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

Desglycinamide-(ARG8)-vasopressin in five trials with memory-disturbed patients

A series of five consecutive clinical trials were performed in which the neuropeptide desglycinamide‐(Arg8)‐vasopressin (DGAVP) was administered to human subjects suffering from cognitive and memory complaints. The patients selected for the study were carefully screened with the aid of neuropsychological assessment procedures. The trials were conducted according to a structured design in which the variables ‘dose’, ‘route of administration’, ‘treatment schedule’, ‘diagnostic group’, and ‘severity of deficit’ were varied from trial to trial in order to find optimal conditions for the possible expression of a peptide effect. The results indicate a statistically significant effect of DGAVP on word list learning in patients with mild brain trauma, suggesting that learning performance and memory retrieval are improved after peptide treatment in these patients. Patients with more severe brain trauma did not respond to peptide treatment. Some DGAVP effects, e.g. increased speed of memory search, were observed in patients with age‐associated memory deficits

Synthesis of tungsten oxide particles with sizes smaller than ten nanometers for the elaboration and the reactivity study of nanothermites

Les réactions thermites sont des réactions chimiques entre un métal réducteur et un oxyde, très exothermiques, utilisées pour des applications civiles et militaires variées comme la soudure ou les systèmes d' initiation. Ces réactions ayant lieu entre deuThermite reactions are very exothermic chemical reactions between a reductive metal and an oxide which are used for a broad range of civilian and military uses, such as soldering or initiation systems. As these reactions take place between two solids, th

Synthesis of tungsten oxide particles with sizes smaller than ten nanometers for the elaboration and the reactivity study of nanothermites

Les réactions thermites sont des réactions chimiques entre un métal réducteur et un oxyde, très exothermiques, utilisées pour des applications civiles et militaires variées comme la soudure ou les systèmes d' initiation. Ces réactions ayant lieu entre deux solides, la réactivité du mélange augmente lorsque celui-ci est structuré à l'échelle nanométrique. Le mélange aluminiumltrioxyde de tungstène est un exemple connu de thermite qui a une bonne réactivité. Dans ce travail, nous présentons diverses synthèses permettant d'obtenir de nombreuses tailles et formes de nanoparticules d'oxyde de tungstène. La synthèse se révélant la plus prometteuse est la synthèse sol-gel non-hydrolytique, en particulier lorsqu'elle est réalisée en autoclave avec chauffage microonde. Ainsi, après un traitement thermique entre 300 et 500 oC, servant à éliminer les résidus organiques, les particules obtenues ont des tailles comprises entre 6 et 40 nm. Aussi, nous montrons au cours de ce travail l' importance de la dispersibilité de l'oxyde pour la formulation d'un mélange thermite. De plus, nous mettons en avant la possibilité d'améliorer la réactivité d'une formulation en la préparant dans l'acétonitrile au lieu de l'hexane, dispersant typiquement utilisé. En outre, nous obtenons des vitesses de combustion de comprimés jusqu'à 15 mis.Thermite reactions are very exothermic chemical reactions between a reductive metal and an oxide which are used for a broad range of civilian and military uses, such as soldering or initiation systems. As these reactions take place between two solids, the reactivity of the mixture increases if it is nanometrically structured. Aluminum and tungsten trioxide mixtures are a known example of thermite mixtures which has a good reactivity. In this work, we present various syntheses yielding many different shapes and sizes of tungsten oxide nanoparticles. The most promising synthesis is the non hydrolytic sol gel synthesis, in particular when carried out in a reactor heated by microwave irradiation. A subsequent thermal treatment between 300 and 500 oC, to eliminate any organic residues, yields 6 to 40 nm particles. Also, we show the importance of the oxide dispersibility regarding the formulation ofa thermite mixture. Moreover, we promote the possibility of improving the reactivity by preparing the mixture in acetonitrile instead of hexane, the typically used dispersant. Furthermore, we obtain pellet combustion speeds up to 15 mis

Etude sur la maladie de Roger : (perforation simple de la cloison interventriculaire).

Par.theses 1901-02. No. 460

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

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

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