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- two beam interferometry (1)
- two-dimensional (1)
- type I AGN (1)
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- ultra-fast laser inscription technology (1)
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Institute
- Institut für Physik und Astronomie (5393) (remove)
Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.
Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.
Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as ‘superstatistics’ or ‘diffusing diffusivity’. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.
Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as ‘superstatistics’ or ‘diffusing diffusivity’. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.
The Sun is a star, which due to its proximity has a tremendous influence on Earth. Since its very first days mankind tried to "understand the Sun", and especially in the 20th century science has uncovered many of the Sun's secrets by using high resolution observations and describing the Sun by means of models. As an active star the Sun's activity, as expressed in its magnetic cycle, is closely related to the sunspot numbers. Flares play a special role, because they release large energies on very short time scales. They are correlated with enhanced electromagnetic emissions all over the spectrum. Furthermore, flares are sources of energetic particles. Hard X-ray observations (e.g., by NASA's RHESSI spacecraft) reveal that a large fraction of the energy released during a flare is transferred into the kinetic energy of electrons. However the mechanism that accelerates a large number of electrons to high energies (beyond 20 keV) within fractions of a second is not understood yet. The thesis at hand presents a model for the generation of energetic electrons during flares that explains the electron acceleration based on real parameters obtained by real ground and space based observations. According to this model photospheric plasma flows build up electric potentials in the active regions in the photosphere. Usually these electric potentials are associated with electric currents closed within the photosphere. However as a result of magnetic reconnection, a magnetic connection between the regions of different magnetic polarity on the photosphere can establish through the corona. Due to the significantly higher electric conductivity in the corona, the photospheric electric power supply can be closed via the corona. Subsequently a high electric current is formed, which leads to the generation of hard X-ray radiation in the dense chromosphere. The previously described idea is modelled and investigated by means of electric circuits. For this the microscopic plasma parameters, the magnetic field geometry and hard X-ray observations are used to obtain parameters for modelling macroscopic electric components, such as electric resistors, which are connected with each other. This model demonstrates that such a coronal electric current is correlated with large scale electric fields, which can accelerate the electrons quickly up to relativistic energies. The results of these calculations are encouraging. The electron fluxes predicted by the model are in agreement with the electron fluxes deduced from the measured photon fluxes. Additionally the model developed in this thesis proposes a new way to understand the observed double footpoint hard X-ray sources.
We develop a method of finding analytical sotutions of the Bogolyubov-de Gennes equations for the excitations of a Bose condensate in the Thomas-Fermi regime in harmonic traps of any asymmetry and introduce a classification of eigenstates. In the case of cylindrical symmetry we emphasize the presence of an accidental degeneracy in the excitation spectrum at certain values of the projection of orbital angular momentum on the symmetry axis and discuss possible consequences of the degeneracy in the context of new signatures of Bose- Einstein condensation
Die vorliegende Arbeit beschäftigt sich mit der Charakterisierung von Seismizität anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss darüber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus für die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen häufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die Möglichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird häufig als Vorläuferphaenomen für starke Erdbeben gedeutet. Es wird eine neue Methode präsentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen ermöglicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erhält man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz dafür nicht hoch genug, um eine Vorhersage im Sinne einer Aussage über den Ort, die Zeit und die Stärke eines zu erwartenden Hauptbebens zu ermöglichen.
The occurrence of earthquakes is characterized by a high degree of spatiotemporal complexity. Although numerous patterns, e.g. fore- and aftershock sequences, are well-known, the underlying mechanisms are not observable and thus not understood. Because the recurrence times of large earthquakes are usually decades or centuries, the number of such events in corresponding data sets is too small to draw conclusions with reasonable statistical significance. Therefore, the present study combines both, numerical modeling and analysis of real data in order to unveil the relationships between physical mechanisms and observational quantities. The key hypothesis is the validity of the so-called "critical point concept" for earthquakes, which assumes large earthquakes to occur as phase transitions in a spatially extended many-particle system, similar to percolation models. New concepts are developed to detect critical states in simulated and in natural data sets. The results indicate that important features of seismicity like the frequency-size distribution and the temporal clustering of earthquakes depend on frictional and structural fault parameters. In particular, the degree of quenched spatial disorder (the "roughness") of a fault zone determines whether large earthquakes occur quasiperiodically or more clustered. This illustrates the power of numerical models in order to identify regions in parameter space, which are relevant for natural seismicity. The critical point concept is verified for both, synthetic and natural seismicity, in terms of a critical state which precedes a large earthquake: a gradual roughening of the (unobservable) stress field leads to a scale-free (observable) frequency-size distribution. Furthermore, the growth of the spatial correlation length and the acceleration of the seismic energy release prior to large events is found. The predictive power of these precursors is, however, limited. Instead of forecasting time, location, and magnitude of individual events, a contribution to a broad multiparameter approach is encouraging.
Hysteresis in the pinning-depinning transitions of spiral waves rotating around a hole in a circular shaped two- dimensional excitable medium is studied both by use of the continuation software AUTO and by direct numerical integration of the reaction-diffusion equations for the FitzHugh-Nagumo model. In order to clarify the role of different factors in this phenomenon, a kinematical description is applied. It is found that the hysteresis phenomenon computed for the reaction-diffusion model can be reproduced qualitatively only when a nonlinear eikonal equation (i.e. velocity- curvature relationship) is assumed. However, to obtain quantitative agreement, the dispersion relation has to be taken into account.
We present a theoretical framework for the analysis of the statistical properties of thermal fluctuations on a lossy transmission line. A quantization scheme of the electrical signals in the transmission line is formulated. We discuss two applications in detail. Noise spectra at finite temperature for voltage and current are shown to deviate significantly from the Johnson-Nyquist limit, and they depend on the position on the transmission line. We analyze the spontaneous emission, at low temperature, of a Rydberg atom and its resonant enhancement due to vacuum fluctuations in a capacitively coupled transmission line. The theory can also be applied to study the performance of microscale and nanoscale devices, including high-resolution sensors and quantum information processors
We present a momentum transfer mechanism mediated by electromagnetic fields that originates in a system of two nearby molecules: one excited (donor D*) and the other in ground state (acceptor A). An intermolecular force related to fluorescence resonant energy or Forster transfer (FRET) arises in the unstable D* A molecular system, which differs from the equilibrium van der Waals interaction. Due to the its finite lifetime, a mechanical impulse is imparted to the relative motion in the system. We analyze the FRET impulse when the molecules are embedded in free space and find that its magnitude can be much greater than the single recoil photon momentum, getting comparable with the thermal momentum (Maxwell-Boltzmann distribution) at room temperature. In addition, we propose that this FRET impulse can be exploited in the generation of acoustic waves inside a film containing layers of donor and acceptor molecules, when a picosecond laser pulse excites the donors. This acoustic transient is distinguishable from that produced by thermal stress due to laser absorption, and may therefore play a role in photoacoustic spectroscopy. The effect can be seen as exciting a vibrating system like a string or organ pipe with light; it may be used as an opto-mechanical transducer.
State-of-the-art organic solar cells exhibit power conversion efficiencies of 18% and above. These devices benefit from the suppression of free charge recombination with regard to the Langevin limit of charge encounter in a homogeneous medium. It is recognized that the main cause of suppressed free charge recombination is the reformation and resplitting of charge-transfer (CT) states at the interface between donor and acceptor domains. Here, we use kinetic Monte Carlo simulations to understand the interplay between free charge motion and recombination in an energetically disordered phase-separated donor-acceptor blend. We identify conditions for encounter-dominated and resplitting-dominated recombination. In the former regime, recombination is proportional to mobility for all parameters tested and only slightly reduced with respect to the Langevin limit. In contrast, mobility is not the decisive parameter that determines the nongeminate recombination coefficient, k(2), in the latter case, where k2 is a sole function of the morphology, CT and charge-separated (CS) energetics, and CT-state decay properties. Our simulations also show that free charge encounter in the phase-separated disordered blend is determined by the average mobility of all carriers, while CT reformation and resplitting involves mostly states near the transport energy. Therefore, charge encounter is more affected by increased disorder than the resplitting of the CT state. As a consequence, for a given mobility, larger energetic disorder, in combination with a higher hopping rate, is preferred. These findings have implications for the understanding of suppressed recombination in solar cells with nonfullerene acceptors, which are known to exhibit lower energetic disorder than that of fullerenes.
Explicit solution of the Lindblad equation for nearly isotropic boundary driven XY spin 1/2 chain
(2010)
Explicit solution for the two-point correlation function in a non-equilibrium steady state of a nearly isotropic boundary driven open XY spin 1/2 chain in the Lindblad formulation is provided. A non-equilibrium quantum phase transition from exponentially decaying correlations to long range order is discussed analytically. In the regime of long range order a new phenomenon of correlation resonances is reported, where the correlation response of the system is unusually high for certain discrete values of the external bulk parameter, e.g. the magnetic field.
The tremendous success of metal-halide perovskites, especially in the field of photovoltaics, has triggered a substantial number of studies in understanding their optoelectronic properties. However, consensus regarding the electronic properties of these perovskites is lacking due to a huge scatter in the reported key parameters, such as work function (Φ) and valence band maximum (VBM) values. Here, we demonstrate that the surface photovoltage (SPV) is a key phenomenon occurring at the perovskite surfaces that feature a non-negligible density of surface states, which is more the rule than an exception for most materials under study. With ultraviolet photoelectron spectroscopy (UPS) and Kelvin probe, we evidence that even minute UV photon fluxes (500 times lower than that used in typical UPS experiments) are sufficient to induce SPV and shift the perovskite Φ and VBM by several 100 meV compared to dark. By combining UV and visible light, we establish flat band conditions (i.e., compensate the surface-state-induced surface band bending) at the surface of four important perovskites, and find that all are p-type in the bulk, despite a pronounced n-type surface character in the dark. The present findings highlight that SPV effects must be considered in all surface studies to fully understand perovskites’ photophysical properties.
In contrast to the common conception that the interfacial energy-level alignment is affixed once the interface is formed, we demonstrate that heterojunctions between organic semiconductors and metal-halide perovskites exhibit huge energy-level realignment during photoexcitation. Importantly, the photoinduced level shifts occur in the organic component, including the first molecular layer in direct contact with the perovskite. This is caused by charge-carrier accumulation within the organic semiconductor under illumination and the weak electronic coupling between the junction components.
The remarkable progress of metal halide perovskites in photovoltaics has led to the power conversion efficiency approaching 26%. However, practical applications of perovskite-based solar cells are challenged by the stability issues, of which the most critical one is photo-induced degradation. Bare CH3NH3PbI3 perovskite films are known to decompose rapidly, with methylammonium and iodine as volatile species and residual solid PbI2 and metallic Pb, under vacuum under white light illumination, on the timescale of minutes. We find, in agreement with previous work, that the degradation is non-uniform and proceeds predominantly from the surface, and that illumination under N-2 and ambient air (relative humidity 20%) does not induce substantial degradation even after several hours. Yet, in all cases the release of iodine from the perovskite surface is directly identified by X-ray photoelectron spectroscopy. This goes in hand with a loss of organic cations and the formation of metallic Pb. When CH3NH3PbI3 films are covered with a few nm thick organic capping layer, either charge selective or non-selective, the rapid photodecomposition process under ultrahigh vacuum is reduced by more than one order of magnitude, and becomes similar in timescale to that under N-2 or air. We conclude that the light-induced decomposition reaction of CH3NH3PbI3, leading to volatile methylammonium and iodine, is largely reversible as long as these products are restrained from leaving the surface. This is readily achieved by ambient atmospheric pressure, as well as a thin organic capping layer even under ultrahigh vacuum. In addition to explaining the impact of gas pressure on the stability of this perovskite, our results indicate that covalently "locking" the position of perovskite components at the surface or an interface should enhance the overall photostability.
We investigate the bifurcation structures in a two-dimensional parameter space (PS) of a parametrically excited system with two degrees of freedom both analytically and numerically. By means of the Renyi entropy of second order K-2, which is estimated from recurrence plots, we uncover that regions of chaotic behavior are intermingled with many complex periodic windows, such as shrimp structures in the PS. A detailed numerical analysis shows that, the stable solutions lose stability either via period doubling, or via intermittency when the parameters leave these shrimps in different directions, indicating different bifurcation properties of the boundaries. The shrimps of different sizes offer promising ways to control the dynamics of such a complex system.
In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments.
We present an excerpt of the document "Quantum Information Processing and Communication: Strategic report on current status, visions and goals for research in Europe", which has been recently published in electronic form at the website of FET (the Future and Emerging Technologies Unit of the Directorate General Information Society of the European Commission, http://www.cordis.lu/ist/fet/qipc-sr.htm). This document has been elaborated, following a former suggestion by FET, by a committee of QIPC scientists to provide input towards the European Commission for the preparation of the Seventh Framework Program. Besides being a document addressed to policy makers and funding agencies (both at the European and national level), the document contains a detailed scientific assessment of the state-of-the-art, main research goals, challenges, strengths, weaknesses, visions and perspectives of all the most relevant QIPC sub-fields, that we report here
We investigate the influence of spatial heterogeneities on various aspects of brittle failure and seismicity in a model of a large strike-slip fault. The model dynamics is governed by realistic boundary conditions consisting of constant velocity motion of regions around the fault, static/kinetic friction laws, creep with depth-dependent coefficients, and 3-D elastic stress transfer. The dynamic rupture is approximated on a continuous time scale using a finite stress propagation velocity ("quasidynamic model''). The model produces a "brittle- ductile'' transition at a depth of about 12.5 km, realistic hypocenter distributions, and other features of seismicity compatible with observations. Previous work suggested that the range of size scales in the distribution of strength-stress heterogeneities acts as a tuning parameter of the dynamics. Here we test this hypothesis by performing a systematic parameter-space study with different forms of heterogeneities. In particular, we analyze spatial heterogeneities that can be tuned by a single parameter in two distributions: ( 1) high stress drop barriers in near- vertical directions and ( 2) spatial heterogeneities with fractal properties and variable fractal dimension. The results indicate that the first form of heterogeneities provides an effective means of tuning the behavior while the second does not. In relatively homogeneous cases, the fault self-organizes to large-scale patches and big events are associated with inward failure of individual patches and sequential failures of different patches. The frequency-size event statistics in such cases are compatible with the characteristic earthquake distribution and large events are quasi-periodic in time. In strongly heterogeneous or near-critical cases, the rupture histories are highly discontinuous and consist of complex migration patterns of slip on the fault. In such cases, the frequency-size and temporal statistics follow approximately power-law relations
We show that realistic aftershock sequences with space-time characteristics compatible with observations are generated by a model consisting of brittle fault segments separated by creeping zones. The dynamics of the brittle regions is governed by static/kinetic friction, 3D elastic stress transfer and small creep deformation. The creeping parts are characterized by high ongoing creep velocities. These regions store stress during earthquake failures and then release it in the interseismic periods. The resulting postseismic deformation leads to aftershock sequences following the modified Omori law. The ratio of creep coefficients in the brittle and creeping sections determines the duration of the postseismic transients and the exponent p of the modified Omori law
Stabilized multi-wavelength emission from a single emitter broad area diode laser (BAL) is realized by utilizing an external cavity with a spectral beam combining architecture. Self-organized emitters that are equidistantly spaced across the slow axis are enforced by the spatially distributed wavelength selectivity of the external cavity. This resulted in an array like near-field emission although the BAL is physically a single emitter without any epitaxial sub-structuring and only one electrical contact. Each of the self-organized emitters is operated at a different wavelength and the emission is multiplexed into one spatial mode with near-diffraction limited beam quality. With this setup, multi-line emission of 31 individual spectral lines centered around and a total spectral width of 3.6 nm is realized with a 1000 mu m wide BAL just above threshold. To the best of our knowledge, this is the first demonstration of such a self-organization of emitters by optical feedback utilizing a spectral beam combining architecture.
The emission characteristics of a novel, specially designed broad area diode laser (BAL) with on-chip transversal Bragg resonance (TBR) grating in lateral direction were investigated in an off-axis external cavity setup. The internal TBR grating defines a low loss transversal mode at a specific angle of incidence and a certain wavelength. By providing feedback at this specific angle with an external mirror, it is possible to select this low loss transverse mode and stabilize the BAL. Near diffraction limited emission with an almost single lobed far field pattern could be realized, in contrast to the double lobed far field pattern of similar setups using standard BALs or phase-locked diode laser arrays. Furthermore, we could achieve a narrow bandwidth emission with a simplified setup without external frequency selective elements. (C) 2014 Optical Society of America
We study the random-field Ising chain in the limit of strong exchange coupling. In order to calculate the free energy we apply a continuous Langevin-type approach. This continuous model can be solved exactly, whereupon we are able to locate the crossover between an exponential and a power-law decay of the free energy with increasing coupling strength. In terms of magnetization, this crossover restricts the validity of the linear scaling. The known analytical results for the free energy are recovered in the corresponding limits. The outcomes of numerical computations for the free energy are presented, which confirm the results of the continuous approach. We also discuss the validity of the replica method which we then utilize to investigate the sample-to-sample fluctuations of the finite size free energy
We develop a statistical theory of the coupling sensitivity of chaos. The effect was first described by Daido [Prog. Theor. Phys. 72, 853 (1984)]; it appears as a logarithmic singularity in the Lyapunov exponent in coupled chaotic systems at very small couplings. Using a continuous-time stochastic model for the coupled systems we derive a scaling relation for the largest Lyapunov exponent. The singularity is shown to depend on the coupling and the systems' mismatch. Generalizations to the cases of asymmetrical coupling and three interacting oscillators are considered, too. The analytical results are confirmed by numerical simulations.
This work incorporates three treatises which are commonly concerned with a stochastic theory of the Lyapunov exponents. With the help of this theory universal scaling laws are investigated which appear in coupled chaotic and disordered systems. First, two continuous-time stochastic models for weakly coupled chaotic systems are introduced to study the scaling of the Lyapunov exponents with the coupling strength (coupling sensitivity of chaos). By means of the the Fokker-Planck formalism scaling relations are derived, which are confirmed by results of numerical simulations. Next, coupling sensitivity is shown to exist for coupled disordered chains, where it appears as a singular increase of the localization length. Numerical findings for coupled Anderson models are confirmed by analytic results for coupled continuous-space Schrödinger equations. The resulting scaling relation of the localization length resembles the scaling of the Lyapunov exponent of coupled chaotic systems. Finally, the statistics of the exponential growth rate of the linear oscillator with parametric noise are studied. It is shown that the distribution of the finite-time Lyapunov exponent deviates from a Gaussian one. By means of the generalized Lyapunov exponents the parameter range is determined where the non-Gaussian part of the distribution is significant and multiscaling becomes essential.
Concerns have been raised that anthropogenic climate change could lead to large-scale singular climate events, i.e., abrupt nonlinear climate changes with repercussions on regional to global scales. One central goal of this thesis is the development of models of two representative components of the climate system that could exhibit singular behavior: the Atlantic thermohaline circulation (THC) and the Indian monsoon. These models are conceived so as to fulfill the main requirements of integrated assessment modeling, i.e., reliability, computational efficiency, transparency and flexibility. The model of the THC is an interhemispheric four-box model calibrated against data generated with a coupled climate model of intermediate complexity. It is designed to be driven by global mean temperature change which is translated into regional fluxes of heat and freshwater through a linear down-scaling procedure. Results of a large number of transient climate change simulations indicate that the reduced-form THC model is able to emulate key features of the behavior of comprehensive climate models such as the sensitivity of the THC to the amount, regional distribution and rate of change in the heat and freshwater fluxes. The Indian monsoon is described by a novel one-dimensional box model of the tropical atmosphere. It includes representations of the radiative and surface fluxes, the hydrological cycle and surface hydrology. Despite its high degree of idealization, the model satisfactorily captures relevant aspects of the observed monsoon dynamics, such as the annual course of precipitation and the onset and withdrawal of the summer monsoon. Also, the model exhibits the sensitivity to changes in greenhouse gas and sulfate aerosol concentrations that are known from comprehensive models. A simplified version of the monsoon model is employed for the identification of changes in the qualitative system behavior against changes in boundary conditions. The most notable result is that under summer conditions a saddle-node bifurcation occurs at critical values of the planetary albedo or insolation. Furthermore, the system exhibits two stable equilibria: besides the wet summer monsoon, a stable state exists which is characterized by a weak hydrological cycle. These results are remarkable insofar, as they indicate that anthropogenic perturbations of the planetary albedo such as sulfur emissions and/or land-use changes could destabilize the Indian summer monsoon. The reduced-form THC model is employed in an exemplary integrated assessment application. Drawing on the conceptual and methodological framework of the tolerable windows approach, emissions corridors (i.e., admissible ranges of CO2- emissions) are derived that limit the risk of a THC collapse while considering expectations about the socio-economically acceptable pace of emissions reductions. Results indicate, for example, a large dependency of the width of the emissions corridor on climate and hydrological sensitivity: for low values of climate and/or hydrological sensitivity, the corridor boundaries are far from being transgressed by any plausible emissions scenario for the 21st century. In contrast, for high values of both quantities low non-intervention scenarios leave the corridor already in the early decades of the 21st century. This implies that if the risk of a THC collapse is to be kept low, business-as-usual paths would need to be abandoned within the next two decades. All in all, this thesis highlights the value of reduced-form modeling by presenting a number of applications of this class of models, ranging from sensitivity and bifurcation analysis to integrated assessment. The results achieved and conclusions drawn provide a useful contribution to the scientific and policy debate about the consequences of anthropogenic climate change and the long-term goals of climate protection. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2003/2004.
In-plane strain and shape analysis of Si/SiGe nanostructures by grazing incidence diffraction
(2000)
We consider networks of chaotic maps with different network topologies. In each case, they are coupled in such a way as to generate synchronized chaotic solutions. By using the methods of control of chaos we are controlling a single map into a predetermined trajectory. We analyze the reaction of the network to such a control. Specifically we show that a line of one-dimensional logistic maps that are unidirectionally coupled can be controlled from the first oscillator whereas a ring of diffusively coupled maps cannot be controlled for more than 5 maps. We show that rings with more elements can be controlled if every third map is controlled. The dependence of unidirectionally coupled maps on noise is studied. The noise level leads to a finite synchronization lengths for which maps can be controlled by a single location. A two-dimensional lattice is also studied. (C) 2005 American Institute of Physics
This paper theoretically analyzes a dielectric elastomer tube actuator (DETA). Subject to a voltage difference between the inner and outer surfaces, the actuator reduces in thickness and expands in length, so that the same voltage will induce an even higher electric field. This positive feedback may cause the actuator to thin down drastically, resulting in electrical breakdown. We obtain an analytical solution of the actuator undergoing finite deformation when the elastomer obeys the neo-Hookean model. The critical strain of actuation is calculated in terms of various parameters of design. We also discuss the effect of the strain-stiffening on electromechanical behavior of DETAs by using the model of freely joined links. (C) 2010 American Institute of Physics. [doi:10.1063/1.3490186]
A membrane of a dielectric elastomer coated with compliant electrodes may form wrinkles as the applied voltage is ramped up. We present a combination of experiment and theory to investigate the transition to wrinkles using a clamped membrane subject to a constant force and a voltage ramp. Two types of transitions are identified. In type-I transition, the voltage-stretch curve is N-shaped, and flat and wrinkled regions coexist in separate areas of the membrane. The type-I transition progresses by nucleation of small wrinkled regions, followed by the growth of the wrinkled regions at the expense of the flat regions, until the entire membrane is wrinkled. By contrast, in type-II transition, the voltage-stretch curve is monotonic, and the entire flat membrane becomes wrinkled with no nucleation barrier. The two types of transitions are analogous to the first and the second order phase transitions. While the type-I transition is accompanied by a jump in the vertical displacement, type-II transition is accompanied by a continuous change in the vertical displacement. Such transitions may enable applications in muscle-like actuation and energy harvesting, where large deformation and large energy of conversion are desired.
New wave frequency and amplitude models for the nightside and dayside chorus waves are built based on measurements from the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrument onboard the Van Allen Probes. The corresponding 3D diffusion coefficients are systematically obtained. Compared with previous commonly-used (typical) parameterizations, the new parameterizations result in differences in diffusion rates that depend on the energy and pitch angle. Furthermore, one-year 3D diffusive simulations are performed using the Versatile Electron Radiation Belt (VERB) code. Both typical and new wave parameterizations simulation results are in a good agreement with observations at 0.9 MeV. However, the new parameterizations for nightside chorus better reproduce the observed electron fluxes. These parameterizations will be incorporated into future modeling efforts.
Atmospheric interactions with land surface in the arctic based on regional climate model solutions
(2014)
How do diverse dynamical patterns arise from the topology of complex networks? We study synchronization dynamics in the cortical brain network of the cat, which displays a hierarchically clustered organization, by modeling each node (cortical area) with a subnetwork of interacting excitable neurons. We find that in the biologically plausible regime the dynamics exhibits a hierarchical modular organization, in particular, revealing functional clusters coinciding with the anatomical communities at different scales. Our results provide insights into the relationship between network topology and functional organization of complex brain networks.
Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in the connection strengths. Here we study synchronization in weighted complex networks and show that the synchronizability of random networks with a large minimum degree is determined by two leading parameters: the mean degree and the heterogeneity of the distribution of node's intensity, where the intensity of a node, defined as the total strength of input connections, is a natural combination of topology and weights. Our results provide a possibility for the control of synchronization in complex networks by the manipulation of a few parameters
Noise-sustained and controlled synchronization of stirred excitable media by external forcing
(2005)
Most of the previous studies on constructive effects of noise in spatially extended systems have focused on static media, e.g., of the reaction diffusion type. Because many active chemical or biological processes occur in a fluid environment with mixing, we investigate here the interplay among noise, excitability, mixing and external forcing in excitable media advected by a chaotic flow, in a two-dimensional FitzHugh-Nagumo model described by a set of reaction- advection-diffusion equations. In the absence of external forcing, noise may generate sustained coherent oscillations of the media in a range of noise intensities and stirring rates. We find that these noise-sustained oscillations can be synchronized by external periodic signals much smaller than the threshold. Analysis of the locking regions in the parameter space of the signal period, stirring rate and noise intensity reveals that the mechanism underlying the synchronization behaviour is a matching between the time scales of the forcing signal and the noise-sustained oscillations. The results demonstrate that, in the presence of a suitable level of noise, the stirred excitable media act as self-sustained oscillatory systems and become much easier to be entrained by weak external forcing. Our results may be verified in experiments and are useful to understand the synchronization of population dynamics of oceanic ecological systems by annual cycles
Dynamical organization of connection weights is studied in scale-free networks of chaotic oscillators, where the coupling strength of a node from its neighbors develops adaptively according to the local synchronization property between the node and its neighbors. We find that when complete synchronization is achieved, the coupling strength becomes weighted and correlated with the topology due to a hierarchical transition to synchronization in heterogeneous networks. Importantly, such an adaptive process enhances significantly the synchronizability of the networks, which could have meaningful implications in the manipulation of dynamical networks
We investigate noise-controlled resonant response of active media to weak periodic forcing, both in excitable and oscillatory regimes. In the excitable regime, we find that noise-induced irregular wave structures can be reorganized into frequency-locked resonant patterns by weak signals with suitable frequencies. The resonance occurs due to a matching condition between the signal frequency and the noise-induced inherent time scale of the media. m:1 resonant regions similar to the Arnold tongues in frequency locking of self-sustained oscillatory media are observed. In the self-sustained oscillatory regime, noise also controls the oscillation frequency and reshapes significantly the Arnold tongues. The combination of noise and weak signal thus could provide an efficient tool to manipulate active extended systems in experiments
We study synchronization behavior in networks of coupled chaotic oscillators with heterogeneous connection degrees. Our focus is on regimes away from the complete synchronization state, when the coupling is not strong enough, when the oscillators are under the influence of noise or when the oscillators are nonidentical. We have found a hierarchical organization of the synchronization behavior with respect to the collective dynamics of the network. Oscillators with more connections (hubs) are synchronized more closely by the collective dynamics and constitute the dynamical core of the network. The numerical observation of this hierarchical synchronization is supported with an analysis based on a mean field approximation and the master stability function. (C) 2006 American Institute of Physics
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
The thermal behavior of poly(methoxydiethylenglycol acrylate) (PMDEGA) is studied in thin hydrogel films on solid supports and is compared with the behavior in aqueous solution. The PMDEGA hydrogel film thickness is varied from 2 to 422 nm. Initially, these films are homogenous, as measured with optical microscopy, atomic force microscopy, X-ray reflectivity, and grazing-incidence small-angle X-ray scattering (GISAXS). However, they tend to de-wet when stored under ambient conditions. Along the surface normal, no long-ranged correlations between substrate and film surface are detected with GISAXS, due to the high mobility of the polymer at room temperature. The swelling of the hydrogel films as a function of the water vapor pressure and the temperature are probed for saturated water vapor pressures between 2,380 and 3,170 Pa. While the swelling capability is found to increase with water vapor pressure, swelling in dependence on the temperature revealed a collapse phase transition of a lower critical solution temperature type. The transition temperature decreases from 40.6 A degrees C to 36.6 A degrees C with increasing film thickness, but is independent of the thickness for very thin films below a thickness of 40 nm. The observed transition temperature range compares well with the cloud points observed in dilute (0.1 wt.%) and semi-dilute (5 wt.%) solution which decrease from 45 A degrees C to 39 A degrees C with increasing concentration.
We study the properties of classical and quantum strongly nonlinear chains by means of extensive numerical simulations. Due to strong nonlinearity, the classical dynamics of such chains remains chaotic at arbitrarily low energies. We show that the collective excitations of classical chains are described by sound waves whose decay rate scales algebraically with the wave number with a generic exponent value. The properties of the quantum chains are studied by the quantum Monte Carlo method and it is found that the low-energy excitations are well described by effective phonon modes with the sound velocity dependent on an effective Planck constant. Our results show that at low energies the quantum effects lead to a suppression of chaos and drive the system to a quasi-integrable regime of effective phonon modes.
We investigate the transition from incoherence to global collective motion in a three-dimensional swarming model of agents with helical trajectories, subject to noise and global coupling. Without noise this model was recently proposed as a generalization of the Kuramoto model and it was found that alignment of the velocities occurs discontinuously for arbitrarily small attractive coupling. Adding noise to the system resolves this singular limit and leads to a continuous transition, either to a directed collective motion or to center-of-mass rotations.
We report on the effect of spatially correlated noise on the velocities of self-propelled particles.
Correlations in the random forces acting on self-propelled particles can induce directed collective motion, i.e., swarming.
Even with repulsive coupling in the velocity directions, which favors a disordered state, strong correlations in the fluctuations can align the velocities locally leading to a macroscopic, turbulent velocity field.
On the other hand, while spatially correlated noise is aligning the velocities locally, the swarming transition to globally directed motion is inhibited when the correlation length of the noise is nonzero, but smaller than the system size.
We analyze the swarming transition in d-dimensional space in a mean field model of globally coupled velocity vectors.
We show that "stochastic bursting" is observed in a ring of unidirectional delay-coupled noisy excitable systems, thanks to the combinational action of time-delayed coupling and noise. Under the approximation of timescale separation, i.e., when the time delays in each connection are much larger than the characteristic duration of the spikes, the observed rather coherent spike pattern can be described by an idealized coupled point processwith a leader-follower relationship. We derive analytically the statistics of the spikes in each unit, the pairwise correlations between any two units, and the spectrum of the total output from the network. Theory is in good agreement with the simulations with a network of theta-neurons. Published under license by AIP Publishing.
We show that a combined action of noise and delayed feedback on an excitable theta-neuron leads to rather coherent stochastic bursting. An idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
We present the Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm for automatic inference of the electron number density from plasma wave measurements made on board NASA's Van Allen Probes mission. A feedforward neural network is developed to determine the upper hybrid resonance frequency, fuhr, from electric field measurements, which is then used to calculate the electron number density. In previous missions, the plasma resonance bands were manually identified, and there have been few attempts to do robust, routine automated detections. We describe the design and implementation of the algorithm and perform an initial analysis of the resulting electron number density distribution obtained by applying NURD to 2.5 years of data collected with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite of the Van Allen Probes mission. Densities obtained by NURD are compared to those obtained by another recently developed automated technique and also to an existing empirical plasmasphere and trough density model.
We present the PINE (Plasma density in the Inner magnetosphere Neural network‐based Empirical) model ‐ a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural‐network‐based Upper hybrid Resonance Determination) algorithm for the period of 1 October 2012 to 1 July 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2≤L≤6 and all local times. We validate and test the model by measuring its performance on independent data sets withheld from the training set and by comparing the model‐predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). The optimal model is based on the 96 h time history of Kp, AE, SYM‐H, and F10.7 indices. The model successfully reproduces erosion of the plasmasphere on the nightside and plume formation and evolution. We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in situ observations by using machine learning techniques.
Abstract
In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network‐based models capture the large‐scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non‐existent, as occurs during geomagnetic storms, the performance of NNs significantly decreases, as networks inherently cannot learn from the limited number of examples. This limitation can be overcome by employing physics‐based modeling during strong geomagnetic storms. Physics‐based models show a stable performance during periods of disturbed geomagnetic activity if they are correctly initialized and configured. In this study, we illustrate how to combine the neural network‐ and physics‐based models of the plasmasphere in an optimal way by using data assimilation. The proposed approach utilizes advantages of both neural network‐ and physics‐based modeling and produces global plasma density reconstructions for both quiet and disturbed geomagnetic activity, including extreme geomagnetic storms. We validate the models quantitatively by comparing their output to the in‐situ density measurements from RBSP‐A for an 18‐month out‐of‐sample period from June 30, 2016 to January 01, 2018 and computing performance metrics. To validate the global density reconstructions qualitatively, we compare them to the IMAGE EUV images of the He+ particle distribution in the Earth's plasmasphere for a number of events in the past, including the Halloween storm in 2003.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
Bimetallic nanostructures comprising plasmonic and catalytic components have recently emerged as a promising approach to generate a new type of photo-enhanced nanoreactors. Most designs however concentrate on plasmon-induced charge separation, leaving photo-generated heat as a side product.
This work presents a photoreactor based on Au-Pd nanorods with an optimized photothermal conversion, which aims to effectively utilize the photo-generated heat to increase the rate of Pd-catalyzed reactions. Dumbbell-shaped Au nanorods were fabricated via a seed-mediated growth method using binary surfactants. Pd clusters were selectively grown at the tips of the Au nanorods, using the zeta potential as a new synthetic parameter to indicate the surfactant remaining on the nanorod surface.
The photothermal conversion of the Au-Pd nanorods was improved with a thin layer of polydopamine (PDA) or TiO2.
As a result, a 60% higher temperature increment of the dispersion compared to that for bare Au rods at the same light intensity and particle density could be achieved.
The catalytic performance of the coated particles was then tested using the reduction of 4-nitrophenol as the model reaction. Under light, the PDA-coated Au-Pd nanorods exhibited an improved catalytic activity, increasing the reaction rate by a factor 3.
An analysis of the activation energy confirmed the photoheating effect to be the dominant mechanism accelerating the reaction. Thus, the increased photothermal heating is responsible for the reaction acceleration.
Interestingly, the same analysis shows a roughly 10% higher reaction rate for particles under illumination compared to under dark heating, possibly implying a crucial role of localized heat gradients at the particle surface.
Finally, the coating thickness was identified as an essential parameter determining the photothermal conversion efficiency and the reaction acceleration.
We present observations of three-dimensional magnetic power spectra in wavevector space to investigate the anisotropy and scalings of sub-Alfvenic solar wind turbulence at magnetohydrodynamic (MHD) scale using the Magnetospheric Multiscale spacecraft. The magnetic power distributions are organized in a new coordinate determined by wavevectors ((kappa) over cap) and background magnetic field ((b) over cap (0)) in Fourier space. This study utilizes two approaches to determine wavevectors: the singular value decomposition method and multispacecraft timing analysis. The combination of the two methods allows an examination of the properties of magnetic field fluctuations in terms of mode compositions without any spatiotemporal hypothesis. Observations show that fluctuations (delta B-perpendicular to 1) in the direction perpendicular to (kappa) over cap and (b) over cap (0) prominently cascade perpendicular to (b) over cap (0), and such anisotropy increases with wavenumbers. The reduced power spectra of 6.8 11 follow Goldreich-Sridhar scalings: (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-5/3) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-2). In contrast, fluctuations within the (k) over cap(b) over cap (0) plane show isotropic behaviors: perpendicular power distributions are approximately the same as parallel distributions. The reduced power spectra of fluctuations within the (k) over cap(b) over cap (0) plane follow the scalings (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-3/2) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-3/2). Comparing frequency-wavevector spectra with theoretical dispersion relations of MHD modes, we find that delta B-perpendicular to 1 are probably associated with Alfven modes. On the other hand, magnetic field fluctuations within the (k) over cap(b) over cap (0) plane more likely originate from fast modes based on their isotropic behaviors. The observations of anisotropy and scalings of different magnetic field components are consistent with the predictions of current compressible MHD theory. Moreover, for the Alfvenic component, the ratio of cascading time to the wave period is found to be a factor of a few, consistent with critical balance in the strong turbulence regime. These results are valuable for further studies of energy compositions of plasma turbulence and their effects on energetic particle transport.
Fast actuation speed, large-shape deformation and robust responsiveness are critical to synthetic soft actuators. A simultaneous optimization of all these aspects without trade-offs remains unresolved. Here we describe porous polymer actuators that bend in response to acetone vapour (24 kPa, 20 degrees C) at a speed of an order of magnitude faster than the state-of-the-art, coupled with a large-scale locomotion. They are meanwhile multi-responsive towards a variety of organic vapours in both the dry and wet states, thus distinctive from the traditional gel actuation systems that become inactive when dried. The actuator is easy-to-make and survives even after hydrothermal processing (200 degrees C, 24 h) and pressing-pressure (100 MPa) treatments. In addition, the beneficial responsiveness is transferable, being able to turn 'inert' objects into actuators through surface coating. This advanced actuator arises from the unique combination of porous morphology, gradient structure and the interaction between solvent molecules and actuator materials.
Many studies of synchronization properties of coupled oscillators, based on the classical Kuramoto approach, focus on ensembles coupled via a mean field. Here we introduce a setup of Kuramoto-type phase oscillators coupled via two mean fields. We derive stability properties of the incoherent state and find traveling wave solutions with different locking patterns; stability properties of these waves are found numerically. Mostly nontrivial states appear when the two fields compete, i.e. one tends to synchronize oscillators while the other one desynchronizes them. Here we identify normal branches which bifurcate from the incoherent state in a usual way, and anomalous branches, appearance of which cannot be described as a bifurcation. Furthermore, hybrid branches combining properties of both are described. In the situations where no stable traveling wave exists, modulated quasiperiodic in time dynamics is observed. Our results indicate that a competition between two coupling channels can lead to a complex system behavior, providing a potential generalized framework for understanding of complex phenomena in natural oscillatory systems.
Low cost, large area, lightweight, stretchable piezoelectric films, based on space-charge electret with a foam structure (i.e., ferroelectrets or piezoelectrets), have been fabricated by using commercially available irradiation cross-linked poly(propylene) (IXPP) foam sheets. Piezoelectric d(33) coefficients are as high as 100pCN(-1). The piezoelectric performance in such IXPP films is well preserved for repeated strains of less than 10%. Piezoelectric d(33) coefficients are frequency independent in the range from 2 to 100Hz. Such new class materials may be applied in sensory skins, smart clothing, bio-inspired systems, microenergy harvesters, and so on.
Engineering the interface between the perovskite absorber and the charge-transporting layers has become an important method for improving the charge extraction and open-circuit voltage (V-OC) of hybrid perovskite solar cells. Conjugated polymers are particularly suited to form the hole-transporting layer, but their hydrophobicity renders it difficult to solution-process the perovskite absorber on top. Herein, oxygen plasma treatment is introduced as a simple means to change the surface energy and work function of hydrophobic polymer interlayers for use as p-contacts in perovskite solar cells. We find that upon oxygen plasma treatment, the hydrophobic surfaces of different prototypical p-type polymers became sufficiently hydrophilic to enable subsequent perovskite junction processing. In addition, the oxygen plasma treatment also increased the ionization potential of the polymer such that it became closer to the valance band energy of the perovskite. It was also found that the oxygen plasma treatment could increase the electrical conductivity of the p-type polymers, facilitating more efficient charge extraction. On the basis of this concept, inverted MAPbI(3) perovskite devices with different oxygen plasma-treated polymers such as P3HT, P3OT, polyTPD, or PTAA were fabricated with power conversion efficiencies of up to 19%.
2D Ruddlesden-Popper perovskite (RPP) solar cells have excellent environmental stability. However, the power conversion efficiency (PCE) of RPP cells remains inferior to 3D perovskite-based cells. Herein, 2D (CH3(CH2)(3)NH3)(2)(CH3NH3)(n-1)PbnI3n+1 perovskite cells with different numbers of [PbI6](4-) sheets (n = 2-4) are analyzed. Photoluminescence quantum yield (PLQY) measurements show that nonradiative open-circuit voltage (V-OC) losses outweigh radiative losses in materials with n > 2. The n = 3 and n = 4 films exhibit a higher PLQY than the standard 3D methylammonium lead iodide perovskite although this is accompanied by increased interfacial recombination at the top perovskite/C-60 interface. This tradeoff results in a similar PLQY in all devices, including the n = 2 system where the perovskite bulk dominates the recombination properties of the cell. In most cases the quasi-Fermi level splitting matches the device V-OC within 20 meV, which indicates minimal recombination losses at the metal contacts. The results show that poor charge transport rather than exciton dissociation is the primary reason for the reduction in fill factor of the RPP devices. Optimized n = 4 RPP solar cells had PCEs of 13% with significant potential for further improvements.
A series of novel platinum-containing carbazole monomers and polymers was synthesized and fully characterized by UV-VIS absorption, luminescence, and photoinduced absorption studies. In these compounds, a carbazole unit is incorporated into the main chain via either a para- or a meta-linkage. We discuss the effects of linkage and polymerization on the energy levels of S-1, T-1, and T-n. The S-1-T-1 splitting observed for the meta-linked monomer (0.4 eV) is only half of that in the para-linked monomer (0.8 eV). Upon polymerization, the exchange energy in the para- linked compound reduces, yet still remains larger than in the meta-linked polymer. We attribute the difference in exchange energy to the difference in wave function overlap between electron and hole in these compounds. (c) 2006 American Institute of Physics
While the performance of laboratory-scale organic solar cells (OSCs) continues to grow, development of high efficiency large area OSCs remains a big challenge. Although a few attempts to produce large area organic solar cells (OSCs) have been reported, there are still challenges on the way to realizing efficient module devices, such as the low compatibility of the thickness-sensitive active layer with large area coating techniques, the frequent need for toxic solvents and tedious optimization processes used during device fabrication. In this work, highly efficient thickness-insensitive OSCs based on PTB7-Th:PC71BM that processed with single-component green solvent 2-methylanisole are presented, in which both junction thickness limitation and solvent toxicity issues are simultaneously addressed. Careful investigation reveals that this green solvent prevents the evolution of PC71BM into large area clusters resulting in reduced charge carrier recombination, and largely eliminates trapping centers, and thus improves the thickness tolerance of the films. These findings enable us to address the scalability and solvent toxicity issues and to fabricate a 16 cm(2) OSC with doctor-blade coating with a state-of-the-art power conversion efficiency of 7.5% using green solvent.
Spectroscopic observations play essential roles in astrophysics. They are crucial for determining physical parameters in our Universe, providing information about the chemistry of various astronomical environments. The proper execution of the spectroscopic analysis requires accounting for all the physical effects that are compatible to the signal-to-noise ratio. We find in this paper the influence on spectroscopy from the atomic/ground state alignment owing to anisotropic radiation and modulated by interstellar magnetic field, has significant impact on the study of interstellar gas. In different observational scenarios, we comprehensively demonstrate how atomic alignment influences the spectral analysis and provide the expressions for correcting the effect. The variations are even more pronounced for multiplets and line ratios. We show the variation of the deduced physical parameters caused by the atomic alignment effect, including alpha-to-iron ratio ([X/Fe]) and ionization fraction. Synthetic observations are performed to illustrate the visibility of such effect with current facilities. A study of Photodissociation regions in rho Ophiuchi cloud is presented to demonstrate how to account for atomic alignment in practice. Our work has shown that due to its potential impact, atomic alignment has to be included in an accurate spectroscopic analysis of the interstellar gas with current observational capability.
Magnetic fields play important roles in many astrophysical processes. However, there is no universal diagnostic for the magnetic fields in the interstellar medium (ISM) and each magnetic tracer has its limitation. Any new detection method is thus valuable. Theoretical studies have shown that submillimetre fine-structure lines are polarized due to atomic alignment by ultraviolet photon-excitation, which opens up a new avenue to probe interstellar magnetic fields. We will, for the first time, perform synthetic observations on the simulated three-dimensional ISM to demonstrate the measurability of the polarization of submillimetre atomic lines. The maximum polarization for different absorption and emission lines expected from various sources, including star-forming regions are provided. Our results demonstrate that the polarization of submillimetre atomic lines is a powerful magnetic tracer and add great value to the observational studies of the submilimetre astronomy.
The galactic interstellar medium is magnetized and turbulent. The magnetic field and turbulence play important roles in many astrophysical mechanisms, including cosmic ray transport, star formation, etc. Therefore, measurements of magnetic field and turbulence information are crucial for the proper interpretation of astronomical observations. Nonetheless, the magnetic field observation is quite challenging, especially, there is not universal magnetic tracer for diffuse medium. Moreover, the modelling of turbulence can be oversimplified due to the lack of observational tools to diagnose the plasma properties of the turbulence in the galactic interstellar medium. The studies presented in this thesis have addressed these challenges by bridging the theoretical studies of magnetic field and turbulence with numerical simulations and observations.
The following research are presented in this thesis. The first observational evidence of the novel magnetic tracer, ground state alignment (GSA), is discovered, revealing the three-dimensional magnetic field as well as 2 orders of magnitude higher precision comparing to previous observational study in the stellar atmosphere of the post-AGB 89 Herculis. Moreover, the application of GSA in the sub-millimeter fine-structure lines is comprehensively studied for different elements and with magnetohydrodynamic simulations. Furthermore, the influence of GSA effect on the spectroscopy is analyzed and it is found that measurable variation will be produced on the spectral line intensity and the line ratio without accounting for the optical pumping process or magnetic field.
Additionally, a novel method to measure plasma modes in the interstellar medium, Signatures from Polarization Analysis (SPA), is proposed and applied to real observations. Magneto-sonic modes are discovered in different types of interstellar medium. An explanation is provided for the long-standing mystery, the origin of γ-ray enhanced emission “Cygnus Cocoon”, based on the comparison between the outcome of SPA and multi-waveband observational data. These novel methods have strong potentials for broader observational applications and will play crucial roles in future multi-wavelength astronomy.
The polarization signatures of blazar emissions are known to be highly variable. In addition to small fluctuations of the polarization angle around a mean value, large (greater than or similar to 180 degrees) polarization angle swings are sometimes observed. We suggest that such phenomena can be interpreted as arising from light travel time effects within an underlying axisymmetric emission region. We present the first simultaneous fitting of the multi-wavelength spectrum, variability, and time-dependent polarization features of a correlated optical and gamma-ray flaring event of the prominent blazar 3C279, which was accompanied by a drastic change in its polarization signatures. This unprecedented combination of spectral, variability, and polarization information in a coherent physical model allows us to place stringent constraints on the particle acceleration and magnetic field topology in the relativistic jet of a blazar, strongly favoring a scenario in which magnetic energy dissipation is the primary driver of the flare event.
We present a detailed analysis of time-and energy-dependent synchrotron polarization signatures in a shock-in-jet model for gamma-ray blazars. Our calculations employ a full three-dimensional radiation transfer code, assuming a helical magnetic field throughout the jet. The code considers synchrotron emission from an ordered magnetic field, and takes into account all light-travel-time and other relevant geometric effects, while the relevant synchrotron self-Compton and external Compton effects are handled with the two-dimensional Monte-Carlo/Fokker-Planck (MCFP) code. We consider several possible mechanisms through which a relativistic shock propagating through the jet may affect the jet plasma to produce a synchrotron and high-energy flare. Most plausibly, the shock is expected to lead to a compression of the magnetic field, increasing the toroidal field component and thereby changing the direction of the magnetic field in the region affected by the shock. We find that such a scenario leads to correlated synchrotron + synchrotron-self-Compton flaring, associated with substantial variability in the synchrotron polarization percentage and position angle. Most importantly, this scenario naturally explains large polarization angle rotations by greater than or similar to 180 degrees, as observed in connection with gamma-ray flares in several blazars, without the need for bent or helical jet trajectories or other nonaxisymmetric jet features.
We compute the local spectrum of the magnetic field near a metallic microstructure at finite temperature. Our main focus is on deviations from a plane-layered geometry for which we review the main properties. Arbitrary geometries are handled with the help of numerical calculations based on surface integral equations. The magnetic noise shows a significant polarization anisotropy above flat wires with finite lateral width, in stark contrast to an infinitely wide wire. Within the limits of a two-dimensional setting, our results provide accurate estimates for loss and dephasing rates in so-called `atom chip traps' based on metallic wires. A simple approximation based on the incoherent summation of local current elements gives qualitative agreement with the numerics, but fails to describe current correlations among neighboring objects.
Microfabricated solid-state surfaces, also called atom chip', have become a well-established technique to trap and manipulate atoms. This has simplified applications in atom interferometry, quantum information processing, and studies of many-body systems. Magnetic trapping potentials with arbitrary geommetries are generated with atom chip by miniaturized current-carrying conductors integrated on a solid substrate. Atoms can be trapped and cooled to microKelvin and even nanoKelvin temperatures in such microchip trap. However, cold atoms can be significantly perturbed by the chip surface, typically held at room temperature. The magnetic field fluctuations generated by thermal currents in the chip elements may induce spin flips of atoms and result in loss, heating and decoherence. In this thesis, we extend previous work on spin flip rates induced by magnetic noise and consider the more complex geometries that are typically encountered in atom chips: layered structures and metallic wires of finite cross-section. We also discuss a few aspects of atom chips traps built with superconducting structures that have been suggested as a means to suppress magnetic field fluctuations. The thesis describes calculations of spin flip rates based on magnetic Green functions that are computed analytically and numerically. For a chip with a top metallic layer, the magnetic noise depends essentially on the thickness of that layer, as long as the layers below have a much smaller conductivity. Based on this result, scaling laws for loss rates above a thin metallic layer are derived. A good agreement with experiments is obtained in the regime where the atom-surface distance is comparable to the skin depth of metal. Since in the experiments, metallic layers are always etched to separate wires carrying different currents, the impact of the finite lateral wire size on the magnetic noise has been taken into account. The local spectrum of the magnetic field near a metallic microstructure has been investigated numerically with the help of boundary integral equations. The magnetic noise significantly depends on polarizations above flat wires with finite lateral width, in stark contrast to an infinitely wide wire. Correlations between multiple wires are also taken into account. In the last part, superconducting atom chips are considered. Magnetic traps generated by superconducting wires in the Meissner state and the mixed state are studied analytically by a conformal mapping method and also numerically. The properties of the traps created by superconducting wires are investigated and compared to normal conducting wires: they behave qualitatively quite similar and open a route to further trap miniaturization, due to the advantage of low magnetic noise. We discuss critical currents and fields for several geometries.
We investigate the lifetime of magnetically trapped atoms above a planar, layered atom chip structure. Numerical calculations of the thermal magnetic noise spectrum are performed, based on the exact magnetic Green function and multi layer reflection coefficients. We have performed lifetime measurements where the center of a side guide trap is laterally shifted with respect to the current carrying wire using additional bias fields. Comparing the experiment to theory, we find a fair agreement and demonstrate that for a chip whose topmost layer is metallic, the magnetic noise depends essentially on the thickness of that layer, as long as the layers below have a, much smaller conductivity; essentially the same magnetic noise would be obtained with a metallic membrane suspended in vacuum. Based on our theory we give general scaling laws of how to reduce the effect of surface magnetic noise on the trapped atoms
Based on micromagnetic simulations and experimental observations of the magnetization and lattice dynamics after the direct optical excitation of the magnetic insulator Bi : YIG or indirect excitation via an optically opaque Pt/Cu double layer, we disentangle the dynamical effects of magnetic anisotropy and magneto-elastic coupling. The strain and temperature of the lattice are quantified via modeling ultrafast x-ray diffraction data. Measurements of the time-resolved magneto-optical Kerr effect agree well with the magnetization dynamics simulated according to the excitation via two mechanisms: the magneto-elastic coupling to the experimentally verified strain dynamics and the ultrafast temperature-induced transient change in the magnetic anisotropy. The numerical modeling proves that, for direct excitation, both mechanisms drive the fundamental mode with opposite phase. The relative ratio of standing spin wave amplitudes of higher-order modes indicates that both mechanisms are substantially active.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
The performance of highly soluble regioregular poly[ (3-hexylthiophene)-co-(3-octylthiophetie)] (P3HTOT) as a semiconducting material in organic field-effect transistors (OFETs) is presented in comparison to that of the corresponding homopolymers. Transistors made from as-prepared layers of P3HTOT exhibit a mobility of ca. 7 x 10(-3) cm(2) V-1 s(-1), which is comparable to the performance of transistors made from as-prepared poly(3-hexylthiophene) (P3HT) and almost 6 times larger than the mobility of transistors prepared with poly(3-octylthiophene) (P3OT). On the other hand, the solubility parameter delta(p) of P3HTOT is close to that of the highly soluble P3OT. Moreover, compared to a physical blend of poly(3-hexylthiophene) and poly(3-octylthiophene), the mobility of P3HTOT devices is almost twice as large and the performance does not degrade upon annealing at elevated temperatures. Therefore, the copolymer approach outlined here may be one promising step toward an optimum balance between a Sufficient processability of the polymers from common organic solvents, a high solid state order, and applicable OFET performances
The optical, structural, and electrical properties of thin layers made from poly(3-hexylthiophene) (P3HT) samples of different molecular weights are presented. As reported in a previous paper by Kline et al., Adv. Mater 2003, 15, 1519, the mobilities of these layers are a strong function of the molecular weight, with the largest mobility found for the largest molecular weight. Atomic force microscopy studies reveal a complex polycrystalline morphology which changes considerably upon annealing. X-ray studies show the occurrence of a layered phase for all P3HT fractions, especially after annealing at 1.50 degreesC . However, there is no clear correlation between the differences in the transport properties and the data from structural investigations. In order to reveal the processes limiting the mobility in these layers, the transistor properties were investigated as a function of temperature. The mobility decreases continuously with increasing temperatures; with the same trend pronounced thermochromic effects of the P3HT films occur. Apparently, the polymer chains adopt a more twisted, disordered conformation at higher temperatures, leading to interchain transport barriers. We conclude that the backbone conformation of the majority of the bulk material rather than the crystallinity of the layer is the most crucial parameter controlling the charge transport in these P3HT layers. This interpretation is supported by the significant blue-shift of the solid-state absorption spectra with decreasing molecular weight, which is indicative of a larger distortion of the P3HT backbone in the low-molecular weight P3HT layers
The effect of oxygen plasma treatment and/or silanization with hexamethyldisilazane (HMDS) on the surface chemistry and the morphology of the SiO2-gate insulator were studied with respect to the performance of organic field effect transistors. Using X-ray photoelectron spectroscopy (XPS), it is shown that silanization leads to the growth of a polysiloxane interfacial layer and that longer silanization times increase the thickness of this layer. Most important, silanization reduces the signal from surface contaminations such as oxidized hydrocarbon molecules. In fact, the lowest concentration of these contaminations was found after a combined oxygen plasma/silanization treatment. The results of these investigations were correlated with the characteristic device parameters of polymer field effect transistors with poly(3-hexylthiophene)s as the semiconducting layer. We found that the field effect mobility correlates with the concentration of contaminations as measured by XPS. We, finally, demonstrate that silanization significantly improves the operational stability of the device in air compared to the untreated devices
The mammalian brain is, with its numerous neural elements and structured complex connectivity, one of the most complex systems in nature. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex networks. Here, we try to shed some light on the relationship between structural and functional connectivities by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the cortical areas by a subnetwork of interacting excitable neurons (multilevel model) and by a neural mass model (population model). With weak couplings, the multilevel model displays biologically plausible dynamics and the synchronization patterns reveal a hierarchical cluster organization in the network structure. We can identify a group of brain areas involved in multifunctional tasks by comparing the dynamical clusters to the topological communities of the network. With strong couplings of multilevel model and by using neural mass model, the dynamics are characterized by well-defined oscillations. The synchronization patterns are mainly determined by the node intensity (total input strengths of a node); the detailed network topology is of secondary importance. The biologically improved multilevel model exhibits similar dynamical patterns in the two regimes. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.
Recent research using the complex network approach has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. It is of importance to understand the implications of such complex network structures in the functional organization of the brain activities. Here we study this problem from the viewpoint of dynamical complex networks. We investigate synchronization dynamics on the corticocortical network of the cat by modeling each node (cortical area) of the network with a sub-network of interacting excitable neurons. We find that the network displays clustered synchronization behavior, and the dynamical clusters coincide with the topological community structures observed in the anatomical network. Our results provide insights into the relationship between the global organization and the functional specialization of the brain cortex.
We investigated the influence of the emitter (amorphous-Si, a-Si, or polythiophene derivatives: poly(3-hexylthiophene), P3HT, and poly(3-[3,6-dioxaheptyl]-thiophene), P3DOT) and the interface passivation (intrinsic a-Si or SiOX and methyl groups or SiOX) on the c-Si based 1 × 1 cm2 planar hybrid heterojunction solar cell parameters. We observed higher short circuit currents for the P3HT or P3DOT/c-Si solar cells than those obtained for a-Si/c-Si devices, independent of the interface passivation. The obtained VOC of 659 mV for the P3DOT/SiOX/c-Si heterojunction solar cell with hydrophilic 3,6-dioxaheptyl side chains is among the highest reported for c-Si/polythiophene devices. The maximum power conversion efficiency, PCE, was 11% for the P3DOT/SiOX/c-Si heterojunction solar cell. Additionally, our wafer lifetime measurements reveal a field effect passivation in the wafer induced by the polythiophenes when deposited on c-Si.