The Materials Science beamline at the Swiss Light Source has been operational since 2001. In late 2010, the original wiggler source was replaced with a novel insertion device, which allows unprecedented access to high photon energies from an undulator installed in a medium-energy storage ring. In order to best exploit the increased brilliance of this new source, the entire front-end and optics had to be redesigned. In this work, the upgrade of the beamline is described in detail. The tone is didactic, from which it is hoped the reader can adapt the concepts and ideas to his or her needs.

The moiré superstructure of a single layer of carbon on ruthenium, where 25×25 graphene honeycombs sit on 23×23 substrate unit cells, is determined from first principles. The density functional theory (DFT) calculations predict two kinds of structural units, Ω and Y, in the supercell, which are identified as moiré beatings or moirons. The related topographic bucklings, or "hills," have distinct carbon conformations and a height of 1.16 Å. The different moirons are observed with scanning tunneling microscopy (STM), and surface x-ray diffraction (SXRD) also discriminates the two. This connects ab initio DFT calculations with STM and SXRD experiments in unit cells containing more than 4000 atoms.

Near-field scanning microwave microscopy is employed for quantitative imaging at 4 GHz of the local impedance for monolayer and few-layer graphene. The microwave response of graphene is found to be thickness dependent and determined by the local sheet resistance of the graphene flake. Calibration of the measurement system and knowledge of the probe geometry allows evaluation of the AC impedance for monolayer and few-layer graphene, which is found to be predominantly active. The use of localized evanescent electromagnetic field in our experiment provides a promising tool for investigations of plasma waves in graphene with wave numbers determined by the spatial spectrum of the near-field. By using near-field microwave microscopy one can perform simultaneous imaging of location, geometry, thickness, and distribution of electrical properties of graphene without a need for device fabrication.

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An automated cluster algorithm is described, applicable to any image where a signal is to be analysed. The algorithm is employed in the context of surface X‐ray diffraction data and extended to automate the data reduction process, which at present limits both the lead time to and the reliability of the retrieved structural information. A detailed evaluation of the constraints used to automate surface X‐ray diffraction data analysis is provided. To overcome limitations of the algorithm and the experiment itself in certain geometries, the full field of view of area detectors is exploited to obtain orders of magnitude improvements in data collection. The method extends the surface X‐ray diffraction technique to new systems and highlights the often archaic approach to the analysis of data collected with a two‐dimensional detector.