Three dimensional quantification of soil hydraulic properties using X-ray Computed Tomography and image based modelling

We demonstrate the application of a high-resolution X-ray Computed Tomography (CT) method to quantify water distribution in soil pores under successive reductive drying. We focus on the wet end of the water release characteristic (WRC) (0 to -75 kPa) to investigate changes in soil water distribution in contrasting soil textures (sand and clay) and structures (sieved and field structured), to determine the impact of soil structure on hydraulic behaviour. The 3D structure of each soil was obtained from the CT images (at a 10 µm resolution). Stokes equations for flow were solved computationally for each measured structure to estimate hydraulic conductivity. The simulated values obtained compared extremely well with the measured saturated hydraulic conductivity values. By considering different sample sizes we were able to identify that the smallest possible representative sample size which is required to determine a globally valid hydraulic conductivity

Assessing the influence of the rhizosphere on soil hydraulic properties using X-ray Computed Tomography and numerical modelling

Understanding the dynamics of water distribution in soil is crucial for enhancing our knowledge of managing soil and water resources. The application of X-ray Computed Tomography (CT) to the plant and soil sciences is now well established. However, few studies have utilised the technique for visualising water in soil pore spaces. Here we utilise this method to visualise the water in soil in situ and in three-dimensions at successive reductive matric potentials in bulk and rhizosphere soil. The measurements are combined with numerical modelling to determine the unsaturated hydraulic conductivity, providing a complete picture of the hydraulic properties of the soil. The technique was performed on soil cores that were sampled adjacent to established roots (rhizosphere soil) and from soil that had not been influenced by roots (bulk soil). A water release curve was obtained for the different soil types using measurements of their pore geometries derived from CT imaging and verified using conventional methods e.g. pressure plates. The water, soil and air phases from the images were segmented and quantified using image analysis. The water release characteristics obtained for the contrasting soils showed clear differences in hydraulic properties between rhizosphere and bulk soil, especially in clay soil. The data suggests that soils influenced by roots (rhizosphere soil) are less porous due to increased aggregation when compared to bulk soil. The information and insights obtained on the hydraulic properties of rhizosphere and bulk soil will enhance our understanding of rhizosphere biophysics and improve current water uptake models

Multi-scale multi-dimensional imaging and characterization of oil shale pyrolysis

In recent years, oil shale has attracted renewed attention as an unconventional energy resource, with vast and largely untapped reserves. Oil shale is a fine-grained sedimentary rock containing a sufficiently high content of immature organic matter from which shale oil and combustible gas can be extracted through pyrolysis. Several complex physical and chemical changes occur during the pyrolysis of oil shale where macromolecular network structures of kerogen are thermally decomposed. The pyrolysis of oil shale leads to the formation of a microscopic pore network in which the oil and gas products flow. The pore structure and the connectivity are significant characteristics which determine fluid flow and ultimate hydrocarbon recovery. In this thesis, a state-of-the-art multi-scale multi-dimensional workflow was applied to image and quantify the Lacustrine Eocene Green River (Mahogany Zone) formation, the world’s largest oil shale deposit. Samples were imaged before, during and after pyrolysis using laboratory and synchrotron-based X-ray Micro-tomography (µCT), Optical Microscopy, Automated Ultra-High Resolution Scanning Electron Microscopy (SEM), MAPS Mineralogy (Modular Automated Processing System) and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM). Results of image analysis using optical (2-D), SEM (2-D), and µCT (3-D) reveal a complex fine-grained microstructure dominated by organic-rich parallel laminations in a tightly bound heterogeneous mineral matrix. MAPS Mineralogy combined with ultrafast measurements highlighted mineralogic textures dominated by dolomite, calcite, K-feldspar, quartz, pyrite and illitic clays. From high resolution backscattered electron (BSE) images, intra-organic, inter-organic-mineral, intra and inter-mineral pores were characterised with varying sizes and geometries. A detailed X-ray µCT study with increasing pyrolysis temperature (300-500°C) at 12 µm, 2 µm and 0.8 µm voxel sizes illuminated the evolution of pore structure, which is shown to be a strong function of the spatial distribution of organic content. In addition, FIB-SEM 3-D visualisations showed an unconnected pore space of 0.5% with pores sizes between 15 nm and 22 nm for the un-pyrolysed sample and a well-connected pore space of 18.2% largely with pores of equivalent radius between 1.6 µm and 2.0 µm for the pyrolysed sample. Synchrotron 4-D results at a time resolution of 160 seconds and a voxel size of 2 µm revealed a dramatic change in porosity accompanying pyrolysis between 390-400°C with the formation of micron-scale heterogeneous pores followed by interconnected fracture networks predominantly along the organic-rich laminations. Combining these techniques provides a powerful tool for quantifying petrophysical properties before, during and after oil shale pyrolysis. Quantitative 2-D, 3-D and 4-D imaging datasets across nm-µm-mm length scales are of great value to better understand, predict and model dynamics of pore structure change and hydrocarbon transport and production during oil shale pyrolysis.Open Acces

Bridging Nano and Micro-scale X-ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray Computed Tomography (X-ray CT) is a well-known non-destructive imaging technique where contrast originates from the materials' absorption coefficients. Novel battery characterization studies on increasingly challenging samples have been enabled by the rapid development of both synchrotron and laboratory-scale imaging systems as well as innovative analysis techniques. Furthermore, the recent development of laboratory nano-scale CT (NanoCT) systems has pushed the limits of battery material imaging towards voxel sizes previously achievable only using synchrotron facilities. Such systems are now able to reach spatial resolutions down to 50 nm. Given the non-destructive nature of CT, in-situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area, and volume expansion during battery operation or cycling. Combined with powerful Artificial Intelligence (AI)/Machine Learning (ML) analysis techniques, extracted 3D tomograms and battery-specific morphological parameters enable the development of predictive physics-based models that can provide valuable insights for battery engineering. These models can predict the impact of the electrode microstructure on cell performances or analyze the influence of material heterogeneities on electrochemical responses. In this work, we review the increasing role of X-ray CT experimentation in the battery field, discuss the incorporation of AI/ML in analysis, and provide a perspective on how the combination of multi-scale CT imaging techniques can expand the development of predictive multiscale battery behavioral models.Comment: 33 pages, 5 figure

A 3D Framework for Characterizing Microstructure Evolution of Li-Ion Batteries

Lithium-ion batteries are commonly found in many modern consumer devices, ranging from portable computers and mobile phones to hybrid- and fully-electric vehicles. While improving efficiencies and increasing reliabilities are of critical importance for increasing market adoption of the technology, research on these topics is, to date, largely restricted to empirical observations and computational simulations. In the present study, it is proposed to use the modern technique of X-ray microscopy to characterize a sample of commercial 18650 cylindrical Li-ion batteries in both their pristine and aged states. By coupling this approach with 3D and 4D data analysis techniques, the present study aimed to create a research framework for characterizing the microstructure evolution leading to capacity fade in a commercial battery. The results indicated the unique capabilities of the microscopy technique to observe the evolution of these batteries under aging conditions, successfully developing a workflow for future research studies

Development of X-ray Tomography Tools for Characterisation of Lithium-Sulfur Batteries

Electrochemical energy storage devices are becoming increasingly ubiquitous in both consumer and industrial applications, driven by a pressing need to reduce carbon emissions for the mitigation of global warming. The electrification of the transport and mobility sector and growth in portable electronic devices demand portable power sources with high energy densities, and lithium-ion (Li-ion) batteries have been adopted extensively in these applications. However, conventional transition metal oxide-based intercalation materials used at the positive electrode are reaching their theoretical limitations, and only relatively minor improvements in theoretical specific capacity can be achieved. // Lithium-sulfur (Li-S) batteries offer higher gravimetric theoretical specific capacity and energy density and are billed as a potential successor to Li-ion technology but suffer from limited cycle life and self-discharge due to complex multi-phase chemistry and parasitic side reactions. // To better understand the fundamental mechanisms behind these processes, advanced characterisation methods involving the use of penetrating radiation (such as X-rays and neutrons) have become invaluable tools to capture the operation and degradation of the Li-S battery. Three-dimensional techniques such as X-ray micro-tomography (micro-CT) are particularly suited to probe the heterogeneous nature of battery electrode microstructures. // In this thesis, main areas of focus will include the application of ex situ and in situ X-ray micro-CT on Li-S batteries and the broader development of in situ tomography cells. The overall scientific aims of this thesis include: measuring the three-dimensional microstructural characteristics of sulfur electrodes; elucidating the three-dimensional nature of both sulfur dissolution and redeposition as a function of state of charge; and developing a better understanding of the transport processes occurring within the Li-S battery and the influence of porosity and tortuosity on electrochemical performance. In parallel, the development of in situ tomography cells capable of electrochemical cycling is an extensive component of this thesis, with applications not solely limited to Li-S batteries or X-ray micro-CT

Three-dimensional mapping of soil chemical characteristics at micrometric scale by combining 2D SEM-EDX data and 3D X-ray CT images

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution

Mapping the Pore Architecture of Structured Catalyst Monoliths from Nanometer to Centimeter Scale with Electron and X-ray Tomographies

The hierarchical pore systems of Pt/Al2O3 exhaust gas aftertreatment catalysts were analyzed with a collection of correlative imaging techniques to monitor changes induced by hydrothermal aging. Synergistic imaging with laboratory X-ray microtomography, synchrotron radiation ptychographic X-ray computed nanotomography, and electron tomography allowed quantitative observation of the catalyst pore architecture from centimeter to nanometer scale. Thermal aging at 750 °C in air and hydrothermal aging at 1050 °C in 10% H2O/air caused increasing structural degradation, which manifested as widespread sintering of Pt particles, increased volume and quantity of macropores (>20 nm), and reduction in effective surface area coupled with decreasing volume and frequency of mesopores (2-20 nm) and micropores (<2 nm). Electron tomography unraveled the three-dimensional (3D) structure with high resolution allowing visualization of meso- and macropores but with samples of maximum 300 nm thickness. To complement this, hard X-ray ptychographic tomography produced quantitative 3D electron density maps of 5 μm diameter samples with spatial resolution <50 nm, effectively filling the resolution gap between electron tomography and hard X-ray microtomography. The obtained 3D volumes are an essential input for future computational modeling of fluid dynamics, mass transport, or diffusion properties and may readily complement bulk one-dimensional porosimetry measurements or simulated porosity