Mixed finite-element methods for elliptic convection-dominated problems arising in semiconductor physics

In this work we develop and analyze an adaptive numerical scheme for simulating a class of macroscopic semiconductor models. At first the numerical modelling of semiconductors is reviewed in order to classify the Energy-Transport models for semiconductors that are later simulated in 2D. In this class of models the flow of charged particles, that are negatively charged electrons and so-called holes, which are quasi-particles of positive charge, as well as their energy distributions are described by a coupled system of nonlinear partial differential equations. A considerable difficulty in simulating these convection-dominated equations is posed by the nonlinear coupling as well as due to the fact that the local phenomena such as "hot electron effects" are only partially assessable through the given data. The primary variables that are used in the simulations are the particle density and the particle energy density. The user of these simulations is mostly interested in the current flow through parts of the domain boundary - the contacts. The numerical method considered here utilizes mixed finite-elements as trial functions for the discrete solution. The continuous discretization of the normal fluxes is the most important property of this discretization from the users perspective. It will be proven that under certain assumptions on the triangulation the particle density remains positive in the iterative solution algorithm. Connected to this result an a priori error estimate for the discrete solution of linear convection-diffusion equations is derived. The local charge transport phenomena will be resolved by an adaptive algorithm, which is based on a posteriori error estimators. At that stage a comparison of different estimations is performed. Additionally a method to effectively estimate the error in local quantities derived from the solution, so-called "functional outputs", is developed by transferring the dual weighted residual method to mixed finite elements. For a model problem we present how this method can deliver promising results even when standard error estimator fail completely to reduce the error in an iterative mesh refinement process.

Analysis and numerical solution of the Peterlin viscoelastic model

Liquids and gasses form a vital part of nature. Many of these are complex fluids with non-Newtonian behaviour. We introduce a mathematical model describing the unsteady motion of an incompressible polymeric fluid. Each polymer molecule is treated as two beads connected by a spring. For the nonlinear spring force it is not possible to obtain a closed system of equations, unless we approximate the force law. The Peterlin approximation replaces the length of the spring by the length of the average spring. Consequently, the macroscopic dumbbell-based model for dilute polymer solutions is obtained. The model consists of the conservation of mass and momentum and time evolution of the symmetric positive definite conformation tensor, where the diffusive effects are taken into account. In two space dimensions we prove global in time existence of weak solutions. Assuming more regular data we show higher regularity and consequently uniqueness of the weak solution. For the Oseen-type Peterlin model we propose a linear pressure-stabilized characteristics finite element scheme. We derive the corresponding error estimates and we prove, for linear finite elements, the optimal first order accuracy. Theoretical error of the pressure-stabilized characteristic finite element scheme is confirmed by a series of numerical experiments.

Numerical coupling of thermal-electric network models and energy-transport equations including optoelectronic semiconductor devices

In this work the numerical coupling of thermal and electric network models with model equations for optoelectronic semiconductor devices is presented. Modified nodal analysis (MNA) is applied to model electric networks. Thermal effects are modeled by an accompanying thermal network. Semiconductor devices are modeled by the energy-transport model, that allows for thermal effects. The energy-transport model is expandend to a model for optoelectronic semiconductor devices. The temperature of the crystal lattice of the semiconductor devices is modeled by the heat flow eqaution. The corresponding heat source term is derived under thermodynamical and phenomenological considerations of energy fluxes. The energy-transport model is coupled directly into the network equations and the heat flow equation for the lattice temperature is coupled directly into the accompanying thermal network. The coupled thermal-electric network-device model results in a system of partial differential-algebraic equations (PDAE). Numerical examples are presented for the coupling of network- and one-dimensional semiconductor equations. Hybridized mixed finite elements are applied for the space discretization of the semiconductor equations. Backward difference formluas are applied for time discretization. Thus, positivity of charge carrier densities and continuity of the current density is guaranteed even for the coupled model.

From lipid bilayers to synaptic vesicles: atomic force microscopy on lipid-based systems

The aim of this thesis was to apply the techniques of the atomic force microscope (AFM) to biological samples, namely lipid-based systems. To this end several systems with biological relevance based on self-assembly, such as a solid-supported membrane (SSM) based sensor for transport proteins, a bilayer of the natural lipid extract from an archaebacterium, and synaptic vesicles, were investigated by the AFM. For the characterization of transport proteins with SSM-sensors proteoliposomes are adsorbed that contain the analyte (transport protein). However the forces governing bilayer-bilayer interactions in solution should be repulsive under physiological conditions. I investigated the nature of the interaction forces with AFM force spectroscopy by mimicking the adsorbing proteoliposome with a cantilever tip, which was functionalized with charged alkane thiols. The nature of the interaction is indeed repulsive, but the lipid layers assemble in stacks on the SSM, which expose their unfavourable edges to the medium. I propose a model by which the proteoliposomes interact with these edges and fuse with the bilayer stacks, so forming a uniform layer on the SSM. Furthermore I characterized freestanding bilayers from a synthetic phospholipid with a phase transition at 41°C and from a natural lipid extract of the archaebacterium Methanococcus jannaschii. The synthetic lipid is in the gel-phase at room temperature and changes to the fluid phase when heated to 50°C. The bilayer of the lipid extract shows no phase transition when heated from room temperature to the growth temperature (~ 50°C) of the archeon. Synaptic vesicles are the containers of neurotransmitter in nerve cells and the synapsins are a family of extrinsic membrane proteins, that are associated with them, and believed to control the synaptic vesicle cycle. I used AFM imaging and force spectroscopy together with dynamic light scattering to investigate the influence of synapsin I on synaptic vesicles. To this end I used native, untreated synaptic vesicles and compared them to synapsin-depleted synaptic vesicles. Synapsin-depleted vesicles were larger in size and showed a higher tendency to aggregate compared to native vesicles, although their mechanical properties were alike. I also measured the aggregation kinetics of synaptic vesicles induced by synapsin I and found that the addition of synapsin I promotes a rapid aggregation of synaptic vesicles. The data indicate that synapsin I affects the stability and the aggregation state of synaptic vesicles, and confirm the physiological role of synapsins in the assembly and regulation of synaptic vesicle pools within nerve cells.