Electron tomography of regularly shaped nanostructures under non‐linear image acquisition

I. (2016) Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing. Ultramicroscopy.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/122396/ A B S T R A C TWe have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionally, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS.

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“…no cupping artefacts [46,47]), as is clearly shown in the line profiles in Fig. 8(c) and (d) for both the V-L 2,3 maps and the HAADF maps.…”

Section: Experimental Study: Reconstructions On Experimental Maps Fromentioning

confidence: 51%

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

et al. 2016

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“…The scattering contribution from a voxel is not just dependent on the nuclei in that voxel, but also of the form of the beam reaching the voxel. Consequently, the signal in HAADF-STEM does not vary linearly with mass-thickness, as has been observed in a number of cases [4][5][6][7][8][9] .…”

Section: Introductionmentioning

confidence: 68%

Optimizing experimental parameters for the projection requirement in HAADF-STEM tomography

et al. 2017

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Tomographic reconstruction algorithms offer a means by which a tilt-series of transmission images can be combined to yield a three dimensional model of the specimen. Conventional reconstruction algorithms assume that the measured signal is a linear projection of some property, typically the density, of the material. Here we report the use of multislice simulations to investigate the extent to which this assumption is met in HAADF-STEM imaging. The use of simulations allows for a systematic survey of a range of materials and microscope parameters to inform optimal experimental design. Using this approach it is demonstrated that the imaging of amorphous materials is in good agreement with the projection assumption in most cases. Images of crystalline specimens taken along zone-axes are found to be poorly suited for conventional linear reconstruction algorithms due to channelling effects which produce enhanced intensities compared with off-axis images, and poor compliance with the projection requirement. Off-axis images are found to be suitable for reconstruction, though they do not strictly meet the linearity requirement in most cases. It is demonstrated that microscope parameters can be selected to yield improved compliance with the projection requirement.

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“…Our implementation is more than an order of magnitude faster than SIRT [4,5]. Previous work has applied the GT concept to TEM images, but the back-projection algorithm used in [7] needs both postreconstruction thresholding and is not proved to be convergent; the algorithm used in [8] is also not proved to be convergent. Our GT implementation [3] was applied to the same nanowire cross-sections ( Fig.…”

Section: Geometric Tomography From Shadow Outlinesmentioning

confidence: 99%

Reconstruction of an InAs nanowire using geometric and algebraic tomography

Pennington

König

Alpers

et al. 2011

J. Phys.: Conf. Ser.

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Geometric tomography and conventional algebraic tomography algorithms are used to reconstruct cross-sections of an InAs nanowire from a tilt series of experimental annular dark-field images. Both algorithms are also applied to a test object to assess what factors affect the reconstruction quality. When using the present algorithms, geometric tomography is faster, but artifacts in the reconstruction may be difficult to recognize.

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Electron tomography of regularly shaped nanostructures under non‐linear image acquisition

Cited by 27 publications

References 28 publications

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

Optimizing experimental parameters for the projection requirement in HAADF-STEM tomography

Reconstruction of an InAs nanowire using geometric and algebraic tomography

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