Spatial modeling of the 3D morphology of hybrid polymer-ZnO solar cells, based on electron tomography data

A spatial stochastic model is developed which describes the 3D nanomorphology of composite materials, being blends of two different (organic and inorganic) solid phases. Such materials are used, for example, in photoactive layers of hybrid polymer zinc oxide solar cells. The model is based on ideas from stochastic geometry and spatial statistics. Its parameters are fitted to image data gained by electron tomography (ET), where adaptive thresholding and stochastic segmentation have been used to represent morphological features of the considered ET data by unions of overlapping spheres. Their midpoints are modeled by a stack of 2D point processes with a suitably chosen correlation structure, whereas a moving-average procedure is used to add the radii of spheres. The model is validated by comparing physically relevant characteristics of real and simulated data, like the efficiency of exciton quenching, which is important for the generation of charges and their transport toward the electrodes.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS468 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Quantitative 3D reconstruction of porous polymers using FIB-SEM tomography -correlating materials structures to properties of coatings for controlled drug release

Porous networks are found in a wide range of different advanced and technologically important materials and influence the materials properties. The networks are active components in for example batteries, food and pharmaceuticals. The interconnectivity of a network strongly influences the transport properties. One example is polymer film coatings for controlled drug release where the porous network acts as a transport path for drugs. The correlation between the detailed structure of the network and the transport properties illustrates the importance of quantifying the interconnectivity in 3D. One approach to image material in 3D is sequential imaging (tomography). Examples of tomography techniques are confocal laser scanning microscopy, x-ray and neutron tomography where the spatial resolution is limited to the micrometre length scale. Transmission electron microscopy tomography and focused ion beam (FIB) combined scanning electron microscope (SEM) tomography are examples of techniques with higher spatial resolution ranging from micrometre to sub-nanometre. In this work the focus is on the understanding of the correlation between the structure and materials properties of phase-separated polymer film coatings used for controlled drug release. We acquired high spatial 3D resolution data on microporous ethyl cellulose and hydroxypropyl cellulose film coatings using FIB-SEM tomography. The tomography was performed after the water soluble hydroxypropyl cellulose phase had been removed leaving a porous network providing a transport path for the drug. We optimised the FIB-SEM parameters and established a generic protocol for porous and poorly conducting materials in order to overcome challenges such as redeposition, curtaining, shadowing effects, charging and sub-surface information due to the pores. In addition, a new self-learning segmentation algorithm was introduced to enable an automatic separation between pores and matrix. The quantification of the porous network was carried out by determining the pore size distribution, tortuosity and interconnectivity. As a final step, diffusion simulations were performed on the FIB-SEM data and correlated with experimentally measured permeability

Doctor of Philosophy

dissertationAdvances in technology have produced efficient and powerful scientific instruments for measuring biological phenomena. In particular, modern microscopes and nextgeneration sequencing machines produce data at such a rate that manual analysis is no longer practical or feasible for meaningful scientific inquiries. Thus, there is a great need for computational strategies to organize and analyze huge amounts of data produced by biological experiments. My work presents computational strategies and software solutions for application in image analysis, human variant prioritization, and metagenomics. The information content of images can be leveraged to answer an extremely broad spectrum of questions ranging from inquiries about basic biological processes to highly specific, application-driven inquiries like the efficacy of a pharmaceutical drug. Modern microscopes can produce images at a rate at which rigorous manual analysis is impossible. I have created software pipelines that automate image analysis in two specific applications domains. In addition, I discuss general image analysis strategies that can be applied to a wide variety of problems. There are tens of millions of known human genetic variants. Prioritizing human variants based on how likely they are to cause disease is of huge importance because of the potential impact on human health. Current variant prioritization methods are limited by their scope, efficiency, and accuracy. I present a variant prioritization method, the VAAST variant prioritizer, which is superior in its scope, efficiency, and accuracy to existing variant prioritization methods. The rise of next-generation sequencing enables huge quantities of sequence to be generated in a short period of time. No field of study has been affected by rapid sequencing more than metagenomics. Metagenomics, the genomic analysis of a population v of microorganisms, has important implications for pathogen detection because metagenomics enables the culture-free detection of microorganisms. I have created Taxonomer, a comprehensive metagenomics pipeline that enables the real-time analysis of read datasets derived from environmental samples

3D Reconstruction of Porous and Poorly Conductive Soft Materials using FIB-SEM Tomography

Focused ion beam combined with scanning electron microscope (FIB-SEM) is a powerful tool that can be utilised to reveal the internal microstructure of materials. It basically uses ions to make cross-sections with high precision and electrons to image the cross-section surface with high spatial resolution. In addition to revealing the internal microstructure, FIB-SEM can be used to perform a sequential slice and image procedure which, after some data processing, can result in a 3D reconstruction of the microstructure, also denoted as FIB-SEM tomography. Focused ion beam tomography is a well-established procedure since 1987. It has been successfully applied to a variety of well conductive materials. However, to perform FIB-SEM tomography on ion and electron beam sensitive as well as poorly conductive soft materials is still challenging. Some of the common challenges are cross-sectioning artefacts, shadowing-effects and charging. The presence of pores adds additional challenges. Fully dense materials provide a planar cross-section while pores expose surface area beneath the planar cross-section surface as well. The sub-surface pore information and the varying intensity from the sub-surface areas give rise to intensity overlaps which complicates the data processing. Several solutions to overcome these challenges have been reported. Examples are milling and imaging at low beam energies and specimen preparations. However, the ultimate aim is to examine porous and poorly conductive soft materials as close to their original state to avoid introduction of artefacts.\ua0\ua0\ua0\ua0 \ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 The aim of this work was to develop a general protocol for optimisation of FIB-SEM tomography parameters for porous and poorly conductive soft materials.The optimised parameters include the energies and currents of the ion and electron beams, reduction of shadowing-effects, choice of electron detector and selection of method for charge neutralisation. In addition, a new self-learning binarisation algorithm is introduced to enable an automatic separation between pores and matrix. The binary data have been used to visualise the interconnectivity in 3D of individual pore paths through phase separated polymer films. The optimised protocol for FIB-SEM tomography is applicable to a variety of porous and poorly conductive soft materials. \ua0\ua0\ua0\ua0\ua0 \ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 \ua0The porous and poorly conductive soft materials in these studies were leached phase separated polymer films intended for controlled drug release coatings in pharmaceuticals. The porous microstructure within the films acts as transport path for the drug. In this work, the complex microstructure has been visualised in 3D. In addition, 3D visualisation of the shortest, intermediate and longest paths through the films, based upon tortuosity calculations, have been performed as well

Nanostructured Fiber Materials and Composites for Tissue Engineering

The demand for organ transplantation is increased day by day, highlighting the necessity for the development of tissue engineering as a part of strategic solution in medical treatments. Nanotechnology has brought a possibility to introduce materials, architectures and specific topographies required for the closet analogies in extracellar matrix (ECM) in native tissue. Among different nanostructured materials, electrospun nanofibers are recommended as an appropriate scaffold for tissue engineering due to their structural, biomedical and biophysical properties.The aim of this thesis was to study the properties of electrospun nanofibers as scaffolds in tissue engineering. To this end, we first studied electrospinning mechanism as a nanofabrication method for the preparation of electrospun nanofibers. Secondly, the structural characteristics of electrospun nanofibers in different morphological conditions were observed by image analysis. In the third step, the comparative study was established between these structural characteristics and the viability of cells. And finally, the effects of nanofiber coating in viability, proliferation and differentiation of mesenchymal stem cells were discussed.Polyacrylonitrile (PAN) nanofibers and carbon nanotube (CNT) reinforced PAN nanofibers were electrospun successfully. A polymer plasticiser, ethylene carbonate (EC), was added into the PAN/CNT solutions. It was observed that increasing the polymer concentration led to a reduction of beads density and an increase in the diameter of the PAN nanofibers. The fiber diameters also increased as a result of the addition of CNTs below the electrical percolation threshold. It was found that the inclusion of EC permits changes in the morphological characteristics of the PAN/CNT nanocomposite fiber regardless of the effects of its conductivity and viscosity.3D nanofibrous chitosan-polyethylene oxide (PEO) scaffolds were fabricated by electrospinning using different processing parameters. The structural characteristics, such as pore size, overall porosity, pore interconnectivity, and scaffold percolative efficiency (SPE), were observed by using detailed image analysis. Mouse fibroblast cells (L929) were cultured in RPMI for 2 days in the presence of various samples of nanofibrous chitosan/PEO scaffolds. Cell attachment and the corresponding mean viability were enhanced from 50% to 110% compared to that of a control even at packed morphologies of scaffolds constituted from pores with nanoscale diameter. To elucidate the correlation between structural characteristics within the depth of the scaffolds’ profile and cell viability, a comparative analysis was proposed. This analysis revealed that larger fiber diameters and pore sizes can enhance cell viability. On the contrary, increasing the other structural elements such as overall porosity and interconnectivity due to a simultaneous reduction in fiber diameter and pore size through the electrospinning process can reduce the viability of cells. In addition, it was found that manipulation of the processing parameters in electrospinning can compensate for the effects of packed morphologies of nanofibrous scaffolds and can thus potentially improve the infiltration and viability of cells.We present a new hybrid scaffold constructed by coating electrospun chitosan/polyethylene oxide (PEO) nanofibers on commercial BioTek polystyrene (PS) scaffold obtained from Sigma Aldrich. The viability and proliferation rate of mesenchymal stem cells (MSCs) seeded on micro-nano structured hybrid scaffold (MNHS) and commercial PS scaffolds were analyzed using the MTT assay. The results of the MTT assay revealed a higher degree of viability and proliferation rate in MSCs seeded on MNHS compared with the commercial PS scaffold. DAPI images also confirmed the higher degree of attachment and viability of MSCs seeded on MNHS. Moreover, MSCs on both scaffolds differentiated to osteoblasts and adipocytes cells, as reflected by the images obtained from Alizarin Red and Oil Red-O staining. Alkaline phosphatase activity (ALP) and calcium content assays revealed that the MNHS has a higher potential for osteogenic differentiation than the commercial scaffold. To quantify the osteoblast and adipocyte gene expression, quantitative RTPCR was carried out for MNHS, commercial scaffold and Tissue culture polystyrene (TCPS). It was found that MNHS can express a higher level of Runt-related transcription factor 2 (Runx2), osteonectin and osteocalcin in osteogenic differentiation as well as increased expression of PPARγ and UCP-1 in adipogenic differentiation. The enhancement of the attachment, viability and proliferation as well as bi-lineage differentiation may result from the biochemical and structural analogies of MNHS to native ECM. Furthermore, it was observed that biocompatible MNHS scaffold can potentially be utilized as a suitable scaffold for bone and connective tissue engineering

Efficient Computation of Adaptive Threshold Surfaces for Image Binarization

The problem of binarization of gray level images acquired under nonuniform illumination is reconsidered. Yanowitz and Bruckstein proposed to use for image binarization an adaptive threshold surface, determined by interpolation of the image gray levels at points where the image gradient is high. The rationale is that high image gradient indicates probable object edges, and there the image values are between the object and the background gray levels. The threshold surface was determined by successive overrelaxation as the solution of the Laplace equation. This work proposes a different method to determine an adaptive threshold surface. In this new method, inspired by multiresolution approximation, the threshold surface is constructed with considerably lower computational complexity and is smooth, yielding faster image binarizations and better visual performance