Papers by Bernhard Schaffer
Journal of physics, Jul 1, 2010
We have developed a novel acquisition methodology for the recording of electron energy loss spect... more We have developed a novel acquisition methodology for the recording of electron energy loss spectra (EELS) using a scanning transmission electron microscope (STEM): Smart Acquisition. Smart Acquisition allows the independent control of probe scanning ...
TEM. EELS, AND EFTEM: APPLICATION TO SEMICONDUCTOR MATERIALS AND DEVICE CHARACTERIZATION Werner G... more TEM. EELS, AND EFTEM: APPLICATION TO SEMICONDUCTOR MATERIALS AND DEVICE CHARACTERIZATION Werner Grogger, Bernhard Schaffer, Ferdinand Hofer FELMI, Graz University of Technology, Steyrergasse 17, A-8010 Graz, Austria ABSTRACT Over the last years ...
CRC Press eBooks, Jan 10, 2018
Energy filtering transmission electron microscopy (EFTEM) is a well established analytical method... more Energy filtering transmission electron microscopy (EFTEM) is a well established analytical method capable of mapping chemical distributions at the nanometre scale. It is based on the energy-loss of transmitted electrons (EEL spectrum) interacting with the sample. Spectrum imaging (SI) is a method to acquire all spectral information for each pixel in an image, so that sophisticated data analysis based on spectroscopy can be applied to create various maps of sample properties. EFTEM SI acquires the data as a series of images, each containing the information of a certain energy-loss range defined by the width of a slit in the energy filter. This slit limits the energy resolution of the data. Conventional systems uses slit widths larger than 3 eV. In this work, EFTEM SI methods using ultra small slit widths (<0.5 eV) were developed. In particular, a new acquisition routine was developed which automatically adapts itself to the strongly varying intensity. The achievable energy resolution of 0.8 eV is comparable to conventional EEL spectroscopy methods. With this energy-resolution, data correction of various aberrations is mandatory. In this thesis, the first algorithm for a complete data correction of drift and distortion along both the spatial and the energy axis was developed. Finally, the new methods were applied to three different examples showing the new mapping possibilities.
Microscopy and Microanalysis, Sep 1, 2003
Light emitting devices (LEDs) based on conjugated organic molecules (oLEDs) or polymers (pLEDS) h... more Light emitting devices (LEDs) based on conjugated organic molecules (oLEDs) or polymers (pLEDS) have been a focus of academic and industrial research for the past decade. The devices usually consist of several layers in a sandwich type structure with layer thicknesses ...
Microscopy and Microanalysis, Jul 30, 2021
Microscopy and Microanalysis, Aug 1, 2007
EELS spectrum imaging [1,2], i.e. the collection of EELS data along the spatial and the energylos... more EELS spectrum imaging [1,2], i.e. the collection of EELS data along the spatial and the energyloss dimensions has progressed to the point where sophisticated spectrum image data processing like thickness deconvolution [3], Kramers-Kronig analysis, MLS-fitting for quantitative compositional image analysis [4,5] or automated elemental occurrence mapping [5] now can almost be carried out routinely. This became possible with the advent of combined spectral aberration-, energy-and spatial-drift correction schemes, carried out simultaneously, giving access to high-quality data [6]. However, depending on the data acquisition mode (STEM or EFTEM), experimental difficulties remain, originating primarily from the large intensity differences within an EELS data set. Although the dynamic range of modern electron detectors has been increased compared to the first generation sensors, with high-end CCDs digitizing electron counts up to 16 bit and more, the huge signal of the zero-loss peak compared to the several orders of magnitude weaker intensities in the core-loss region still requires the operator to adjust experimental conditions, preventing the acquisition of both components into one data set under identical electron optical conditions. For EFTEM spectrum imaging this problem can be overcome with an approach that encompasses an automated, dynamic change of image acquisition conditions, as first shown by P. Thomas [3,7]. This idea was improved further by adding extra interactivity and robustness, in the sense that conditions can be changed during the acquisition, allowing for instance to throw away artificial frames, to speed up acquisition in regions of less importance and hence to optimize the total dose on the sample. Further flexibility results from the fact that sophisticated logging is carried out, ensuring maximum compatibility with post-acquisition correction schemes. In brief, our procedure comprises the input of some standard parameters such as slit width, energy range and energy step-size, plus some extra factors, like the targeted intensities, the intended exposure times for a single image acquisition and the maximum number of frames for a particular energy-loss. Other switches are used to prefer multiple frames over longer exposure times for instance. Multiple frames can be corrected for sample drift prior to summation, reducing drift-caused image blur. Energy drift and spectral aberration correction can be applied as additional post-processing steps (Fig 1a,b). A data set acquired by this approach is shown in Fig. 2, taken from a multilayered oxide system, fabricated by pulsed laser PVD (a). The elements contained therein give rise to various edges in the range from 50eV up to 2.2keV (c,d), not yet visible in the uncorrected, unscaled spectrum (b).
Microscopy and Microanalysis, Sep 1, 2007
The characterization of nanostructured devices and functional materials at a nanometer scale is p... more The characterization of nanostructured devices and functional materials at a nanometer scale is paramount for the understanding of the physical or chemical properties. The significant enhancement of the energy resolution in the new generation of commercially available monochromated transmission electron microscopes makes it possible to obtain high quality electron energy-loss spectra. These spectra can be measured with an energy resolution in the range of 0.1-0.2 eV by means of nanometer-sized electron probes. In particular, one can obtain improved information not only about the chemical composition of a sample, but also about chemical bonding [1] and optical properties [2]. The advent of aberration correctors [3] incorporated into the illumination and/or imaging system of (S)TEMs will further improve the performance, thus leading to major advances in materials research.
Analytical and Bioanalytical Chemistry, Sep 14, 2007
In this work we show how energy-filtered imaging can be used to obtain spectrum images of electro... more In this work we show how energy-filtered imaging can be used to obtain spectrum images of electron energy-loss spectrometric data. Focus is placed on improved energy resolution within these data sets. Using two multilayer samples (GaN/AlN and InP/InAs), we demonstrate the advantages of spectrum-imaging and its extended mapping capabilities. Plasmon-ratio maps are used to quickly create high-contrast material maps with high signal-to-noise ratio, ratio-contrast plots are used to gain optimum settings for the ratio maps, and plasmon-position maps are used to map small shifts of the energy position of bulk plasmon peaks.
Ultramicroscopy, Aug 1, 2007
We present a fully automated method for three-dimensional (3D) elemental analysis demonstrated us... more We present a fully automated method for three-dimensional (3D) elemental analysis demonstrated using a ceramic sample of chemistry (Ca)MgTiO(x). The specimen is serially sectioned by a focused ion beam (FIB) microscope, and energy-dispersive X-ray spectrometry (EDXS) is used for elemental analysis of each cross-section created. A 3D elemental model is reconstructed from the stack of two-dimensional (2D) data. This work concentrates on issues arising from process automation, the large sample volume of approximately 17 x 17 x 10 microm(3), and the insulating nature of the specimen. A new routine for post-acquisition data correction of different drift effects is demonstrated. Furthermore, it is shown that EDXS data may be erroneous for specimens containing voids, and that back-scattered electron images have to be used to correct for these errors.
Ultramicroscopy, Dec 1, 2004
Energy filtering transmission electron microscopy (EFTEM) is a widely used technique in many area... more Energy filtering transmission electron microscopy (EFTEM) is a widely used technique in many areas of scientific research. Image contrast in energy-filtered images arises from specific scattering events such as the ionization of atoms. By combining a set of two or more images, relative sample thickness maps or elemental distribution maps can be easily created. It is also possible to acquire a whole series of energy-filtered images to do more complex data analysis. However, whenever several images are combined to extract certain information, problems are introduced due to sample drift between the exposures. In order to obtain artifact-free information, this spatial drift has to be taken care of. Manual alignment by overlaying and shifting the images to find the best overlap is usually very accurate but extremely time consuming for larger data sets. When large amounts of images are recorded in an EFTEM series, manual correction is no longer a reasonable option. Hence, automatic routines have been developed that are mostly based on the cross-correlation algorithm. Existing routines, however, sometimes fail and again make time consuming manual adjustments necessary. In this paper we describe a new approach to the drift correction problem by incorporating a statistical treatment of the data and we present our statistically determined spatial drift (SDSD) correction program. We show its improved performance by applying it to a typical EFTEM series data block.
Ultramicroscopy, Jul 1, 2005
Software is an integral part of all electron microscopy systems, encompassing hardware control, d... more Software is an integral part of all electron microscopy systems, encompassing hardware control, data acquisition and processing. It is unlikely that any one software system will meet all the requirements of experienced users. However, if the software supports custom scripting, then users are well placed to address any shortcomings by writing their own software. In this paper, we highlight the
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Papers by Bernhard Schaffer
Using DigitalMicrograph as a platform we will discuss issues of scientific image understanding and processing which sometimes are software specific, but more often generally apply to scientific data analysis with any software. We will then explore some common image transformations and filters and discuss their impact on the validity of data. Throughout this chapter we will repeatedly use the DigitalMicrograph Scripting Language as a complimentary tool so that you can pick up the valuable scripting skill as we go along.
Over the recent years I have been compiling task oriented tutorials on the use of DM scripting into this handbook. The book is not meant as a course book and it does not offer a well-structured way of learning scripting. It is aimed at no particular audience or experience level but rather concentrates on certain tasks and how one could achieve them.