“Quantitative annular dark field scanning transmission electron microscopy for nanoparticle atom-counting : what are the limits?”.de Backer A, De wael A, Gonnissen J, Martinez GT, Béché, A, MacArthur KE, Jones L, Nellist PD, Van Aert S, Journal of physics : conference series 644, 012034 (2015). http://doi.org/10.1088/1742-6596/644/012034
Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
DOI: 10.1088/1742-6596/644/012034
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“Quantitative annular dark field scanning transmission electron microscopy for nanoparticle atom-counting: What are the limits?”.De Backer A, De Wael A, Gonnissen J, Martinez GT, Béché, A, MacArthur KE, Jones L, Nellist PD, Van Aert S, Journal of physics : conference series 644Electron Microscopy and Analysis Group Conference (EMAG), JUN 02-JUL 02, 2015, Manchester, ENGLAND, 012034 (2015). http://doi.org/10.1088/1742-6596/644/1/012034
Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT)
DOI: 10.1088/1742-6596/644/1/012034
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“Optimizing Experimental Conditions for Accurate Quantitative Energy-Dispersive X-ray Analysis of Interfaces at the Atomic Scale”. MacArthur KE, Yankovich AB, Béché, A, Luysberg M, Brown HG, Findlay SD, Heggen M, Allen LJ, Microscopy And Microanalysis , 1 (2021). http://doi.org/10.1017/S1431927621000246
Abstract: The invention of silicon drift detectors has resulted in an unprecedented improvement in detection efficiency for energy-dispersive X-ray (EDX) spectroscopy in the scanning transmission electron microscope. The result is numerous beautiful atomic-scale maps, which provide insights into the internal structure of a variety of materials. However, the task still remains to understand exactly where the X-ray signal comes from and how accurately it can be quantified. Unfortunately, when crystals are aligned with a low-order zone axis parallel to the incident beam direction, as is necessary for atomic-resolution imaging, the electron beam channels. When the beam becomes localized in this way, the relationship between the concentration of a particular element and its spectroscopic X-ray signal is generally nonlinear. Here, we discuss the combined effect of both spatial integration and sample tilt for ameliorating the effects of channeling and improving the accuracy of EDX quantification. Both simulations and experimental results will be presented for a perovskite-based oxide interface. We examine how the scattering and spreading of the electron beam can lead to erroneous interpretation of interface compositions, and what approaches can be made to improve our understanding of the underlying atomic structure.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 1.891
DOI: 10.1017/S1431927621000246
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“Dose limited reliability of quantitative annular dark field scanning transmission electron microscopy for nano-particle atom-counting”. de Backer A, Martinez GT, MacArthur KE, Jones L, Béché, A, Nellist PD, Van Aert S, Ultramicroscopy 151, 56 (2015). http://doi.org/10.1016/j.ultramic.2014.11.028
Abstract: Quantitative annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique to characterise nano-particles on an atomic scale. Because of their limited size and beam sensitivity, the atomic structure of such particles may become extremely challenging to determine. Therefore keeping the incoming electron dose to a minimum is important. However, this may reduce the reliability of quantitative ADF STEM which will here be demonstrated for nano-particle atom-counting. Based on experimental ADF STEM images of a real industrial catalyst, we discuss the limits for counting the number of atoms in a projected atomic column with single atom sensitivity. We diagnose these limits by combining a thorough statistical method and detailed image simulations.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 29
DOI: 10.1016/j.ultramic.2014.11.028
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