Transmission electron microscopy (TEM) is a very powerful technique to investigate materials down to their atomic components. Its versatility allows quantifying samples from their shape to the nature of their constituents and surroundings. However, the strong interaction of the electron beam with matter potentially induces damages in samples under investigation, especially for those composed of soft matter such as zeolites, metal organic frameworks (MOFs) and most life science samples. Current workarounds involve the reduction of the beam intensity, such as in the so-called low dose imaging, or increase of the detector performances as provided e.g. by direct electron detectors.
Recently, improvement in signal processing lead to the development of compressed sensing [1, 2], a numerical algorithm based on the assumption that real life images are sparse in some particular well-chosen basis. Images can then be expressed with much less components than what required by the Nyquist sampling theorem. By extension, not all pixels in a given image are necessary and only a random selection of them is sufficient to retrieve the original image with fidelity. By definition, compressed sensing is a very dose efficient technique as only parts of the sample need to be exposed to the electron beam to reconstruct a faithful image. So far, only theoretical implementations of compressed sensing were investigated in the TEM community, focused mostly on the case of tomographic reconstructions .
Very recently, we demonstrated the first physical implementation of compressed sensing in a Scanning TEM (STEM) based on the use of a solenoid as a fast beam blanker . The solenoid is placed in the condenser plane of a STEM in a specially designed condenser aperture holder with feedthrough electrical contacts. By synchronizing the STEM signal with the current source driving the solenoid, we successfully acquired compressed images by shifting the beam away from the region of interest on blanked pixels. The case of both medium scale imaging (Fig.1) and high resolution imaging (Fig. 2) was investigated and reconstructed using the SPGL1 algorithm  with a signal compression of 80%. The present setup, although still quite far from low dose imaging conditions, has lead to successful imaging of a cross grating and a SrTiO3 sample. Latest results revealed that a checkerboard pattern, the most demanding pattern for the fast beam blanker, could be acquired with a dwell time of 40 µs and a beam deflection of 225 nm, as shown in Fig. 3.
By further improving the experimental setup, we expect reducing the acquisition dwell time to values within the µs range. Such improvements will offer possibilities for realizing improved images and tomography experiments of electron beam sensitive materials.
 Candes E. J. et al., Communications on Pure and Applied Mathematics, 59 (2006) 1207-1223.
 Donoho, D., IEEE Transactions on Information Theory 52 (2006) 1289-1306.
 Saghi Z. et al., Advanced Structural and Chemical Imaging 1 (2015) 1-10.
 Béché A., Goris B., Freitag B. and Verbeeck J., APL 108 (2016) 093103.
 Van den Berg E. and Friedlander M. P., SIAM Journal on Scientific Computing, 31 (2008) 890-912.
Aknowledgments: A.B and J.V. acknowledge funding from the ERC Grant No. 278510 VORTEX and under a contract for an Integrated Infrastructure Initiative No. 312483 ESTEEM2. B.G. acknowledges the FWO for a postdoctoral research grant.
To cite this abstract:Armand Béché, Bart Goris, Bert Freitag, Jo Verbeeck; Compressed sensing for beam sensitive materials imaging in Scanning Transmission Electron Microscopy. The 16th European Microscopy Congress, Lyon, France. https://emc-proceedings.com/abstract/compressed-sensing-for-beam-sensitive-materials-imaging-in-scanning-transmission-electron-microscopy/. Accessed: May 24, 2019
EMC Abstracts - https://emc-proceedings.com/abstract/compressed-sensing-for-beam-sensitive-materials-imaging-in-scanning-transmission-electron-microscopy/