Publications

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.

This chapter is on multiobjective bilevel optimization, i.e. on bilevel optimization problems with multiple objectives on the lower or on the upper level, or even on both levels. We give an overview on the major optimality notions used in multiobjective optimization. We provide characterization results for the set of optimal solutions of multiobjective optimization problems by means of scalarization functionals and optimality conditions. These can be used in theoretical and numerical approaches to multiobjective bilevel optimization.As multiple objectives arise in multiobjective optimization as well as in bilevel optimization problems, we also point out the results on the connection between these two classes of optimization problems. Finally, we give reference to numerical approaches which have been followed in the literature to solve these kind of problems. We concentrate in this chapter on nonlinear problems, while the results and statements naturally also hold for the linear case.