Plexciton Dynamics: Exciton−Plasmon Coupling in a J-Aggregate−Au Nanoshell Complex Provides a Mechanism for Nonlinearity

Ultrafast intraband Auger process in self-doped colloidal quantum dots

The star-coupled linear underdamped system subject to multiplicative quadratic noise and periodic sinusoidal excitation are considered. The multiplicative noise is modeled as a quadratic polynomial function of symmetric trichotomous noise. Firstly, the stability conditions of the system and the stationary solution of the mean field are deduced by establishing the differential equations of the mean field. Then the synchronization conditions of the principal and general particles are obtained respectively. These conditions are beneficial for studying the collective behavior of the system and the motion characteristics of particles in different situations. Then the output signal-to-noise ratio of the coupled system is derived in detail for the first time. Moreover, the dynamic behaviors of the system are analyzed by analytical results and numerical simulations, including the collective behavior under different conditions, and the concrete influence of parameters on the output signal-to-noise ratio.

This article investigates a stochastic fast-slow fishery economic model with Allee effect. The fast-slow dynamic behavior of the deterministic system is discussed by using the theory of singular perturbation. Research shows that singular Hopf bifurcations will occur under the influence of strong Allee effect, while the dynamic behavior of the system will be more complex under the influence of weak Allee effect, resulting in relaxation oscillations. For the stochastic system, the existence of stationary distribution is discussed for both stochastic fast-slow system and system with time scale parameter as ordinary parameter. Then, the stochastic bifurcation behavior of the system is discussed, and it is found that stochastic-P bifurcation and stochastic-D bifurcation will occur. Finally, the correctness of the conclusion is verified through numerical simulation.

Computational analysis of neural networks has a significant effect to recognise the behaviour of synaptic neurons. In the past few years, dynamical systems and nonlinear phenomena related to dynamics of neurons achieve much attention. These structures are typically modeled by set of ordinary differential equations (ODE) which represent a well understanding approach in order to explore dynamic behavior of the network [1]. In fact, these equations are mathematically consistent with the performance of biological structures. One of the parameters which possesses prominent effect on the whole activity of the ensembles is the strength among neural networks that appears in ODE equations. Changing in strength of a typical network might lead to transition between phases which are identified by different local and global bifurcations. In addition, the main aspect which leads to complexity of these structures is interactions between intrinsically oscillatory neurons and their influence on each other [2]. These interactions could be considered as coupled systems among neurons or network oscillators. In coupled systems each oscillator is determined by a coupling strength and the states of oscillatory networks. Therefore, bifurcation analysis can be useful method to be taken into account. In this work, we applied bifurcation theory as a promising mathematical method to reveal the dynamical behavior of a biological system (neural network zoom for this purpose). For this purpose the computational of local and global bifurcations has been done using AUTO software’s package [3]. Knowing that Saddle Node bifurcation (SNB) is used to detect stability of the networks, whereas creations of periodic solutions are corresponds to Hopf bifurcation (HB). Also, it should be noted that heteroclinic bifurcation is utilized to investigate sequential switching activity in the neural ensembles in phase space [4]. All of these approaches employed in analyzing our models. Moreover, the synchronous activity of neural populations could be extracted from ODE equations. Through the simulation of a single ensemble, we concluded that, increase in number of neurons and consequently connections between them in ensembles leads to more complexity in dynamical behavior of the system (Figure ​(Figure1A).1A). We also found that if we consider some specific neurons with dominant coupling strength in comparison with oscillatory neurons in the whole systems, the ensembles will experience instability in some cases. Furthermore, in this research electrical coupling between ensembles had considerable importance for us. Drawing bifurcation diagram for different kinds of ensembles let us to deduced that, when the values of electrical couplings becomes near to each other (Figures 1B and 1C), It shows the chaotic behavior of the system. We also got some interesting result about the effect of strength intensity on intrinsically oscillatory neurons. Further researches on this subject are in progress. Figure 1 A. Phase space diagram of each ensembles. B. Schematic diagram of ensemble. C. The bifurcation diagram of two typical electrical coupling.

In this cumulative dissertation, I want to present my contributions to the field of plasmonic nanoparticle science. Plasmonic nanoparticles are characterised by resonances of the free electron gas around the spectral range of visible light. In recent years, they have evolved as promising components for light based nanocircuits, light harvesting, nanosensors, cancer therapies, and many more. This work exhibits the articles I authored or co-authored in my time as PhD student at the University of Potsdam. The main focus lies on the coupling between localised plasmons and excitons in organic dyes. Plasmon–exciton coupling brings light–matter coupling to the nanoscale. This size reduction is accompanied by strong enhancements of the light field which can, among others, be utilised to enhance the spectroscopic footprint of molecules down to single molecule detection, improve the efficiency of solar cells, or establish lasing on the nanoscale. When the coupling exceeds all decay channels, the system enters the strong coupling regime. In this case, hybrid light–matter modes emerge utilisable as optical switches, in quantum networks, or as thresholdless lasers. The present work investigates plasmon–exciton coupling in gold–dye core–shell geometries and contains both fundamental insights and technical novelties. It presents a technique which reveals the anticrossing in coupled systems without manipulating the particles themselves. The method is used to investigate the relation between coupling strength and particle size. Additionally, the work demonstrates that pure extinction measurements can be insufficient when trying to assess the coupling regime. Moreover, the fundamental quantum electrodynamic effect of vacuum induced saturation is introduced. This effect causes the vacuum fluctuations to diminish the polarisability of molecules and has not yet been considered in the plasmonic context. The work additionally discusses the reaction of gold nanoparticles to optical heating. Such knowledge is of great importance for all potential optical applications utilising plasmonic nanoparticles since optical excitation always generates heat. This heat can induce a change in the optical properties, but also mechanical changes up to melting can occur. Here, the change of spectra in coupled plasmon–exciton particles is discussed and explained with a precise model. Moreover, the work discusses the behaviour of gold nanotriangles exposed to optical heating. In a pump–probe measurement, X-ray probe pulses directly monitored the particles’ breathing modes. In another experiment, the triangles were exposed to cw laser radiation with varying intensities and illumination areas. X-ray diffraction directly measured the particles’ temperature. Particle melting was investigated with surface enhanced Raman spectroscopy and SEM imaging demonstrating that larger illumination areas can cause melting at lower intensities. An elaborate methodological and theoretical introduction precedes the articles. This way, also readers without specialist’s knowledge get a concise and detailed overview of the theory and methods used in the articles. I introduce localised plasmons in metal nanoparticles of different shapes. For this work, the plasmons were mostly coupled to excitons in J-aggregates. Therefore, I discuss these aggregates of organic dyes with sharp and intense resonances and establish an understanding of the coupling between the two systems. For ab initio simulations of the coupled systems, models for the systems’ permittivites are presented, too. Moreover, the route to the sample fabrication – the dye coating of gold nanoparticles, their subsequent deposition on substrates, and the covering with polyelectrolytes – is presented together with the measurement methods that were used for the articles.

The dynamic behavior of complex systems is a well-known challenge within engineering. The major drawback of dependency modeling approaches for system analysis such as the Design Structure Matrix is that they depict a static view on the system and therefore only allow very limited statements about the dynamic behavior of systems even though the structure mainly defines the system's behavior. Approaches to model the dynamic behavior of complex systems such as System Dynamics, do not offer the possibilities of dependency modeling, as static aspects such as the underlying structure of the system cannot be easily described. This paper proposes a framework for a structure-based analysis of the dynamic behavior of systems and combines dependency modeling approaches and System Dynamics. The framework can be used as an approach to generate dynamic system understanding, decision support through simulation experiments and benchmark different process structures by analyzing the relationship between underlying structure and dynamic behavior of the system. This allows for a projection of the performance of the system over time, based on its structure. The paper gives an overview of the framework, including the initial structural Multiple Domain Matrix model, the dynamizing and customizing of the model, model verification, the simulation of different variants of the underlying system structure and the analysis of the system structure based on the simulation results. The framework is applied within an exemplary case study where two different system structures of a design process are analyzed.

In engineering design, an issue for using complex simulation models in system analysis are unknown causes for dynamic system behavior, which make parameterization difficult. This paper presents a case study in which a structured system analysis is used for the parameterization of complex dynamic multi-domain models. The dynamic system behavior of an impact wrench during fastening of a bolt is analyzed and modeled using the Contact and Channel Approach for structured parameterization of a multibody simulation model. This qualitative model building serves as a basis for a simulation model that quantifies the relations of design parameters and system behavior. Comparison with experimental test results is done as a validation. With this approach, the behavior identified in the simulation model could be traced back in a structured way to its cause in the system embodiment. The simulation model represented the real dynamic system behavior with an initial sufficient precision, but showed a lack of precision in detail. On this basis, the Contact and Channel Model was extended by adding additional statistical behavior of the system. Parameters of the system embodiment were identified qualitatively to improve the simulation model. A limitation in qualitative modeling of dynamic changes in the system has been identified that needs to be addressed in further research.

Suspension systems are essential in vehicles to provide both passenger comfort and vibration isolation from road bumps. It is necessary to develop a comprehensive numerical model to study and analyze the dynamic behavior of these systems. This study aims to introduce a comprehensive finite element model to investigate the dynamic behavior of double wishbone vehicle suspension system considering links flexibility. Plane frame element based on Timoshenko beam theory (TBT) is adopted to model the suspension links. Flexibility of the joints connecting the suspension links are modeled using the revolute joint element. Viscoelastic, viscous and proportional damping models are considered to simulate the damping effect. Newmark technique, as unconditionally stable technique is adopted to solve the finite element dynamic equation of motion. The developed procedure is verified by comparing the obtained results with the available analytical and numerical results and an excellent agreement is found. To demonstrate the effectiveness of the developed model, parametric studies are conducted to show the effects of the road bump profiles, the vehicle speed, and the material damping on the dynamic behavior of suspension system. The obtained results are supportive in the design and manufacturing processes of such suspension systems.

Since phasor measurement units (PMUs) are being deployed in power systems, many different applications of such devices are being studied even before they are actually being employed. This paper documents an extensive study on dynamic behavior of the Iranian power system based on eigenvalue and participation factor analysis. The main problem with eigenvalue analysis is that because power systems are highly nonlinear, the result much depends on the operating conditions and the contingency. To overcome this shortcoming some have suggested complicated nonlinear theories, such as Lyapunov functions. Such approaches are not much applicable for such large scale systems. In this study first four different accurate models of the Iran power system, based on a particular loads and generations at four different seasons of 2009, have been developed. Then based on most recorded events, different scenarios are simulated in Iran Power systems and based on eigenvalue analysis the oscillatory modes have been identified. Then the generators which affect the dominant roots are determined by the summation of all the participation factors at different events and at the four models. Fine tuning of installed power system stabilizers of these generators shows a considerable improvement in dynamic behavior of the system at different operating conditions.

As a new type of electronic components, a memristive device is receiving worldwide attention and can enrich the dynamical behaviors of the oscillating system. In this paper, we propose a 3D jerk system by introducing a generalized memristive device. It is found that the dynamical behaviors of the system are sensitive to the initial conditions even the system parameters are fixed, which results in the coexistence of multiple attractors. And there exists different transition behaviors depending on the selection of the parameters and initial values. Thereby, it is one important type of the candidate system for secure communication since the reconstruction of accurate state space becomes more difficult. Moreover, we build a hardware circuit and the experimental results effectively confirm the theoretical analyses.

Large-scale deployment of multiple structures within a Floating Offshore Wind Farm (FOWF) will place many challenges on both the approach to effective integrity management and the demand to reduce through-life operating costs. Additionally, wind farm designers and operators will need to consider the issues related to design robustness in the design of their systems, whereby rational robustness criteria are applied to address possible accidental conditions that are not explicitly addressed in code-specified design basis conditions. This paper will review the significant advances in the approach to integrity management that have been recently made in the mature offshore oil industry and relate them to the nascent offshore wind industry. In particular, the requirement for consideration across the full lifecycle of the potential for threat introduction and the application of controls to prevent or mitigate the evolution of those threats will be described. This includes threats that may be inadvertently introduced during the design, manufacturing and installation phases, in addition to the more traditional rate-based degradation mechanisms such as fatigue, corrosion and wear that occur once the facility is in operation. The challenges that commercial-scale wind farm developments will face relate particularly to integrity issues arising in the design, manufacturing and installation phases, where the focus needs to ensure that degradation threats are not being introduced into the deployment of multiple repeat-copy units. The issues of common cause/common mode degradation threats will have much higher significance for a commercial-scale wind farm, where rectification of a common issue across a large number of floating units could have significant impacts in terms of reliability, operating costs, insurance premiums and power purchase agreements. FOWF mooring system designs are also likely to be more optimized than that for a typical one-off offshore oil facility. This will require the wind farm designer to have a deep understanding of the fundamental dynamic behavior of the overall system and the local dynamic behaviors of the components within the mooring system in order to be able to fully identify the types of threats that may be present. This may also involve robustness considerations where there may be step changes in the dynamic behavior of the system, often termed as cliff-edge effects. The paper will outline issues that wind farm designers will need to consider in building integrity considerations into the design and execution phases of a development, as well as the opportunities that risk-based integrity management processes offer in terms of through-life condition verification and inspection optimization.

Gear systems are commonly used in vehicles, and the vibration of the gear system was paid more attention in recent years. In this paper, the dynamic behavior of gear system with stochastic perturbation of system parameters was analyzed. A stochastic nonlinear dynamic model of gear system, with consideration of the stochastic perturbation of system parameters, was established. The influences of stochastic perturbation of system parameters, such as excitation frequency, damping ratio, and backlash, on the dynamic behavior of the system were discussed. It was found that when the perturbation intensity is weak, the topological structure of the system solutions will not change, and there is no transition of the attractors. But if the perturbation intensity increases further, there will be transition between the attractors. In general, for single-DOF gear system, the multi-periodic attractor will jump to the quasi-period-1 attractor. But the quasi-period-1 attractor will not jump to other attractors. If the perturbation intensity is considerable great, bi-directional transition will occur. Yet, the probability of transition from multi-periodic attractor to quasi-period-1 attractor is greater than the probability of transition from multi-periodic attractor to other attractors. Which provide theoretical basis for effective vibration control of gear system.

In this paper, an improved railway wheelset system is presented. The dynamical behaviors of the system are investigated, including dissipativity and invariance of the system, stability of zero‐equilibrium point, and the bifurcation characteristics of railway wheelset system at zero equilibrium point. Furthermore, the chaotic behaviors of the motion of railway wheelset and the dynamical behaviors of the railway wheelset system under geometric constraint are studied. It shows that the railway wheelset system has complex dynamical phenomena owing to nonlinear factor and the railway wheelset system may have different complex dynamical behaviors with different nonlinear parameters. In addition, the motion of railway wheelset also has chaotic behaviors under geometric constraint. Finally, the chaos control of the railway wheelset system is achieved by using linear feedback control method. The numerical simulations are carried out in order to analyze the complex phenomena of the railway wheelset system.

Summary In order to examine the static and dynamic behavior of the pantograph-catenary system, a special teat facility is established and described in this paper. Since the catenary is difficult to be modeled by a hardware teat facility indoor, a mixed theoretical-experimental technique is introduced, in which the pantograph is an actual one but the catenary is just an input of a mathematical model. Bayed on setting up the hybrid simulation teat device of the pantograph-catenary system, the dynamic behavior of the system under overhead equipment with variant parameters is analyzed for different speed. The effect of the presag and the surface irregularities of contact wire on current-collection has been studied.

In this paper, a novel four-dimensional(4D) fractional-order chaotic system is proposed deduced from the model of ferromagnetic resonance. The attractor is a three-dimensional (3D) torus like the Olympic nest in Beijing when the system is in stable state. Dynamic behaviors of the novel 4D ferromagnetic system are analyzed in detail, such as phase portrait, Poincare map, Lyapunov exponents and bifurcation diagram. Then the influence of the fractional-order on the dynamic behaviors of this system is analyzed. Numerical simulation results illustrate the feasibility of the novel system.