Statistical Effective Diffusivity Estimation in Porous Media Using an Integrated On-site Imaging Workflow for Synchrotron Users

Transport in porous media plays an essential role for many physical, engineering, biological and environmental processes. Novel synchrotron imaging techniques and image-based models have enabled more robust quantification of geometric structures that influence transport through the pore space. However, image-based modelling is computationally expensive, and end users often require, while conducting imaging campaign, fast and agile bulk-scale effective parameter estimates that account for the pore-scale details. In this manuscript we enhance a pre-existing image-based model solver known as OpenImpala to estimate bulk-scale effective transport parameters. In particular, the boundary conditions and equations in OpenImpala were modified in order to estimate the effective diffusivity in an imaged system/geometry via a formal multi-scale homogenisation expansion. Estimates of effective pore space diffusivity were generated for a range of elementary volume sizes to estimate when the effective diffusivity values begin to converge to a single value. Results from OpenImpala were validated against a commercial finite element method package COMSOL Multiphysics (abbreviated as COMSOL). Results showed that the effective diffusivity values determined with OpenImpala were similar to those estimated by COMSOL. Tests on larger domains comparing a full image-based model to a homogenised (geometrically uniform) domain that used the effective diffusivity parameters showed differences below 2 % error, thus verifying the accuracy of the effective diffusivity estimates. Finally, we compared OpenImpala’s parallel computing speeds to COMSOL. OpenImpala consistently ran simulations within fractions of minutes, which was two orders of magnitude faster than COMSOL providing identical supercomputing specifications. In conclusion, we demonstrated OpenImpala’s utility as part of an on-site tomography processing pipeline allowing for fast and agile assessment of porous media processes and to guide imaging campaigns while they are happening at synchrotron beamlines

A high-throughput analysis of high-resolution X-ray CT images of stems of olive and citrus plants resistant and susceptible to Xylella fastidiosa

The bacterial plant pathogen Xylella fastidiosa causes disease in several globally important crops. However, some cultivars harbour reduced bacterial loads and express few symptoms. Evidence considering plant species in isolation suggests xylem structure influences cultivar susceptibility to X. fastidiosa. We test this theory more broadly by analysing high-resolution synchrotron X-ray computed tomography of healthy and infected plant vasculature from two taxonomic groups containing susceptible and resistant varieties: two citrus cultivars (sweet orange cv. Pera, tangor cv. Murcott) and two olive cultivars (Koroneiki, Leccino). Results found the susceptible plants had more vessels than resistant ones, which could promote within-host pathogen spread. However, features associated with resistance were not shared by citrus and olive. While xylem vessels in resistant citrus stems had comparable diameters to those in susceptible plants, resistant olives had narrower vessels that could limit biofilm spread. And while differences among olive cultivars were not detected, results suggest greater vascular connectivity in resistant compared to susceptible citrus plants. We hypothesize that this provides alternate flow paths for sustaining hydraulic functionality under infection. In summary, this work elucidates different physiological resistance mechanisms between two taxonomic groups, while supporting the existence of an intertaxonomical metric that could speed up the identification of candidate-resistant plants.</p

Image-based modelling of transport processes in real battery electrodes and other electrochemical devices: the development of OpenImpala

In recent years, x-ray tomography has emerged as a powerful analytical tool in the study of batteries and the processes occurring within. A region of specific interest is the porous electrode and, in particular, the heterogeneous geometry of the porous structure. This thesis introduces the reader to different imaging and physics-based modelling methods used to study the lithium-ion battery. It’s found that none of the image-based models presented in the literature scale well with an increasing number of computational cores. This results in representative elementary volumes being used to approximate the heterogeneity of the porous electrode structure. There is a gap in the literature for the development of a highly parallelisable code that can solve physics equations across large datasets typical of modern tomography. The work presented in this thesis sets out to develop such a code in order to aid understanding of the physical processes within the battery. This thesis also examines the use of x-ray computed tomography to analyse different electrochemical devices, including titanium dioxide electrodes for an aluminium-ion battery, lithium titanate electrodes for a supercapacitor, and lithium iron phosphate electrodes for a lithium-ion battery

Dataset supporting the thesis &#39;Image-Based Modelling of Transport Processes in Real Battery Electrodes and Other Electrochemical Devices: The Development of OpenImpala&#39;

This dataset contains the underlying data for the figures presented in the associated thesis &quot;Image-Based Modelling of Transport Processes in Real Battery Electrodes and Other Electrochemical Devices: The Development of OpenImpala&quot;. The data is stored as a combination of .xlsx, .raw and .tiff files. The files are grouped into zip folders by chapter. Data in Chapter 1 are related to the publication Le Houx, James, and Denis Kramer. &quot;X-ray tomography for lithium ion battery electrode characterisation&mdash;A review.&quot; Energy Reports 7 (2021): 9-14, DOI:10.1016/\-j.egyr.2021.02.063. Data in Chapter 3 are related to the publications: Le Houx, James, Markus Osenberg, Matthias Neumann, Joachim R. Binder, Volker Schmidt, Ingo Manke, Thomas Carraro, and Denis Kramer. &quot;Effect of Tomography Resolution on Calculation of Microstructural Properties for Lithium Ion Porous Electrodes.&quot; ECS Transactions 97, no. 7 (2020): 255, DOI:10.1149/09707.\-0255ecst and Le Houx, James and Denis Kramer. &quot;OpenImpala: OPEN source IMage based PArallisable Linear Algebra solver.&quot; SoftwareX 15 (2021): 100729, DOI:10.1016/j.\-softx.2021.100729. Data in Chapter 4 are related to the publications: Ojha, Manoranjan, James Le Houx, Radha Mukkabla, Denis Kramer, Richard George Andrew Wills, and Melepurath Deepa. &quot;Lithium titanate/pyrenecarboxylic acid decorated carbon nanotubes hybrid-Alginate gel supercapacitor.&quot; Electrochimica Acta 309 (2019): 253-263, DOI:10.1016/j.electacta.2019.03.211 and Fraser, Ewan, James Le Houx, Luis Fernando Arenas, Kahanda Koralage Ranga Dinesh and Richard Wills. &quot;The soluble lead flow battery: Image-based modelling of porous carbon electrodes.&quot; Journal of Energy Storage 52 (2022): 104791, DOI:10.1016/j.est.2022.104791. </span

OpenImpala: OPEN source IMage based PArallisable Linear Algebra solver

Image-based modelling has emerged as a popular method within the field of lithium-ion battery modelling due to its ability to represent the heterogeneity of the porous electrodes. A common challenge from image-based modelling is the size of 3D tomography datasets, which can be of the order of several billion voxels. Previously, different approximation methods have been used to simplify the computational problem, but each of these come with associated limitations. Here we develop a data-driven, fully parallelisable, image-based modelling framework called OpenImpala. Micro X-ray computed tomography (CT) is used to obtain 3D microstructural data from samples non-destructively. These 3D datasets are then directly used as the computational domain for finite-differences based direct physical modelling (e.g. to solve the diffusion equation directly on the CT obtained datasets). OpenImpala then calculates the equivalent homogenised transport coefficients for the given microstructure. These coefficients are written into parameterised files for direct compatibility with two popular continuum battery models: PyBamm and DandeLiion, facilitating the link between different scales of computational battery modelling. OpenImpala has been shown to scale well with an increasing number of computational cores on distributed memory architectures, making it applicable to large datasets typical of modern tomography

X-ray tomography for lithium ion battery electrode characterisation — A review

In recent years, x-ray tomography has emerged as a powerful analytical tool for the study of lithium ion batteries and the processes occurring within. A region of specific interest is the electrode and, in particular, the heterogeneous and porous structure. The present paper is a review of studies that use x-ray tomography to characterise electrode structure, at both the cell and microstructure scales. At the cell level, x-ray tomography is used to investigate macroscopic design parameters, such as anode and cathode thicknesses, packing density and alignment of assembled cells, as well as to visualise any macroscopic structural defects, such as islanding. At the microstructure level, x-ray tomography allows for quantitative analysis of electrode structures to ascertain parameters such as particle size, tortuosity and volume fraction. The paper also explores different techniques that have been used across the field, from ex-situ, in-situ and operando techniques, to multimodal imaging methods, tomography informed design and results informed imaging

Physics based modelling of porous lithium ion battery electrodes—A review

Mathematical models have been used extensively to simulate physical and electrochemical processes occurring inside lithium-ion batteries. Physical based models, coupled with experimental validation, have revealed greater scientific understanding of the processes inside the battery. A region of specific interest is the porous electrode. However, the heterogeneous geometry of the porous structure presents practical difficulties in developing suitable models. The present paper is a review of the studies on the physical modelling of lithium ion porous electrodes. Here we review common methods to model the (de)intercalation behaviour of porous Li-ion battery electrodes. Advantages and drawbacks are contrasted to highlight some challenges that suggest directions and priorities for further research in the field

Dataset in support of the publication: Statistical effective diffusivity estimation in porous media using an integrated on-site imaging workflow for synchrotron users

Data set supporting the manuscript &#39;Statistical effective diffusivity estimation in porous media using an integrated on-site imaging workflow for synchrotron users&#39; published in the journal Transport in Porous Media The data contains a stack of images used to generate the image based models that are used for benchmarking the homogenization protocol. </span

Lithium titanate/pyrenecarboxylic acid decorated carbon nanotubes hybrid - Alginate gel supercapacitor

A facile scalable strategy is reported for the synthesis of a hybrid of lithium titanate (Li4Ti5O12 or LTO) and 1-pyrenecarboxylic acid decorated multiwalled carbon nanotubes (PCA@CNTs). LTO platelets comprising of quasi-spherical nanoparticles afford short diffusion paths for electrolyte ions. PCA@CNTs, enhance the electrical conductivity of the nearly insulating LTO by 3 orders of magnitude, thus maximizing the ion-uptake capability of the hybrid. Symmetric and asymmetric supercapacitors with the LTO/PCA@CNTs hybrid supported over Ni foam substrates are assembled with a novel Li+ conducting alginate gel, in air without any inert conditions that are typically used for all LTO based devices. The gel shows an average ionic conductivity of ∼8.4 mS cm−1 at room temperature, and is found to be electrochemically stable over a wide operational voltage window of ∼2.5 V. Benefitting from the synergy of electrical double layer (EDL) storage afforded by PCA@CNTs, ion-storage by LTO through a redox reaction and EDL, and the ease ion-movement across the cell due to the open architecture of CNTs, the asymmetric LTO/PCA@CNTs hybrid cell outperforms the symmetric cells by a large margin. The best areal specific capacitance (SC), volumetric SC and energy density are ∼54 mF cm−2, ∼4.3 F cm−3 (at 0.5 mA cm−2) and ∼3.7 mWh cm−3 (at a power density of 49.6 mW cm−3) significantly enhanced for the asymmetric LTO/PCA@CNTs hybrid cell, compared to the symmetric- PCA@CNTs and hybrid cells. The design is simple to implement and can serve as a prototype to develop a range of yet unexplored LTO/carbon nanomaterial based supercapacitors

Statistical effective diffusivity estimation in porous media using an integrated on-site imaging workflow for synchrotron users

Transport in porous media plays an essential role for many physical, engineering, biological and environmental processes. Novel synchrotron imaging techniques and image-based models have enabled more robust quantification of geometric structures that influence transport through the pore space. However, image-based modelling is computationally expensive, and end users often require, while conducting imaging campaign, fast and agile bulk-scale effective parameter estimates that account for the pore-scale details. In this manuscript we enhance a pre-existing image-based model solver known as OpenImpala to estimate bulk-scale effective transport parameters. In particular, the boundary conditions and equations in OpenImpala were modified in order to estimate the effective diffusivity in an imaged system/geometry via a formal multi-scale homogenisation expansion. Estimates of effective pore space diffusivity were generated for a range of elementary volume sizes to estimate when the effective diffusivity values begin to converge to a single value. Results from OpenImpala were validated against a commercial finite element method package COMSOL Multiphysics (abbreviated as COMSOL). Results showed that the effective diffusivity values determined with OpenImpala were similar to those estimated by COMSOL. Tests on larger domains comparing a full image-based model to a homogenised (geometrically uniform) domain that used the effective diffusivity parameters showed differences below 2 % error, thus verifying the accuracy of the effective diffusivity estimates. Finally, we compared OpenImpala’s parallel computing speeds to COMSOL. OpenImpala consistently ran simulations within fractions of minutes, which was two orders of magnitude faster than COMSOL providing identical supercomputing specifications. In conclusion, we demonstrated OpenImpala’s utility as part of an on-site tomography processing pipeline allowing for fast and agile assessment of porous media processes and to guide imaging campaigns while they are happening at synchrotron beamlines