Orientation Mapping of Graphene Using 4D STEM-in-SEM

Published

October 13, 2020

Author(s)

Benjamin W. Caplins, Jason D. Holm, Ryan M. White, Robert R. Keller

Abstract

A scanning diffraction technique is implemented in the scanning electron microscope. The technique, referred to as 4D STEM-in-SEM (four-dimensional scanning transmission electron microscopy in the scanning electron microscope), collects a diffraction pattern from each point on a sample which is saved to disk for further analysis. The diffraction patterns are collected using an on-axis lens-coupled phosphor/CCD arrangement. Synchronization between the electron beam and the camera exposure is accomplished with off-the-shelf data acquisition hardware. Graphene is used as a model system to test the sensitivity of the instrumentation and develop some basic analysis techniques. The data show interpretable diffraction patterns from monolayer graphene with integration times as short as 0.5 ms with a beam current of 245 pA 7.65 x 10^5 incident electrons per pixel). Diffraction patterns are collected at a rate of ca. 100/s from the mm to nm length scales. Using a grain boundary as a `knife-edge', the spatial resolution of the technique is demonstrated to be <5.6 nm (edge-width 25%-75%). Analysis of the orientation of the diffraction patterns yields an angular (orientation) precision of <0.19 deg (full width at half maximum) for unsupported monolayer graphene. In addition, it is demonstrated that the 4D datasets have the information content necessary to analyze complex and heterogeneous multilayer graphene films.

Citation

Ultramicroscopy

Volume

219

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.ultramic.2020.113137

Local Download

Keywords

scanning transmission electron microscopy, STEM, scanning electron microscopy, SEM, STEM-in- SEM, 4D STEM, graphene, 2d materials, orientation

Citation

Caplins, B. , Holm, J. , White, R. and Keller, R. (2020), Orientation Mapping of Graphene Using 4D STEM-in-SEM, Ultramicroscopy, [online], https://doi.org/10.1016/j.ultramic.2020.113137 (Accessed December 11, 2024)