Abstract: We introduce a modified version of the Hirshfeld charge analysis method and demonstrate its accurateness by calculating the charge transfer between the paramagnetic molecule NO2 and graphene. The charge transfer between paramagnetic molecules and a graphene layer as calculated with ab initio methods can crucially depend on the size of the supercell used in the calculation. This has important consequences for adsorption studies involving paramagnetic molecules such as NO2 physisorbed on graphene or on carbon nanotubes. © 2008 American Institute of Physics.

Abstract: The majority of researchers, conservators and curators recognise that atmospheric pollution is one of the major threats to works of art. In principle, all atmospheric particles, when deposited onto art objects can be considered harmful because of their potential in causing deterioration. Moreover, under certain conditions, particulate matter can induce and intensify surface damage, particularly because of its potential to serve as centre for moisture condensation and adsorbent of gaseous pollutants. To investigate the potential harm that these particles can cause, comprehensive characterisation of the particulate matter is necessary. Particulate matter was collected at the Rubens' House Museum in Antwerp, Belgium, where a unique exhibit of the paintings and living quarters of Peter Paul Rubens (1577-1640) are seen. Size segregated aerosol samples were collected for analyses of bulk and single particle elemental and molecular compositions. They were analysed by electron probe micro-analysis, utilising facilities for low-Z element determination, and by energy-dispersive x-ray fluorescence, to investigate the elemental composition of individual particles and bulk samples, and by micro Raman spectrometry, to elucidate the molecular composition. Results are interpreted separately and as a whole with the specific aim of identifying compounds that could contribute to the chemical reactions taking place on the surfaces of artefacts and which could potentially cause degradation of the objects.

Abstract: Electron energy loss spectroscopy (EELS) is an ideal tool to obtain chemical information from nanoscale volumes. Quantification of the experimental spectra however has prevented for a long time access to the available information in a reliable and reproducible way. We present recent advances in model-based quantification of EELS spectra and show that we obtain the best possible precision for a given dataset, as well as remarkably good accuracies when applied to three different materials. The results are shown to be far superior over conventional quantification techniques and could hold a promise for standardless quantification of EELS spectra.