530 Physik
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- ageing (2)
- anomalous diffusion (2)
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- critical avalanche dynamics (2)
- gene regulatory networks (2)
- memory and delay (2)
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Institut
The high-latitudinal thermospheric processes driven by the solar wind and Interplanetary Magnetic Field (IMF) interaction with the Earth magnetosphere are highly variable parts of the complex dynamic plasma environment, which represent the coupled Magnetosphere – Ionosphere – Thermosphere (MIT) system. The solar wind and IMF interactions transfer energy to the MIT system via reconnection processes at the magnetopause. The Field Aligned Currents (FACs) constitute the energetic links between the magnetosphere and the Earth ionosphere. The MIT system depends on the highly variable solar wind conditions, in particular on changes of the strength and orientation of the IMF.
In my thesis, I perform an investigation on the physical background of the complex MIT system using the global physical - numerical, three-dimensional, time-dependent and self-consistent Upper Atmosphere Model (UAM). This model describes the thermosphere, ionosphere, plasmasphere and inner magnetosphere as well as the electrodynamics of the coupled MIT system for the altitudinal range from 80 (60) km up to the 15 Earth radii.
In the present study, I developed and investigated several variants of the high-latitudinal electrodynamic coupling by including the IMF dependence of FACs into the UAM model. For testing, the various variants were applied to simulations of the coupled MIT system for different seasons, geomagnetic activities, various solar wind and IMF conditions. Additionally, these variants of the theoretical model with the IMF dependence were compared with global empirical models. The modelling results for the most important thermospheric parameters like neutral wind and mass density were compared with satellite measurements. The variants of the UAM model with IMF dependence show a good agreement with the satellite observations. In comparison with the empirical models, the improved variants of the UAM model reproduce a more realistic meso-scale structures and dynamics of the coupled MIT system than the empirical models, in particular at high latitudes. The new configurations of the UAM model with IMF dependence contribute to the improvement of space weather prediction.
Recent experiments show that transcription factors (TFs) indeed use the facilitated diffusion mechanism to locate their target sequences on DNA in living bacteria cells: TFs alternate between sliding motion along DNA and relocation events through the cytoplasm. From simulations and theoretical analysis we study the TF-sliding motion for a large section of the DNA-sequence of a common E. coli strain, based on the two-state TF-model with a fast-sliding search state and a recognition state enabling target detection. For the probability to detect the target before dissociating from DNA the TF-search times self-consistently depend heavily on whether or not an auxiliary operator (an accessible sequence similar to the main operator) is present in the genome section. Importantly, within our model the extent to which the interconversion rates between search and recognition states depend on the underlying nucleotide sequence is varied. A moderate dependence maximises the capability to distinguish between the main operator and similar sequences. Moreover, these auxiliary operators serve as starting points for DNA looping with the main operator, yielding a spectrum of target detection times spanning several orders of magnitude. Auxiliary operators are shown to act as funnels facilitating target detection by TFs.
Recent experiments show that transcription factors (TFs) indeed use the facilitated diffusion mechanism to locate their target sequences on DNA in living bacteria cells: TFs alternate between sliding motion along DNA and relocation events through the cytoplasm. From simulations and theoretical analysis we study the TF-sliding motion for a large section of the DNA-sequence of a common E. coli strain, based on the two-state TF-model with a fast-sliding search state and a recognition state enabling target detection. For the probability to detect the target before dissociating from DNA the TF-search times self-consistently depend heavily on whether or not an auxiliary operator (an accessible sequence similar to the main operator) is present in the genome section. Importantly, within our model the extent to which the interconversion rates between search and recognition states depend on the underlying nucleotide sequence is varied. A moderate dependence maximises the capability to distinguish between the main operator and similar sequences. Moreover, these auxiliary operators serve as starting points for DNA looping with the main operator, yielding a spectrum of target detection times spanning several orders of magnitude. Auxiliary operators are shown to act as funnels facilitating target detection by TFs.
Semi-empirical sea-level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers, in the following global mean temperature. This model class evolved as a supplement to process-based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea-level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea-level rise. Semi-empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea-level rise, consistently giving significantly higher projections than process-based models.
In the following different aspects of semi-empirical sea-level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level, and to infer past global temperature from sea-level data via inverse modelling. Periods studied encompass the instrumental period, covered by tide gauges (starting 1700 CE (Common Era) in Amsterdam) and satellites (first launched in 1992 CE), the era from 1000 BCE (before CE) to present, and the full length of the Holocene (using proxy data). Accordingly different data, model formulations and implementations have been used. It could be shown in Bittermann et al. (2013) that SEMs correctly predict 20th century sea-level when calibrated with data until 1900 CE. SEMs also turned out to give better predictions than the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report (AR4, IPCC (2007)) models, for the period from 1961–2003 CE.
With the first multi-proxy reconstruction of global sea-level as input, estimate of the human-induced component of modern sea-level change and projections of future sea-level rise were calculated (Kopp et al. (2016)). It turned out with 90% confidence that more than 40 % of the observed 20th century sea-level rise is indeed anthropogenic. With the new semi-empirical and IPCC (2013) 5th assessment report (AR5) projections the gap between SEM and process-based model projections closes, giving higher credibility to both. Combining all scenarios, from strong mitigation to business as usual, a global sea-level rise of 28–131 cm relative to 2000 CE, is projected with 90% confidence. The decision for a low carbon pathway could halve the expected global sea-level rise by 2100 CE.
Present day temperature and thus sea level are driven by the globally acting greenhouse-gas forcing. Unlike that, the Milankovich forcing, acting on Holocene timescales, results mainly in a northern-hemisphere temperature change. Therefore a semi-empirical model can be driven with northernhemisphere temperatures, which makes it possible to model the main subcomponent of sea-level change over this period. It showed that an additional positive constant rate of the order of the estimated Antarctic sea-level contribution is then required to explain the sea-level evolution over the Holocene. Thus the global sea level, following the climatic optimum, can be interpreted as the sum of a temperature induced sea-level drop and a positive long-term contribution, likely an ongoing response to deglaciation coming from Antarctica.
Organic bulk heterojunction (BHJ) solar cells based on polymer:fullerene blends are a promising alternative for a low-cost solar energy conversion. Despite significant improvements of the power conversion efficiency in recent years, the fundamental working principles of these devices are yet not fully understood. In general, the current output of organic solar cells is determined by the generation of free charge carriers upon light absorption and their transport to the electrodes in competition to the loss of charge carriers due to recombination.
The object of this thesis is to provide a comprehensive understanding of the dynamic processes and physical parameters determining the performance. A new approach for analyzing the characteristic current-voltage output was developed comprising the experimental determination of the efficiencies of charge carrier generation, recombination and transport, combined with numerical device simulations.
Central issues at the beginning of this work were the influence of an electric field on the free carrier generation process and the contribution of generation, recombination and transport to the current-voltage characteristics. An elegant way to directly measure the field dependence of the free carrier generation is the Time Delayed Collection Field (TDCF) method. In TDCF charge carriers are generated by a short laser pulse and subsequently extracted by a defined rectangular voltage pulse. A new setup was established with an improved time resolution compared to former reports in literature. It was found that charge generation is in general independent of the electric field, in contrast to the current view in literature and opposed to the expectations of the Braun-Onsager model that was commonly used to describe the charge generation process. Even in cases where the charge generation was found to be field-dependend, numerical modelling showed that this field-dependence is in general not capable to account for the voltage dependence of the photocurrent. This highlights the importance of efficient charge extraction in competition to non-geminate recombination, which is the second objective of the thesis.
Therefore, two different techniques were combined to characterize the dynamics and efficiency of non-geminate recombination under device-relevant conditions. One new approach is to perform TDCF measurements with increasing delay between generation and extraction of charges. Thus, TDCF was used for the first time to measure charge carrier generation, recombination and transport with the same experimental setup. This excludes experimental errors due to different measurement and preparation conditions and demonstrates the strength of this technique. An analytic model for the description of TDCF transients was developed and revealed the experimental conditions for which reliable results can be obtained. In particular, it turned out that the $RC$ time of the setup which is mainly given by the sample geometry has a significant influence on the shape of the transients which has to be considered for correct data analysis.
Secondly, a complementary method was applied to characterize charge carrier recombination under steady state bias and illumination, i.e. under realistic operating conditions. This approach relies on the precise determination of the steady state carrier densities established in the active layer. It turned out that current techniques were not sufficient to measure carrier densities with the necessary accuracy. Therefore, a new technique {Bias Assisted Charge Extraction} (BACE) was developed. Here, the charge carriers photogenerated under steady state illumination are extracted by applying a high reverse bias. The accelerated extraction compared to conventional charge extraction minimizes losses through non-geminate recombination and trapping during extraction. By performing numerical device simulations under steady state, conditions were established under which quantitative information on the dynamics can be retrieved from BACE measurements.
The applied experimental techniques allowed to sensitively analyse and quantify geminate and non-geminate recombination losses along with charge transport in organic solar cells. A full analysis was exemplarily demonstrated for two prominent polymer-fullerene blends.
The model system P3HT:PCBM spincast from chloroform (as prepared) exhibits poor power conversion efficiencies (PCE) on the order of 0.5%, mainly caused by low fill factors (FF) and currents. It could be shown that the performance of these devices is limited by the hole transport and large bimolecular recombination (BMR) losses, while geminate recombination losses are insignificant. The low polymer crystallinity and poor interconnection between the polymer and fullerene domains leads to a hole mobility of the order of 10^-7 cm^2/Vs which is several orders of magnitude lower than the electron mobility in these devices. The concomitant build up of space charge hinders extraction of both electrons and holes and promotes bimolecular recombination losses.
Thermal annealing of P3HT:PCBM blends directly after spin coating improves crystallinity and interconnection of the polymer and the fullerene phase and results in comparatively high electron and hole mobilities in the order of 10^-3 cm^2/Vs and 10^-4 cm^2/Vs, respectively. In addition, a coarsening of the domain sizes leads to a reduction of the BMR by one order of magnitude. High charge carrier mobilities and low recombination losses result in comparatively high FF (>65%) and short circuit current (J_SC ≈ 10 mA/cm^2). The overall device performance (PCE ≈ 4%) is only limited by a rather low spectral overlap of absorption and solar emission and a small V_OC, given by the energetics of the P3HT.
From this point of view the combination of the low bandgap polymer PTB7 with PCBM is a promising approach. In BHJ solar cells, this polymer leads to a higher V_OC due to optimized energetics with PCBM. However, the J_SC in these (unoptimized) devices is similar to the J_SC in the optimized blend with P3HT and the FF is rather low (≈ 50%). It turned out that the unoptimized PTB7:PCBM blends suffer from high BMR, a low electron mobility of the order of 10^-5 cm^2/Vs and geminate recombination losses due to field dependent charge carrier generation.
The use of the solvent additive DIO optimizes the blend morphology, mainly by suppressing the formation of very large fullerene domains and by forming a more uniform structure of well interconnected donor and acceptor domains of the order of a few nanometers. Our analysis shows that this results in an increase of the electron mobility by about one order of magnitude (3 x 10^-4 cm^2/Vs), while BMR and geminate recombination losses are significantly reduced. In total these effects improve the J_SC (≈ 17 mA/cm^2) and the FF (> 70%). In 2012 this polymer/fullerene combination resulted in a record PCE for a single junction OSC of 9.2%.
Remarkably, the numerical device simulations revealed that the specific shape of the J-V characteristics depends very sensitively to the variation of not only one, but all dynamic parameters. On the one hand this proves that the experimentally determined parameters, if leading to a good match between simulated and measured J-V curves, are realistic and reliable. On the other hand it also emphasizes the importance to consider all involved dynamic quantities, namely charge carrier generation, geminate and non-geminate recombination as well as electron and hole mobilities. The measurement or investigation of only a subset of these parameters as frequently found in literature will lead to an incomplete picture and possibly to misleading conclusions.
Importantly, the comparison of the numerical device simulation employing the measured parameters and the experimental $J-V$ characteristics allows to identify loss channels and limitations of OSC. For example, it turned out that inefficient extraction of charge carriers is a criticical limitation factor that is often disobeyed. However, efficient and fast transport of charges becomes more and more important with the development of new low bandgap materials with very high internal quantum efficiencies. Likewise, due to moderate charge carrier mobilities, the active layer thicknesses of current high-performance devices are usually limited to around 100 nm. However, larger layer thicknesses would be more favourable with respect to higher current output and robustness of production. Newly designed donor materials should therefore at best show a high tendency to form crystalline structures, as observed in P3HT, combined with the optimized energetics and quantum efficiency of, for example, PTB7.
We define and study in detail utraslow scaled Brownian motion (USBM) characterized by a time dependent diffusion coefficient of the form . For unconfined motion the mean squared displacement (MSD) of USBM exhibits an ultraslow, logarithmic growth as function of time, in contrast to the conventional scaled Brownian motion. In a harmonic potential the MSD of USBM does not saturate but asymptotically decays inverse-proportionally to time, reflecting the highly non-stationary character of the process. We show that the process is weakly non-ergodic in the sense that the time averaged MSD does not converge to the regular MSD even at long times, and for unconfined motion combines a linear lag time dependence with a logarithmic term. The weakly non-ergodic behaviour is quantified in terms of the ergodicity breaking parameter. The USBM process is also shown to be ageing: observables of the system depend on the time gap between initiation of the test particle and start of the measurement of its motion. Our analytical results are shown to agree excellently with extensive computer simulations.
We define and study in detail utraslow scaled Brownian motion (USBM) characterized by a time dependent diffusion coefficient of the form . For unconfined motion the mean squared displacement (MSD) of USBM exhibits an ultraslow, logarithmic growth as function of time, in contrast to the conventional scaled Brownian motion. In a harmonic potential the MSD of USBM does not saturate but asymptotically decays inverse-proportionally to time, reflecting the highly non-stationary character of the process. We show that the process is weakly non-ergodic in the sense that the time averaged MSD does not converge to the regular MSD even at long times, and for unconfined motion combines a linear lag time dependence with a logarithmic term. The weakly non-ergodic behaviour is quantified in terms of the ergodicity breaking parameter. The USBM process is also shown to be ageing: observables of the system depend on the time gap between initiation of the test particle and start of the measurement of its motion. Our analytical results are shown to agree excellently with extensive computer simulations.
Temperature-memory polymers remember the temperature, where they were deformed recently, enabled by broad thermal transitions. In this study, we explored a series of crosslinked poly[ethylene-co-(vinyl acetate)] networks (cPEVAs) comprising crystallizable polyethylene (PE) controlling units exhibiting a pronounced temperature-memory effect (TME) between 16 and 99 °C related to a broad melting transition (∼100 °C). The nanostructural changes in such cPEVAs during programming and activation of the TME were analyzed via in situ X-ray scattering and specific annealing experiments. Different contributions to the mechanism of memorizing high or low deformation temperatures (Tdeform) were observed in cPEVA, which can be associated to the average PE crystal sizes. At high deformation temperatures (>50 °C), newly formed PE crystals, which are established during cooling when fixing the temporary shape, dominated the TME mechanism. In contrast, at low Tdeform (<50 °C), corresponding to a cold drawing scenario, the deformation led preferably to a disruption of existing large crystals into smaller ones, which then fix the temporary shape upon cooling. The observed mechanism of memorizing a deformation temperature might enable the prediction of the TME behavior and the knowledge based design of other TMPs with crystallizable controlling units.
Temperature-memory polymers remember the temperature, where they were deformed recently, enabled by broad thermal transitions. In this study, we explored a series of crosslinked poly[ethylene-co-(vinyl acetate)] networks (cPEVAs) comprising crystallizable polyethylene (PE) controlling units exhibiting a pronounced temperature-memory effect (TME) between 16 and 99 °C related to a broad melting transition (∼100 °C). The nanostructural changes in such cPEVAs during programming and activation of the TME were analyzed via in situ X-ray scattering and specific annealing experiments. Different contributions to the mechanism of memorizing high or low deformation temperatures (Tdeform) were observed in cPEVA, which can be associated to the average PE crystal sizes. At high deformation temperatures (>50 °C), newly formed PE crystals, which are established during cooling when fixing the temporary shape, dominated the TME mechanism. In contrast, at low Tdeform (<50 °C), corresponding to a cold drawing scenario, the deformation led preferably to a disruption of existing large crystals into smaller ones, which then fix the temporary shape upon cooling. The observed mechanism of memorizing a deformation temperature might enable the prediction of the TME behavior and the knowledge based design of other TMPs with crystallizable controlling units.
Function by structure
(2015)
The main goal of this cumulative thesis is the derivation of surface emissivity data in the infrared from radiance measurements of Venus. Since these data are diagnostic of the chemical composition and grain size of the surface material, they can help to improve knowledge of the planet’s geology. Spectrally resolved images of nightside emissions in the range 1.0-5.1 μm were recently acquired by the InfraRed Mapping channel of the Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M-IR) aboard ESA’s Venus EXpress (VEX). Surface and deep atmospheric thermal emissions in this spectral range are strongly obscured by the extremely opaque atmosphere, but three narrow spectral windows at 1.02, 1.10, and 1.18 μm allow the sounding of the surface. Additional windows between 1.3 and 2.6 μm provide information on atmospheric parameters that is required to interpret the surface signals. Quantitative data on surface and atmosphere can be retrieved from the measured spectra by comparing them to simulated spectra. A numerical radiative transfer model is used in this work to simulate the observable radiation as a function of atmospheric, surface, and instrumental parameters. It is a line-by-line model taking into account thermal emissions by surface and atmosphere as well as absorption and multiple scattering by gases and clouds. The VIRTIS-M-IR measurements are first preprocessed to obtain an optimal data basis for the subsequent steps. In this process, a detailed detector responsivity analysis enables the optimization of the data consistency. The measurement data have a relatively low spectral information content, and different parameter vectors can describe the same measured spectrum equally well. A usual method to regularize the retrieval of the wanted parameters from a measured spectrum is to take into account a priori mean values and standard deviations of the parameters to be retrieved. This decreases the probability to obtain unreasonable parameter values. The multi-spectrum retrieval algorithm MSR is developed to additionally consider physically realistic spatial and temporal a priori correlations between retrieval parameters describing different measurements. Neglecting geologic activity, MSR also allows the retrieval of an emissivity map as a parameter vector that is common to several spectrally resolved images that cover the same surface target. Even applying MSR, it is difficult to obtain reliable emissivity maps in absolute values. A detailed retrieval error analysis based on synthetic spectra reveals that this is mainly due to interferences from parameters that cannot be derived from the spectra themselves, but that have to be set to assumed values to enable the radiative transfer simulations. The MSR retrieval of emissivity maps relative to a fixed emissivity is shown to effectively avoid most emissivity retrieval errors. Relative emissivity maps at 1.02, 1.10, and 1.18 μm are finally derived from many VIRTIS-M-IR measurements that cover a surface target at Themis Regio. They are interpreted as spatial variations relative to an assumed emissivity mean of the target. It is verified that the maps are largely independent of the choice of many interfering parameters as well as the utilized measurement data set. These are the first Venus IR emissivity data maps based on a consistent application of a full radiative transfer simulation and a retrieval algorithm that respects a priori information. The maps are sufficiently reliable for future geologic interpretations.
The subject of the present thesis is the one-dimensional Bose gas. Since long-rang order is destroyed by infra-red fluctuations in one dimension, only the formation of a quasi-condensate is possible, which exhibits suppressed density fluctuations, but whose phase fluctuates strongly. It is shown that modified mean-field theories based on a symmetry-breaking approach can even characterise phase coherence properties of such a quasi-condensate properly. A correct description of the transition from the degenerate ideal Bose gas to the quasi-condensate, which is a smooth cross-over rather than a phase transition, is not possible though. Basic conditions for the applicability of the theories are not fulfilled in this regime, such that the existence of a critical point is predicted.
The theories are compared on the basis of their excitation sprectum, equation of state, density fluctuations and related correlation functions. High-temperature expansions of the corresponding integrals are derived analytically for the numerical evaluation of the self-consistent integral equations. Apart from that, the Stochastic Gross-Pitaevskii equation (SGPE), a non-linear Langevin equation, is analysed numerically by means of Monte-Carlo simulations and the results are compared to those of the mean-field theories. In this context, a lot of attention is payed to the appropriate choice of the parameters. The simulations prove that the SGPE is capable of describing the cross-over properly, but highlight the limitations of the widely used local density approximation as well.