructure evolution, resulting in the formation of smaller clusters and more isolated defects. This effect is more significant for the vacancy cluster formation and size distribution.

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↗
DOE OSTI2017

Simulations of irradiated-enhanced segregation and phase separation in Fe–Cu–Mn alloys

For reactor pressure vessel steels, the addition of Cu, Mn, and Ni has a positive effect on mechanical, corrosion and radiation resistance properties. However, experiments show that radiation-enhanced segregation and/or phase separation is one of important material property degradation processes. In this work, we developed a model integrating rate theory and phase-field approaches to investigate the effect of irradiation on solute segregation and phase separation. The rate theory is used to describe the accumulation and clustering of radiation defects while the phase-field approach describes the effect of radiation defects on phase stability and microstructure evolution. The Fe-Cu-Mn ternary alloy is taken as a model system. The free energies used in the phase-field model are from CALPHAD. Spatial dependent radiation damage from atomistic simulations is introduced into the simulation cell for a given radiation dose rate. The radiation effect on segregation and phase separation is taken into account through the defect concentration dependence of solute mobility. With the model the effect of temperatures and radiation rates on Cu and Mn segregation and Cu-rich phase nucleation are systematically investigated. The segregation and nucleation mechanisms are analyzed. The simulations demonstrated that the nucleus of Cu precipitates has a core-shell composition profile, i.e., Cu rich at center and Mn rich at the interface, in good agreement with the theoretical calculation as well as experimental observations.

Li, Boyan↗
DOE OSTI2019

Quantifying uncertainty in the process-structure relationship for Al–Cu solidification

Phase field method (PFM) is a simulation tool to predict microstructural evolution during solidification and is helpful to establish the process-structure relationship for alloys. The robustness of the relationship however is affected by model-form and parameter uncertainties in PFM. In this paper, the uncertainty associated with the thermodynamic and process parameters of PFM is studied and quantified. Surrogate modeling is used to interpolate four quantities of interests (QoIs), including dendritic perimeter, area, primary arm length, and solute segregation, as functions of thermodynamic and process parameters. A sparse grid approach is applied to mitigate the curse-of-dimensionality computational burden in uncertainty quantification. Polynomial chaos expansion is employed to obtain the probability density functions of the QoIs. The effect of parameter uncertainty on the Al–Cu dendritic growth during solidification simulation are investigated. Here, the results show that the dendritic morphology varies significantly with respect to the interface mobility and the initial temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interstitial hydrogen enhances the mobility of some grain boundaries in tungsten

Segregation of interstitials at a grain boundary (GB) is known to generally lower its mobility. This phenomenon, called 'solute-drag', has important ramifications on the process of recrystallization and microstructural evolution. Here, we present predictions from molecular dynamics (MD) simulations which demonstrate that interstitial hydrogen in tungsten can in fact increase the mobility of some GBs which exhibit shear coupling. Assuming a disconnection-based mechanism, activation energies and pre-factors for disconnection nucleation are predicted from simulations of shear-coupled motion. In GBs where enhanced mobility is predicted, interstitial H reduces both the activation energy and the pre-factor for disconnection nucleation, thus effectively increasing the mobility. For GBs with diminished mobility, MD predicts that presence of interstitial H reduces the pre-factor and, in some cases, increases the activation energy. The reduction in the activation energy inferred from MD simulations are confirmed by nudged elastic band calculations. Temperature-dependent structural transitions are observed for some GBs, and the effect of interstitial H is found to change with the changes in structure. The effect of interstitial H is predicted to be complex and highly variable, providing some plausible explanations for experimental observations on the recrystallization of tungsten in presence of H-loaded plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Linking initial microstructure and local response during quasistatic granular compaction

In this study, we performed experiments combining three-dimensional x-ray diffraction and x-ray computed tomography to explore the relationship between microstructure and local force and strain during quasistatic granular compaction. We found that initial void space around a grain and contact coordination number before compaction can be used to predict regions vulnerable to above-average local force and strain at later stages of compaction. We also found correlations between void space around a grain and coordination number, and between grain stress and maximum interparticle force, at all stages of compaction. Finally, we observed grains that fracture to have an above-average initial local void space and a below-average initial coordination number. In conclusion, our findings provide (1) a detailed description of microstructure evolution during quasistatic granular compaction, (2) an approach for identifying regions vulnerable to large values of strain and interparticle force, and (3) methods for identifying regions of a material with large interparticle forces and coordination numbers from measurements of grain stress and local porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Equation of Motion for a Grain Boundary

Grain boundary (GB) migration controls many forms of microstructural evolution in polycrystalline materials. Recent theory, simulations, and experiments demonstrate that GB migration is controlled by the motion of discrete line defects or disconnections. We present a continuum equation of motion for grain boundary derived from the underlying discrete disconnection mechanism. We also present an equation of motion for the junctions where multiple grain boundaries meet—as is always the case in a polycrystal. The resulting equation of motion naturally exhibits junction drag—a widely observed phenomena in junction dynamics in solids and liquids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Role of Reversible Phase Transformation for Strong Piezoelectric Performance at the Morphotropic Phase Boundary

A functional material with coexisting energetically equivalent phases often exhibits extraordinary properties such as piezoelectricity, ferromagnetism, and ferroelasticity, which is simultaneously accompanied by field-driven reversible phase transformation. The study on the interplay between such phase transformation and the performance is of great importance. Here, we have experimentally revealed the important role of field-driven reversible phase transformation in achieving enhanced electromechanical properties using in situ high-energy synchrotron x-ray diffraction combined with 2D geometry scattering technology, which can establish a comprehensive picture of piezoelectric-related microstructural evolution. High-throughput experiments on various Pb/Bi-based perovskite piezoelectric systems suggest that reversible phase transformation can be triggered by an electric field at the morphotropic phase boundary and the piezoelectric performance is highly related to the tendency of electric-field-driven phase transformation. A strong tendency of phase transformation driven by an electric field generates peak piezoelectric response. Further, phase-field modeling reveals that the polarization alignment and the piezoelectric response can be much enhanced by the electric-field-driven phase transformation. In conclusion, the proposed mechanism will be helpful to design and optimize the new piezoelectrics, ferromagnetics, or other related functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dynamics of interaction between dislocations and point defects in bcc iron

The interaction between dislocations and point defects is crucial for many physical properties and phenomena in materials, such as strengthening mechanisms, dislocation bias and void swelling, creep, and impurity segregation around dislocations. Conventional dislocation-point defect interaction models use approximations based on elasticity theory and/or based on assumptions that transition states energies can be deduced from the binding energies of the defects. In this paper, we present the transport properties of point defects near dislocations based on the actual saddle-point configuration of vacancies and self-interstitial atoms as a function of position with respect to screw and edge dislocations in a model system (bcc iron) using the self-evolving atomistic kinetic Monte Carlo. Here, KMC simulations reveal defect dynamics near dislocations are highly anisotropic and correlated, particularly for dumbbells in the compressive field of the edge dislocation, which could result in zones near dislocation cores where dumbbells are less efficiently absorbed compared with vacancies. This study provides accurate saddle-point configurations and energies required to properly describe the dynamics of point defects around dislocations, allowing fundamental insights on the transport mechanisms which are essential for understanding microstructural evolution and mechanical properties of metallic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Shear banding mechanism in compressed nanocrystalline ceramic nanopillars

Localization of deformation in shear bands is widely observed preceding intense damage and fracture in ductile or granular materials. However, mechanisms about how shear bands form are generally not known. Here, we show that nanocrystalline ceramic (NCC) nanopillars of ZrN fracture by shear banding under compression. The microstructure evolution of entire shear banding process was in situ monitored by electron imaging and diffraction. Results show that the nanopillars deform through a series of granular activities due to intermittent nucleation and propagation of dislocations. The stress drops associated with the dislocation activities are relatively small since dislocation avalanches are restricted in NCCs because of the effect of nanograin size. Localized and cooperative granular activities, as well as nanocracks, are discovered in the regions where shear bands form. A model about shear band and nanocrack formation is proposed. These findings thus demonstrate for the first time of spatial and temporal nature of intermittent granular activities, leading to shear band formation in NCCs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Atomistic simulation of defect-dislocation interactions in concentrated solid-solution alloys

The interaction between point defects and dislocations plays a crucial role in governing material properties and microstructural evolutions under external stimuli, such as mechanical deformation and irradiation. Here, we present an atomistic study of the interactions between point defects and dislocations in concentrated solid-solution alloys (CSAs). Using molecular statics and kinetic Monte Carlo methods, we demonstrate that the strain energy and stress field distribution induced by a dislocation in CSAs are highly inhomogeneous along the dislocation line, which leads to heterogeneity of defect-dislocation interactions. Specifically, the interactions are spatially different and screened by the random arrangement of different elemental species. Furthermore, such localization of defect-dislocation interaction indicates that the “dislocation-bias” mechanism that is a driving force for radiation-induced void swelling can be suppressed in concentrated alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structure and migration of heavily irradiated grain boundaries and dislocations in Ni in the athermal limit

The microstructural evolution at and near preexisting grain boundaries (GBs) and dislocations in materials under high radiation doses is still poorly understood. In this work, we use the creation relaxation algorithm (CRA) developed for atomistic modeling of high-dose irradiation in bulk materials to probe the athermal limit of saturation of GB and dislocation core regions under irradiation in fcc Ni. We find that, upon continuously subjecting a single dislocation or GB to Frenkel pair creation in the athermal limit, a local steady-state disordered defect structure is reached with excess properties that fluctuate around constant values. Case studies are given for a straight screw dislocation which elongates into a helix under irradiation and several types of low- and high-angle GBs, which exhibit coupled responses such as absorption of extrinsic dislocations, roughening, and migration. A positive correlation is found between the initial GB energy and the local steady-state GB energy under irradiation across a wide variety of GB types. Metastable GB structures with similar density in the defect core region but different initial configurations are found to converge to the same limiting structure under CRA. The mechanical responses of pristine and irradiated dislocations and GB structures are compared under an applied shear stress. Irradiated screw and edge dislocations are found to exhibit a hardening response, migrating at larger flow stresses than their pristine counterparts. Mobile GBs are found to exhibit softening or hardening responses depending on GB character. Although some GBs recover their initial pristine structures upon migration outside of the radiation zone, many GBs sustain different flow stresses corresponding to altered mobile core structures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

HiSPoD : a program for high-speed polychromatic X-ray diffraction experiments and data analysis on polycrystalline samples

Here, a high-speed X-ray diffraction technique was recently developed at the 32-ID-B beamline of the Advanced Photon Source for studying highly dynamic, yet non-repeatable and irreversible, materials processes. In experiments, the microstructure evolution in a single material event is probed by recording a series of diffraction patterns with extremely short exposure time and high frame rate. Owing to the limited flux in a short pulse and the polychromatic nature of the incident X-rays, analysis of the diffraction data is challenging. Here, HiSPoD , a stand-alone Matlab-based software for analyzing the polychromatic X-ray diffraction data from polycrystalline samples, is described. With HiSPoD , researchers are able to perform diffraction peak indexing, extraction of one-dimensional intensity profiles by integrating a two-dimensional diffraction pattern, and, more importantly, quantitative numerical simulations to obtain precise sample structure information.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗