Identification and classification of geometrical parameeters related to foot pathologies

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Ultrafast charge-transfer in organic photovoltaic interfaces: geometrical and functionalization effects

Understanding the microscopic mechanisms of electronic excitation in organic photovoltaic cells is a challenging problem in the design of efficient devices capable of performing sunlight harvesting. Here we develop and apply an ab initio approach based on time-dependent density functional theory and Ehrenfest dynamics to investigate photoinduced charge transfer in small organic molecules. Our calculations include mixed quantum–classical dynamics with ions moving classically and electrons quantum mechanically, where no experimental external parameter other than the material geometry is required. We show that the behavior of photocarriers in zinc phthalocyanine (ZnPc) and C60 systems, an effective prototype system for organic solar cells, is sensitive to the atomic orientation of the donor and the acceptor units as well as the functionalization of covalent molecules at the interface. In particular, configurations with the ZnPc molecules facing on C60 facilitate charge transfer between substrate and molecules that occurs within 200 fs. In contrast, configurations where ZnPc is tilted above C60 present extremely low carrier injection efficiency even at longer times as an effect of the larger interfacial potential level offset and higher energetic barrier between the donor and acceptor molecules. An enhancement of charge injection into C60 at shorter times is observed as binding groups connect ZnPc and C60 in a dyad system. Our results demonstrate a promising way of designing and controlling photoinduced charge transfer on the atomic level in organic devices that would lead to efficient carrier separation and maximize device performance.

Catalytic reactions with palladium supported on mesocellular foam : Applications in hydrogenation, isomerization, and C-C bond forming reactions

The major part of this thesis concerns the development of catalytic methodologies based on palladium nanoparticles immobilized on aminopropyl-functionalized siliceous mesocellular foam (Pd0-AmP-MCF). The catalytic activity of the precursor to the nanocatalyst, PdII-AmP-MCF is also covered by this work. In the first part the application of Pd0-AmP-MCF in Suzuki-Miyaura cross-coupling reactions and transfer hydrogenation of alkenes under microwave irradiation is described. Excellent reactivity was observed and a broad range of substrates were tolerated for both transformations. The Pd0-AmP-MCF exhibited high recyclability as well as low metal leaching in both cases. The aim of the second part was to evaluate the catalytic efficiency of the closely related PdII-AmP-MCF for cycloisomerization of various acetylenic acids. The catalyst was able to promote formation of lactones under mild conditions using catalyst loadings of 0.3 - 0.5 mol% at temperatures of up to 50 oC in the presence of Et3N. By adding 1,4-benzoquinone to the reaction, the catalyst could be recycled four times without any observable decrease in the activity. The selective arylation of indoles at the C-2 position using Pd-AmP-MCF and symmetric diaryliodonium salts is presented in the third part. These studies revealed that Pd0-AmP-MCF was more effective than PdII-AmP-MCF for this transformation. Variously substituted indoles as well as diaryliodonium salts were tolerated, giving arylated indoles in high yields within 15 h at 20 - 50 oC in H2O. Only very small amounts of Pd leaching were observed and in this case the catalyst exhibited moderate recyclability. The final part of the thesis describes the selective hydrogenation of the C=C in different α,β-unsaturated systems. The double bond was efficiently hydrogenated in high yields both under batch and continuous-flow conditions. High recyclability and low metal leaching were observed in both cases.

Memory effects and geometrical considerations in open quantum systems

This thesis discusses memory effects in open quantum systems with an emphasis on the Breuer, Laine, Piilo (BLP) measure of non-Markovianity. It is shown how the calculation of the measure can be simplifed and how quantum information protocols can bene t from memory e ects. The superdense coding protocol is used as an example of this. The quantum Zeno effect will also be studied from the point of view of memory e ects. Finally the geometric ideas used in simplifying the calculation of the BLP measure are applied in studying the amount of resources needed for detecting bipartite quantum correlations. It is shown that to decide without prior information if an unknown quantum state is entangled or not, an informationally complete measurement is required. The first part of the thesis contains an introduction to the theoretical ideas such as quantum states, closed and open quantum systems and necessary mathematical tools. The theory is then applied in the second part of the thesis as the results obtained in the original publications I-VI are presented and discussed.

Geometrical measurements in three-dimensional quantum gravity

A set of observables is described for the topological quantum field theory which describes quantum gravity in three space-time dimensions with positive signature and positive cosmological constant. The simplest examples measure the distances between points, giving spectra and probabilities which have a geometrical interpretation. The observables are related to the evaluation of relativistic spin networks by a Fourier transform.

Competition and fixation of cohorts of adaptive mutations under Fisher geometrical model

One of the simplest models of adaptation to a new environment is Fisher's Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations-mutation cohorts-along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation-FGM.

Zig-zagging in geometrical reasoning in technological collaborative environments: a Mathematical Working Space-framed study concerning cognition and affect

This study highlights the importance of cognition-affect interaction pathways in the construction of mathematical knowledge. Scientific output demands further research on the conceptual structure underlying such interaction aimed at coping with the high complexity of its interpretation. The paper discusses the effectiveness of using a dynamic model such as that outlined in the Mathematical Working Spaces (MWS) framework, in order to describe the interplay between cognition and affect in the transitions from instrumental to discursive geneses in geometrical reasoning. The results based on empirical data from a teaching experiment at a middle school show that the use of dynamic geometry software favours students’ attitudinal and volitional dimensions and helps them to maintain productive affective pathways, affording greater intellectual independence in mathematical work and interaction with the context that impact learning opportunities in geometric proofs. The reflective and heuristic dimensions of teacher mediation in students’ learning is crucial in the transition from instrumental to discursive genesis and working stability in the Instrumental-Discursive plane of MWS.

Plasmon-enhanced two-photon-induced isomerization for highly-localized light-based actuation of inorganic/organic interfaces

Two-photon initiated photo-isomerization of an azobenzene moiety adsorbed on silver nanoparticles (Ag NPs) is demonstrated. The azobenzene is linked to a materials-binding peptide that brings it into intimate contact with the Ag NP surface, producing a dramatic enhancement of its two-photon absorbance. An integrated modeling approach, combining advanced conformational sampling with Quantum Mechanics/Capacitance Molecular Mechanics and response theory, shows that charge transfer and image charges in the Ag NP generate local fields that enhance two-photon absorption of the cis isomer, but not the trans isomer, of adsorbed molecules. Moreover, dramatic local field enhancement is expected near the localized surface plasmon resonance (LSPR) wavelength, and the LSPR band of the Ag NPs overlaps the azobenzene absorbance that triggers cis to trans switching. As a result, the Ag NPs enable two-photon initiated cis to trans isomerization, but not trans to cis isomerization. Confocal anti-Stokes fluorescence imaging shows that this effect is not due to local heating, while the quadratic dependence of switching rate on laser intensity is consistent with a two-photon process. Highly localized two-photon initiated switching could allow local manipulation near the focal point of a laser within a 3D nanoparticle assembly, which cannot be achieved using linear optical processes.

Geometrical Methods in Multivariate Risk Management: Algorithms and Applications

This thesis builds a framework for evaluating downside risk from multivariate data via a special class of risk measures (RM). The peculiarity of the analysis lies in getting rid of strong data distributional assumptions and in orientation towards the most critical data in risk management: those with asymmetries and heavy tails. At the same time, under typical assumptions, such as the ellipticity of the data probability distribution, the conformity with classical methods is shown. The constructed class of RM is a multivariate generalization of the coherent distortion RM, which possess valuable properties for a risk manager. The design of the framework is twofold. The first part contains new computational geometry methods for the high-dimensional data. The developed algorithms demonstrate computability of geometrical concepts used for constructing the RM. These concepts bring visuality and simplify interpretation of the RM. The second part develops models for applying the framework to actual problems. The spectrum of applications varies from robust portfolio selection up to broader spheres, such as stochastic conic optimization with risk constraints or supervised machine learning.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Regioregular poly(3-hexyl-thiophene) helical self-organization on carbon nanotubes

Mixtures of Regioregular Poly(3-hexyl-thiophene) (rrP3HT) and multi wall carbon nanotubes have been investigated by Scanning Tunneling Microscopy in Ultra High Vacuum. Carbon nanotubes covered by rrP3HT have been imaged and analyzed, providing a clear evidence that this polymer self assembles on the nanotube surface following geometrical constraints and adapting its equilibrium chain-to-chain distance. Largely spaced covered nanotubes have been analyzed to investigate the role played by nanotube chirality in the polymer wrapping, evidencing strong rrP3HT interactions along well defined directions.