Ultimate Image Processing for Scanning Transmission Electron Microscopy

75339-Annular-dark-field scanning transmission electron microscopy (ADF-STEM) makes possible the formation of incoherent electron images with atomic-scale spatial resolution. However, two sources of error degrade the quality of these images: (1) electron counting noise and (2) blurring, which results from either geometric aberrations in the electron optics or the physics of the beam-sample interaction. This project will develop both off-line and on-line ¿ the latter in near real time ¿ image-reconstruction software for the denoising and deconvolution of two-dimensional ADF-STEM image data. In addition, new data-acquisition and post-processing techniques for the generation of three-dimensional atomic-scale images will be explored. Phase I will: (1) elucidate the noise properties of ADF-STEM electron microscopes; (2) elucidate the blurring properties of ADF electron microscopes; (3) incorporate the results of (1) and (2) into a non-parametric image reconstruction regimen that eliminates noise and increases spatial resolution in two-dimensional ADF-STEM images; (4) apply minimum-complexity principles to the parametric determination of atomic positions in two-dimensional ADF-STEM images; and (5) attempt to extend the results to three-dimensional atomic-scale imaging. Commercial Applications and Other Benefits as described by the awardee: The image-processing capabilities provided by this software should be amenable for licensing to commercial electron-microscope manufacturers.