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In this chapter we review the basic principles of photocurrent generation in bulk heterojunction organic solar cells, discuss the loss channels limiting their efficiency, and present case studies of several polymer-fullerene blends. Using steady-state and transient, optical, and electrooptical techniques, we create a precise picture of the fundamental processes that ultimately govern solar cell efficiency.
This thesis discusses heat and charge transport phenomena in single-crystalline Silicon penetrated by nanometer-sized pores, known as mesoporous Silicon (pSi). Despite the extensive attention given to it as a thermoelectric material of interest, studies on microscopic thermal and electronic transport beyond its macroscopic characterizations are rarely reported. In contrast, this work reports the interplay of both.
PSi samples synthesized by electrochemical anodization display a temperature dependence of specific heat 𝐶𝑝 that deviates from the characteristic 𝑇^3 behaviour (at 𝑇<50𝐾). A thorough analysis reveals that both 3D and 2D Einstein and Debye modes contribute to this specific heat. Additional 2D Einstein modes (~3 𝑚𝑒𝑉) agree reasonably well with the boson peak of SiO2 in pSi pore walls. 2D Debye modes are proposed to account for surface acoustic modes causing a significant deviation from the well-known 𝑇^3 dependence of 𝐶𝑝 at 𝑇<50𝐾.
A novel theoretical model gives insights into the thermal conductivity of pSi in terms of porosity and phonon scattering on the nanoscale. The thermal conductivity analysis utilizes the peculiarities of the pSi phonon dispersion probed by the inelastic neutron scattering experiments. A phonon mean-free path of around 10 𝑛𝑚 extracted from the presented model is proposed to cause the reduced thermal conductivity of pSi by two orders of magnitude compared to p-doped bulk Silicon. Detailed analysis indicates that compound averaging may cause a further 10-50% reduction. The percolation threshold of 65% for thermal conductivity of pSi samples is subsequently determined by employing theoretical effective medium models.
Temperature-dependent electrical conductivity measurements reveal a thermally activated transport process. A detailed analysis of the activation energy 𝐸𝐴𝜎 in the thermally activated transport exhibits a Meyer Neldel compensation rule between different samples that originates in multi-phonon absorption upon carrier transport. Activation energies 𝐸𝐴𝑆 obtained from temperature-dependent thermopower measurements provide further evidence for multi-phonon assisted hopping between localized states as a dominant charge transport mechanism in pSi, as they systematically differ from the determined 𝐸𝐴𝜎 values.
Auf der Grundlage von Sonnenphotometermessungen an drei Messstationen (AWIPEV/ Koldewey in Ny-Ålesund (78.923 °N, 11.923 °O) 1995–2008, 35. Nordpol Driftstation – NP-35 (84.3–85.5 °N, 41.7–56.6 °O) März/April 2008, Sodankylä (67.37 °N, 26.65 °O) 2004–2007) wird die Aerosolvariabilität in der europäischen Arktis und deren Ursachen untersucht. Der Schwerpunkt liegt dabei auf der Frage des Zusammenhanges zwischen den an den Stationen gemessenen Aerosolparametern (Aerosol optische Dicke, Angström Koeffizient, usw.) und dem Transport des Aerosols sowohl auf kurzen Zeitskalen (Tagen) als auch auf langen Zeitskalen (Monate, Jahre). Um diesen Zusammenhang herzustellen, werden für die kurzen Zeitskalen mit dem Trajektorienmodell PEP-Tracer 5-Tage Rückwärtstrajektorien in drei Starthöhen (850 hPa, 700 hPa, 500 hPa) für die Uhrzeiten 00, 06, 12 und 18 Uhr berechnet. Mit Hilfe der nicht-hierarchischen Clustermethode k-means werden die berechneten Rückwärtstrajektorien dann zu Gruppen zusammengefasst und bestimmten Quellgebieten und den gemessenen Aerosol optischen Dicken zugeordnet. Die Zuordnung von Aerosol optischer Dicke und Quellregion ergibt keinen eindeutigen Zusammenhang zwischen dem Transport verschmutzter Luftmassen aus Europa oder Russland bzw. Asien und erhöhter Aerosol optischer Dicke. Dennoch ist für einen konkreten Einzelfall (März 2008) ein direkter Zusammenhang von Aerosoltransport und hohen Aerosol optischen Dicken nachweisbar. In diesem Fall gelangte Waldbrandaerosol aus Südwestrussland in die Arktis und konnte sowohl auf der NP-35 als auch in Ny-Ålesund beobachtet werden. In einem weiteren Schritt wird mit Hilfe der EOF-Analyse untersucht, inwieweit großskalige atmosphärische Zirkulationsmuster für die Aerosolvariabilität in der europäischen Arktis verantwortlich sind. Ähnlich wie bei der Trajektorienanalyse ist auch die Verbindung der atmosphärischen Zirkulation zu den Photometermessungen an den Stationen in der Regel nur schwach ausgeprägt. Eine Ausnahme findet sich bei der Betrachtung des Jahresganges des Bodendruckes und der Aerosol optischen Dicke. Hohe Aerosol optische Dicken treten im Frühjahr zum einen dann auf, wenn durch das Islandtief und das sibirische Hochdruckgebiet Luftmassen aus Europa oder Russland/Asien in die Arktis gelangen, und zum anderen, wenn sich ein kräftiges Hochdruckgebiet über Grönland und weiten Teilen der Arktis befindet. Ebenso zeigt sich, dass der Übergang zwischen Frühjahr und Sommer zumindest teilweise bedingt ist durch denWechsel vom stabilen Polarhoch im Winter und Frühjahr zu einer stärker von Tiefdruckgebieten bestimmten arktischen Atmosphäre im Sommer. Die geringere Aerosolkonzentration im Sommer kann zum Teil mit einer Zunahme der nassen Deposition als Aerosolsenke begründet werden. Für Ny-Ålesund wird neben den Transportmustern auch die chemische Zusammensetzung des Aerosols mit Hilfe von Impaktormessungen an der Zeppelinstation auf dem Zeppelinberg (474m ü.NN) nahe Ny-Ålesund abgeleitet. Dabei ist die positive Korrelation der Aerosoloptischen Dicke mit der Konzentration von Sulfationen und Ruß sehr deutlich. Beide Stoffe gelangen zu einem Großteil durch anthropogene Emissionen in die Atmosphäre. Die damit nachweisbar anthropogen geprägte Zusammensetzung des arktischen Aerosols steht im Widerspruch zum nicht eindeutig herstellbaren Zusammenhang mit dem Transport des Aerosols aus Industrieregionen. Dies kann nur durch einen oder mehrere gleichzeitig stattfindende Transformationsprozesse (z. B. Nukleation von Schwefelsäurepartikeln) während des Transportes aus den Quellregionen (Europa, Russland) erklärt werden.
Over the past decades, there has been a growing interest in ‘extreme events’ owing to the increasing threats that climate-related extremes such as floods, heatwaves, droughts, etc., pose to society. While extreme events have diverse definitions across various disciplines, ranging from earth science to neuroscience, they are characterized mainly as dynamic occurrences within a limited time frame that impedes the normal functioning of a system. Although extreme events are rare in occurrence, it has been found in various hydro-meteorological and physiological time series (e.g., river flows, temperatures, heartbeat intervals) that they may exhibit recurrent behavior, i.e., do not end the lifetime of the system. The aim of this thesis to develop some
sophisticated methods to study various properties of extreme events.
One of the main challenges in analyzing such extreme event-like time series is that they have large temporal gaps due to the paucity of the number of observations of extreme events. As a result, existing time series analysis tools are usually not helpful to decode the underlying
information. I use the edit distance (ED) method to analyze extreme event-like time series in their unaltered form. ED is a specific distance metric, mainly designed to measure the similarity/dissimilarity between point process-like data. I combine ED with recurrence plot techniques to identify the recurrence property of flood events in the Mississippi River in the United States. I also use recurrence quantification analysis to show the deterministic properties
and serial dependency in flood events.
After that, I use this non-linear similarity measure (ED) to compute the pairwise dependency in extreme precipitation event series. I incorporate the similarity measure within the framework of complex network theory to study the collective behavior of climate extremes. Under this architecture, the nodes are defined by the spatial grid points of the given spatio-temporal climate dataset. Each node is associated with a time series corresponding to the temporal evolution
of the climate observation at that grid point. Finally, the network links are functions of the pairwise statistical interdependence between the nodes. Various network measures, such as degree, betweenness centrality, clustering coefficient, etc., can be used to quantify the network’s topology. We apply the methodology mentioned above to study the spatio-temporal coherence pattern of extreme rainfall events in the United States and the Ganga River basin, which reveals its relation to various climate processes and the orography of the region.
The identification of precursors associated with the occurrence of extreme events in the near future is extremely important to prepare the masses for an upcoming disaster and mitigate the potential risks associated with such events. Under this motivation, I propose an in-data prediction recipe for predicting the data structures that typically occur prior to extreme events using the Echo state network, a type of Recurrent Neural Network which is a part of the reservoir
computing framework. However, unlike previous works that identify precursory structures in the same variable in which extreme events are manifested (active variable), I try to predict these structures by using data from another dynamic variable (passive variable) which does not show large excursions from the nominal condition but carries imprints of these extreme events. Furthermore, my results demonstrate that the quality of prediction depends on the magnitude
of events, i.e., the higher the magnitude of the extreme, the better is its predictability skill. I show quantitatively that this is because the input signals collectively form a more coherent pattern for an extreme event of higher magnitude, which enhances the efficiency of the machine to predict the forthcoming extreme events.
The dynamics of noisy bistable systems is analyzed by means of Lyapunov exponents and measures of complexity. We consider both the classical Kramers problem with additive white noise and the case when the barrier fluctuates due to additional external colored noise. In case of additive noise we calculate the Lyapunov exponents and all measures of complexity analytically as functions of the noise intensity resp. the mean escape time. For the problem of fluctuating barrier the usual description of the dynamics with the mean escape time is not sufficient. The application of the concept of measures of complexity allows to describe the structures of motion in more detail. Most complexity measures sign the value of correlation time at which the phenomenon of resonant activation occurs with an extremum.
Strange nonchaotic attractors typically appear in quasiperiodically driven nonlinear systems. Two methods of their characterization are proposed. The first one is based on the bifurcation analysis of the systems, resulting from periodic approximations of the quasiperiodic forcing. Secondly, we propose th characterize their strangeness by calculating a phase sensitivity exponent, that measures the sensitivity with respect to changes of the phase of the external force. It is shown, that phase sensitivity appears if there is a non-zero probability for positive local Lyapunov exponents to occur.
This paper presents a study of the galactic environment of a chemically pristine (<0.6 per cent solar metallicity) Lyman Limit system (LLS) discovered along the sightline towards QSO SDSSJ 135726.27+043541.4 (Z(QSO) = 1.233) at projected distance d = 126 physical kpc (pkpc) from a luminous red galaxy (LRG) at z = 0.33. Combining deep Hubble Space Telescope images, MUSE integral field spectroscopic data, and wide-field redshift survey data has enabled an unprecedented, ultradeep view of the environment around this LRG-LLS pair. A total of 12 galaxies, including the LRG, are found at d less than or similar to 400 pkpc and line-of-sight velocity Delta v < 600 km S-1 of the LLS, with intrinsic luminosity ranging from 0.001 L-* to 2 L-* and a corresponding stellar mass range of M-star approximate to 10(7-11) M-circle dot. All 12 galaxies contribute to a total mass of M-star = 1.6 x 10(11) M-circle dot with approximate to 80 per cent contained in the LRG. The line-of-sight velocity dispersion of these galaxies is found to be sigma (group) = 230 km s(-1) with the centre of mass at d(group) = 118 pkpc and line-of-sight velocity offset of Delta v(group) = 181 km s(-1) from the LLS. Three of these are located at d less than or similar to 100 pkpc from the LLS, and they are all faint with intrinsic luminosity less than or similar to 0.02 L-* and gas-phase metallicity of approximate to 10 per cent solar in their interstellar medium. The disparity in the chemical enrichment level between the LLS and the group members suggests that the LLS originates in infalling intergalactic medium and that parts of the intergalactic gas near old and massive galaxies can still remain chemically pristine through the not too distant past.
We investigate properties of quantum mechanical systems in the light of quantum information theory. We put an emphasize on systems with infinite-dimensional Hilbert spaces, so-called continuous-variable systems'', which are needed to describe quantum optics beyond the single photon regime and other Bosonic quantum systems. We present methods to obtain a description of such systems from a series of measurements in an efficient manner and demonstrate the performance in realistic situations by means of numerical simulations. We consider both unconditional quantum state tomography, which is applicable to arbitrary systems, and tomography of matrix product states. The latter allows for the tomography of many-body systems because the necessary number of measurements scales merely polynomially with the particle number, compared to an exponential scaling in the generic case. We also present a method to realize such a tomography scheme for a system of ultra-cold atoms in optical lattices. Furthermore, we discuss in detail the possibilities and limitations of using continuous-variable systems for measurement-based quantum computing. We will see that the distinction between Gaussian and non-Gaussian quantum states and measurements plays an crucial role. We also provide an algorithm to solve the large and interesting class of naturally occurring Hamiltonians, namely frustration free ones, efficiently and use this insight to obtain a simple approximation method for slightly frustrated systems. To achieve this goals, we make use of, among various other techniques, the well developed theory of matrix product states, tensor networks, semi-definite programming, and matrix analysis.
The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS.
The performance of the recently commissioned spectrometer PEAXIS for resonant inelastic soft X-ray scattering (RIXS) and X-ray photoelectron spectroscopy and its hosting beamline U41-PEAXIS at the BESSY II synchrotron are characterized. The beamline provides linearly polarized light from 180 eV to 1600 eV allowing for RIXS measurements in the range 200-1200 eV. The monochromator optics can be operated in different configurations to provide either high flux with up to 10(12) photons s(-1) within the focal spot at the sample or high energy resolution with a full width at half maximum of <40 meV at an incident photon energy of similar to 400 eV. The measured total energy resolution of the RIXS spectrometer is in very good agreement with theoretically predicted values obtained by ray-tracing simulations. PEAXIS features a 5 m-long RIXS spectrometer arm that can be continuously rotated about the sample position by 106 degrees within the horizontal photon scattering plane, thus enabling the study of momentum-transfer-dependent excitations. Selected scientific examples are presented to demonstrate the instrument capabilities, including measurements of excitations in single-crystalline NiO and in liquid acetone employing a fluid cell sample manipulator. Planned upgrades of the beamline and the RIXS spectrometer to further increase the energy resolution to similar to 100 meV at 1000 eV incident photon energy are discussed.