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2012 | Buch

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Modeling Nanoscale Imaging in Electron Microscopy

herausgegeben von: Thomas Vogt, Wolfgang Dahmen, Peter Binev

Verlag: Springer US

Buchreihe : Nanostructure Science and Technology

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Modeling Nanoscale Imaging in Electron Microscopy presents the recent advances that have been made using mathematical methods to resolve problems in microscopy. With improvements in hardware-based aberration software significantly expanding the nanoscale imaging capabilities of scanning transmission electron microscopes (STEM), these mathematical models can replace some labor intensive procedures used to operate and maintain STEMs. This book, the first in its field since 1998, will also cover such relevant concepts as superresolution techniques, special denoising methods, application of mathematical/statistical learning theory, and compressed sensing.

Inhaltsverzeichnis

Frontmatter

Kantianism at the Nano-scale

Abstract

The smallest object that the human eye can detect has dimensions of around 50 microns. So there is a sense in which a sphere that is, say, 10 microns in diameter, is invisible to us. Some philosophers have argued that the invisibility, to us, of a 10 microns sphere has epistemological significance that, in particular, our knowledge about and our understanding of such things may be qualitatively different from our knowledge and understanding of directly observable objects. Along with many other philosophers, I find this view untenable. It seems clear that although they are not directly observable to us, 10 microns spheres are nonetheless the same sort of thing as their larger cousins (the 50 microns spheres). Indeed, there are creatures whose visual apparatus works more or less as ours does that can directly see 10 microns spheres.

Michael Dickson

The Application of Scanning Transmission Electron Microscopy (STEM) to the Study of Nanoscale Systems

Abstract

In this chapter, the basic principles of atomic resolution scanning transmission electron microscopy (STEM) will be described. Particular attention will be paid to the benefits of the incoherent Z-contrast imaging technique for structural determination and the benefits of aberration correction for improved spatial resolution and sensitivity in the acquired images. In addition, the effect that the increased beam current in aberration corrected systems has on electron beam-induced structural modifications of inorganic systems will be discussed. Procedures for controlling the electron dose will be described along with image processing methods that enable quantified information to be extracted from STEM images. Several examples of the use of aberration-corrected STEM for the study of nanoscale systems will be presented; a quantification of vacancies in clathrate systems, a quantification of N doping in GaAs, a quantification of the size distribution in nanoparticle catalysts, and an observation of variability in dislocation core composition along a low-angle grain boundary in SrTiO₃. The potential for future standardized methods to reproducibly quantify structures determined by STEM and/or high-resolution TEM will also be discussed.

N. D. Browning, J. P. Buban, M. Chi, B. Gipson, M. Herrera, D. J. Masiel, S. Mehraeen, D. G. Morgan, N. L. Okamoto, Q. M. Ramasse, B. W. Reed, H. Stahlberg

High Resolution ExitWave Restoration

Abstract

We review the use of restoration methods that recover the complex specimen exit wave from a suitably conditioned data set of high resolution transmission electron microscope images. Various levels of theory underlying the post-acquisition processing required are described together with the requirements for aberration measurement.

Sarah J. Haigh, Angus I. Kirkland

Compressed Sensing and Electron Microscopy

Abstract

Compressed sensing (CS) is a relatively new approach to signal acquisition which has as its goal to minimize the number of measurements needed of the signal in order to guarantee that it is captured to a prescribed accuracy. It is natural to inquire whether this new subject has a role to play in electron microscopy (EM). In this chapter, we shall describe the foundations of CS and then examine which parts of this new theory may be useful in EM.

Peter Binev, Wolfgang Dahmen, Ronald DeVore, Philipp Lamby, Daniel Savu, Robert Sharpley

High-Quality Image Formation by Nonlocal Means Applied to High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF–STEM)

Abstract

We outline a new systematic approach to extracting high-quality information from HAADF–STEM images which will be beneficial to the characterization of beam-sensitive materials. The idea is to treat several, possibly many, low-electron dose images with specially adapted digital image processing concepts at a minimum allowable spatial resolution. Our goal is to keep the overall cumulative electron dose as low as possible while still staying close to an acceptable level of physical resolution. We shall present the main conceptual imaging concepts and restoration methods that we believe are suitable for carrying out such a program and, in particular, allow one to correct special acquisition artifacts which result in blurring, aliasing, rastering distortions, and noise.

Peter Binev, Francisco Blanco-Silva, Douglas Blom, Wolfgang Dahmen, Philipp Lamby, Robert Sharpley, Thomas Vogt

Center of Mass Operators for Cryo-EM—Theory and Implementation

Abstract

A central task in recovering the structure of a macromolecule using cryo-electron microscopy is to determine a three-dimensional model of the macromolecule from many of its two-dimensional projection images, taken from random and unknown directions. We have recently proposed the globally consistent angular reconstitution (GCAR) [7], which allows to determine a three-dimensional model of the molecule without assuming any prior knowledge on the reconstructed molecule or the distribution of its viewing directions. In this chapter we briefly introduce the idea behind the algorithm [7], and describe several improvements and implementation details required in order to apply it on experimental data. In particular, we extend GCAR with self-stabilizing refinement iterations that increase its robustness to noise, modify the common lines detection procedure to handle the relative (unknown) shifts between images, and demonstrate the algorithm on real data obtained by an electron microscope.

Amit Singer, Yoel Shkolnisky

Backmatter

Titel: Modeling Nanoscale Imaging in Electron Microscopy
herausgegeben von: Thomas Vogt
Wolfgang Dahmen
Peter Binev
Verlag: Springer US
Electronic ISBN: 978-1-4614-2191-7
Print ISBN: 978-1-4614-2190-0
DOI: https://doi.org/10.1007/978-1-4614-2191-7

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