Accurate EELS background subtraction – an adaptable method in MATLAB

Fung, Kayleigh L.Y.; Fay, Michael W.; Collins, Sean M.; Kepaptsoglou, Demie M.; Skowron, Stephen T.; Ramasse, Quentin M.; Khlobystov, Andrei N.

Abstract

Electron energy-loss spectroscopy (EELS) is a technique that can give useful information on elemental composition and bonding environments. However in practice, the complexity of the background contributions, which can arise from multiple sources, can hamper the interpretation of the spectra. As a result, background removal is both an essential and difficult part of EELS analysis, especially during quantification of elemental composition. Typically, a power law is used to fit the background but this is often not suitable for many spectra such as in the low-loss region (< 50 eV) and when there are overlapping EELS edges. In this article, we present a series of scripts written in MATLAB v. R2019b that aims to provide statistical information on the model used to fit the background, allowing the user to determine the accuracy of background subtraction. The scripts were written for background subtraction of vibrational EELS in the ultralow-loss region near the zero-loss peak but can also be applied to other kinds of EEL spectra. The scripts can use a range of models for fitting, provided by the Curve Fitting Toolbox of MATLAB, and the user is able to precisely define the window for fitting as well as for edge integration. We demonstrate the advantages of using these scripts by comparing their background subtraction of example spectra to the most commonly used software, Gatan Microscopy Suite 3. The example spectra include those containing multiple scattering, multiple overlapping peaks, as well as vibrational EELS. Additionally, a comprehensive guide to using the scripts has been included in the Supplementary Information.

Citation

Fung, K. L., Fay, M. W., Collins, S. M., Kepaptsoglou, D. M., Skowron, S. T., Ramasse, Q. M., & Khlobystov, A. N. (2020). Accurate EELS background subtraction – an adaptable method in MATLAB. Ultramicroscopy, 217, Article 113052. https://doi.org/10.1016/j.ultramic.2020.113052

• Journal Article Type: Article
• Acceptance Date: Jun 21, 2020
• Online Publication Date: Jun 25, 2020
• Publication Date: Oct 1, 2020
• Deposit Date: Jun 25, 2020
• Publicly Available Date: Jun 26, 2021
• Journal: Ultramicroscopy
• Print ISSN: 0304-3991
• Electronic ISSN: 1879-2723
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 217
• Article Number: 113052
• DOI: https://doi.org/10.1016/j.ultramic.2020.113052
• Keywords: Instrumentation; Atomic and Molecular Physics, and Optics; Electronic, Optical and Magnetic Materials
• Public URL: https://nottingham-repository.worktribe.com/output/4710623
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0304399120302035?via%3Dihub