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arxiv: 1803.05837 · v2 · pith:TT3M2E7Cnew · submitted 2018-03-15 · ❄️ cond-mat.mtrl-sci

Automated image acquisition for low-dose STEM at atomic resolution

classification ❄️ cond-mat.mtrl-sci
keywords dataacquisitionsampleautomatedbeamdamagedoseelectron
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Beam damage is a major limitation in electron microscopy that becomes increasingly severe at higher resolution. One possible route to circumvent radiation damage, which forms the basis for single-particle electron microscopy and related techniques, is to distribute the dose over many identical copies of an object. For the acquisition of low-dose data, ideally no dose should be applied to the region of interest prior to the acquisition of data. We present an automated approach that can collect large amounts of data efficiently by acquiring images in an user-defined area-of-interest with atomic resolution. We demonstrate that the stage mechanics of the Nion UltraSTEM, combined with an intelligent algorithm to move the sample, allows the automated acquisition of atomically resolved images from micron-sized areas of a graphene substrate. Moving the sample stage automatically in a regular pattern over the area-of-interest enables the collection of data from pristine sample regions without exposing them to the electron beam before recording an image. Therefore, it is possible to obtain data with minimal dose (no prior exposure from focusing), which is only limited by the minimum signal needed for data processing. This enables us to prevent beam induced damage in the sample and to acquire large datasets within a reasonable amount of time.

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