Comparison of three-dimensional analysis and stereological techniques for quantifying lithium-ion battery electrode microstructures

Lithium-ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium-ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3-D imaging techniques, quantitative assessment of 3-D microstructures from 2-D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two-dimensional (2-D) data sets. In this study, stereological prediction and three-dimensional (3-D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium-ion battery electrodes were imaged using synchrotron-based X-ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2-D image sections generated from tomographic imaging, whereas direct 3-D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2-D image sections is bound to be associated with ambiguity and that volume-based 3-D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially-dependent parameters, such as tortuosity and pore-phase connectivity

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

Personalised body counter calibration using anthropometric parameters

This book describes the development of a new method for personalisation of efficiency factors in partial body counting. Its achieved goal is the quantification of uncertainties in those factors due to variation in anatomy of the measured persons, and their reduction by correlation with anthropometric parameters. The method was applied to a detector system at the In Vivo Measurement Laboratory at Karlsruhe Institute of Technology using Monte Carlo simulation and computational phantoms

Characterization of contaminated sites and monitoring of processes accompanying bioremediation using spectral induced polarization imaging

Measurements of spectral induced polarization (SIP) provide information about the electrical conduction and polarization properties of the subsurface, and their frequency dependence. Several laboratory studies in the last decade have highlighted the advantages of the SIP method for environmental applications. Nevertheless, to date only a few studies have been conducted at the field scale. This work demonstrates the application of SIP imaging at the field scale for the characterization of contaminants as well as for the monitoring of processes associated with the microbial remediation of contaminated sites. The first part of this work presents a series of well-controlled measurements collected in the laboratory in order to investigate the distribution of data error in SIP tomographic measurements. Based on a thorough analysis of discrepancies between normal and reciprocal measurements, a power-law error model is proposed to quantify the error present in phase measurements. Implementation of the proposed error model in the inversion algorithm demonstrates an improvement in the resolution of the SIP images. Based on the methodology proposed for the data analysis, the second part of this work investigates the potential of SIP images to discriminate between the source zone and the plume of dissolved contaminants in a BTEX (benzene, toluene, ethylbenzene and xylene) contaminated site. For dissolved BTEX (concentrations below 1.7 g/l), imaging results reveal an increase in the polarization values with increasing BTEX concentrations. An abrupt decrease to low polarization values is observed at higher BTEX concentrations (> 1.7 g/l) associated with the occurrence of free-phase products. Moreover, for BTEX concentrations below saturation concentration, the spectral response in the low frequencies ( The application of SIP imaging for the monitoring of a bioremediation technique is presented in the third part of this work. The studied remediation technique involves the stimulation of iron and sulfate reducing bacteria through acetate injection to remove aqueous uranium from groundwater. SIP monitoring images collected over a two-year period reveal spatiotemporal changes in the polarization of aquifer sediments. These changes correlate with variations in the concentrations of aqueous iron (Fe(II)) in groundwater and precipitation of metallic minerals (e.g., FeS) following the iterative stimulation of iron and sulfate reducing microorganism. However, poor reciprocity in the raw-data was observed for measurements collected at frequencies higher than 4 Hz, most probably as a result of electromagnetic coupling. To overcome electromagnetic coupling at high frequencies, field procedures were improved permitting the collection of time-lapse SIP data sets with a good reciprocity in the frequency bandwidth between 0.06 and 256 Hz, as presented in the fourth part of this work. Cole-Cole model fitted to pixel values extracted from the computed SIP images permitted the determination of the chargeability and time constant. The determination of such parameters is critical for the application of existing petropyhsical models required for the hydrogeological characterization of the site. Results presented here reveal changes in time constant and chargeability values consistent with variations in groundwater geochemistry and pore-space geometry (due the accumulation of metallic particles) resulting from the stimulation of subsurface microbial activity. Based on the results presented in this study, SIP imaging appears to be a suitable technique (i) to discriminate between source zone and plume of non-aqueous-phase contaminants, like BTEX; (ii) to monitor remediation techniques in order to maintain favorable conditions for the efficient remediation of contaminants; and (iii) to infer hydrogeological information of the shallow subsurface based on existing petro-physical models, for the assessment of contaminated sites and the evaluation of remediation techniques.Charakterisierung von Schadstoffen im Untergrund und Prozessen im Zusammenhang mit mikrobiellem Abbau an kontaminierten Standorten mittels der Spektrale Induzierte Polarization (SIP)-Bildgebung Die Methode der spektralen induzierten Polarisation (SIP) liefert Informationen über elektrische Leitfähigkeits- und Polarisationseigenschaften des Untergrundes und deren Frequenzabhängigkeit. Im vergangenen Jahrzehnt haben verschiedene Laborstudien die Vorteile des Einsatzes von SIP im Umweltbereich aufgezeigt. Dennoch wurden bis heute nur wenige Untersuchungen auf Feldskala durchgeführt. Diese Arbeit veranschaulicht die Anwendung der SIP-Bildgebung zur Charakterisierung von Schadstoffen im Untergrund und Prozessen im Zusammenhang mit mikrobiellem Abbau an kontaminierten Standorten. Die erste Studie beschäftigt sich mit Labormessungen, die an einem Tank durchgeführt wurden, um die Verteilung des Datenfehlers bei SIP-Messungen zu charakterisieren. Mittels einer statistischen Auswertung der Differenzen von normal und reziprok gemessenen Rohdaten wurde ein exponentielles Phase-Fehlermodell formuliert. Die Implementierung dieses Fehlermodells in einen Inversionsalgorithmus zeigt eine Verbesserung in der Auflösung der invertierten SIP-Tomogramme. In der zweiten Studie wird das Potential der SIP-Bildgebung zur Differenzierung von Quell- und Transportzonen von BTEXen (Benzol, Toluol, Ethylbenzol und Xylol) geprüft. Die Messungen wurden auf dem Gelände eines ehemaligen Hydrierwerkes durchgeführt. Die SIP- Antworten zeigen einen Anstieg der Polarisation bei BTEX-Konzentrationen unterhalb der Sättigungskonzentration (~1.7 g/l). Eine deutliche Abnahmeder Polarisation ist bei höheren BTEX-Konzentrationen und dem Auftreten von freie-Phase Produkten zu verzeichnen. Außerdem weist das spektrale Antwortsignal bei BTEX-Konzentrationen bis zu 1.7 g/l einen charakteristischen Höchstwert in der Frequenz auf, wohingegen höhere BTEX- Konzentrationen und das Auftreten von freie-Phase Produkten am Schadstoffherd eher ein flaches Spektrum und einen geringen Polarisationseffekt für Frequenzen bis 40 Hz zeigen. Die SIP-Antworten wurden mittels Debye-Zerlegung modelliert, um die Korrelation zwischen den spektralen Parametern und den BTEX-Schadstoffen zu ermitteln. Der dritte Teil der vorliegenden Arbeit behandelt die Anwendung der SIP-Bildgebung als Beobachtungsverfahren der Langzeiteffizienz einer Bio-Remediationstechnik. Diese benutzt Acetat-Injektionen zur Stimulierung von eisen(Fe)- und sulfatreduzierenden Bakterien, die gelöstes Uran aus dem Grundwasser entfernen können. Das Monitoring über einen Zeitraum von zwei Jahren zeigt sowohl räumliche als auch zeitliche Änderungen des Polarisationseffekts im Aquifer. Diese Änderungen korrelieren mit dem Anstieg des gelösten Eisens (Fe(II)) sowie mit der Ausfällung metallischer Minerale (z.B. FeS) nach der iterativen Stimulierung eisen- und sulfatreduzierender Mikroorganismen. Eine geringe Reziprozität in den Rohdaten wurde auf Grund elektromagnetischer Kopplung bei Frequenzen von mehr als 4 Hz festgestellt. Um diese elektromagnetische Kopplung zu minimieren, wird im letzten Kapitel dieser Studie eine Methode zur Feldmessung vorgestellt, die das Aufzeichnen von SIP-Daten zu verschiedenen Zeiten mit einer guten Reziprozität im Frequenzbereich von 0,06 bis 256 Hz erlaubt. Die Tomogramme ermöglichen für unterschiedliche Zeiten die Bestimmung der charakteristischen Zeitkonstante, die für die Anwendung von petrophysikalischen Modellen aus Labormessungen notwendig ist. Die gemessenen Änderungen von Zeitkonstante und Aufladbarkeit stimmen dabei mit Änderungen in der Geochemie des Grundwassers und der Porenraumgeometrie überein, die durch die unterirdische Stimulierung der mikrobakteriellen Aktivität erzeugt wurden. Basierend auf den beobachteten Korrelationen erweist sich die SIP-Bildgebung als eine geeignete Technik, um (i) zwischen Quell- und Transport-Bereichen von nicht oder schwer wasserlöslichen organischen Schadstoffen, wie BTEXen, zu unterscheiden und (ii) über den Einsatz von Sanierungsmaßnahmen zur Entscheidungsunterstützung über den effizienten Einsatz der Remediationstechnik zu überwachen und (iii) hydrogeologische Informationen des nahen Untergrundes unter Zuhilfenahme petrophysikalischer Modelle zur Beurteilung kontaminierter Standorte und Evaluation geeigneter Sanierungsmaßnahmen abzuleiten.Mediciones de inducci6n polarizada espectral (SIP por sus siglas en ingles) penniten obtener informaci6n acerca de las propiedades de conducci6n y polarizaci6n electrica del subsuelo, y su dependencia a diferentes frecuencias. Comunmente utilizada para la prospecci6n de yacimientos metalicos, en los ultimos a:fi.os varios estudios en el laboratorio han demostrado las ventajas de la aplicaci6n del metodo de SIP en el area ambiental. Sin embargo, a la fecha, muy pocas investigaciones han sido llevados acabo en el campo. A traves de cuatro estudios, este trabajo intenta demostrar las aplicaci6n de la tecnica de imagenes de SIP para la caracterizaci6n de contaminantes y el monitoreo de procesos asociados con tecnicas bioremediaci6n para sitios contaminados. La primera parte de este estudio presenta una serie de mediciones tomadas en un tanque en el laboratorio, con el fi.n de investigar la distribuci6n y caracteiisticas del error presente en m ediciones tomografi.cas de S IP. Por medio de un detallado analisis estadistico de las discrepancias entre mediciones nonnales y reciprocas, se propone modelo matematico para cuantificar el error presente en mediciones de SIP. La implementaci6n de este modelo, en el algoritmo de inversi6n, penniti6 la obtenci6n de imagenes de SIP con una mayor resoluci6n. La segunda parte de este trabajo investiga la posibilidad de distinguir zonas fuente y pluma de dispersi6n, para sitios contaminados con BTEX (benceno, tolueno, ethybenceno y xileno ). Las imagenes de SIP, revelaron un incremento en los valores de polarizaci6n inducida relacionado con el incremento en las concentraciones de BTEX, para concentraciones de BTEX menores a 1.7 g/1. Un abrupto cambio a valores muy bajos de polarizaci6n inducida se reporta para concentraciones de BTEX mayores a 1.7 g/1 y la presencia de fase libre del contaminante. Ademas, la respuesta espectral revelo un modelo tipico de Cole-Cole en las bajas frecuencias ( La tercera parte de este trabajo presenta la aplicaci6n de imagenes de SIP para el monitoreo de una tecnica de bioremediaci6n. Dicha remediaci6n consiste en la inyecci6n de acetato para estimular el crecimiento y actividad de bacterias reductoras de hierro y sulfatos. Dichas bacterias son capaces de disinuir las concentraciones de uranio presente en agua subterranea de un sitio contaminado. El monitoreo a lo largo de mas de dos afios demostr6 un decremento en las concentraciones de uranio en el agua subterranea, asi como cambios en la polarizaci6n de los sedimentos del subsuelo. Estos cambios estan estrechamente relacionados con variaciones en las concentraciones de hierro disuelto en agua subteminea (Fe(II)) y la precipitaci6n de rninerales rnetalicos (por ejernplo FeS) causados por la estirnulaci6n de actividad de los rnicroorganisrnos. Sin ernbargo, rnediciones de SIP en frecuencias rnayores a 4 Hz revelaron una alta contarninaci6n de los datos por campos electrornagneticos parasitos, provocando una rnala correlaci6n entre rnediciones normales y reciprocas. Para poder incrernentar la calidad de rnediciones a frecuencias rnayores a 4 Hz, en este trabajo se propone una rnejora en las tecnicas de campo. Con base en estos nuevos procedirnientos, se obtuvieron datos confiables en un ancho de banda de 0.06 a 256 Hz, corno se desc1i.be en el cuarto estudio de este trabajo. Irnagenes de SIP para dichos datos perrnitieron deterrninar los valores de cargabilidad (asociada con la rnagnitud del efecto de polarizaci6n espectral) y la constante de tiernpo (inversamente proporcional a la frecuencia en el que se registr6 el mayor efecto de polarizaci6n inducida). La obtenci6n de dichos parametros es critica para poder aplicarlos modelos petro-fisicos existentes. Cambios en cargabilidad y la constante de tiernpo observados son consistentes con variaciones en la quirnica de agua subterranea y en la geometria del espacio poroso del acuifero causado por la estirnulaci6n de microorganismos en el subsuelo. Con base en los resultatlos presentados en este estudio, la tecnica de imagenes de SIP demuestra ser una herramienta util para (i) la caracterizaci6n de la zona fuente y pluma de contaminantes, como BTEX; (ii) para el monitoreo de procesos durante la rernediaci6n de contarninantes (por ejemplo cambios en el agua subterranea), de forma que se puedan rnantener condiciones que fuvorecen la remediaci6n de contaminantes; y (iii) para estimar informaci6n hidrogeol6gica del subsuelo (tal corno conductividad hidraulica) con base en modelos petro-fisicos existentes, tal que se pueda predecir el transporte de contaminantes o la perdida en la eficacia en las tecnicas de remediaci6n

Quantification of the pore size distribution of soils:assessment of existing software using tomographic and synthetic 3D images

The pore size distribution (PSD) of the void space is widely used to predict a range of processes in soils. Recent advances in X-ray computed tomography (CT) now afford novel ways to obtain exact data on pore geometry, which has stimulated the development of algorithms to estimate the pore size distribution from 3D data sets. To date there is however no clear consensus on how PSDs should be estimated, and in what form PSDs are best presented. In this article, we first review the theoretical principles shared by the various methods for PSD estimation. Then we select methods that are widely adopted in soil science and geoscience, and we use a robust statistical method to compare their application to synthetic image samples, for which analytical solutions of PSDs are available, and X-ray CT images of soil samples selected from different treatments to obtain wide ranging PSDs. Results indicate that, when applied to the synthetic images, all methods presenting PSDs as pore volume per class size (i.e., Avizo, CTAnalyser, BoneJ, Quantim4, and DTM), perform well. Among them, the methods based on Maximum Inscribed Balls (Bone J, CTAnalyser, Quantim4) also produce similar PSDs for the soil samples, whereas the Delaunay Triangulation Method (DTM) produces larger estimates of the pore volume occupied by small pores, and Avizo yields larger estimates of the pore volume occupied by large pores. By contrast, the methods that calculate PSDs as object population fraction per volume class (Avizo, 3DMA, DFS-FIJI) perform inconsistently on the synthetic images and do not appear well suited to handle the more complex geometries of soils. It is anticipated that the extensive evaluation of method performance carried out in this study, together with the recommendations reached, will be useful to the porous media community to make more informed choices relative to suitable PSD estimation methods, and will help improve current practice, which is often ad hoc and heuristic

Characterization of breast tissues in density and effective atomic number basis via spectral X-ray computed tomography

Differentiation of breast tissues is challenging in X-ray imaging because tissues might share similar or even the same linear attenuation coefficients $\mu$. Spectral computed tomography (CT) allows for more quantitative characterization in terms of tissue density and effective atomic number by exploiting the energy dependence of $\mu$. In this work, 5 mastectomy samples and a phantom with inserts mimicking breast soft tissues were evaluated in a retrospective study. The samples were imaged at three monochromatic energy levels in the range of 24 - 38 keV at 5 mGy per scan using a propagation-based phase-contrast setup at SYRMEP beamline at the Italian national synchrotron Elettra. A custom-made algorithm incorporating CT reconstructions of an arbitrary number of spectral energy channels was developed to extract the density and effective atomic number of adipose, fibro-glandular, pure glandular, tumor, and skin from regions selected by a radiologist. Preliminary results suggest that, via spectral CT, it is possible to enhance tissue differentiation. It was found that adipose, fibro-glandular and tumorous tissues have average effective atomic numbers (5.94 $\pm$ 0.09, 7.03 $\pm$ 0.012, and 7.40 $\pm$ 0.10) and densities (0.90 $\pm$ 0.02, 0.96 $\pm$ 0.02, and 1.07 $\pm$ 0.03 g/cm$^{3}$) and can be better distinguished if both quantitative values are observed together.Comment: 26 pages, 7 figures, submitted to Physics in Medicine and Biolog

Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution

In this article, we present a novel data assimilation strategy in pore-scale imaging and demonstrate that this makes it possible to robustly address reactive inverse problems incorporating Uncertainty Quantification (UQ). Pore-scale modeling of reactive flow offers a valuable opportunity to investigate the evolution of macro-scale properties subject to dynamic processes. Yet, they suffer from imaging limitations arising from the associated X-ray microtomography (X-ray microCT) process, which induces discrepancies in the properties estimates. Assessment of the kinetic parameters also raises challenges, as reactive coefficients are critical parameters that can cover a wide range of values. We account for these two issues and ensure reliable calibration of pore-scale modeling, based on dynamical microCT images, by integrating uncertainty quantification in the workflow. The present method is based on a multitasking formulation of reactive inverse problems combining data-driven and physics-informed techniques in calcite dissolution. This allows quantifying morphological uncertainties on the porosity field and estimating reactive parameter ranges through prescribed PDE models with a latent concentration field and dynamical microCT. The data assimilation strategy relies on sequential reinforcement incorporating successively additional PDE constraints. We guarantee robust and unbiased uncertainty quantification by straightforward adaptive weighting of Bayesian Physics-Informed Neural Networks (BPINNs), ensuring reliable micro-porosity changes during geochemical transformations. We demonstrate successful Bayesian Inference in 1D+Time and 2D+Time calcite dissolution based on synthetic microCT images with meaningful posterior distribution on the reactive parameters and dimensionless numbers