Quantitative analysis of spectroscopic low energy electron microscopy data: High-dynamic range imaging, drift correction and cluster analysis.

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.

Imaging pulsed laser deposition growth of homo-epitaxial SrTiO3 by low-energy electron microscopy.

By combining low-energy electron microscopy with in situ pulsed laser deposition we have developed a new technique for film growth analysis, making use of both diffraction and real-space information. Working at the growth temperature, we can use: the intensity and profile variations of the specular beam to follow the coverage in a layer-by-layer fashion; real-space microscopy to follow e.g. atomic steps at the surface; and electron reflectivity to probe the unoccupied band structure of the grown material. Here, we demonstrate our methodology for homo-epitaxial growth of SrTiO3. Interestingly, the same combination of techniques will also be applicable to hetero-epitaxial oxide growth, largely extending the scope of research possibilities.

Striped nanoscale phase separation at the metal-insulator transition of heteroepitaxial nickelates.

Nucleation processes of mixed-phase states are an intrinsic characteristic of first-order phase transitions, typically related to local symmetry breaking. Direct observation of emerging mixed-phase regions in materials showing a first-order metal-insulator transition (MIT) offers unique opportunities to uncover their driving mechanism. Using photoemission electron microscopy, we image the nanoscale formation and growth of insulating domains across the temperature-driven MIT in NdNiO3 epitaxial thin films. Heteroepitaxy is found to strongly determine the nanoscale nature of the phase transition, inducing preferential formation of striped domains along the terraces of atomically flat stepped surfaces. We show that the distribution of transition temperatures is a local property, set by surface morphology and stable across multiple temperature cycles. Our data provide new insights into the MIT of heteroepitaxial nickelates and point to a rich, nanoscale phenomenology in this strongly correlated material.