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DOE OSTI2025

Microstructure Scale Lithium-Ion Battery Modeling: Part I. On Through-Plane Heterogeneity, Impact of Mesh Representation, and Differences between Macro- and Microscale Models

Li-ion battery performance and degradation are strongly correlated with the electrode microstructures and can be modeled at different scales, each with their own limitations. Herein, we compare predictions achieved with a macro- and a micro-scale model, that is, respectively, neglecting or considering the microstructural heterogeneity of the composite electrodes, on virtual numerically generated and real microstructures. While both models are in relative agreement at the low charge rates, differences arise for fast charging scenarios and especially for the real, highly heterogenous, microstructures. The microscale model predicts that electrolyte concentration saturation and depletion, respectively, at the back of the cathode and of the anode are exacerbated, and that lithium plating occurs earlier for real microstructures. The present work also indicates that the mesh representation significantly impacts the microscale model predictions, and consequently that microscale models should add surface area as a parameter to consider explicitly surface roughness. This article is the first of a series, with subsequent entries further investigating in-plane heterogeneities, lithium plating, and the impact of microstructure representativity on model predictions.

25 ENERGY STORAGE↗

DOE OSTI2019

Modeling and Simulation of Microstructure Evolution and Deformation in an Irradiated Environment

The ability to predict the behavior of structural components in a nuclear power plant is critical to the nuclear industry. Structural metals in the primary loop of nuclear power plants must endure challenges such as irradiation and mechanical and thermal loading, and these structural metal components must continue to function in potential transient and accident conditions throughout the operational lifetime of the power plant. This extreme operational environment changes the metal microstructure by creating additional defects. The physical interactions of dislocations with these defects govern how the metal will respond to future conditions. Therefore predicting the mechanical response of these metals requires a set of physically based and reliable models of dislocation and defect interactions. These microstructure elements include glide mobile and immobile dislocations, geometrically necessary dislocations, twinning dislocations, irradiation defects, and thermal aging defects. We present here a continuum dislocation dynamics crystal plasticity framework to capture the interaction mechanisms of these dislocations and defects, verified with a combination of benchmark problems and comparisons with experimental data for two different types of structural metals: alpha iron and nickel-based alloys. In our simulations of $\alpha$ iron we highlight the advantages of applying a Monte Carlo stochastic model of cross slip dislocation motion and show the importance of capturing the 3D nature of glide dislocation and self-interstitial atom loop radiation defect interactions. We demonstrate coupling of glide dislocations with geometrically necessary dislocations to capture the influence of lattice bending, including the sensitivity of the geometrically necessary dislocations to changes in the grain boundary angle. We further examine the interaction of glide dislocations with the twin dislocations and thermally aged defects which have been observed in a nickel-based alloy with additional models. Finally we assess the reliability of this crystal plasticity framework by comparing two dislocation glide velocity models across the range of normal operation temperatures. In successfully applying our crystal plasticity framework to multiple metals, we provide further evidence of the reliability of our approach. The results of this mechanism-based continuum dislocation dynamics crystal plasticity framework can be used to inform engineering scale models throughout the nuclear industry.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Digital polycrystalline microstructure generation using diffusion probabilistic models

Accurate micromechanical simulation of polycrystalline materials requires a realistic digital representation of the grain scale microstructure. Here, this work demonstrates the use of a generative diffusion probabilistic model for synthesizing single phase polycrystalline realizations. The model performs well and is capable of producing realistic microstructures consisting of not just simple equiaxed structures but also structures exhibiting more complex spatial arrangements. Masked microstructure generation reveals that the model is context aware of morphological descriptors which may be encoded in the latent space. Training on more diverse data sets, with scaled up architectures, may enable development of future models capable of synthesizing even more complex microstructural features.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Experimental and Modeling Studies on the Microstructures and Properties of Oxidized Aluminum Nitride Ceramic Substrates

Oxidation of aluminum nitride (AlN) ceramic substrates doped with 2 wt.% Y{sub 2}O{sub 3} was performed in air at temperatures ranging from 1000 to 1300 °C for various lengths of time. Microstructure, bending strength, and thermal conductivity of the oxidized AlN substrates were studied experimentally and also via mathematical models. The results show that the oxide layer formed on the AlN substrates is composed of α-Al{sub 2}O{sub 3} nanocrystallines and interconnected micropores. Longitudinal and transverse cracks are induced in the oxide layer under tensile and shear stresses, respectively. Intergranular oxidation of the AlN grains close to the oxide layer/AlN interface also occurs, leading to widening and cracking of the AlN grain boundaries. These processes result in the monotonous degradation of bending strength and thermal conductivity of the oxidized AlN substrates. Two mathematic models concerning these properties of the oxidized AlN substrates versus the oxide layer thickness were put forward. They fit well with the experimental results.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Understanding the Implications of a LINAC’s Microstructure on Devices and Photocurrent Models

Here, the effect of a linear accelerator’s (LINAC’s) microstructure (i.e., train of narrow pulses) on devices and the associated transient photocurrent models are investigated. The data indicate that the photocurrent response of Si-based RF bipolar junction transistors and RF p-i-n diodes is considerably higher when taking into account the microstructure effects. Similarly, the response of diamond, SiO 2 , and GaAs photoconductive detectors (standard radiation diagnostics) is higher when taking into account the microstructure. This has obvious hardness assurance implications when assessing the transient response of devices because the measured photocurrent and dose rate levels could be underestimated if microstructure effects are not captured. Indeed, the rate the energy is deposited in a material during the microstructure peaks is much higher than the filtered rate which is traditionally measured. In addition, photocurrent models developed with filtered LINAC data may be inherently inaccurate if a device is able to respond to the microstructure.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

EchemAMR (electro-chemical microsctructure scale models with adaptive meshing) [SWR-23-111]

A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. Electrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.

Sitaraman, Hariswaran↗

DOE OSTI2021

Computational Tools for Additive Manufacture of Tailored Microstructure and Properties

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Currently most additive builds use a single set of process parameters (e.g. laser power and scan speed) which results in a part with a homogenous microstructure that provides a singular performance level. To move beyond this state, Raytheon Technologies Research Center worked to create a set of computational tools to track material evolution through each step of the additive process. Computational fluid dynamics and phase field models for microstructure evolution as a function of processing parameters, and crystal plasticity models fully coupling microstructure and mechanical properties for performance predictions were leveraged to establish a connection between additive parameters and the final microstructure. This framework was utilized to tailor spatially-varying mechanical properties in a part by appropriately controlling the microstructure evolution during the additive process. Specifically, a turbine blade was 3D printed from nickel superalloy IN718 using laser powder bed fusion with coarse grains in the airfoil section which experiences the highest temperatures and is creep limited while finer grains were printed in the root of the blade which experience higher stresses but at lower temperatures and is therefore fatigue limited. The benefit of being able to intentionally insert coarse grains in the high temperature region of the blade was showcased with a microstructure sensitive creep model that indicates longer creep life for coarser grains.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2015

An atomistically informed mesoscale model for growth and coarsening during discharge in lithium-oxygen batteries

An atomistically informed mesoscale model is developed for the deposition of a discharge product in a Li-O{sub 2} battery. This mescocale model includes particle growth and coarsening as well as a simplified nucleation model. The model involves LiO{sub 2} formation through reaction of O{sub 2}{sup −} and Li{sup +} in the electrolyte, which deposits on the cathode surface when the LiO{sub 2} concentration reaches supersaturation in the electrolyte. A reaction-diffusion (rate-equation) model is used to describe the processes occurring in the electrolyte and a phase-field model is used to capture microstructural evolution. This model predicts that coarsening, in which large particles grow and small ones disappear, has a substantial effect on the size distribution of the LiO{sub 2} particles during the discharge process. The size evolution during discharge is the result of the interplay between this coarsening process and particle growth. The growth through continued deposition of LiO{sub 2} has the effect of causing large particles to grow ever faster while delaying the dissolution of small particles. The predicted size evolution is consistent with experimental results for a previously reported cathode material based on activated carbon during discharge and when it is at rest, although kinetic factors need to be included. The approach described in this paper synergistically combines models on different length scales with experimental observations and should have applications in studying other related discharge processes, such as Li{sub 2}O{sub 2} deposition, in Li-O{sub 2} batteries and nucleation and growth in Li-S batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Irradiation-induced chemical disordering in ceramics: The case of SiC

Chemical disordering is one feature of damage that occurs in irradiation environments and is common in ceramic compounds. This paper reviews irradiation-induced chemical disordering in SiC-based materials at elevated temperatures. Here the results were obtained using advanced analytical tools to characterize atomistic defects and to evaluate the chemistry of defect clusters and homonuclear bond structures. Finally, this paper demonstrates that chemical disordering is crucial to understanding microstructural stability and establishing a mechanistic modeling of microstructural evolution of irradiated SiC.

36 MATERIALS SCIENCE↗

DOE OSTI2022

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Thermo-mechanical modeling and experimental validation for multilayered metallic microstructures

This paper presents thermo-mechanical modeling on multilayered metallic microstructures consisting of two bilayers that enable 3D deployment once being Joule heated. Additionally, a representative design of such microstructures, as well as their working principle is introduced. Furthermore, a mathematical model is derived using Euler–Bernoulli beam theory, and analytical solutions describing out-of-plane displacement of the multilayered microstructures when uniformly heated, which is validated by finite element analysis. Parametric analysis on thermal load and dimensional change of beam shows a good agreement between the analytical solutions and results given by finite element analysis. The phases of the near-equiatomic NiTi layer are analyzed by EDS and XRD, which prove to be austenite during the Joule heating process. The mechanical properties of austenite NiTi are incorporated into the analytical solutions that provides a good estimation of 3D deployment of microstructures made of NiTi and aluminum. The experimental results provide an approximately 7 µm out-of-plane deployment by applying a uniform temperature increase of 132 K, and parametric analysis on the dimension of top aluminum beam offers another promising approach to larger 3D deployment. The proposed mathematical model provides an efficient tool for predicting the out-of-plane deployment of such multilayered microstructures.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A phase-field approach to model multi-axial and microstructure dependent fracture in nuclear grade graphite

The fracture behavior of nuclear grade graphites is strongly influenced by underlying microstructural features such as the character of filler particles, and the distribution of pores and voids. These microstructural features influence the crack nucleation and propagation behavior, resulting in quasi-brittle fracture with a tortuous crack path and significant scatter in measured bulk strength. This paper uses a phase-field method to model the microstructural and multi-axial fracture in H-451, a historic variant of nuclear graphite that provides the basis for an idealized study on a legacy grade. The representative volume elements are constructed from randomly located pores with random size obtained from experimentally determined log-normal distribution. The representative volume elements are then subjected to simulated multi-axial loading, and a reasonable agreement of the resulting fracture stress with experiments is obtained. Finally, quasi-brittle stress-strain evolution with a tortuous crack path is also observed from the simulations and is consistent with experimental results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

The microstructure and rheology of a model, thixotropic nanoparticle gel under steady shear and large amplitude oscillatory shear (LAOS)

The microstructure-rheology relationship for a model, thermoreversible nanoparticle gel is investigated using a new technique of time-resolved neutron scattering under steady and time-resolved large amplitude oscillatory shear (LAOS) flows. A 21 vol. % gel is tested with varying strength of interparticle attraction. Shear-induced structural anisotropy is observed as butterfly scattering patterns and quantified through an alignment factor. Measurements in the plane of flow show significant, local anisotropy develops with alignment along the compressional axis of flow, providing new insights into how gels flow. The microstructure-rheology relationship is analyzed through a new type of structure-Lissajous plot that shows how the anisotropic microstructure is responsible for the observed LAOS response, which is beyond a response expected for a purely viscous gel with constant structure. The LAOS shear viscosities are observed to follow the “Delaware-Rutgers” rule. Rheological and microstructural data are successfully compared across a broad range of conditions by scaling the shear rate by the strength of attraction, providing a method to compare behavior between steady shear and LAOS experiments. However, important differences remain between the microstructures measured at comparatively high frequency in LAOS experiments and comparable steady shear experiments that illustrate the importance of measuring the microstructure to properly interpret the nonlinear, dynamic rheological response.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Microscopic model for exchange bias from grain-boundary disorder in a ferromagnet/antiferromagnet thin film with a nanocrystalline microstructure

Monte Carlo spin simulations were coupled to a Voronoi microstructure-generator to predict the magnitude and behavior of exchange bias in a ferromagnet/antiferromagnet (AF) thin film bilayer with a nanocrystalline microstructure. Our model accounts for the effects of irregular grain-shapes, finite-sized particles, and the possible presence of local random-fields originating from the antiferromagnet's grain-boundary regions. As the grain-boundary represents a crystal-structure distortion, we model the local effect on the exchange constants in the Gaussian approximation which can cause regions resembling a spin glass confined to an unusual 2D topology. Although an ensemble of completely disconnected AF grains isolated by non-magnetic barriers provides a small exchange bias, the introduction of a spin-glass network at the boundaries causes a four-fold enhancement in the magnitude of the loop-shift. This implies the importance of local grain-boundary behavior in defect-engineered antiferromagnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Instantiation of crystal plasticity simulations for micromechanical modelling with direct input from microstructural data collected at light sources

Novel non-destructive characterization techniques performed at light sources provide previously inaccessible 3-D mesoscopic information on the deformation of polycrystalline materials. One major difficulty for interpretation of these experiments through micromechanical modelling is the likelihood that processing and/or mounting the sample introduce residual stresses in the specimen. These stresses need to be incorporated into crystal plasticity formulations, for these models to operate directly from microstructural images and be predictive. To achieve this, the initial micromechanical state of each voxel needs to be specified. Here in this letter we present a method for incorporating grain-averaged residual stresses for instantiation of crystal plasticity simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Computational Modeling of Heterogeneity of Stress, Charge, and Cyclic Damage in Composite Electrodes of Li-Ion Batteries

Charge heterogeneity is a prevalent feature in many electrochemical systems. In a commercial cathode of Li-ion batteries, the composite is hierarchically structured across multiple length scales including the sub-micron single-crystal primary-particle domains up to the macroscopic particle ensembles. The redox kinetics of charge transfer and mass transport strongly couples with mechanical stresses. This interplay catalyzes substantial heterogeneity in the charge (re)distribution, stresses, and mechanical damage in the composite electrode during charging and discharging. We assess the heterogeneous electrochemistry and mechanics in a LiNi x Mn y Co z O 2 (NMC) cathode using a fully coupled electro-chemo-mechanics model at the cell level. A microstructure-resolved model is constructed based on the synchrotron X-ray tomography data. We calculate the stress field in the composite and then quantitatively evaluate the kinetics of surface charge transfer and Li transport biased by mechanical stresses. We further model the cyclic behavior of the cell. The repetitive deformation of the active particles and the weakening of the interfacial strength cause gradual increase of the interfacial debonding. The mechanical damage impedes electron transfer, incurs more charge heterogeneity, and results in the capacity degradation in batteries over cycles.

25 ENERGY STORAGE↗

DOE OSTI2023

Model-based quantification of margins and uncertainties in metal additive manufacturing for process design and qualification

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

36 MATERIALS SCIENCE↗