Collaborative research: ITR: global multi-scale kinetic simulations of the earth's magnetosphere using parallel discrete event simulation

Issued as final reportNational Science Foundation (U.S.

Asynchronous Discrete Event Schemes for PDEs

A new class of asynchronous discrete-event simulation schemes for advection-diffusion-reaction equations are introduced, which is based on the principle of allowing quanta of mass to pass through faces of a Cartesian finite volume grid. The timescales of these events are linked to the flux on the the face, and the schemes are self-adaptive, local in time and space. Experiments are performed on realistic physical systems related to porous media flow applications, including a large 3D advection diffusion equation and advection diffusion reaction systems. The results are compared to highly accurate results where the temporal evolution is computed with exponential integrator schemes using the same finite volume discretisation. This allows a reliable estimation of the solution error. Our results indicate a first order convergence of the error as a control parameter is decreased

CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab

CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS models. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output

Efficient numerical schemes for porous media flow

Partial di erential equations (PDEs) are important tools in modeling complex phenomena, and they arise in many physics and engineering applications. Due to the uncertainty in the input data, stochastic partial di erential equations (SPDEs) have become popular as a modelling tool in the last century. As the exact solutions are unknown, developing e cient numerical methods for simulating PDEs and SPDEs is a very important while challenging research topic. In this thesis we develop e cient numerical schemes for deterministic and stochastic porous media ows. More schemes are based on the computing of the matrix exponential functions of the non diagonal matrices, we use new e cient techniques: the real fast L eja points and the Krylov subspace techniques. For the deterministic ow and transport problem, we consider two deterministic exponential integrator schemes: the exponential time di erential stepping of order one (ETD1) and the exponential Euler midpoint (EEM) with nite volume method for discretization in space. We give the time and space convergence proof for the ETD1 scheme and illustrate with simulations in two and three dimensions that the exponential integrators are e - cient and accurate for advection dominated deterministic transport ow in heterogeneous anisotropic porous media compared to standard semi implicit and implicit schemes. For the stochastic ow and transport problem, we consider the general parabolic SPDEs in a Hilbert space, using the nite element method for discretization in space (although nite di erence or nite volume can be used as well). We use a linear functional of the noise and the standard Brownian increments to develop and give convergence proofs of three new e cient and accurate schemes for additive noise, one called the modi ed semi{ implicit Euler-Maruyama scheme and two stochastic exponential integrator schemes, and two stochastic exponential integrator schemes for multiplicative and additive noise. The schemes are applied to two dimensional ow and transport

Asynchronous and exponential based numerical schemes for porous media flow

A great many physical phenomena are modelled by partial di erential equations (PDEs), and numerical schemes often have to be employed to approximate the solutions to these equations where analytical solutions cannot be found. We develop and analyse here new schemes belonging to two broad classes, schemes that are asynchronous, and exponential integrators. We apply these schemes to test models of advection-di usion-reaction processes that occur in porous media ow. Asynchronous schemes allow di erent parts of the physical domain to evolve at different rates. We develop a class of asynchronous schemes that progress by discrete events, where a single event is the transfer of a unit of mass through the domain, according to the local ux. These schemes are intended to focus computational e ort where it is most needed, as a high local ux will cause the algorithm to automatically take more events in that part of the domain. We develop the simplest version of this scheme, and then develop further schemes by adding modi cations to address potential shortcomings. Numerical experiments indicate a number of interesting relations between the parameters of these schemes. Particularly, the error of the schemes seems to be rst order with respect to a control parameter we call the mass unit. Some analysis is conducted which can pave the way towards robust theoretical understanding of these schemes in the future. Exponential integrators are time stepping schemes which exactly solve the linear part of a semilinear ODE system. This class of schemes requires the approximation of a matrix exponential in every step, and one successful modern method is the Krylov subspace projection method. We investigate, through analysis and experiment, the e ect of breaking down a single timestep into multiple substeps, recycling the Krylov subspace to minimise costs. Our results indicate that this can increase accuracy and e ciency. We show the results of an investigation into developing a class of `semi-exponential' Runge-Kutta type schemes, which use an exponential integrator for the initial stage and then essentially ful l classical order conditions for the remaining stages. Finally, we return to the concept of asynchronicity in a di erent form. With the advent of massively parallel machines, there is increasing interest in developing domain-decomposition type schemes that are robust to random failures or delays in communication between processing elements. This is because in massively parallel machines, communication between processors is likely to be the signi cant bottleneck in execution time. Recently the e ect of such communication delay with a simple domain-decomposed Euler timestepping solver applied to a linear PDE has been investigated with promising results. Here, inspired by exponential integrators, we investigate the natural extension of this, by replacing the Euler timestepping with the evaluation of the appropriate matrix exponential on the sub-domain. We have performed experiments simulating the communication delay and the results are also promising

Integrated 2D-3D free surface hydro-environmental modelling

An integrated horizontally two- and fully three-dimensional numerical model system has been developed based on a combined unstructured and σ-coordinate grid to simulate the flow and water quality process in large water bodies with a focus on the three dimensional behaviours at specific areas. The model is based on the time dependent Reynolds-Averaged Navier-Stokes equations with a non-hydrostatic pressure distribution and a baroclinic force being incorporated in the three dimensional (3D) model. The two sub models interact dynamically during the solution procedure with no time-step restriction due to integration. The main idea is to use a fractional step algorithm for each model and then integrate the two models fraction by fraction. Hybrid 2D-3D finite volume cells have been introduced for the link nodes which are partly in the 2D domain and partly in the 3D domain. Thus an interpolation/averaging procedure at the interface and domain overlapping is no longer needed. The 3D model uses the projection method for pressure calculation. The advection equation is solved by the semi-Lagrangian method. Other components are solved via the finite element - finite volume (FV) method. The water surface is determined implicitly through a global matrix equation created by assembling the domain's matrices. The cell integrals are calculated analytically to eliminate a common source of numerical diffusion due to the use of approximation techniques for the FV integrals. The horizontal gradients of the density and shear stresses are calculated on true horizontal planes, in order to avoid artificial velocity and diffusion in highly stratified flows. Neumann interpolation elements with virtual nodes have been introduced at Neumann type of boundaries for more accuracy. The integrated model has been verified using analytical solutions and benchmark test cases, including the Ekman velocity distribution, wind driven circulation, lock exchange and integrated 2D-3D flows in basin. The results show the model is capable of the model for accurate simulation and implicit 2D-3D integration. Keywords: integrated modelling, hydrodynamic numerical model, non-hydrostatic, unstructured mesh, hybrid finite element finite volume method.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Integrated 2D-3D free surface hydro-environmental modelling

An integrated horizontally two- and fully three-dimensional numerical model system has been developed based on a combined unstructured and σ-coordinate grid to simulate the flow and water quality process in large water bodies with a focus on the three dimensional behaviours at specific areas. The model is based on the time dependent Reynolds-Averaged Navier-Stokes equations with a non-hydrostatic pressure distribution and a baroclinic force being incorporated in the three dimensional (3D) model. The two sub models interact dynamically during the solution procedure with no time-step restriction due to integration. The main idea is to use a fractional step algorithm for each model and then integrate the two models fraction by fraction. Hybrid 2D-3D finite volume cells have been introduced for the link nodes which are partly in the 2D domain and partly in the 3D domain. Thus an interpolation/averaging procedure at the interface and domain overlapping is no longer needed. The 3D model uses the projection method for pressure calculation. The advection equation is solved by the semi-Lagrangian method. Other components are solved via the finite element - finite volume (FV) method. The water surface is determined implicitly through a global matrix equation created by assembling the domain's matrices. The cell integrals are calculated analytically to eliminate a common source of numerical diffusion due to the use of approximation techniques for the FV integrals. The horizontal gradients of the density and shear stresses are calculated on true horizontal planes, in order to avoid artificial velocity and diffusion in highly stratified flows. Neumann interpolation elements with virtual nodes have been introduced at Neumann type of boundaries for more accuracy. The integrated model has been verified using analytical solutions and benchmark test cases, including the Ekman velocity distribution, wind driven circulation, lock exchange and integrated 2D-3D flows in basin. The results show the model is capable of the model for accurate simulation and implicit 2D-3D integration. Keywords: integrated modelling, hydrodynamic numerical model, non-hydrostatic, unstructured mesh, hybrid finite element finite volume method

Device Physics of Organic Solar Cells: Drift-Diffusion Simulation in Comparison with Experimental Data of Solar Cells Based on Small Molecules

This thesis deals with the device physics of organic solar cells. Organic photovoltaics (OPV) is a field of applied research which has been growing rapidly in the last decade leading to a current record value of power-conversion efficiency of 10 percent. One major reason for this boom is a potentially low-cost production of solar modules on flexible (polymer) substrate. Furthermore, new application are expected by flexible or semitransparent organic solar cells. That is why several OPV startup companies were launched in the last decade. Organic solar cells consist of hydrocarbon compounds, deposited as ultrathin layers (some tens of nm) on a substrate. Absorption of light leads to molecular excited states (excitons) which are strongly bound due to the weak interactions and low dielectric constant in a molecular solid. The excitons have to be split into positive and negative charges, which are subsequently collected at different electrodes. An effective dissociation of excitons is provided by a heterojunction of two molecules with different frontier orbital energies, such that the electron is transfered to the (electron) acceptor and the positive charge (hole) remains on the donor molecule. This junction can be realized by two distinct layers forming a planar heterojunction or by an intermixed film of donor and acceptor, resulting in a bulk heterojunction. Electrodes are attached to the absorber to collect the charges by providing an ohmic contact in the optimum case. This work focuses on the electrical processes in organic solar cells developing and employing a one-dimensional drift-diffusion model. The electrical model developed here is combined with an optical model and covers the diffusion of excitons, their separation, and the subsequent transport of charges. In contrast to inorganics, charge-carrier mobilities are low in the investigated materials and charge transport is strongly affected by energy barriers at the electrodes. The current-voltage characteristics (J-V curve) of a solar cell reflect the electrical processes in the device. Therefore, the J-V curve is selected as means of comparison between systematic series of simulation and experimental data. This mainly qualitative approach allows for an identification of dominating processes and provides microscopic explanations. One crucial issue, as already mentioned, is the contact between absorber layer and electrode. Energy barriers lead to a reduction of the power-conversion efficiency due to a decrease in the open-circuit voltage or the fill factor by S-shaped J-V curve (S-kink), which are often observed for organic solar cells. It is shown by a systematic study that the introduction of deliberate barriers for charge-carrier extraction and injection can cause such S-kinks. It is explained by simulated electrical-field profiles why also injection barriers lead to a reduction of the probability for charge-carrier extraction. A pile-up of charge carriers at an extraction barrier is confirmed by measurements of transient photocurrents. In flat heterojunction solar cells an additional reason for S-kinks is found in an imbalance of electron and hole mobilities. Due to the variety of reasons for S-kinks, methods and criteria for a distinction are proposed. These include J-V measurements at different temperatures and of samples with varied layer thicknesses. Most of the studies of this this work are based on experimental data of solar cells comprisiing the donor dye zinc phthalocyanine and the acceptor fullerene C60. It is observed that the open-circuit voltage of these devices depends on the mixing ratio of ZnPc:C60. A comparison of experimental and simulation data indicates that the reason is a changed donor-acceptor energy gap caused by a shift of the ionization potential of ZnPc. A spatial gradient in the mixing ratio of a bulk heterojunction is also investigated as a donor(acceptor)-rich mixture at the hole(electron)-collecting contact is supposed to assist charge extraction. This effect is not observed, but a reduction of charge-carrier losses at the “wrong” electrode which is seen at an increase in the open-circuit voltage. The most important intrinsic loss mechanism of a solar cell is bulk recombination which is treated at the example of ZnPc:C60 devices in the last part of this work. An examination of the dependence of the open-circuit voltage on illumination intensity shows that the dominating recombination mechanism shifts from trap-assisted to direct recombination for higher intensities. A variation of the absorption profile within the blend layer shows that the probability of charge-carrier extraction depends on the locus of charge-carrier generation. This results in a fill factor dependent on the absorption profile. The reason is an imbalance in charge-carrier mobilities which can be influenced by the mixing ratio. The work is completed by a simulation study of the influence of charge-carrier mobilities and different recombination processes on the J-V curve and an identification of a photoshunt dominating the experimental linear photocurrent-voltage characteristics in reverse bias.:Abstract - Kurzfassung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v 1 Introduction 1.1 Energy supply and climate change . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Development of (organic) photovoltaics . . . . . . . . . . . . . . . . . . 3 1.3 Structure and scope of this thesis . . . . . . . . . . . . . . . . . . . . . . 6 I Basics 2 Photovoltaic Energy Conversion 2.1 Fundamentals of solar thermal energy conversion . . . . . . . . . . .11 2.1.1 The solar spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1.2 Black-body irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14 2.1.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 15 2.2 Basics of semiconductor physics . . . . . . . . . . . . . . . . . . . . . . 16 2.2.1 Band structure, electrons and holes . . . . . . . . . . . . . . . . . . 16 2.2.2 Quasi-Fermi levels and electrochemical potentials . . . . . . . . . .22 2.3 Transformation of thermal radiation into chemical energy . . . . . 28 2.4 From chemical energy to electrical energy . . . . . . . . . . . .. . . . . 29 2.5 Possible solar-cell realizations . . . . . . . . . . . . . . . . . . . . . . . . 33 2.5.1 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.5.2 Heterojunction and dye solar cells . . . . . . . . . . . . . . . . . . . . 36 2.5.3 The p-i-n concept with wide-gap transport layers . . . . . . . . . 37 2.6 Maximum efficiency – Shockley-Queisser limit . . . . . . . . . . . . . .38 2.7 Novel concepts and classification of solar cells . . . . . . . . . . . . . 41 3 Organic Solar Cells 3.1 Energetics of organic molecules . . . . . . . . . . . . . . . . . . . . . . . 43 3.1.1 From atoms to molecules . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.1.2 From single molecules to a molecular solid . . . . . . . . . . . . . . 50 3.2 Energy and charge transport in organic semiconductors . . . . . . 52 3.2.1 Exciton transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.2.2 Charge transport - Gaussian disorder model . . . . . . . . . . . . .53 3.3 Working principle of donor-acceptor heterojunction solar cells . .57 3.3.1 Particle losses, quantum efficiency, and photocurrent . . . . . . .57 3.3.2 Energy losses, potential energy, and photovoltage . . . . . . . . 62 3.3.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 66 3.3.4 Understanding the J-V curve in the MIM picture . . . . . . . . . . .68 3.3.5 Introduction to analytical models describing the photocurrent 70 3.4 Metal-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.4.1 Conventional metal-semiconductor interfaces: Barriers and Schottky contacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.4.2 Metal-organic interfaces: Disorder and ICT . . . . . . . . . . . . . . 79 3.5 Experimental realization of small-molecule solar cells . . . . . . . . 80 3.5.1 Stacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.5.2 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83 3.5.3 Fabrication details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 3.6 Basic characterization methods . . . . . . . . . . . . . . . . . . . . . . . 92 3.6.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 92 3.6.2 Spectrally resolved measurements . . . . . . . . . . . . . . . . . . . 93 3.6.3 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4 Modeling 4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 4.2 The drift-diffusion model in general . . . . . . . . . . . . . . . . . . . . 99 4.2.1 Derivation and conditions . . . . . . . . . . . . . . . . . . . . . . . . . . 99 4.2.2 The Einstein Relation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103 4.2.3 Poisson’s equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 4.2.4 Differential equation system . . . . . . . . . . . . . . . . . . . . . . . .105 4.3 Implementation of the algorithm . . . . . . . . . . . . . . . . . . . . . . 106 4.3.1 Basics of the algorithm and discretization . . . . . . . . . . . . . . 107 4.3.2 Calculation of the electric field . . . . . . . . . . . . . . . . . . . . . . 108 4.3.3 Calculation of rates of change . . . . . . . . . . . . . . . . . . . . . . 109 4.3.4 Calculation of the time step . . . . . . . . . . . . . . . . . . . . . . . . 111 4.3.5 Detection of steady state and transient currents . . . . . . . . . 111 4.4 Implemented models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 4.4.1 Charge carrier mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 4.4.2 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 4.4.3 Traps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 4.4.4 Gaussian density of states . . . . . . . . . . . . . . . . . . . . . . . . 120 4.5 Contacts as boundary conditions . . . . . . . . . . . . . . . . . . . . . 121 4.6 Organic-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . 124 4.6.1 Charge transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 4.6.2 Generation and recombination . . . . . . . . . . . . . . . . . . . . . . 127 4.7 The simulation tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 4.8 Verification with analytical solutions . . . . . . . . . . . . . . . . . . . 129 4.8.1 Single-carrier devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 4.8.2 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 4.9 Experimental determination of material properties . . . . . . . . . 136 4.10 Summary and main input parameters . . . . . . . . . . . . . . . . . 140 II Results and Discussion 5 Simulation Study on Single-Layer Bulk-Heterojunction Solar Cells 5.1 Investigated device structure and definitions . . . . . . . . . . . . . 144 5.2 On the optimum mobility, contact properties, and the open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 5.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146 5.2.2 Investigated mobility and recombination models . . . . . . . . . .147 5.2.3 Recombination only in the BHJ (selective contacts) . . . . . . . . 149 5.2.4 Recombination (also) at electrodes (non-selective contacts) . .155 5.2.5 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158 5.2.6 Effect of energy-level bending on the open-circuit voltage . . . 161 5.3 Photocurrent and characteristic points in simulated J-V curves . .163 5.3.1 Negligible bulk recombination . . . . . . . . . . . . . . . . . . . . . . . .164 5.3.2 Bulk-recombination-limited photocurrent . . . . . . . . . . . . . . . 167 5.4 The effect of disorder on the open-circuit voltage . . . . . . . . . . .169 5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172 6 Influence of Injection and Extraction Barriers on Open-Circuit Voltage and J-V Curve Shape studied at a Variation of Hole Transport Layer and Donor Materials 6.1 Methodological approach . . . . . . . . . . . . . . . . . . . . . . . . . . . .174 6.2 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 6.2.1 Fingerprints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 6.2.2 Current-voltage characteristics under illumination . . . . . . . . . 181 6.3 Detailed microscopic explanations . . . . . . . . . . . . . . . . . . . . . .181 6.3.1 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .184 6.3.2 Extraction barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187 6.3.3 Comparison between flat and bulk heterojunction . . . . . . . . . 188 6.4 Current-voltage curves in a logarithmic plot . . . . . . . . . . . . . . .188 6.5 Detailed analysis of the material combination MeO-TPD and BPAPF as donor and hole transport layer . . . . . . . . . . . . . . . . . . . . . . . . . . 190 6.5.1 The interfaces BPAPF/MeO-TPD and MeO-TPD/BPAPF measured by photoelectron spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . 190 6.5.2 Dependence of the J-V curve shape on layer thicknesses . . . . 195 6.5.3 Dependence of the S-kink on temperature . . . . . . . . . . . . . . 198 6.5.4 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 200 6.6 Summary and final remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 207 7 Imbalanced Mobilities causing S-shaped J-V Curves in Planar Heterojunction Solar Cells 7.1 Imbalanced mobilities in simulation . . . . . . . . . . . . . . . . . . . . . 209 7.2 Experimental verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214 7.2.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 216 7.2.2 Transient photocurrents . . . . . . . . . . . . . . . . . . . . . . . . . . 219 7.3 Field-dependent exciton dissociation as an additional source of S-kinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221 7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 8 Open-Circuit Voltage and J-V Curve Shape of ZnPc:C60 Solar Cells with Varied Mixing Ratio and Hole Transport Layer 8.1 Experimental approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223 8.2 The open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . .225 8.3 The role of the hole transport layer and of doping . . . . . . . . . .228 8.4 Explaining the open-circuit voltage as a function of mixing ratio 230 8.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 9 Effect of Concentration Gradients in ZnPc:C60 Bulk Heterojunction Solar Cells 9.1 Investigated devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 9.2 Current-voltage results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 9.2.1 Fill factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 9.2.2 Short-circuit current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 9.2.3 Open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 9.3 Voltage dependent external quantum efficiency data . . . . . . . . 245 9.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .247 10 Role of the Generation Profile and Recombination in ZnPc:C60 Solar Cells 10.1 Idea and solar-cell design . . . . . . . . . . . . . . . . . . . . . . . . . . 249 10.1.1 Absorption data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 10.1.2 Simulated generation profiles . . . . . . . . . . . . . . . . . . . . . . 253 10.2 Correlation of fill factor with generation profile and imbalance in mobilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 10.2.1 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 10.2.2 Monochromatic J-V curves . . . . . . . . . . . . . . . . . . . . . . . . 258 10.2.3 Voltage dependent external quantum efficiency . . . . . . . . . 259 10.3 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 10.3.1 Exponential region of dark J-V curves . . . . . . . . . . . . . . . . 261 10.3.2 J-V data dependent on illumination intensity . . . . . . . . . . . 265 10.3.3 Lifetime of charge carriers . . . . . . . . . . . . . . . . . . . . . . . . 271 10.4 Comparison with simulations . . . . . . . . . . . . . . . . . . . . . . . . 273 10.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 11 Linear Saturation Behavior 11.1 Definition of the photoshunt . . . . . . . . . . . . . . . . . . . . . . . . 279 11.2 Quasi-linear photocurrent in simulation . . . . . . . . . . . . . . . . 280 11.3 Experimental approach and results . . . . . . . . . . . . . . . . . . . 281 11.3.1 Identification of the main source of the photoshunt . . . . . . 283 11.3.2 Investigation of the thickness dependence of the saturation 285 11.3.3 Photoshunt in flat heterojunction ZnPc/C60 solar cells . . . . 289 11.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292 III Summary and Outlook 12 Main Results 12.1 Interpretation of current-voltage curves . . . . . . . . . . . . . . . . 295 12.2 Stack design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 12.3 Main conclusions on the applicability of the developed drift-diffusion simulation to organic solar cells . . . . . . . . . . . . . . . . . . . . . . . . . . 302 13 Further Analyses and Possible Extensions of the Simulation 13.1 Frequency response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 13.2 Reverse tunneling currents and tandem cells . . . . . . . . . . . . . 307 13.2.1 Reverse current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 13.2.2 J-V curves of tandem cells . . . . . . . . . . . . . . . . . . . . . . . . 309 13.3 Further points to examine . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Appendix A Lists A.1 List of symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 A.2 List of abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318 A.3 List of constants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 B Simulation data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 C Experimental data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Acknowledgments - Danksagung 361Diese Dissertation beschäftigt sich mit der Physik organischer Solarzellen. Die organische Photovoltaik ist ein Forschungsgebiet, dem in den letzten zehn Jahren enorme Aufmerksamkeit zu Teil wurde. Der Grund liegt darin, dass diese neuartigen Solarzellen, deren aktueller Rekordwirkungsgrad bei 10 Prozent liegt, ein Potential für eine kostengünstige Produktion auf flexiblem (Polymer)substrat aufweisen und aufgrund ihrer Vielfältigkeit neue Anwendungsbereiche für die Photovoltaik erschließen. Organische Solarzellen bestehen aus ultradünnen (einige 10 nm) Schichten aus Kohlenwasserstoffverbindungen. Damit der photovoltaische Effekt genutzt werden kann, müssen die durch Licht angeregten Molekülzustände zu freien Ladungsträgern führen, wobei positive und negative Ladung an unterschiedlichen Kontakten extrahiert werden. Für eine effektive Trennung dieser stark gebundenden lokalisierten angeregten Zustände (Exzitonen) ist eine Grenzfläche zwischen Molekülen mit unterschiedlichen Energieniveaus der Grenzorbitale erforderlich, sodass ein Elektron auf einem Akzeptor- und eine positive Ladung auf einem Donatormolekül entstehen. Diese Grenzschicht kann als planarer Heteroübergang durch zwei getrennte Schichten oder als Volumen-Heteroübergang in einer Mischschicht realisiert werden. Die Absorberschichten werden durch Elektroden kontaktiert, wobei es für effiziente Solarzellen erforderlich ist, dass diese einen ohmschen Kontakt ausbilden, da ansonsten Verluste zu erwarten sind. Diese Arbeit behandelt im Besonderen die elektrischen Prozesse einer organischen Solarzelle. Dafür wird ein eindimensionales Drift-Diffusionsmodell entwickelt, das den Transport von Exzitonen, deren Trennung an einer Grenzfläche und die Ladungsträgerdynamik beschreibt. Abgesehen von den Exzitonen gilt als weitere Besonderheit einer organischen Solarzelle, dass sie aus amorphen, intrinsischen und sehr schlecht leitfähigen Absorberschichten besteht. Elektrische Effekte sind an der Strom-Spannungskennlinie (I-U ) sichtbar, die in dieser Arbeit als Hauptvergleichspunkt zwischen experimentellen Solarzellendaten und den Simulationsergebnissen dient. Durch einen weitgehend qualitativen Vergleich können dominierende Prozesse bestimmt und mikroskopische Erklärungen gefunden werden. Ein wichtiger Punkt ist der schon erwähnte Kontakt zwischen Absorberschicht und Elektrode. Dort auftretende Energiebarrieren führen zu einem Einbruch im Solarzellenwirkungsgrad, der sich durch eine Verringerung der Leerlaufspanung und/oder S-förmigen Kennlinien (S