Electron injection in dye sensitised solar cells

In this thesis, the dynamics and quantum yields of electron injection occurring in liquid and solid state dye sensitised solar cells (DSSCs) based on titanium dioxide (TiO2) anodes sensitised with Ru – polypyridyl or organic dyes have been measured. The electron injection process is investigated through both experimental and modelling studies. A transient emission technique based on time correlated single photon counting (TCSPC) has been developed to measure the kinetics and yields of injection occurring in both films and devices. Other processes occurring in the device are probed using a range of experimental techniques, including transient absorption spectroscopy and transient photovoltage. Initially the principles of the TCSPC measurement technique are introduced and the procedure for measuring the injection in samples is outlined. Comparison of appropriate control sample measurements, which show transient emission decay dynamics in the absence of electron injection, with the TiO2 sample traces enables the quantification of injection occurring in each experimental sample. TCSPC emission decays associated with each sample are then fitted using stretch exponential functions constrained by two degrees of freedom. This TCSPC technique for measuring electron injection dynamics is validated by showing agreement with previously published kinetics for an analogous system as measured by a well established ultrafast transient absorption technique. The fits to the TCSPC decay dynamics are also shown to be accurately replicated by Monte Carlo integrations based on a previously published model of the active dye / TiO2 interface in the DSSCs. The technique is extended to probing DSSCs employing a range of different sensitisers and measuring the kinetics under different operating conditions occurring within the DSSCs where injection is found to only depend strongly on the concentration of potential determining additives. The first results chapter describes the TCSPC technique and gives examples of the data analysis procedures associated with each transient emission decay measurement. The agreement between injection kinetics measured using TCSPC with those measured using ultrafast transient absorption technique is highlighted. The model of 5 the active dye / TiO2 DSSC interface is introduced and Monte Carlo integrations based on this physical model are shown to agree well with the experimental data. The second results chapter extends the measurement of injection kinetics to different Ru – polypyridyl based sensitisers. Injection kinetics are measured for a structure – function dye series and the observed variations in the kinetics and yields are explained with reference to the dye / TiO2 interface. The measurements are extended to completely solid state DSSCs and successful fitting of the TCSPC data with integrations based on the physical model show dispersive injection kinetics observed in solid state DSSCs are controlled by the same parameters as the liquid cells. The third chapter looks at a variety of factors which may affect injection in complete, operating DSSCs. The factors addressed include presence of the commonly used iodide / triiodide redox couple, residual effects of acid versus base film synthesis procedures, effect of increasing the Fermi level in the DSSC and changing the concentration of potential determining ions in the redox electrolyte. The major controlling factor is found to be the concentration of the potential determining, commonly used tert – butyl pyridine device additive and implications of this on DSSC performance are discussed. The last chapter compares device parameters for DSSCs based on successful organic sensitiser with DSSCs based on the commonly used Ru – polypyridyl N719. Features which control the performance of organic dyes in general are outlined and the reduced performance of DSSCs employing these dyes is explained

Networks of ⋅/G/∞\cdot/G/\infty Server Queues with Shot-Noise-Driven Arrival Intensities

We study infinite-server queues in which the arrival process is a Cox process (or doubly stochastic Poisson process), of which the arrival rate is given by shot noise. A shot-noise rate emerges as a natural model, if the arrival rate tends to display sudden increases (or: shots) at random epochs, after which the rate is inclined to revert to lower values. Exponential decay of the shot noise is assumed, so that the queueing systems are amenable for analysis. In particular, we perform transient analysis on the number of customers in the queue jointly with the value of the driving shot-noise process. Additionally, we derive heavy-traffic asymptotics for the number of customers in the system by using a linear scaling of the shot intensity. First we focus on a one dimensional setting in which there is a single infinite-server queue, which we then extend to a network setting

Linear Stochastic Fluid Networks: Rare-Event Simulation and Markov Modulation

We consider a linear stochastic fluid network under Markov modulation, with a focus on the probability that the joint storage level attains a value in a rare set at a given point in time. The main objective is to develop efficient importance sampling algorithms with provable performance guarantees. For linear stochastic fluid networks without modulation, we prove that the number of runs needed (so as to obtain an estimate with a given precision) increases polynomially (whereas the probability under consideration decays essentially exponentially); for networks operating in the slow modulation regime, our algorithm is asymptotically efficient. Our techniques are in the tradition of the rare-event simulation procedures that were developed for the sample-mean of i.i.d. one-dimensional light-tailed random variables, and intensively use the idea of exponential twisting. In passing, we also point out how to set up a recursion to evaluate the (transient and stationary) moments of the joint storage level in Markov-modulated linear stochastic fluid networks

The TIGER Model: Application of detailed passenger and freight transport in a regional CGE setting

The present paper describes the construction and first empirical application of the TIGER model (TIGER is an abbreviation of “Transport and Infrastructure General Equilibrium model for Regionsâ€). The TIGER model belongs to the group of regional CGE models, applying a mix of conventional modelling techniques used in standard computable general equilibrium models and New Economic Geography elements. The TIGER model can be used to evaluate transport policies on economic and environmental effects. Innovative features of the TIGER model are the detailed modelling of the transport sector and modelling of commuting and migration decisions. The approach of the TIGER model is to model cross-border related transport policies on a disaggregate level, with freight and passenger transport flows, allowing for different transport modes (road, water, rail), distinguishing between public and private transport, and for different transport motives. Commuting trips will be modelled in detail, by a location-attraction function, jointly determining area of residence and place of work. The TIGER model is constructed as a regional model on the NUTS-3 level for Belgium, the Netherlands, Luxemburg and a part of Germany, where regions are linked by interregional trade flows, transport trips and migration. In a similar way the model can be extended to all NUTS-3 regions in Europe. This paper will relate on the construction of the database for the model and the addition of innovative elements in the model, necessary to model transnational passenger and freight flows. The construction of the model is based on the available data in the TRANSTOOLS database. The detail offered by the TIGER model allows for a quantitative evaluation of effects of several transport policies with a transnational dimension in the Benelux and Germany. We will present results of the TIGER model based on a current project in the Benelux.