Tropfenbasierte Multiphasen – Mikroreaktionstechnologie in organisch-chemischer Synthese

In der vorliegenden Doktorarbeit werden neue, mikrofluidische Verfahren, zur Durchführung chemischer Reaktionen in mehrphasigen Systemen präsentiert. rnDas Einschließen von Reaktionspartnern in einzelne Segmente, deren Volumina im Bereich von Mikro- bis Femtoliter liegen und die dadurch erzeugten enormen, spezifischen Oberflächen, ermöglichen Massentransportprozesse über die Phasengrenzfläche zwischen einzelnen Segmenten, drastisch zu intensivieren. Aufgrund geringer räumlicher Ausdehnungen einzelner Kompartimente und durch vorherrschende, zirkulierende Strömungen in den einzelnen Abschnitten, sind Diffusions- und Konvektionsprozesse in diesen rasch, sodass an der Grenzfläche gebildete, reaktive Intermediate in sehr kurzen Zeitintervallen umgesetzt werden können. rnrn

Quantifying The Diffusion And Erosion Of Degradable Hydrogels Using A Microfluidic Technique

Hydrogels are composed of cross-linked networks of hydrophilic polymers that are biocompatible due to their high water content. Mass transfer through hydrogels has been suggested as an effective method of drug delivery, specifically in degradable polymers to minimize lasting effects within the body. Diffusion of small molecules in poly (ethylene glycol) diacrylate (PEG-DA) and dextran methacrylate (dex-MA) hydrogels was characterized in a microfluidic device and by complementary techniques. Microfluidic devices were prepared by crosslinking a formulation of hydrogel and photo-initiator, with and without visible dye, using photolithography to define a central microchannel. Channel sizes within the devices were approximately 600 ¿m to simulate vessels within the body. The microfluidic technique allows for both image and effluent analyses. To visualize the diffusive behavior within the dextran hydrogel, methylene blue and sulforhodamine 101 dyes were used in both elution and uptake experiments. Three analysis techniques for measuring diffusion coefficients were used to quantify the diffusion of solute in the hydrogel, including optical microscopy, characterization of device effluent, and NMR analyses. The optical microscopy technique analyzes images of the dye diffusion captured by a stereomicroscope to generate dye concentration v. position profiles. The data was fit to a diffusion model to determine diffusion coefficients and the dye release profile. In a typical elution experiment, aqueous solution is pumped through the microchannel and dye diffuses out of the hydrogel and into the aqueous phase. During elution, images are taken at regular time intervals and the effluent was collected. Analysis of the device effluent was performed using ultraviolet-visible (UV/Vis) spectroscopy to determine the effluent dye concentration and thus a short-time diffusion coefficient. Nuclear magnetic resonance (NMR) was used to determine a free diffusion coefficient of molecules in hydrogel without the effect of a concentration gradient. Diffusion coefficients for methylene blue and sulforhodamine 101 dyes in dex-MA hydrogel calculated using the three analysis methods all agree well. It was determined that utilizing a combination of the three techniques offers greater insight into molecular diffusion in hydrogels than employing each technique individually. The use of the same microfluidic devices used to measure diffusion is explored in the use of studying the degradation of dex-MA hydrogels. By combining what is known about the degradation rate in regards to the effect of pH and crosslinking and the ability to use a dye solution in contrast to establish the hydrogel boundaries could be a novel approach to studying hydrogel degradation.

Anelastic strain recovery and elastic properties of ODP Leg 123 oceanic basalt samples

A knowledge of rock stress is fundamental for improving our understanding of oceanic crustal mechanisms and lithospheric dynamic processes. However, direct measurements of stress in the deep oceans, and in particular stress magnitudes, have proved to be technically difficult. Anelastic strain recovery measurements were conducted on 15 basalt core samples from Sites 765 and 766 during Leg 123. Three sets of experiments were performed: anelastic strain recovery monitoring, dynamic elastic property measurements, and thermal azimuthal anisotropy observations. In addition, a range of other tests and observations were recorded to characterize each of the samples. One common feature of the experimental results and observations is that apparently no consistent orientation trend exists, either between the different measurements on each core sample or between the same sets of measurements on the various core samples. However, some evidence of correspondence between velocity anisotropy and anelastic strain recovery exists, but this is not consistent for all the core samples investigated. Thermal azimuthal anisotropy observations, although showing no conclusive correlations with the other results, were of significant interest in that they clearly exhibited anisotropic behavior. The apparent reproducibility of this behavior may point toward the possibility of rocks that retain a "memory" of their stress history, which could be exploited to derive stress orientations from archived core. Anelastic strain recovery is a relatively new technique. Because use of the method has extended to a wider range of rock types, the literature has begun to include examples of rocks that contracted with time. Strong circumstantial evidence exists to suggest that core-sample contractions result from the slow diffusion of pore fluids from a preexisting microcrack structure that permits the rock to deflate at a greater rate than the expansion caused by anelastic strain recovery. Both expansions and contractions of the Leg 123 cores were observed. The basalt cores have clearly been intersected by an abundance of preexisting fractures, some of which pass right through the samples, but many are intercepted or terminate within the rock matrix. Thus, the behavior of the core samples will be influenced not only by the properties of the rock matrix between the fractures, but also by how these macro- and micro-scale fractures mutually interact. The strain-recovery curves recorded during Leg 123 for each of the 15 basalt core samples may reflect the result of two competing time dependent processes: anelastic strain recovery and pore pressure recovery. Were these the only two processes to influence the gauge responses, then one might expect that given the additional information required, established theoretical models might be used to determine consistent stress orientations and reliable stress magnitudes. However, superimposed upon these competing processes is their respective interaction with the preexisting fractures that intersect each core. Evidence from our experiments and observations suggests that these fractures have a dominating influence on the characteristics of the recovery curves and that their effects are complex.

First results from stable-istope measurements on ice cores from Dronning Maud Land

The European Project for Ice Coring in Antarctica (EPICA) focuses on the drilling of two deep ice cores, the first at Dome C and the second at Kohnen station (75°00' S, 0°04' E) in Dronning Maud Land (DML). This paper deals with stable-isotope records from ice cores drilled in DML. In the first season, the deep EPICA DML core reached a depth of 450 m, recovering ice approximately 7000 years old. Generally, the d18O record indicates a stable Holocene climate and shows low variability. However, during the last 4000 years (based on a preliminary time-scale) the d18O values decrease continuously by about 0.6%, and the deuterium excess values increase by about 0.5%. The correlation between d18O and the deuterium excess d is investigated for a 50m long core section and the near-surface snow. High-pass filtered profiles are positively correlated, whereas the correlation between low-pass filtered profiles is negative. A post-depositional effect due to diffusion processes can be seen in a sub-annually resolved profile from snow-pit samples. Changes in the seasonality of the evolution of the snow cover and the consequences for stable-isotope content are demonstrated with data from ice core B31.

The rise and fall in the price of food, fuel and manufactured goods : interdependency between prices and technology determining comparative advantages and development paths

Green innovation, which enables us to extract energy from food crops, caused a food shortage in 2008. Countries suffering severe damage started to reconsider their agricultural policy with the aim of becoming more autonomous. The food price hike of the time looks like a reversal of the celebrated Singer-Prebisch thesis proposed in the 1950s. This paper examines the consequences of this trend on the comparative advantages and development strategies of developing countries. For that purpose, first, trends and short-run fluctuations in the prices of fuel and bio-energy crops are investigated. It is shown that the price series of fuels and the crops are synchronized only after the fuel extracting technology came into effect. Second, the reversal of the Singer-Prebisch thesis is underpinned by the generic form of an endogenous growth model developed by Rebelo (1991). It is shown that as an economy grows, appreciation of the non-reproducible, such as mineral resources and raw labor, over the reproducible, such as capital goods, is the norm rather than an anomaly. Third, the consequences of the food price hike and underlying capital accumulation on the development strategies of labor-abundant and low-income countries are explored. It is concluded that the impact of the food price hikes on the alteration of a development strategy is only incremental, without reinforcement from raw-labor-saving innovation. A case study of inventions by JUKI Corporation, a world-leader in the sewing machine market exemplifies the fact that, of all the major inventions the company have made, raw-labor-saving inventions have not dominated, although JUKI's machines are sold to one of the most raw-labor-intensive industries.

Diffusion of Zn into GaAs and AlGaAs from isothermal Liquid-phase epitaxy solutions

In this work we present results of zinc diffusion in GaAs using the liquid phase epitaxy technique from liquid solutions of Ga‐As‐Zn and Ga‐As‐Al‐Zn. Using silicon‐doped n‐GaAs substrates, working at a diffusion temperature of 850 °C, and introducing a dopant concentration ranging 1018–1019 cm−3, the most important findings regarding the diffusion properties are as follows: (a) zinc concentration in the solid depends on the square root of zinc atomic fraction in the liquid; (b) the diffusion is dominated by the interstitial‐substitutional process; (c) the diffusivity D varies as about C3 in the form D=2.9×10−67C3.05; (d) aluminum plays the role of the catalyst of the diffusion process, if it is introduced in the liquid solution, since it is found that D varies as (γAsXlAs)−1; (e) the zinc interstitial is mainly doubly ionized (Zn++i); (f) the zinc diffusion coefficient in Al0.85 Ga0.15 As is about four times greater than in GaAs; (g) by means of all these results, it is possible to control zinc diffusion processes in order to obtain optimized depth junctions and doping levels in semiconductor device fabrication.

Lifetime improvement after phosphorous diffusion gettering on upgraded metallurgical grade silicon

Wide experimental evidence of the phosphorus diffusion gettering beneficial effect on solar grade silicon is found by measuring electron effective lifetime and interstitial iron concentration in as-grown and post processed samples from two ingots of upgraded metallurgical grade silicon produced by Ferrosolar. Results after two different P-diffusion processes are compared: P emitter diffusion at 850ºC followed by fast cool-down (called “standard process”) or followed by slow cool-down (called “extended process”). It is shown that final lifetimes of this low cost material are in the range of those obtained with conventional material. The extended process can be beneficial for wafers with specific initial distribution and concentration of iron, e.g. materials with high concentration of big Fe precipitates, while for other cases the standard process is enough efficient. An analysis based on the comparison of measured lifetime and dissolved iron concentration with theoretical calculations helps to infer the initial iron distribution and concentration, and according to that, choose the more effective type of gettering.

Effects of adsorbed phase on diffusion of subcritical hydrocarbons in activated carbon at low pressures

Diffusions of free and adsorbed molecules of subcritical hydrocarbons in activated carbon were investigated to study the influence of adsorbed molecules on both diffusion processes at low pressures. A collision reflection factor, defined as the fraction of molecules undergoing collision to the solid surface over reflection from the surface, is incorporated into Knudsen diffusivity and surface diffusivity in meso/macropores. Since the porous structure of activated carbon is bimodal in nature, the diffusion of adsorbed molecules is contributed by that of weakly adsorbed molecules on the meso/macropore surfaces and that of strongly adsorbed molecules in the small confinement of micropores. The mobility of adsorbed molecules on the meso/macropore surface is characterized by the surface diffusivity D-mu 2, while that in the micropore is characterized by D-mu 1. In our study with subcritical hydrocarbons, we have found that the former increases almost linearly with pressure, while the latter exhibits a sharp increase at a very low-pressure region and then decreases beyond a critical pressure. This critical pressure is identified as a pressure at which the micropores are saturated.

A scalarization technique for computing the power and exponential moments of gaussian random matrices

We consider the problems of computing the power and exponential moments EXs and EetX of square Gaussian random matrices X=A+BWC for positive integer s and real t, where W is a standard normal random vector and A, B, C are appropriately dimensioned constant matrices. We solve the problems by a matrix product scalarization technique and interpret the solutions in system-theoretic terms. The results of the paper are applicable to Bayesian prediction in multivariate autoregressive time series and mean-reverting diffusion processes.

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Ionic and molecular diffusion in cementitious materials

The work described in this thesis is an attempt to provide improved understanding of the effects of several factors affecting diffusion in hydrated cement pastes and to aid the prediction of ionic diffusion processes in cement-based materials. Effect of pore structure on diffusion was examined by means of comparative diffusion studies of quaternary ammonium ions with different ionic radii. Diffusivities of these ions in hydrated pastes of ordinary portland cement with or without addition of fly ash were determined by a quasi-steady state technique. The restriction of the pore geometry on diffusion was evaluated from the change of diffusivity in response to the change of ionic radius. The pastes were prepared at three water-cement ratios, 0.35, 0.50 and 0.65. Attempts were made to study the effect of surface charge or the electrochemical double layer at the pore/solution interface on ionic diffusion. An approach was to evaluate the zeta potentials of hydrated cement pastes through streaming potential measurements. Another approach was the comparative studies of the diffusion kinetics of chloride and dissolved oxygen in hydrated pastes of ordinary portland cement with addition of 0 and 20% fly ash. An electrochemical technique for the determination of oxygen diffusivity was also developed. Non-steady state diffusion of sodium potassium, chloride and hydroxyl ions in hydrated ordinary portland cement paste of water-cement ratio 0.5 was studied with the aid of computer-modelling. The kinetics of both diffusion and ionic binding were considered for the characterization of the concentration profiles by Fick's first and second laws. The effect of the electrostatic interactions between ions on the overall diffusion rates was also considered. A general model concerning the prediction of ionic diffusion processes in cement-based materials has been proposed.

Opinion leaders' role in innovation diffusion:a simulation study

This study investigates the critical role that opinion leaders (or influentials) play in the adoption process of new products. Recent existing reseach evidence indicates a limited effect of opinion leaders on diffusion processes, yet these studies take into account merely the network position of opinion leaders without addressing their influential power. Empirical findings of our study show that opinion leaders, in addition to having a more central network position, possess more accurate knowledge about a product and tend to be less susceptible to norms and more innovative. Experiments that address these attributes, using an agent-based model, demonstrate that opinion leaders increase the speed of the information stream and the adoption process itself. Furthermore, they increase the maximum adoption percentage. These results indicate that targeting opinion leaders remains a valuable marketing strategy.

Functional Transfer Theorems for Maxima of Stationary Processes

2000 Mathematics Subject Classification: 60G70, 60F12, 60G10.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.

Latent Space and Social Psychological Models of Diffusion

The problem of social diffusion has animated sociological thinking on topics ranging from the spread of an idea, an innovation or a disease, to the foundations of collective behavior and political polarization. While network diffusion has been a productive metaphor, the reality of diffusion processes is often muddier. Ideas and innovations diffuse differently from diseases, but, with a few exceptions, the diffusion of ideas and innovations has been modeled under the same assumptions as the diffusion of disease. In this dissertation, I develop two new diffusion models for "socially meaningful" contagions that address two of the most significant problems with current diffusion models: (1) that contagions can only spread along observed ties, and (2) that contagions do not change as they spread between people. I augment insights from these statistical and simulation models with an analysis of an empirical case of diffusion - the use of enterprise collaboration software in a large technology company. I focus the empirical study on when people abandon innovations, a crucial, and understudied aspect of the diffusion of innovations. Using timestamped posts, I analyze when people abandon software to a high degree of detail.

To address the first problem, I suggest a latent space diffusion model. Rather than treating ties as stable conduits for information, the latent space diffusion model treats ties as random draws from an underlying social space, and simulates diffusion over the social space. Theoretically, the social space model integrates both actor ties and attributes simultaneously in a single social plane, while incorporating schemas into diffusion processes gives an explicit form to the reciprocal influences that cognition and social environment have on each other. Practically, the latent space diffusion model produces statistically consistent diffusion estimates where using the network alone does not, and the diffusion with schemas model shows that introducing some cognitive processing into diffusion processes changes the rate and ultimate distribution of the spreading information. To address the second problem, I suggest a diffusion model with schemas. Rather than treating information as though it is spread without changes, the schema diffusion model allows people to modify information they receive to fit an underlying mental model of the information before they pass the information to others. Combining the latent space models with a schema notion for actors improves our models for social diffusion both theoretically and practically.

The empirical case study focuses on how the changing value of an innovation, introduced by the innovations' network externalities, influences when people abandon the innovation. In it, I find that people are least likely to abandon an innovation when other people in their neighborhood currently use the software as well. The effect is particularly pronounced for supervisors' current use and number of supervisory team members who currently use the software. This case study not only points to an important process in the diffusion of innovation, but also suggests a new approach -- computerized collaboration systems -- to collecting and analyzing data on organizational processes.