Determining oxygen relaxations at an interface: A comparative study between transmission electron microscopy techniques

• Published in: Ultramicroscopy Vol. 181; pp. 178 - 190
• Main Authors: Gauquelin, N., van den Bos, K.H.W., Béché, A., Krause, F.F., Lobato, I., Lazar, S., Rosenauer, A., Van Aert, S., Verbeeck, J.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.10.2017
• Subjects: High-resolution (scanning) transmission electron microscopy (HR (S)TEM); Interfaces in perovskite materials; Quantitative electron microscopy; Statistical parameter estimation theory; High-resolution (scanning) transmission electron microscopy (HR (S)TEM); Interfaces in perovskite materials; Statistical parameter estimation theory; Quantitative electron microscopy
• ISSN: 0304-3991; 1879-2723
• DOI: 10.1016/j.ultramic.2017.06.002

•We report a quantitative comparison between TEM techniques.•Statistical parameter estimation theory is used to measure column positions.•Light and heavy columns are located with picometer precision for all techniques.•Precision improves by post-processing techniques. (scan distortion and sample drift)•Ultimate precision determined in counting noise limited scenario. Nowadays, aberration corrected transmission electron microscopy (TEM) is a popular method to characterise nanomaterials at the atomic scale. Here, atomically resolved images of nanomaterials are acquired, where the contrast depends on the illumination, imaging and detector conditions of the microscope. Visualization of light elements is possible when using low angle annular dark field (LAADF) STEM, annular bright field (ABF) STEM, integrated differential phase contrast (iDPC) STEM, negative spherical aberration imaging (NCSI) and imaging STEM (ISTEM). In this work, images of a NdGaO3-La0.67Sr0.33MnO3 (NGO-LSMO) interface are quantitatively evaluated by using statistical parameter estimation theory. For imaging light elements, all techniques are providing reliable results, while the techniques based on interference contrast, NCSI and ISTEM, are less robust in terms of accuracy for extracting heavy column locations. In term of precision, sample drift and scan distortions mainly limits the STEM based techniques as compared to NCSI. Post processing techniques can, however, partially compensate for this. In order to provide an outlook to the future, simulated images of NGO, in which the unavoidable presence of Poisson noise is taken into account, are used to determine the ultimate precision. In this future counting noise limited scenario, NCSI and ISTEM imaging will provide more precise values as compared to the other techniques, which can be related to the mechanisms behind the image recording.