Rheology of arrested colloids : a parameter study using novel experimental methods

The steadily increasing diversity of colloidal systems demands for new theoretical approaches and a cautious experimental characterization. Here we present a combined rheological and microscopical study of colloids in their arrested state whereas we did not aim for a generalized treatise but rather focused on a few model colloids, liquid crystal based colloidal suspensions and sedimented colloidal films. We laid special emphasis on the understanding of the mutual influence of dominant interaction mechanisms, structural characteristics and the particle properties on the mechanical behavior of the colloid. The application of novel combinations of experimental techniques played an important role in these studies. Beside of piezo-rheometry we employed nanoindentation experiments and associated standardized analysis procedures. These rheometric methods were complemented by real space images using confocal microscopy. The flexibility of the home-made setup allowed for a combination of both techniques and thereby for a simultaneous rheological and three-dimensional structural analysis on a single particle level. Though, the limits of confocal microscopy are not reached by now. We show how hollow and optically anisotropic particles can be utilized to quantify contact forces and rotational motions for individual particles. In future such data can contribute to a better understanding of particle reorganization processes, such as the liquidation of colloidal gels and glasses under shear.

3D Direct Simulation Monte Carlo Modelling of the Inner Gas Coma of Comet 67P/Churyumov-Gerasimenko: A Parameter Study

Direct Simulation Monte Carlo (DSMC) is a powerful numerical method to study rarefied gas flows such as cometary comae and has been used by several authors over the past decade to study cometary outflow. However, the investigation of the parameter space in simulations can be time consuming since 3D DSMC is computationally highly intensive. For the target of ESA's Rosetta mission, comet 67P/Churyumov-Gerasimenko, we have identified to what extent modification of several parameters influence the 3D flow and gas temperature fields and have attempted to establish the reliability of inferences about the initial conditions from in situ and remote sensing measurements. A large number of DSMC runs have been completed with varying input parameters. In this work, we present the simulation results and conclude on the sensitivity of solutions to certain inputs. It is found that among cases of water outgassing, the surface production rate distribution is the most influential variable to the flow field.

Stresses in reinforced nozzle-cylinder attachments under external moment loadings analyzed by the finite-element method : a parameter study /

"ORNL/NUREG-52."

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Astrophysikalische Bedingungen für einen r-Prozess im Hoch-Entropie-Wind von Typ II Supernovae

Sterne mit einer Anfangsmasse zwischen etwa 8 und 25 Sonnenmassen enden ihre Existenz mit einer gewaltigen Explosion, einer Typ II Supernova. Die hierbei entstehende Hoch-Entropie-Blase ist ein Bereich am Rande des sich bildenden Neutronensterns und gilt als möglicher Ort für den r-Prozess. Wegen der hohen Temperatur T innerhalb der Blase ist die Materie dort vollkommen photodesintegriert. Das Verhältnis von Neutronen zu Protonen wird durch die Elektronenhäufigkeit Ye beschrieben. Die thermodynamische Entwicklung des Systems wird durch die Entropie S gegeben. Da die Expansion der Blase schnell vonstatten geht, kann sie als adiabatisch betrachtet werden. Die Entropie S ist dann proportional zu T^3/rho, wobei rho die Dichte darstellt. Die explizite Zeitentwicklung von T und rho sowie die Prozessdauer hängen von Vexp, der Expansionsgeschwindigkeit der Blase, ab. Der erste Teil dieser Dissertation beschäftigt sich mit dem Prozess der Reaktionen mit geladenen Teilchen, dem alpha-Prozess. Dieser Prozess endet bei Temperaturen von etwa 3 mal 10^9 K, dem sogenannten "alpha-reichen" Freezeout, wobei überwiegend alpha-Teilchen, freie Neutronen sowie ein kleiner Anteil von mittelschweren "Saat"-Kernen im Massenbereich um A=100 gebildet werden. Das Verhältnis von freien Neutronen zu Saatkernen Yn/Yseed ist entscheidend für den möglichen Ablauf eines r-Prozesses. Der zweite Teil dieser Arbeit beschäftigt sich mit dem eigentlichen r-Prozess, der bei Neutronenanzahldichten von bis zu 10^27 Neutronen pro cm^3 stattfindet, und innerhalb von maximal 400 ms sehr neutronenreiche "Progenitor"-Isotope von Elementen bis zum Thorium und Uran bildet. Bei dem sich anschliessendem Ausfrieren der Neutroneneinfangreaktionen bei 10^9 K und 10^20 Neutronen pro cm^3 erfolgt dann der beta-Rückzerfall der ursprünglichen r-Prozesskerne zum Tal der Stabilität. Diese Nicht-Gleichgewichts-Phase wird in der vorliegenden Arbeit in einer Parameterstudie eingehend untersucht. Abschliessend werden astrophysikalische Bedingungen definiert, unter denen die gesamte Verteilung der solaren r-Prozess-Isotopenhäufigkeiten reproduziert werden können.

Rod-shaped plasmonic sensors

Plasmonic nanoparticles exhibit strong light scattering efficiency due to the oscillations of their conductive electrons (plasmon), which are excited by light. For rod-shaped nanoparticles, the resonance position is highly tunable by the aspect ratio (length/width) and the sensitivity to changes in the refractive index in the local environment depends on their diameter, hence, their volume. Therefore, rod-shaped nanoparticles are highly suitable as plasmonic sensors.rnWithin this thesis, I study the formation of gold nanorods and nanorods from a gold-copper alloy using a combination of small-angle X-ray scattering and optical extinction spectroscopy. The latter represents one of the first metal alloy nanoparticle synthesis protocols for producing rod-shaped single crystalline gold-copper (AuxCu(1-x)) alloyed nanoparticles. I find that both length and width independently follow an exponential growth behavior with different time-constants, which intrinsically leads to a switch between positive and negative aspect ratio growth during the course of the synthesis. In a parameter study, I find linear relations for the rate constants as a function of [HAuCl4]/[CTAB] ratio and [HAuCl4]/[seed] ratio. Furthermore, I find a correlation of final aspect ratio and ratio of rate constants for length and width growth rate for different [AgNO3]/[HAuCl4] ratios. I identify ascorbic acid as the yield limiting species in the reaction by the use of spectroscopic monitoring and TEM. Finally, I present the use of plasmonic nanorods that absorb light at 1064nm as contrast agents for photoacoustic imaging (BMBF project Polysound). rnIn the physics part, I present my automated dark-field microscope that is capable of collecting spectra in the range of 450nm to 1750 nm. I show the characteristics of that setup for the spectra acquisition in the UV-VIS range and how I use this information to simulate measurements. I show the major noise sources of the measurements and ways to reduce the noise and how the combination of setup charactersitics and simulations of sensitivity and sensing volume can be used to select appropriate gold rods for single unlabeled protein detection. Using my setup, I show how to estimate the size of gold nano-rods directly from the plasmon linewidth measured from optical single particle spectra. Then, I use this information to reduce the distribution (between particles) of the measured plasmonic sensitivity S by 30% by correcting for the systematic error introduced from the variation in particle size. I investigate the single particle scattering of bowtie structures — structures consisting of two (mostly) equilateral triangles pointing one tip at each other. I simulate the spectra of the structures considering the oblique illumination angle in my setup, which leads to additional plasmon modes in the spectra. The simulations agree well with the measurements form a qualitative point of view.rn

Finite Element Based Nonlinear Normalization of Human Lumbar Intervertebral Disc Stiffness to Account for Its Morphology

Disc degeneration, usually associated with low back pain and changes of intervertebral stiffness, represents a major health issue. As the intervertebral disc (IVD) morphology influences its stiffness, the link between mechanical properties and degenerative grade is partially lost without an efficient normalization of the stiffness with respect to the morphology. Moreover, although the behavior of soft tissues is highly nonlinear, only linear normalization protocols have been defined so far for the disc stiffness. Thus, the aim of this work is to propose a nonlinear normalization based on finite elements (FE) simulations and evaluate its impact on the stiffness of human anatomical specimens of lumbar IVD. First, a parameter study involving simulations of biomechanical tests (compression, flexion/extension, bilateral torsion and bending) on 20 FE models of IVDs with various dimensions was carried out to evaluate the effect of the disc's geometry on its compliance and establish stiffness/morphology relations necessary to the nonlinear normalization. The computed stiffness was then normalized by height (H), cross-sectional area (CSA), polar moment of inertia (J) or moments of inertia (Ixx, Iyy) to quantify the effect of both linear and nonlinear normalizations. In the second part of the study, T1-weighted MRI images were acquired to determine H, CSA, J, Ixx and Iyy of 14 human lumbar IVDs. Based on the measured morphology and pre-established relation with stiffness, linear and nonlinear normalization routines were then applied to the compliance of the specimens for each quasi-static biomechanical test. The variability of the stiffness prior to and after normalization was assessed via coefficient of variation (CV). The FE study confirmed that larger and thinner IVDs were stiffer while the normalization strongly attenuated the effect of the disc geometry on its stiffness. Yet, notwithstanding the results of the FE study, the experimental stiffness showed consistently higher CV after normalization. Assuming that geometry and material properties affect the mechanical response, they can also compensate for one another. Therefore, the larger CV after normalization can be interpreted as a strong variability of the material properties, previously hidden by the geometry's own influence. In conclusion, a new normalization protocol for the intervertebral disc stiffness in compression, flexion, extension, bilateral torsion and bending was proposed, with the possible use of MRI and FE to acquire the discs' anatomy and determine the nonlinear relations between stiffness and morphology. Such protocol may be useful to relate the disc's mechanical properties to its degree of degeneration.

Osmotic dehydration in plant tissues

The primary aim of the thesis is to provide a comprehensive investigation of the osmotic dehydration processes in plant tissue. Effort has been concentrated on the modelling for simulating the processes. Two mathematical models for simulating the mass transfer during osmotic dehydration processes in plant tissues are developed and verified using existing experimental data. Both models are based on the mechanism of diffusion and convection of any mobile material that can transport in plant tissues. The mass balance equation for the transport of each constituent is established separately for intracellular and extra-cellular volumes with taking into account the mass transfer across the cell membrane the intracellular and extra-cellular volumes and the shrinkage of the whole tissue. The contribution from turgor pressure is considered in both models. Model two uses Darcy’s law to build the relation between shrinkage velocity and hydrostatic pressure in each volume because the plant tissue can be considered as the porous medium. Moreover, it has been extended to solve the multi-dimensional problems. A lot of efforts have been made to the parameter study and the sensitivity analyses. The parameters investigated including the concentration of the osmotic solution, diffusion coefficient, permeability of the cell membrane, elastic modulus of the cell wall, critical cell volume etc. The models allow us to quantitatively simulate the time evolution of intracellular and extra-cellular volumes as well as the time evolution of concentrations in each cross-section.

Low severity Fischer-Tropsch synthesis for the production of synthetic hydrocarbon fuels

Currently, the main source for the production of liquid transportation fuels is petroleum, the continued use of which faces many challenges including depleting oil reserves, significant oil price rises, and environmental concerns over global warming which is widely believed to be due to fossil fuel derived CO2 emissions and other greenhouse gases. In this respect, lignocellulosic or plant biomass is a particularly interesting resource as it is the only renewable source of organic carbon that can be converted into liquid transportation fuels. The gasification of biomass produces syngas which can then be converted into synthetic liquid hydrocarbon fuels by means of the Fischer-Tropsch (FT) synthesis. This process has been widely considered as an attractive option for producing clean liquid hydrocarbon fuels from biomass that have been identified as promising alternatives to conventional fossil fuels like diesel and kerosene. The resulting product composition in FT synthesis is influenced by the type of catalyst and the reaction conditions that are used in the process. One of the issues facing this conversion process is the development of a technology that can be scaled down to match the scattered nature of biomass resources, including lower operating pressures, without compromising liquid composition. The primary aims of this work were to experimentally explore FT synthesis at low pressures for the purpose of process down-scaling and cost reduction, and to investigate the potential for obtaining an intermediate FT synthetic crude liquid product that can be integrated into existing refineries under the range of process conditions employed. Two different fixed-bed micro-reactors were used for FT synthesis; a 2cm3 reactor at the University of Rio de Janeiro (UFRJ) and a 20cm3 reactor at Aston University. The experimental work firstly involved the selection of a suitable catalyst from three that were available. Secondly, a parameter study was carried out on the 20cm3 reactor using the selected catalyst to investigate the influence of reactor temperature, reactor pressure, space velocity, the H2/CO molar ratio in the feed syngas and catalyst loading on the reaction performance measured as CO conversion, catalyst stability, product distribution, product yields and liquid hydrocarbon product composition. From this parameter study a set of preferred operating conditions was identified for low pressure FT synthesis. The three catalysts were characterized using BET, XRD, TPR and SEM. The catalyst selected was an unpromoted Co/Al2O3 catalyst. FT synthesis runs on the 20cm3 reactor at Aston were conducted for 48 hours. Permanent gases and light hydrocarbons (C1-C5) were analysed in an online GC-TCD/FID at hourly intervals. The liquid hydrocarbons collected were analyzed offline using GC-MS for determination of fuel composition. The parameter study showed that CO conversion and liquid hydrocarbon yields increase with increasing reactor pressure up to around 8 bar, above which the effect of pressure is small. The parameters that had the most significant influence on CO conversion, product selectivity and liquid hydrocarbon yields were reactor temperature and catalyst loading. The preferred reaction conditions identified for this research were: T = 230ºC, P = 10 bar, H2/CO = 2.0, WHSV = 2.2 h-1, and catalyst loading = 2.0g. Operation in the low range of pressures studied resulted in low CO conversions and liquid hydrocarbon yields, indicating that low pressure BTL-FT operation may not be industrially viable as the trade off in lower CO conversions and once-through liquid hydrocarbon product yields has to be carefully weighed against the potential cost savings resulting from process operation at lower pressures.

Synthesis and characterisation of polyacrylonitrile and its derived carbon materials

Carbon is a versatile material which is composed of different allotropes, and also come in with different structures. Carbon nanofibres (CNFs) is one dimensional carbon nanomaterials, which have exhibited superior mechanical properties, great specific area, good electrical conductivity, good biocompatibility, and ease of modification. In addition to the lower cost associated to compare with carbon nanotubes (CNTs), CNFs have been attracted in numerous applications, such as reinforcement materials, filtrations, Li-ion battery, supercapacitor as well as tissue engineering, just to list a few. Therefore, it is a great deal to understand the relationship between the fabrication conditions and the characteristics of the resulted CNFs. In this project, electrospun PAN NFs were used as precursor material to fabricate carbon nanofibres. In order to produce CNFs with good morphology, the processing parameters of PAN nanofibres by electrospinning was optimized toward to the morphology at solution concentration of 12 wt%. The optimized processing parameters at given concentration were 16 kV, 14 cm and 1.5 mL/h, which led to the formation of PAN NFs with average fibre diameter of approximately 260 nm. Along with the effect of processing parameter study, the effect of concentration on the morphology was also carried out at optimized processing parameters. It was found that by increasing concentration of PAN solution from 2 to 16%, the resulted PAN transformed from beads only, to beaded fibres and finally to smooth fibres. With further increasing concentration the morphology of smooth fibres remain with increase in the fibre diameter. Electrospun PAN NFs with average fibre of 306 nm was selected to be converted into CNFs by using standard heating procedures, stabilisation in air at 280 °C and carbonization in N2. The effect of carbonization temperature ranging from 500 to 1000 °C was investigated, by using SEM, FTIR, Raman, and Impedance spectroscopy. With increasing carbonization temperature from 500 to 1000 °C, the diameter of NFs was decreased from 260 to 187, associated with loss of almost all functional groups of NFs. It was indicated by Raman results, that the graphitic crystallite size was increased from 2.62 to 5.24 nm, and the activation energy obtained for this growth was 7570 J/mol. Furthermore, impedance results (i.e. Cole-Cole plot) revealed that the electrical characteristic of CNFs transitioned from being insulating to electrically conducting in nature, suggested by the different electrical circuits extracted from Cole-Cole plots with carbonization temperature from 500 to 800 °C. The carbonization on PAN NFs with diameter of ~431nm was carried out by using novel route, microwave plasma enhance chemical vapour deposition (MPECVD) process. To compare with carbonized PAN NFs by using conventional route, MPECVD was not only able to facilitate carbonization process, but more interestingly can form carbon nanowalls (CNWs) grown on the surfaces of carbonized PAN NFs. Suggested by the unique morphology, the potential applications for the resulted carbon fibrous hybrid materials are supercapacitor electrode material, filtrations, and etc., The method developed in this project required one step less, compared with other literature. Therefore, using MPECVD on stabilised PAN NFs is proposed as economical, and straightforward approach towards mass production of carbon fibrous hybrid materials containing CNWs.

Lateral load distribution for curved steel I -girder bridges

Lateral load distribution factor is a key factor for designing and analyzing curved steel I-girder bridges. In this dissertation, the effects of various parameters on moment and shear distribution for curved steel I-girder bridges were studied using the Finite Element Method (FEM). The parameters considered in the study were: radius of curvature, girder spacing, overhang, span length, number of girders, ratio of girder stiffness to overall bridge stiffness, slab thickness, girder longitudinal stiffness, cross frame spacing, and girder torsional inertia. The variations of these parameters were based on the statistical analysis of the real bridge database, which was created by extracting data from existing or newly designed curved steel I-girder bridge plans collected all over the nation. A hypothetical bridge superstructure model that was made of all the mean values of the data was created and used for the parameter study. ^ The study showed that cross frame spacing and girder torsional inertia had negligible effects. Other parameters had been identified as key parameters. Regression analysis was conducted based on the FEM analysis results and simplified formulas for predicting positive moment, negative moment, and shear distribution factors were developed. Thirty-three real bridges were analyzed using FEM to verify the formulas. The ratio of the distribution factor obtained from the formula to the one obtained from the FEM analysis, which was referred to as the g-ratio, was examined. The results showed that the standard deviation of the g-ratios was within 0.04 to 0.06 and the mean value of the g-ratios was greater than unity by one standard deviation. This indicates that the formulas are conservative in most cases but not overly conservative. The final formulas are similar in format to the current American Association of State Highway and Transportation Officials (AASHTO) Load Resistance and Factor Design (LRFD) specifications. ^ The developed formulas were compared with other simplified methods. The outcomes showed that the proposed formulas had the most accurate results among all methods. ^ The formulas developed in this study will assist bridge engineers and researchers in predicting the actual live load distribution in horizontally curved steel I-girder bridges. ^

First principles LDA+U and GGA+U study of cerium oxides: Dependence on the effective U-parameter

The electronic structure and properties of cerium oxides (CeO2 and Ce2O3) have been studied in the framework of the LDA+U and GGA(PW91)+U implementations of density functional theory. The dependence of selected observables of these materials on the effective U parameter has been investigated in detail. The examined properties include lattice constants, bulk moduli, density of states, and formation energies of CeO2 and Ce2O3. For CeO2, the LDA+U results are in better agreement with experiment than the GGA+U results whereas for the computationally more demanding Ce2O3 both approaches give comparable accuracy. Furthermore, as expected, Ce2O3 is much more sensitive to the choice of the U value. Generally, the PW91 functional provides an optimal agreement with experiment at lower U energies than LDA does. In order to achieve a balanced description of both kinds of materials, and also of nonstoichiometric CeO2¿x phases, an appropriate choice of U is suggested for LDA+U and GGA+U schemes. Nevertheless, an optimum value appears to be property dependent, especially for Ce2O3. Optimum U values are found to be, in general, larger than values determined previously in a self-consistent way.

First principles LDA+U and GGA+U study of cerium oxides: Dependence on the effective U-parameter

The electronic structure and properties of cerium oxides (CeO2 and Ce2O3) have been studied in the framework of the LDA+U and GGA(PW91)+U implementations of density functional theory. The dependence of selected observables of these materials on the effective U parameter has been investigated in detail. The examined properties include lattice constants, bulk moduli, density of states, and formation energies of CeO2 and Ce2O3. For CeO2, the LDA+U results are in better agreement with experiment than the GGA+U results whereas for the computationally more demanding Ce2O3 both approaches give comparable accuracy. Furthermore, as expected, Ce2O3 is much more sensitive to the choice of the U value. Generally, the PW91 functional provides an optimal agreement with experiment at lower U energies than LDA does. In order to achieve a balanced description of both kinds of materials, and also of nonstoichiometric CeO2¿x phases, an appropriate choice of U is suggested for LDA+U and GGA+U schemes. Nevertheless, an optimum value appears to be property dependent, especially for Ce2O3. Optimum U values are found to be, in general, larger than values determined previously in a self-consistent way.