Quantitative analysis of spectroscopic Low Energy Electron Microscopy data: High-dynamic range imaging, drift correction and cluster analysis

Abstract

For many complex materials systems, low-energy electron microscopy (LEEM) offers detailed insights into morphology and crystallography by naturally combining real-space and reciprocal-space information. Its unique strength, however, is that all measurements can easily be performed energy-dependently. Consequently, one should treat LEEM measurements as multi-dimensional, spectroscopic datasets rather than as images to fully harvest this potential. Here we describe a measurement and data analysis approach to obtain such quantitative spectroscopic LEEM datasets with high lateral resolution. The employed detector correction and adjustment techniques enable measurement of true reflectivity values over four orders of magnitudes of intensity. Moreover, we show a drift correction algorithm, tailored for LEEM datasets with inverting contrast, that yields sub-pixel accuracy without special computational demands. Finally, we apply dimension reduction techniques to summarize the key spectroscopic features of datasets with hundreds of images into two single images that can easily be presented and interpreted intuitively. We use cluster analysis to automatically identify different materials within the field of view and to calculate average spectra per material. We demonstrate these methods by analyzing bright-field and dark-field datasets of few-layer graphene grown on silicon carbide and provide a high-performance Python implementation.

References in corpus (12)

• Scikit-learn: Machine Learning in Python
• scikit-image: Image processing in Python
• Quasi-free Standing Epitaxial Graphene on SiC by Hydrogen Intercalation
• Microscopic thickness determination of thin graphite films formed on SiC from quantized oscillation in reflectivity of low-energy electrons
• The quasi-free-standing nature of graphene on H-saturated SiC(0001)
• Low-energy Electron Reflectivity from Graphene
• Good Colour Maps: How to Design Them
• Intrinsic Instability of Aberration-Corrected Electron Microscopes
• Stacking domains in graphene on silicon carbide: a pathway for intercalation
• Quantifying work function differences using low-energy electron microscopy: the case of mixed-terminated strontium titanate
• Measuring the Local Twist Angle and Layer Arrangement in Van der Waals Heterostructures
• Signal Enhancement as Minimization of Relevant Information Loss

Cited by in corpus (6)

• Imaging moiré deformation and dynamics in twisted bilayer graphene
• Direct evidence for flat bands in twisted bilayer graphene from nano-ARPES
• Optical Near-Field Electron Microscopy
• Low-energy electron microscopy as a tool for analysis of self-assembled molecular layers on surfaces
• Low-energy electron microscopy intensity-voltage data -- factorization, sparse sampling, and classification
• Low-Energy Electron Microscopy contrast of stacking boundaries: comparing twisted few-layer graphene and strained epitaxial graphene on silicon carbide