A symmetry-derived mechanism for atomic resolution imaging.

We introduce an image-contrast mechanism for scanning transmission electron microscopy (STEM) that derives from the local symmetry within the specimen. For a given position of the electron probe on the specimen, the image intensity is determined by the degree of similarity between the exit electron-intensity distribution and a chosen symmetry operation applied to that distribution. The contrast mechanism detects both light and heavy atomic columns and is robust with respect to specimen thickness, electron-probe energy, and defocus. Atomic columns appear as sharp peaks that can be significantly narrower than for STEM images using conventional disk and annular detectors. This fundamentally different contrast mechanism complements conventional imaging modes and can be acquired simultaneously with them, expanding the power of STEM for materials characterization.

Pixelated detectors and improved efficiency for magnetic imaging in STEM differential phase contrast.

The application of differential phase contrast imaging to the study of polycrystalline magnetic thin films and nanostructures has been hampered by the strong diffraction contrast resulting from the granular structure of the materials. In this paper we demonstrate how a pixelated detector has been used to detect the bright field disk in aberration corrected scanning transmission electron microscopy (STEM) and subsequent processing of the acquired data allows efficient enhancement of the magnetic contrast in the resulting images. Initial results from a charged coupled device (CCD) camera demonstrate the highly efficient nature of this improvement over previous methods. Further hardware development with the use of a direct radiation detector, the Medipix3, also shows the possibilities where the reduction in collection time is more than an order of magnitude compared to the CCD. We show that this allows subpixel measurement of the beam deflection due to the magnetic induction. While the detection and processing is data intensive we have demonstrated highly efficient DPC imaging whereby pixel by pixel interpretation of the induction variation is realised with great potential for nanomagnetic imaging.