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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Segregated Approach for Modeling the Electrochemistry in the 3-D Microstructure of Li-Ion Batteries and Its Acceleration Using Block Preconditioners

Abstract Battery performance is strongly correlated with electrode microstructure. Electrode materials for lithium-ion batteries have complex microstructure geometries that require millions of degrees of freedom to solve the electrochemical system at the microstructure scale. A fast-iterative solver with an appropriate preconditioner is then required to simulate large representative volume in a reasonable time. In this work, a finite element electrochemical model is developed to resolve the concentration and potential within the electrode active materials and the electrolyte domains at the microstructure scale, with an emphasis on numerical stability and scaling performances. The block Gauss-Seidel (BGS) numerical method is implemented because the system of equations within the electrodes is coupled only through the nonlinear Butler–Volmer equation, which governs the electrochemical reaction at the interface between the domains. The best solution strategy found in this work consists of splitting the system into two blocks—one for the concentration and one for the potential field—and then performing block generalized minimal residual preconditioned with algebraic multigrid, using the FEniCS and the Portable, Extensible Toolkit for Scientific Computation libraries. Significant improvements in terms of time to solution (six times faster) and memory usage (halving) are achieved compared with the MUltifrontal Massively Parallel sparse direct Solver. Additionally, BGS experiences decent strong parallel scaling within the electrode domains. Last, the system of equations is modified to specifically address numerical instability induced by electrolyte depletion, which is particularly valuable for simulating fast-charge scenarios relevant for automotive application.

25 ENERGY STORAGE↗
DOE OSTI2020

Mechanistic Analysis of Microstructural Attributes to Lithium Plating in Fast Charging

Metallic lithium deposition on graphite anodes is a critical degradation mode in lithium-ion batteries, which limits safety and fast charge capability. A conclusive strategy to mitigate lithium deposition under fast charging yet remains elusive. Herein, we examine the role of electrode microstructure in mitigating lithium plating behavior under various operating conditions, including fast charging. The multilength scale characteristics of the electrode microstructure lead to a complex interaction of transport and kinetic limitations that significantly governs the cell performance and the occurrence of Li plating. We demonstrate, based on a comprehensive mesoscale analysis, that the performance and degradation can be significantly modulated via systematic design improvements at the hierarchy of length scales. It is found that the improvement in kinetic and transport characteristics achievable at disparate scales can dramatically affect Li plating propensity.

25 ENERGY STORAGE↗
DOE OSTI2021

SOC Synthetic Microstructure Bank

QUICK START: Start with property_library.html (can be found by typing the filename into the query box) and use the interactive table to filter, sort, and select a microstructure with the desired properties. Search for the alphabetic code to obtain the corresponding dataset. Full description: This is a bank of 1,970 unique 3-phase electrode microstructure files. When you account for reassigning phase IDs (e.g. declare that 1=Ni and 2=pore, instead of 1=pore and 2=Ni), it actually represents 5,910 unique electrode microstructures, each of which could be considered to be either an air or a fuel electrode (e.g. declare that the phase IDs correspond to pore, Ni, and YSZ; or that they correspond to pore, LSCF, and GDC; or whatever electron-conductor and ion-conductor combination is being studied). The voxel size is 50 nm and each electrode file contains a 4x4 grid of (12.5 micron)^3 sub-volumes. If placed together in a grid, they comprise a 50x50x12.5 micron electrode (note that the interfaces between sub-volumes will be sharp; this can be mitigated via simulating annealing/relaxation). The sub-volumes can also be used individually for a reasonably sized 12.5 micron cubic region-of-interest. A user can simply consider the voxel size to be a different value to rescale the volumes (and all of their morphological features, including particle size) as desired. These microstructures were generated using DREAM3D. The general procedure is outlined in https://doi.org/10.1016/j.jpowsour.2018.03.025 The file names are an alphabetic code having to do with the input parameters used in DREAM3D when they were generated. Most users would be best served by starting with the file property_library.html or property_library_subvols.html (which lists properties for each individual subvolume). These files contain a catalogue of the actual, measured properties of every microstructure in the database. Any combination of property values can be filtered and sorted until a desired electrode is found, at which point the user can find the file corresponding to that alphabetic code. The properties in the catalogue include connected TPB density, and for each phase: phase fraction, average particle size, polydispersity of particle size, tortuosity, and connected pair-wise interfacial area. They also include what fraction of each property is connected through to the interfaces of the volume. If the desired combination of properties is not found at first, remember that the phase IDs can be re-assigned arbitrarily, e.g. swapping 1s and 2s. In fact, the database was generated with this in mind so as not to generate redundant microstructures. If the database does not contain the desired property combinations, try to search for the other possible permutations of those properties with re-assigned phase IDs. Please cite https://doi.org/10.1149/10301.0909ecst for use. Please contact the maintainer, William K. Epting, for additional information or assistance.

3D microstructure↗
DOE OSTI2025

Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response

Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive, that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the analysis. A representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response to evaluate the predictions representativeness, and thus relevance, of a microstructure scale electrochemical model. The microstructure parameter deviation propagations to the electrochemical response have been quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Representativity analysis determines a cell FOV of 144.4 × 154.4 μm 2 is large enough to establish a convergence on the representative section areas for low-intermediate C-rate (≤2.5 C), therefore positively concludes on the model representativeness for these rates, but is not large enough to conclude for higher rates.

25 ENERGY STORAGE↗
DOE OSTI2026

Electrode and Microstructure Dependence of Oxygen Diffusion in Ferroelectric Hafnium Zirconium Oxide Thin Films

Hafnia-based ferroelectrics hold promise to reduce energy demand for computing by enabling compute-in-memory and as non-volatile memories. The ferroelectric phase in this material system is, in part, stabilized by oxygen vacancies. While oxygen vacancies may be a necessity for phase stability, they limit device endurance through diffusion and accumulation into conducting channels. Herein, it is shown that oxygen diffusion is spatially variable within individual grains of ferroelectric hafnium zirconium oxide (HZO). Using 18 O tracers and finite difference modeling, it is shown that grain boundaries and regions near electrode interfaces allow for relatively rapid oxygen diffusion, with values as much as 10 4 larger than the grain cores. Further, the selection of electrode material affects the diffusion coefficients across all microstructural regions. HZO films in contact with TiN electrodes result in more oxygen-deficient HZO films and higher oxygen diffusion coefficients. Tungsten electrodes result in fewer vacancies and lower diffusion coefficients. Diffusion activation energy differences between the HZO with the two electrodes is reconciled by differing populations of charged and uncharged oxygen vacancies. This insight into the local vacancy populations and diffusion pathways provides a platform for designing hafnia-based films, deposition processes, and integration strategies to reduce vacancy gradients and improve performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Secondary Pore Network Design Optimization Analytical Diffusion Model for Lithium Ion Battery

Fast ion transport along the electrode thickness is required for Lithium ion battery (LIB) to sustain continuous high-rate discharge or charge currents, which is a desired feature for the fast charging of electric vehicle batteries. Advance in LIB electrode manufacturing allows to control, to a certain extent, the electrode microstructure architecture in order to improve the macroscopic performances of these devices. For instance, several groups have experimentally tested architectures tailored specifically to increase the through plane ionic diffusion in regards for fast charge application by adding channels or groove-like large pores oriented along the electrode thickness. These voids do not replace the existing pores of the electrode microstructure but consist in a second, coarser, pore network, called the secondary pore network (SPN). The model quantifies the impact of SPN on ionic diffusion with a composite electrode through a simple analytical approach, considering various pore channel geometries and comparing to standard electrodes with identical gravimetric and identical volumetric specific theoretical capacity. The goal is to find optimal SPN design parameters according to three optimization objectives aiming to balance the improved overall through-plane, thanks to the coarse aligned channels, and the degraded in-plane diffusion, due to the porous matrix densification required to maintain gravimetric and volumetric specific theoretical capacity. The analytical model must be considered as a pre-screening tool to quickly investigate large design space, that can be refined later with more complex electrochemical CPU-expensive numerical models.

Usseglio Viretta, Francois↗
DOE OSTI2023

Engineering Redox Flow Battery Electrodes with Spatially Varying Porosity Using Non‐Solvent‐Induced Phase Separation

Redox flow batteries (RFBs) are a promising electrochemical platform for efficiently and reliably delivering electricity to the grid. Within the RFB, porous carbonaceous electrodes facilitate electrochemical reactions and distribute the flowing electrolyte. Tailoring electrode microstructure and surface area can improve RFB performance, lowering costs. Electrodes with spatially varying porosity may increase electrode utilization and provide surface area in reaction‐limited zones; however, the efficacy of such designs remains an open area of research. Herein, a non‐solvent‐induced phase‐separation (NIPS) technique that enables the reproducible synthesis of macrovoid‐free electrodes with well‐defined across‐thickness porosity gradients is described. The monotonically varying porosity profile is quantified and the physical properties and surface chemistries of porosity‐gradient electrodes are compared with macrovoid‐containing electrode, also synthesized by NIPS. Then, the electrochemical and fluid dynamic performance of the porosity‐gradient electrodes is evaluated, exploring the effect of changing the direction of the porosity gradient and benchmarking against the macrovoid‐containing electrode. Lastly, the performance is examined in a vanadium RFB, finding that the porosity‐gradient electrode outperforms the macrovoid electrode, is independent of gradient direction, and performs favorably compared to advanced electrodes in the contemporary literature. It is anticipated that the approach motivates further exploration of microstructurally tailored electrodes in electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2025

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗
DOE OSTI2024

Carbon-Binder Optimization for Lithium-Ion Battery Extreme Fast Charge

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

carbon-binder additives↗
DOE OSTI2022

Carbon-Binder Weight Loading Optimization for Improved Lithium-Ion Battery Rate Capability

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

25 ENERGY STORAGE↗
DOE OSTI2020

MATBOX (Microstructure Analysis Toolbox) [SWR-20-76]

MATBOX is a MATLAB application for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization, result three-dimensional visualization and result correlation, and microstructure meshing. MATBOX was originally developed to analyze electrode microstructures for lithium ion batteries; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphic-User Interface.

Usseglio Viretta, Francois↗
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 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 OSTI2020

Tracking nickel oxide reduction in solid oxide cells via ex-situ ptychographic nano-tomography

In solid oxide cell (SOC) electrodes, nickel oxide reduction is a fundamental step occurring during the initial stages of cell operation. The reduction procedure is considered to be crucial in producing the final fuel electrode microstructure. This work studies the reduction reaction occurring in a SOC fuel electrode by means of X-ray ptychographic nanotomography. The same microstructure is analyzed in its pristine state and after 1 h of reduction at 850 °C, in dry hydrogen. The microstructure evolution is discussed in terms of changes in volume fractions, surface areas, and connectivity of the different constituent materials. The pore network in the unreduced cermet is revealed to be fully isolated, implying that reduction proceeds inwards from the edges of the sample towards the center. For the given experimental conditions we report that reduction is complete after 1 h of treatment but the resulting nickel network is not yet percolated and detached from the yttria-stabilized zirconia.

25 ENERGY STORAGE↗
DOE OSTI2021

Toward Optimizing Electrospun Nanofiber Fuel Cell Catalyst Layers: Microstructure and Pt Accessibility

This work investigates how local ionomer/platinum (Pt) interactions and ionomer distribution in electrospun Pt/Vulcan nanofiber electrodes impact ionomer coverage, proton accessibility, and oxygen reduction reaction (ORR) performance in proton-exchange membrane fuel cells. Insights from various in situ electrochemical diagnostics were utilized in conjunction with ex situ microscopic characterization to understand how the electrode microstructure—both at the aggregate level and near the ionomer/platinum interface—is affected by electrospinning in comparison to ultrasonic spraying. The effect of the carrier polymer poly(acrylic acid) (PAA) concentration from 5–20 wt % (with respect to total ink solids) on the resulting nanofiber morphology is discussed. Electron microscopy observations and CO displacement measurements indicated that Pt/Vulcan nanofibers prepared with a higher PAA concentration (15 wt %) were conformally coated with a film of ionomer on the exterior of the fiber, which resulted in an overall lower ionomer coverage on both Pt and carbon throughout the fiber diameter. In contrast, 10 wt % PAA leads to a uniform intrafiber distribution of the ionomer within the fibers, increasing the overall ionomer coverage and proton accessibility under both wet and dry conditions. These differences in the local ionomer coverage on Pt between 10 and 15 wt % PAA were also attributed to differences in the adsorption/interaction affinities between PAA and the ionomer onto the catalyst surface in the ink using zeta potential measurements. Additional fuel cell electrochemical tests on the electrospun electrodes show improvements in ORR kinetics and high-current-density H 2 /air performance compared to the ultrasonically sprayed electrodes.

25 ENERGY STORAGE↗
DOE OSTI2018

Microstructure Characterization and Modeling for Improved Electrode Design

As part of DOE's Computer-Aided Engineering of Batteries Program, the National Renewable Energy Laboratory is developing detailed models capturing the influence of lithium-ion battery electrode design, recipe and processing on the electrode's microstructure and relating that microstructure to device-level performance. Given the difficulty in obtaining 3D microstructural images of the electrode's inert components, team member Purdue University developed an algorithm to computationally generate the so-called carbon-binder domain (CBD) for any given recipe. Mesoscale models explore the device-level impact of the CBD phase on multiple idealized and actual electrode geometries. With the inclusion of this CBD phase, microstructure models are used to predict the tortuosity of 14 different graphite and NMC electrode designs. Tortuosity predictions are shown in good agreement with experimental direct measurement and electrochemical rate studies.

25 ENERGY STORAGE↗
NASA NTRS1992

A new composite electrode architecture for energy storage devices

The research objective is to determine how the electrode microstructure (architecture) affect the performance of the nickel hydroxide electrochemical system. It was found that microstructure and additional surface area makes a difference. The best architectures are the FIBREX/nickel and nickel fiber composite electrodes. The conditioning time for full utilization was greatly reduced. The accelerated increase in capacity vs. cycling appears to be a good indicator of the condition of the electrode/active material microstructure and morphology. Conformal deposition of the active material may be indicated and important. Also higher utilizations were obtained; greater than 80 pct. after less than 5 cycles and greater than 300 pct. after more than 5 cycles using nickel fiber composite electrode assuming a 1 electron transfer per equivalent.

Ferro, Richard E.↗