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

Al-Afeef, A., Bobynko, J., Cockshott, W. P., Craven, A. J., Zuazo, I., Barges, P. and MacLaren, I. (2016) Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing. Ultramicroscopy, 170, pp. 96-106. (doi:10.1016/j.ultramic.2016.08.004) (PMID:27566049)

[img]
Preview
Text
122396.pdf - Accepted Version

933kB

Abstract

We 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). Additionaly, 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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cockshott, Dr William and Craven, Professor Alan and Al-Afeef, Mr Ala and MacLaren, Dr Ian
Authors: Al-Afeef, A., Bobynko, J., Cockshott, W. P., Craven, A. J., Zuazo, I., Barges, P., and MacLaren, I.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Physics and Astronomy
Journal Name:Ultramicroscopy
Publisher:Elsevier
ISSN:0304-3991
ISSN (Online):1879-2723
Published Online:09 August 2016
Copyright Holders:Copyright © 2016 Elsevier
First Published:First published in Ultramicroscopy 170:96-106
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
530481Prec-Hi-Mn: Precipitation in high manganese steels.Ian MaclarenEuropean Commission (EC)RFSR-CT-2010-00P&A - PHYSICS & ASTRONOMY