Charge-transport simulations in organic semiconductors

In this thesis we have extended the methods for microscopic charge-transport simulations for organic semiconductors. In these materials the weak intermolecular interactions lead to spatially localized charge carriers, and the charge transport occurs as an activated hopping process between diabatic states. In addition to weak electronic couplings between these states, different electrostatic environments in the organic material lead to a broadening of the density of states for the charge energies which limits carrier mobilities.rnThe contributions to the method development includern(i) the derivation of a bimolecular charge-transfer rate,rn(ii) the efficient evaluation of intermolecular (outer-sphere) reorganization energies,rn(iii) the investigation of effects of conformational disorder on intramolecular reorganization energies or internal site energiesrnand (iv) the inclusion of self-consistent polarization interactions for calculation of charge energies.These methods were applied to study charge transport in amorphous phases of small molecules used in the emission layer of organic light emitting diodes (OLED).rnWhen bulky substituents are attached to an aromatic core in order to adjust energy levels or prevent crystallization, a small amount of delocalization of the frontier orbital to the substituents can increase electronic couplings between neighboring molecules. This leads to improved charge-transfer rates and, hence, larger charge-mobility. We therefore suggest using the mesomeric effect (as opposed to the inductive effect) when attaching substituents to aromatic cores, which is necessary for example in deep blue OLEDs, where the energy levels of a host molecule have to be adjusted to those of the emitter.rnFurthermore, the energy landscape for charges in an amorphous phase cannot be predicted by mesoscopic models because they approximate the realistic morphology by a lattice and represent molecular charge distributions in a multipole expansion. The microscopic approach shows that a polarization-induced stabilization of a molecule in its charged and neutral states can lead to large shifts, broadening, and traps in the distribution of charge energies. These results are especially important for multi-component systems (the emission layer of an OLED or the donor-acceptor interface of an organic solar cell), if the change in polarizability upon charging (or excitation in case of energy transport) is different for the components. Thus, the polarizability change upon charging or excitation should be added to the set of molecular parameters essential for understanding charge and energy transport in organic semiconductors.rnWe also studied charge transport in self-assembled systems, where intermolecular packing motives induced by side chains can increase electronic couplings between molecules. This leads to larger charge mobility, which is essential to improve devices such as organic field effect transistors, where low carrier mobilities limit the switching frequency.rnHowever, it is not sufficient to match the average local molecular order induced by the sidernchains (such as the pitch angle between consecutive molecules in a discotic mesophase) with maxima of the electronic couplings.rnIt is also important to make the corresponding distributions as narrow as possible compared to the window determined by the closest minima of thernelectronic couplings. This is especially important in one-dimensional systems, where charge transport is limited by the smallest electronic couplings.rnThe immediate implication for compound design is that the side chains should assist the self-assemblingrnprocess not only via soft entropic interactions, but also via stronger specific interactions, such as hydrogen bonding.rnrnrnrn

Computer simulations of colloidal fluids in confinement

Computer-Simulationen von Kolloidalen Fluiden in Beschränkten Geometrien Kolloidale Suspensionen, die einen Phasenübergang aufweisen, zeigen eine Vielfalt an interessanten Effekten, sobald sie auf eine bestimmte Geometrie beschränkt werden, wie zum Beispiel auf zylindrische Poren, sphärische Hohlräume oder auf einen Spalt mit ebenen Wänden. Der Einfluss dieser verschiedenen Geometrietypen sowohl auf das Phasenverhalten als auch auf die Dynamik von Kolloid-Polymer-Mischungen wird mit Hilfe von Computer-Simulationen unter Verwendung des Asakura-Oosawa- Modells, für welches auf Grund der “Depletion”-Kräfte ein Phasenübergang existiert, untersucht. Im Fall von zylindrischen Poren sieht man ein interessantes Phasenverhalten, welches vom eindimensionalen Charakter des Systems hervorgerufen wird. In einer kurzen Pore findet man im Bereich des Phasendiagramms, in dem das System typischerweise entmischt, entweder eine polymerreiche oder eine kolloidreiche Phase vor. Sobald aber die Länge der zylindrischen Pore die typische Korrelationslänge entlang der Zylinderachse überschreitet, bilden sich mehrere quasi-eindimensionale Bereiche der polymerreichen und der kolloidreichen Phase, welche von nun an koexistieren. Diese Untersuchungen helfen das Verhalten von Adsorptionshysteresekurven in entsprechenden Experimenten zu erklären. Wenn das Kolloid-Polymer-Modellsystem auf einen sphärischen Hohlraum eingeschränkt wird, verschiebt sich der Punkt des Phasenübergangs von der polymerreichen zur kolloidreichen Phase. Es wird gezeigt, dass diese Verschiebung direkt von den Benetzungseigenschaften des Systems abhängt, was die Beobachtung von zwei verschiedenen Morphologien bei Phasenkoexistenz ermöglicht – Schalenstrukturen und Strukturen des Janustyps. Im Rahmen der Untersuchung von heterogener Keimbildung von Kristallen innerhalb einer Flüssigkeit wird eine neue Simulationsmethode zur Berechnung von Freien Energien der Grenzfläche zwischen Kristall- bzw. Flüssigkeitsphase undWand präsentiert. Die Resultate für ein System von harten Kugeln und ein System einer Kolloid- Polymer-Mischung werden anschließend zur Bestimmung von Kontaktwinkeln von Kristallkeimen an Wänden verwendet. Die Dynamik der Phasenseparation eines quasi-zweidimensionalen Systems, welche sich nach einem Quench des Systems aus dem homogenen Zustand in den entmischten Zustand ausbildet, wird mit Hilfe von einer mesoskaligen Simulationsmethode (“Multi Particle Collision Dynamics”) untersucht, die sich für eine detaillierte Untersuchung des Einflusses der hydrodynamischen Wechselwirkung eignet. Die Exponenten universeller Potenzgesetze, die das Wachstum der mittleren Domänengröße beschreiben, welche für rein zwei- bzw. dreidimensionale Systeme bekannt sind, können für bestimmte Parameterbereiche nachgewiesen werden. Die unterschiedliche Dynamik senkrecht bzw. parallel zu den Wänden sowie der Einfluss der Randbedingungen für das Lösungsmittel werden untersucht. Es wird gezeigt, dass die daraus resultierende Abschirmung der hydrodynamischen Wechselwirkungsreichweite starke Auswirkungen auf das Wachstum der mittleren Domänengröße hat.

Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Equality and Diversity in the Dutch Welfare State

Under the Constitution, the equality principle is very important in the Netherlands. This article argues that there is little evidence for equal citizenship in the Netherlands. There is anti-discrimination legislation in the Netherlands, but it is not very robust. The core argument in this article is that the equality principle must be supplemented by the diversity principle. Diversity is multi-dimensional and can refer to religion, philosophy of life, political persuasion, race (ethnicity), gender, nationality, sexual orientation, age, disability and chronic illness. In this paper multi-culturalism and disability are taken into account and we make a comparison of the social position of disabled people and people from ethnic minorities. Policies on diversity are needed to arrive at diverse citizenship in a varied society. This implies that a distinction has to be made between political citizenship and cultural citizenship. The former has to do with equality, and the latter with diversity.

Control concept for autonomous changeable material flow systems

Today’s material flow systems for mass customization or dynamic productions are usually realized with manual transportation systems. However new concepts in the domain of material flow and device control like function-oriented modularization and intelligent multi-agent-systems offer the possibility to employ changeable and automated material flow systems in dynamic production structures. These systems need the ability to react on unplanned and unexpected events autonomously.

The Interplay of Power and Trust in Platform Ecosystems of the Enterprise Application Software Industry

In recent years, the formerly oligopolistic Enterprise Application Software (EAS) industry began to disintegrate into focal inter-firm networks with one huge, powerful, and multi-national plat-form vendor as the center, surrounded by hundreds or even thousands of small, niche players that act as complementors. From a theoretical point of view, these platform ecosystems may be governed by two organizing principles - trust and power. However, it is neither from a practical nor from a theoretical perspective clear, how trust and power relate to each other, i.e. whether they act as complements or substitutes. This study tries to elaborate our understanding of the relationship of trust and power by exploring their interplay using multi-dimensional conceptual-izations of trust and power, and by investigating potential dynamics in this interplay over the course of a partnership. Based on an exploratory multiple-case study of seven dyadic partner-ships between four platform vendors, and seven complementors, we find six different patterns of how trust and power interact over time. These patterns bear important implications for the suc-cessful management of partnerships between platform vendors and complementors, and clarify the theoretical debate surrounding the relationship of trust and power.

Guaranteed greedy routing in overlay networks

Greedy routing can be used in mobile ad-hoc networks as geographic routing protocol. This paper proposes to use greedy routing also in overlay networks by positioning overlay nodes into a multi-dimensional Euclidean space. Greedy routing can only be applied when a routing decision makes progress towards the final destination. Our proposed overlay network is built such that there will be always progress at each forwarding node. This is achieved by constructing at each node a so-called nearest neighbor convex set (NNCS). NNCSs can be used for various applications such as multicast routing, service discovery and Quality-of-Service routing. NNCS has been compared with Pastry, another topology-aware overlay network. NNCS has superior relative path stretches indicating the optimality of a path.

A new measure for party coherence: Applying a physics-based concept to the Swiss party system

The paper revives a theoretical definition of party coherence as being composed of two basic elements, cohesion and factionalism, to propose and apply a novel empirical measure based on spin physics. The simultaneous analysis of both components using a single measurement concept is applied to data representing the political beliefs of candidates in the Swiss general elections of 2003 and 2007, proposing a connection between the coherence of the beliefs party members hold and the assessment of parties being at risk of splitting. We also compare our measure with established polarization measures and demonstrate its advantage with respect to multi-dimensional data that lack clear structure. Furthermore, we outline how our analysis supports the distinction between bottom-up and top-down mechanisms of party splitting. In this way, we are able to turn the intuition of coherence into a defined quantitative concept that, additionally, offers a methodological basis for comparative research of party coherence. Our work serves as an example of how a complex systems approach allows to get a new perspective on a long-standing issue in political science.

Self, writing and feminine transactions in Virginia Woolf's Orlando and Clarice Lispector’s The stream of life

Este artículo realiza un acercamiento a Orlando, de Virginia Woolf, y a Agua viva, de Clarice Lispector, como obras que logran escribir la multiplicidad, la fluidez y la contingencia del ser. Jugando con las convenciones de la biografía y la autobiografía respectivamente, estas obras encuentran los medios para presentar un sujeto multidimensional y para mostrar, en particular, cómo la dimensión relacional, forjada por un orden simbólico patriarcal, ha hecho de la mujer el “otro" del hombre; un “otro" que debe ser dominado. Se exploran en este artículo los conceptos de “economía masculina" y “economía femenina" teorizados por Hélène Cixous y se propone al lenguaje poético como un medio capaz de eludir los dictados del falocentrismo. Lo poético, que no puede ser nunca agotado por uno o varios sistemas de significación, brinda la posibilidad de ir más allá de las categorizaciones y de explorar la multiplicidad. Tanto Orlando como Agua viva muestran las estrategias y las esperanzas de personajes y escritoras que ven en el lenguaje poético, en la “escritura femenina" como la entiende Cixous, el potencial de desarticular la “economía masculina" y abrir un nuevo espacio para sujetos diversos, múltiples y complejos.

Estimación de la Reflectividad del Multitrayecto en Entornos Urbanos en Radares de Apertura Sintética

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range. SAR synthesizes a large aperture radar in order to achieve finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, today¿s new scenes force SAR systems to work in urban environments. Consequently, multiple-bounce returns are added to direct-scatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor resolution. By analyzing the quadratic phase error (QPE), this paper demonstrates that Earth¿s curvature influences the defocusing degree of multipath returns. In addition to the QPE, other parameters such as integrated sidelobe ratio (ISLR), peak sidelobe ratio (PSLR), contrast and entropy provide us with the tools to identify direct-scatter echoes in images containing undesired returns coming from multipath.

Multipath Reflectivity Estimation in Urban Environments for Synthetic Aperture Radar Images

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range. SAR synthesizes a large aperture radar in order to achieve a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, today¿s new scenes force SAR systems to work in urban environments. Consequently, multiple-bounce returns are added to directscatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor resolution. By analyzing the quadratic phase error (QPE), this paper demonstrates that Earth¿s curvature influences the defocusing degree of multipath returns. In addition to the QPE, other parameters such as integrated sidelobe ratio (ISLR), peak sidelobe ratio (PSLR), contrast (C) and entropy (E) provide us with the tools to identify direct-scatter echoes in images containing undesired returns coming from multipath.

New Technique for Static Target Detection in Dense-Multipath Urban Environments

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range with a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, new uses of Unmanned Aerial Vehicles (UAVs) for civilian-security applications force SAR systems to work in much more complex scenes such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. They are known as ghost images, since they obscure true target image and lead to poor resolution. All this may involve a significant problem in applications related to surveillance and security. In this work, an innovative multipath mitigation technique is presented in which Time Reversal (TR) concept is applied to SAR images when the target is concealed in clutter, leading to TR-SAR technique. This way, the effect of multipath is considerably reduced ?or even removed?, recovering the lost resolution due to multipath propagation. Furthermore, some focusing indicators such as entropy (E), contrast (C) and Rényi entropy (RE) provide us with a good focusing criterion when using TR-SAR.

Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.

Regularized model learning in EDAs for continuous and multi-objective optimization

Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.