End-to-end three-dimensional designing of complex disordered materials from limited data using machine learning

Precise 3D representation of complex materials, here the lithium-ion batteries, is a critical step toward designing optimized energy storage systems. One requires obtaining several such samples for a more accurate evaluation of uncertainty and variability, which in turn can be costly and time demanding. Using 3D models is crucial when it comes to evaluating the transport and heat capacity of batteries. Further, such models represent the microstructures more precisely where connectivity and heterogeneity can be detected. However, 3D images are hard to access, and the available images are often collected in two dimensions (2D). Such 2D images, on the other hand, are more accessible and often have higher resolution. In this paper, a deep learning method has been applied to take advantage of 2D images and build 3D models of heterogeneous materials through which more accurate characterization and physical evaluations can be achieved. While being trained using only 2D images, the proposed framework can be utilized to generate 3D images. The proposed method is applied to a few realistic 3D images of lithium-ion battery electrodes. The results indicate that the implemented method can reproduce important structural properties while the flow and heat properties are within an acceptable range.

Polymer–Nickel Composite Filaments for 3D Printing of Open Porous Materials

Catalysis has been a key way of improving the efficiency-to-cost ratio of chemical and electrochemical processes. There have been recent developments in catalyst materials that enable the development of novel and more sophisticated devices that, for example, can be used in applications, such as membranes, batteries or fuel cells. Since catalytic reactions occur on the surface, most catalyst materials are based on open porous structures, which facilitates the transport of fluids (gas or liquid) and chemical (or electrochemical) specific surface activity, thus determining the overall efficiency of the device. Noble metals are typically used for low temperature catalysis, whereas lower cost materials, such as nickel, are used for catalysis at elevated temperatures. 3D printing has the potential to produce a more sophisticated fit for purpose catalyst material. This article presents the development, fabrication and performance comparison of three thermoplastic composites where PLA (polylactic acid), PVB (polyvinyl butyral) or ABS (acrylonitrile butadiene styrene) were used as the matrix, and nickel particles were used as filler with various volume fractions, from 5 to 25 vol%. The polymer–metal composites were extruded in the form of filaments and then used for 3D FDM (Fused Deposition Modeling) printing. The 3D printed composites were heat treated to remove the polymer and sinter the nickel particles. 3D printed composites were also prepared using nickel foam as a substrate to increase the final porosity and mechanical strength of the material. The result of the study demonstrates the ability of the optimized filament materials to be used in the fabrication of high open porosity (over 60%) structures that could be used in high-temperature catalysis and/or electrocatalysis.

A Probabilistic Formulation of the Diffusion Coefficient in Porous Media as Function of Porosity

We investigate the upscaling of diffusive transport parameters using a stochastic framework. At sub-REV (representative elementary volume) scale, the complexity of the pore space geometry leads to a significant scatter of the observed diffusive transport. We study a large set of volumes reconstructed from focused ion beam-scanning electron microscopy data. Each individual volume provides us sub-REV measurements on porosity and the so-called transport-ability, being a dimensionless parameter representing the ratio of diffusive flux through the porous volume to that through an empty volume. The detected scatter of the transport-ability is mathematically characterized through a probability distribution function (PDF) with a mean and variance as function of porosity, which includes implicitly the effect of pore structure differences among sub-REV volumes. We then investigate domain size effects and predict when REV scale is reached. While the scatter in porosity observations decreases linearly with increasing sample size as expected, the observed scatter in transport-ability does not converge to zero. Our results confirm that differences in pore structure impact transport parameters at all scales. Consequently, the use of PDFs to describe the relationship of effective transport coefficients to porosity is advantageous to deterministic semiempirical functions. We discuss the consequences and advocate the use of PDFs for effective parameters in both continuum equations and data interpretation of experimental or computational work. The presented statistics-based upscaling technique of sub-REV microscopy data provides a new tool in understanding, describing and predicting macroscopic transport behavior of microporous media.

Modeling the impedance response and steady state behaviour of porous CGO-based MIEC anodes

Mixed ionic and electronic conducting (MIEC) materials recently gained much interest for use as anodes in solid oxide fuel cell (SOFC) applications. However, many processes in MIEC-based porous anodes are still poorly understood and the appropriate interpretation of corresponding electrochemical impedance spectroscopy (EIS) data is challenging. Therefore, a model which is capable to capture all relevant physico-chemical processes is a crucial prerequisite for systematic materials optimization. In this contribution we present a comprehensive model for MIEC-based anodes providing both the DC-behaviour and the EIS-spectra. The model enables one to distinguish between the impact of the chemical capacitance, the reaction resistance, the gas impedance and the charge transport resistance on the EIS-spectrum and therewith allows its appropriate interpretation for button cell conditions. Typical MIEC-features are studied with the model applied to gadolinium doped ceria (CGO) anodes with different microstructures. The results obtained for CGO anodes reveal the spatial distribution of the reaction zone and associated transport distances for the charge carriers and gas species. Moreover, parameter spaces for transport limited and surface reaction limited situations are depicted. By linking bulk material properties, microstructure effects and the cell design with the cell performance, we present a way towards a systematic materials optimization for MIEC-based anodes.

Biobased foams for thermal insulation: material selection, processing, modelling, and performance

With the urgent need for the development of sustainable materials and a circular economy, a surge of research regarding biobased materials and associated processing methods has resulted in many experimental biobased foams. Although several biobased foams are already shown to have thermal and mechanical properties competitive with expanded polystyrene, there remains a fundamental knowledge gap leading to limited understanding of the principles that determine performance. This review outlines the progress in this burgeoning field, introducing materials selection and processing, comparing performance, examining efforts in modelling physical properties, and discusses challenges in applying models to real biobased systems. The focus is on low thermal conductivity, which is a critical property for temperature-controlled applications such as packaging for refrigerated/frozen foods, medications, and vaccines as well as building materials. Currently, the trend in the field is moving towards fully biobased and compostable foams, though partially biobased polyurethane foams remain the most consistent performers. To illustrate the foam structure–property relationship, thermal conductivity, cell size, and density data were compiled. Given the complexity of biobased foams, heat transfer models aid in identifying crucial variables. However, data relevant to the insulation capability of biobased foams is not fully reported in many references. To address this issue, we employed a dimensional analysis to fill the gaps, revealing a power law correlation between thermal conductivity and relative density. Our approach is not intended as a robust prediction technique, but rather a simple demonstration of how biobased foams data could be utilized to predict the most promising materials and methods.

This review outlines the progress in biobased foams with a focus on low thermal conductivity. It introduces materials selection and processing, compares performance, examines modelling of physical properties, and discusses challenges in applying models to real systems.

An Anisotropic Microstructure Evolution in a Solid Oxide Fuel Cell Anode

The presented research shows that the long-term operation of a solid oxide fuel cell can lead to substantial anisotropic changes in anode material. The morphology of microstructure in the investigated stack was observed before and after the aging test using electron nanotomography. The microstructural parameters were estimated based on the obtained digital representation of the anode microstructure. Anisotropy was discovered in two of the three phases that constitute the anode, namely nickel and pores. The third component of the anode, which is yttrium-stabilized zirconia, remains isotropic. The changes appear at the microscale and significantly affect the transport phenomena of electrons and gasses. The obtained results indicate that the reference anode material that represents the microstructure before the aging test has isotropic properties which evolve toward strong anisotropy after 3800 h of constant operation. The presented findings are crucial for a credible numerical simulation of solid oxide fuel cells. They indicate that all homogeneous models must adequately account for the microstructure parameters that define the anisotropy of transport phenomena, especially if microstructural data is taken from a post-operational anode.

Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes

Despite numerous studies presenting advances in tomographic imaging and analysis of lithium ion batteries, graphite-based anodes have received little attention. Weak X-ray attenuation of graphite and, as a result, poor contrast between graphite and the other carbon-based components in an electrode pore space renders data analysis challenging. Here we demonstrate operando tomography of weakly attenuating electrodes during electrochemical (de)lithiation. We use propagation-based phase contrast tomography to facilitate the differentiation between weakly attenuating materials and apply digital volume correlation to capture the dynamics of the electrodes during operation. After validating that we can quantify the local electrochemical activity and microstructural changes throughout graphite electrodes, we apply our technique to graphite-silicon composite electrodes. We show that microstructural changes that occur during (de)lithiation of a pure graphite electrode are of the same order of magnitude as spatial inhomogeneities within it, while strain in composite electrodes is locally pronounced and introduces significant microstructural changes.

FIB-SEM Tomography Probes the Mesoscale Pore Space of an Individual Catalytic Cracking Particle

The overall performance of a catalyst particle strongly depends on the ability of mass transport through its pore space. Characterizing the three-dimensional structure of the macro- and mesopore space of a catalyst particle and establishing a correlation with transport efficiency is an essential step toward designing highly effective catalyst particles. In this work, a generally applicable workflow is presented to characterize the transport efficiency of individual catalyst particles. The developed workflow involves a multiscale characterization approach making use of a focused ion beam-scanning electron microscope (FIB-SEM). SEM imaging is performed on cross sections of 10.000 μm², visualizing a set of catalyst particles, while FIB-SEM tomography visualized the pore space of a large number of 8 μm³ cubes (subvolumes) of individual catalyst particles. Geometrical parameters (porosity, pore connectivity, and heterogeneity) of the material were used to generate large numbers of virtual 3D volumes resembling the sample's pore space characteristics, while being suitable for computationally demanding transport simulations. The transport ability, defined as the ratio of unhindered flow over hindered flow, is then determined via transport simulations through the virtual volumes. The simulation results are used as input for an upscaling routine based on an analogy with electrical networks, taking into account the spatial heterogeneity of the pore space over greater length scales. This novel approach is demonstrated for two distinct types of industrially manufactured fluid catalytic cracking (FCC) particles with zeolite Y as the active cracking component. Differences in physicochemical and catalytic properties were found to relate to differences in heterogeneities in the spatial porosity distribution. In addition to the characterization of existing FCC particles, our method of correlating pore space with transport efficiency does also allow for an up-front evaluation of the transport efficiency of new designs of FCC catalyst particles.

3D Microstructure Effects in Ni-YSZ Anodes: Influence of TPB Lengths on the Electrochemical Performance

3D microstructure-performance relationships in Ni-YSZ anodes for electrolyte-supported cells are investigated in terms of the correlation between the triple phase boundary (TPB) length and polarization resistance (R_pol). Three different Ni-YSZ anodes of varying microstructure are subjected to eight reduction-oxidation (redox) cycles at 950 °C. In general the TPB lengths correlate with anode performance. However, the quantitative results also show that there is no simplistic relationship between TPB and R_pol. The degradation mechanism strongly depends on the initial microstructure. Finer microstructures exhibit lower degradation rates of TPB and R_pol. In fine microstructures, TPB loss is found to be due to Ni coarsening, while in coarse microstructures reduction of active TPB results mainly from loss of YSZ percolation. The latter is attributed to weak bottlenecks associated with lower sintering activity of the coarse YSZ. The coarse anode suffers from complete loss of YSZ connectivity and associated drop of TPB_active by 93%. Surprisingly, this severe microstructure degradation did not lead to electrochemical failure. Mechanistic scenarios are discussed for different anode microstructures. These scenarios are based on a model for coupled charge transfer and transport, which allows using TPB and effective properties as input. The mechanistic scenarios describe the microstructure influence on current distributions, which explains the observed complex relationship between TPB lengths and anode performances. The observed loss of YSZ percolation in the coarse anode is not detrimental because the electrochemical activity is concentrated in a narrow active layer. The anode performance can be predicted reliably if the volume-averaged properties (TPB_active, effective ionic conductivity) are corrected for the so-called short-range effect, which is particularly important in cases with a narrow active layer.

3D Microstructure Effects in Ni-YSZ Anodes: Prediction of Effective Transport Properties and Optimization of Redox Stability

This study investigates the influence of microstructure on the effective ionic and electrical conductivities of Ni-YSZ (yttria-stabilized zirconia) anodes. Fine, medium, and coarse microstructures are exposed to redox cycling at 950 °C. FIB (focused ion beam)-tomography and image analysis are used to quantify the effective (connected) volume fraction (Φ_eff), constriction factor (β), and tortuosity (τ). The effective conductivity (σ_eff) is described as the product of intrinsic conductivity (σ₀) and the so-called microstructure-factor (M): σ_eff = σ₀ × M. Two different methods are used to evaluate the M-factor: (1) by prediction using a recently established relationship, M_pred = εβ^0.36/τ^5.17, and (2) by numerical simulation that provides conductivity, from which the simulated M-factor can be deduced (M_sim). Both methods give complementary and consistent information about the effective transport properties and the redox degradation mechanism. The initial microstructure has a strong influence on effective conductivities and their degradation. Finer anodes have higher initial conductivities but undergo more intensive Ni coarsening. Coarser anodes have a more stable Ni phase but exhibit lower YSZ stability due to lower sintering activity. Consequently, in order to improve redox stability, it is proposed to use mixtures of fine and coarse powders in different proportions for functional anode and current collector layers.

Preparation and Characterization of Li-Ion Graphite Anodes Using Synchrotron Tomography

We present an approach for multi-layer preparation to perform microstructure analysis of a Li-ion cell anode active material using synchrotron tomography. All necessary steps, from the disassembly of differently-housed cells (pouch and cylindrical), via selection of interesting layer regions, to the separation of the graphite-compound and current collector, are described in detail. The proposed stacking method improves the efficiency of synchrotron tomography by measuring up to ten layers in parallel, without the loss of image resolution nor quality, resulting in a maximization of acquired data. Additionally, we perform an analysis of the obtained 3D volumes by calculating microstructural characteristics, like porosity, tortuosity and specific surface area. Due to a large amount of measurable layers within one stacked sample, differences between aged and pristine material (e.g., significant differences in tortuosity and specific surface area, while porosity remains constant), as well as the homogeneity of the material within one cell could be recognized.