Nanocartography: Planning for success in analytical electron microscopy

TL;DR

This paper introduces nanocartography, a methodology combining predictive stage motion with crystallographic data to optimize electron microscopy analysis, reducing time and increasing confidence in data collection.

Contribution

It presents a novel nanocartography approach that links stage positions with microstructural and crystallographic information for improved microscopy analysis.

Findings

Reduces analysis time in electron microscopy

Enhances confidence in data collection

Enables solving complex crystallographic unknowns

Abstract

With the increasing diversity in material systems, ever-expanding number of analysis techniques, and the large capital costs of next generation instruments the ability to quickly and efficiently collect data in the electron microscope has become paramount to successful data analysis. Therefore, this research proposes a methodology of nanocartography that combines predictive stage motion with crystallographic information to provide microscopists with a sample map that can both reduce analysis time and improve confidence in data collected. Having a road map of the stage positions linked to microstructural (e.g., interfaces and growing directions) and crystallographic orientation data (e.g., specific poles and planes) provides microscopists with the ability to solve orientation relationships, create oblique tilt series movies, and also solve complex crystallographic unknowns at extremely small scales with minimal information. Most importantly, it can convert any sample orientation relationships across microscopes to increase optimization and collaboration throughout the field.