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Records |
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Author |
Parrilla, M.; De Wael, K. |
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Title |
Wearable self‐powered electrochemical devices for continuous health management |
Type |
A1 Journal article |
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Year |
2021 |
Publication |
Advanced Functional Materials |
Abbreviated Journal |
Adv Funct Mater |
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Volume |
31 |
Issue |
50 |
Pages |
2107042 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Antwerp Electrochemical and Analytical Sciences Lab (A-Sense Lab) |
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Abstract |
The wearable revolution is already present in society through numerous gadgets. However, the contest remains in fully deployable wearable (bio)chemical sensing. Its use is constrained by the energy consumption which is provided by miniaturized batteries, limiting the autonomy of the device. Hence, the combination of materials and engineering efforts to develop sustainable energy management is paramount in the next generation of wearable self-powered electrochemical devices (WeSPEDs). In this direction, this review highlights for the first time the incorporation of innovative energy harvesting technologies with top-notch wearable self-powered sensors and low-powered electrochemical sensors toward battery-free and self-sustainable devices for health and wellbeing management. First, current elements such as wearable designs, electrochemical sensors, energy harvesters and storage, and user interfaces that conform WeSPEDs are depicted. Importantly, the bottlenecks in the development of WeSPEDs from an analytical perspective, product side, and power needs are carefully addressed. Subsequently, energy harvesting opportunities to power wearable electrochemical sensors are discussed. Finally, key findings that will enable the next generation of wearable devices are proposed. Overall, this review aims to bring new strategies for an energy-balanced deployment of WeSPEDs for successful monitoring of (bio)chemical parameters of the body toward personalized, predictive, and importantly, preventive healthcare. |
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Wos |
000694642500001 |
Publication Date |
2021-09-09 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume  |
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Series Issue |
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Edition |
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ISSN |
1616-301x |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
12.124 |
Times cited |
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Open Access |
OpenAccess |
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Notes |
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Approved |
Most recent IF: 12.124 |
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Call Number |
UA @ admin @ c:irua:181306 |
Serial |
8750 |
| Permanent link to this record |
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Author |
Fatermans, J.; de Backer, A.; den Dekker, A.J.; Van Aert, S. |
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Title |
Atom column detection |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
177-214 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
By combining statistical parameter estimation and model-order selection using a Bayesian framework, the maximum a posteriori (MAP) probability rule is proposed in this chapter as an objective and quantitative method to detect atom columns from high-resolution scanning transmission electron microscopy (HRSTEM) images. The validity and usefulness of this approach is demonstrated to both simulated and experimental annular dark-field (ADF) STEM images, but also to simultaneously acquired annular bright-field (ABF) and ADF STEM image data. |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177531 |
Serial |
6775 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Atom counting |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
91-144 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity. |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177529 |
Serial |
6776 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Efficient fitting algorithm |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
73-90 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT) |
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Abstract |
An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic-resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required. |
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Corporate Author |
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Place of Publication |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177528 |
Serial |
6778 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
General conclusions and future perspectives |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
243-253 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale. |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177533 |
Serial |
6781 |
| Permanent link to this record |
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Author |
Fatermans, J.; de Backer, A.; den Dekker, A.J.; Van Aert, S. |
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Title |
Image-quality evaluation and model selection with maximum a posteriori probability |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
215-242 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
The maximum a posteriori (MAP) probability rule for atom column detection can also be used as a tool to evaluate the relation between scanning transmission electron microscopy (STEM) image quality and atom detectability. In this chapter, a new image-quality measure is proposed that correlates well with atom detectability, namely the integrated contrast-to-noise ratio (ICNR). Furthermore, the working principle of the MAP probability rule is described in detail showing a close relation to the principles of model-selection methods. |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177532 |
Serial |
6782 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Introduction |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1-28 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT) |
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Abstract |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177525 |
Serial |
6784 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Optimal experiment design for nanoparticle atom counting from ADF STEM images |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
145-175 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
In this chapter, the principles of detection theory are used to quantify the probability of error for atom counting from high-resolution scanning transmission electron microscopy (HRSTEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom counting using the expression of the probability of error. We show that for very thin objects the low-angle annular dark-field (LAADF) regime is optimal and that for thicker objects the optimal inner detector angle increases. |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177530 |
Serial |
6785 |
| Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Statistical parameter estimation theory : principles and simulation studies |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
29-72 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities. |
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Wos |
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Publication Date |
2021-03-06 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISSN |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Impact Factor |
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Times cited |
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Open Access |
Not_Open_Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177527 |
Serial |
6788 |
| Permanent link to this record |
