Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.

Imaging and chemical analysis of individual metallofullerene molecules were successfully carried out without massive destruction using a scanning transmission electron microscope (STEM) operated at 30 kV. Electron energy-loss spectroscopy (EELS) unambiguously identified the constituent atom of each metallofullerene molecule. The profile of EELS chemical map measured across the single atom provides a rough estimate of EELS signal delocalization, which is considerably reduced using accelerating voltage as low as 30 kV.

Extended abstract of a paper presented at Microscopy and Microanalysis 2010 in Portland, Oregon, USA, August 1 – August 5, 2010.

Extended abstract of a paper presented at Microscopy and Microanalysis 2010 in Portland, Oregon, USA, August 1 – August 5, 2010.

Extended abstract of a paper presented at Microscopy and Microanalysis 2009 in Richmond, Virginia, USA, July 26 – July 30, 2009

Extended abstract of a paper presented at Microscopy and Microanalysis 2009 in Richmond, Virginia, USA, July 26 – July 30, 2009

Extended abstract of a paper presented at Microscopy and Microanalysis 2009 in Richmond, Virginia, USA, July 26 – July 30, 2009

Extended abstract of a paper presented at Microscopy and Microanalysis 2009 in Richmond, Virginia, USA, July 26 – July 30, 2009

Extended abstract of a paper presented at Microscopy and Microanalysis 2007 in Ft. Lauderdale, Florida, USA, August 5 – August 9, 2007

Extended abstract of a paper presented at Microscopy and Microanalysis 2007 in Ft. Lauderdale, Florida, USA, August 5 – August 9, 2007

Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois, USA, July 30 – August 3, 2006

A series of recent experiments, using electron as well as photon probes [1-3], have attracted considerable interest on the importance of surface plasmon modes in nanostructured media such as nanospheres, nanotubes, nanowires, nanopores or nanoholes.

The basic principle for STEM operation had early been recognized to be well suited to the investigation of cases where non penetrating electrons propagate at a given impact parameter from an external surface (along "aloof7 trajectories, using a terminology proposed by Warmack et al. [4]). One of the most spectacular effect is that signals attributed to the excitation of-surface plasmon modes could be detected in vacuum at distances as large as a few tens of nanometers from the outside surface of a specimen, see for instance [5] for the planar geometry and [6], for the spherical one. Most interpretations accounting for the spatial dependence of EELS spectra in the "aloof geometries, rely on models using the bulk dielectric coefficients of the material to describe the induced charges and polarization responsible for the specimen electric field acting on the probe electron and consequently for the measured energy loss.

The sophisticated acquisition procedures now available in time or space resolved spectroscopies, also known as spectrum-imaging modes, produce large amounts of data which require specific developments for efficient processing and information extraction. For instance, in electron energy-loss spectroscopy (EELS), a line-spectrum consists of typically one hundred spectra recorded at regular intervals when scanning the subnanometer incident electron probe across the feature of interest: interfaces, multilayers or nanostructures of various shapes and dimensions. The useful information in any of these spectra depends on many factors such as the problem under investigation, the involved energy-loss range or the signal-to-noise ratio of the different features. However it is generally contained in the spectral changes, as well in energy channel as in position along the sequence.

To detect, measure and identify these variations, new methods have to be developed and the accompanying algorithms to be implemented. A first category encompasses all the routines which apply successively to all spectra in the sequence the well-known software which have been elaborated for processing individual spectra.