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Author Fatermans, J.; den Dekker, A. J.; Müller-Caspary, K.; Lobato, I.; O’Leary, C. M.; Nellist, P. D.; Van Aert, S.
Title Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images Type A1 Journal article
Year (down) 2018 Publication Physical review letters Abbreviated Journal Phys Rev Lett
Volume 121 Issue 5 Pages 056101
Keywords A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Abstract Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.
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Publisher Place of Publication Editor
Language Wos 000440143200007 Publication Date 2018-07-30
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-9007 ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor 8.462 Times cited 6 Open Access OpenAccess
Notes The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through Project fundings (No. WO.010.16N, No. G.0368.15N, No. G.0502.18N). The authors are grateful to M. Van Bael and P. Lievens (KU Leuven) and to L. M. Liz-Marzán (CIC biomaGUNE and Ikerbasque) for providing the samples. This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (Grant Agreement No. 770887). Approved Most recent IF: 8.462
Call Number EMAT @ emat @c:irua:152819 Serial 5004
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