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arXiv · 1910.05763

Low-Energy Electron Potentiometry

Abstract

In a lot of systems, charge transport is governed by local features rather than being a global property as suggested by extracting a single resistance value. Consequently, techniques that resolve local structure in the electronic potential are crucial for a detailed understanding of electronic transport in realistic devices. Recently, we have introduced a new potentiometry method based on low-energy electron microscopy (LEEM) that utilizes characteristic features in the reflectivity spectra of layered materials [1]. Performing potentiometry experiments in LEEM has the advantage of being fast, offering a large field of view and the option to zoom in and out easily, and of being non-invasive compared to scanning-probe methods. However, not all materials show clear features in their reflectivity spectra. Here we, therefore, focus on a different version of low-energy electron potentiometry (LEEP) that uses the mirror mode transition, i.e. the drop in electron reflectivity around zero electron landing energy when they start to interact with the sample rather than being reflected in front of it. This transition is universal and sensitive to the local electrostatic surface potential (either workfunction or applied potential). It can consequently be used to perform LEEP experiments on a broader range of material compared to the method described in Ref. [1]. We provide a detailed description of the experimental setup and demonstrate LEEP on workfunction-related intrinsic potential variations on the Si(111) surface and for a metal-semiconductor-metal junction with an external bias applied. In the latter, we visualize the Schottky effect at the metal-semiconductor interface. Finally, we compare how robust the two LEEP techniques discussed above are against image distortions due to sample inhomogeneities or contamination.

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BibTeXRIS

Johannes Jobst, Jaap Kautz, Maria Mytiliniou, Rudolf M. Tromp Sense Jan van der Molen. 2019-10-13. Low-Energy Electron Potentiometry. https://doi.org/10.1016/j.ultramic.2017.05.015

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