Python/Raspberry Pi-based Low Energy Electron Diffraction Imaging and Analysis for Surface Science

Abstract

Low Energy Electron Diffraction (LEED) is a powerful tool for 2D structures on surfaces and is critical for studying new materials for superconductivity and quantum computing. Real time diffraction patterns on a hemispherical phosphor screen are recorded with high dynamic range and synchronized with other experimental variables. Spot pattern detection and automatic analysis provides experimental insight and system monitoring. I'll briefly introduce LEED and show how spot patterns are analyzed off-line then describe the new Raspberry Pi High Quality Camera and how to capture high dynamic range images. The Raspberry Pi 4 is a powerful computer which can coordinate the real-time imaging with other experimental parameters by directly controlling equipment via RS-232 and USB & monitoring others via GPIB. Last I'll show how automatic spot detection via NumPy/SciPy and OpenCV on Raspberry Pi are used to analyze data in real time and provide the experimenter new insight into the results.

Description