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The Notion of Resolution

  • S. Van Aert
  • Arnold J. den Dekker
  • D. Van Dyck
  • A. Van den Bos

In microscopy, resolution has always been, and still is, an important issue. Since it is not an unambiguously defined physical quantity, it is interpreted in many ways (den Dekker and van den Bos, 1997). The purpose of this chapter is, on the one hand, to briefly review past and existing resolution definitions and methods, and, on the other hand, to present alternative quantitative definitions of resolution based on model fitting. Throughout this chapter, emphasis will be placed on electron microscopy. Using model fitting, the resolution will principally be discussed in terms of the precision with which unknown quantities, atom positions in particular, can be measured. It will be shown that a precision of the order of 0.01 Å is in principle possible even with an electron microscope that is not corrected for spherical and chromatic aberration. Once atom positions can be measured with a precision of 0.01 Å they can be used as input data for theoretical ab initio calculations (Muller, 1998, 1999; Spence, 1999; Kisielowski et al., 2001b). Such calculations make it possible to calculate the properties of a material with a given structure. In this way, the combination of precise experimental structure determination and theoretical calculations contributes to the understanding of the properties–structure relation. A complete understanding of this relation, combined with recent progress in building materials atom by atom, will enable materials science to evolve toward materials design, that is, from describing and understanding toward predicting materials with interesting properties (Wada, 1996; Olson, 1997, 2000; Reed and Tour, 2000; Browning et al., 2001).

Keywords

Point Spread Function Scanning Transmission Electron Microscopy Diffraction Limit Spherical Aberration Joint Probability Density Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • S. Van Aert
    • 1
  • Arnold J. den Dekker
    • 2
  • D. Van Dyck
    • 1
  • A. Van den Bos
    • 3
  1. 1.University of AntwerpBelgium
  2. 2.Delft Centre for Systems and ControlDelft University of TechnologyNetherlands
  3. 3.Delft University of TechnologyNetherlands

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