Publikationen

We are concerned with the design of Model Predictive Control (MPC) schemes such that asymptotic stability of the resulting closed loop is guaranteed - even if the linearization at the desired set point fails to be stabilizable. Therefore, we propose constructing the stage cost based on the homogeneous approximation and rigorously show that applying MPC yields an asymptotically stable closed-loop behavior if the homogeneous approximation is asymptotically null controllable. To this end, we verify cost controllability - a condition relating the current state, the stage cost, and the growth of the value function with respect to time - for this class of systems in order to provide stability and performance guarantees for the proposed MPC scheme without stabilizing terminal costs or constraints.

Micro and nanoparticles are not only understood as components of materials but as small functional units too. Particles can be designed for the primary transduction of physical and chemical signals and, therefore, become a valuable component in sensing systems. Due to their small size, they are particularly interesting for sensing in microfluidic systems, in microarray arrangements and in miniaturized biotechnological systems and microreactors, in general. Here, an overview of the recent development in the preparation of micro and nanoparticles for sensing purposes in microfluidics and application of particles in various microfluidic devices is presented. The concept of sensor particles is particularly useful for combining a direct contact between cells, biomolecules and media with a contactless optical readout. In addition to the construction and synthesis of micro and nanoparticles with transducer functions, examples of chemical and biological applications are reported.

Potentiostatic deposition of silicon is performed in sulfolane (SL) and ionic liquid (IL) electrolytes. Electrochemical quartz crystal microbalance with damping monitoring (EQCM-D) is used as main analytical tool for the characterization of the reduction process. The apparent molar mass (Mapp) is applied for in situ estimation of the layer contamination. By means of this approach, appropriate electrolyte composition and substrate type are selected to optimize the structural properties of the layers. The application of SL electrolyte results in silicon deposition with higher efficiency compared to the IL 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide, [BMP][TFSI]. This has been associated with the instability of the IL in the presence of silicon tetrachloride and the enhanced incorporation of IL decomposition products into the growing silicon deposit. X-ray photoelectron spectroscopy (XPS) analysis supports the results about the layer composition, as suggested from the microgravimetric experiments. Attention has been given to the impact of practically relevant substrates (i.e., Cu, Ni, and vitreous carbon) on the reduction process. An effective deposition can be carried out on the metal electrodes in both electrolytes due to accelerated reaction kinetics for these types of substrates. However, on vitreous carbon (VC), a successful reduction of SiCl4 can only be accomplished in the IL, while the electroreduction process in SL is dominated by the decomposition of the electrolyte. For short deposition times, the scanning electron microscopy (SEM) images display rough morphologies in the nanometer range, which evolve further to structures with increased length scale of the surface roughness. The development of a rough interface during deposition, resulting in QCM damping at advanced stages of the process, is interpreted by a model accounting for the resistive force caused by the interaction of the liquid with a nonuniform layer interface. By using this approach, the individual contributions of the surface roughness and viscoelastic effects to the measured damping values are estimated.

Energy-resolved secondary electron spectroscopy has been performed on air-exposed standard Cu samples and modified Cu surfaces that are tested and possibly applied to efficiently suppress electron cloud formation in the high-luminosity upgrade of the Large Hadron Collider at CERN. The Cu samples comprise pristine oxygen-free, carbon-coated and laser-structured surfaces, which were characterized prior to and after electron irradiation and rare-gas ion bombardment. Secondary-electron and reflected-electron yields measured with low charge dose of the samples exhibit a universal dependence on the energy of the primary impinging electrons. State-of-the-art models can successfully be used to describe the spectroscopic data. The supplied spectral dependence of electron emission and integrated electron yield as well as the derived parametrization can serve as a basis for forthcoming simulations of electron cloud formation and multipacting.