High speed/low dose analytical electron microscopy with dynamic sampling

•An algorithmic approach to high speed/low area dose analytical imaging is proposed.•A facile implementation on conventional and arbitrary STEMs is developed.•The method is evaluated on several prototypical analytical specimens.•Over an order of magnitude acceleration/area dose reduction is demonstr...

Full description

Saved in:
Bibliographic Details
Published in:Micron (Oxford, England : 1993) England : 1993), 2018-05, Vol.108, p.31-40
Main Authors: Hujsak, Karl A., Roth, Eric W., Kellogg, William, Li, Yue, Dravid, Vinayak P.
Format: Article
Language:English
Subjects:
Dose reduction
Dynamic sampling
Electron energy loss spectroscopy
Energy dispersive X-Ray spectroscopy
Machine learning
Scanning transmission electron microscopy
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•An algorithmic approach to high speed/low area dose analytical imaging is proposed.•A facile implementation on conventional and arbitrary STEMs is developed.•The method is evaluated on several prototypical analytical specimens.•Over an order of magnitude acceleration/area dose reduction is demonstrated experimentally. Technological advances in electron microscopy, particularly improved detectors and aberration correctors, have led to higher throughput and less invasive imaging of materials and biological structures by enhancing signal-to-noise ratios at lower electron exposures. Analytical methods, such as electron energy loss spectroscopy (EELS) and energy dispersive x-ray spectrometry (EDS), have also benefitted and offer a rich set of local elemental and bonding information with nano-or atomic resolution. However, spatially resolved spectrum imaging with EELS and EDS continue to be difficult to scale due to limited detector collection angles or high signal background, requiring hours or even days for full maps. We present the principle and application of a Multi-Objective Autonomous Dynamic Sampling (MOADS) method which can accelerate spectrum mapping in EELS or EDS by over an order of magnitude. Initial guesses about the true spectrum images are constructed as measurements are collected, which allows the prediction of points which contribute information/contrast. In this fashion, an intelligently selected and reduced set of points which best approximate the true spectrum image are autonomously collected on-the-fly to save considerable time and/or radiative area dose. We implemented MOADS as a software add-on to arbitrary commercial Scanning Transmission Electron Microscopes (STEMs) equipped with a Gatan Digital Micrograph (DM, Gatan ©) interface. We demonstrate the efficacy of our proposed method on several prototypical analytical specimens, as well as dose sensitive materials. It is expected that MOADS and similar supervised dynamic sampling approaches may open the exploration of large area analytical maps or the imaging of beam reactive materials not previously thought feasible.
ISSN:0968-4328
1878-4291
DOI:10.1016/j.micron.2018.03.001