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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. |
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Title |
Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images |
Type |
A1 Journal article |
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Year  |
2018 |
Publication |
Physical review letters |
Abbreviated Journal |
Phys Rev Lett |
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Volume |
121 |
Issue |
5 |
Pages |
056101 |
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Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab |
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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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Wos |
000440143200007 |
Publication Date |
2018-07-30 |
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Series Volume |
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Edition |
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ISSN |
0031-9007 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
8.462 |
Times cited |
6 |
Open Access |
OpenAccess |
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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 |
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Call Number |
EMAT @ emat @c:irua:152819 |
Serial |
5004 |
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