Electron tomography combining ESEM and STEM: A new 3D imaging technique

cited By 13International audienceThis paper presents the development and the application of a new electron tomography technique based on STEM (Scanning Transmission Electron Microscopy) configuration in ESEM (Environmental Scanning Electron Microscopy). This combination provides a new approach for the characterization of the 3D structure of materials, as it optimizes a compromise between the resolution level of a few tens of nm and the large tomogram size due to the high thickness of transparency. The method is well adapted for non-conductive samples, and exhibits good contrast even for materials with low atomic number. The paper describes the development of a dedicated stage for this new tomography technique. Taking advantage of the size of the ESEM chamber, the range of tilt angles is not limited by the space around the sample. The performance of this device is illustrated through the three-dimensional characterization of samples issued from materials science and chosen to illustrate the results in resolution, contrast and thickness. © 2011 Elsevier B.V

Feature Adaptive Sampling for Scanning Electron Microscopy

A new method for the image acquisition in scanning electron microscopy (SEM) was introduced. The method used adaptively increased pixel-dwell times to improve the signal-to-noise ratio (SNR) in areas of high detail. In areas of low detail, the electron dose was reduced on a per pixel basis, and a-posteriori image processing techniques were applied to remove the resulting noise. The technique was realized by scanning the sample twice. The first, quick scan used small pixel-dwell times to generate a first, noisy image using a low electron dose. This image was analyzed automatically, and a software algorithm generated a sparse pattern of regions of the image that require additional sampling. A second scan generated a sparse image of only these regions, but using a highly increased electron dose. By applying a selective low-pass filter and combining both datasets, a single image was generated. The resulting image exhibited a factor of ≈3 better SNR than an image acquired with uniform sampling on a Cartesian grid and the same total acquisition time. This result implies that the required electron dose (or acquisition time) for the adaptive scanning method is a factor of ten lower than for uniform scanning