Order in Atom Columns Ð Imaging Beyond the Virtual Crystal Approximation
Abstract
In the past decade aberration-corrected scanning transmission electron microscopy (STEM) has revolutionized nanoscale imaging: electron probes of 100 pm size can separate atom columns and the imaging contrast of atom columns correlates with the atomic number Z of the chemical element as Z2 in the dark field (DF) and can be calculated using multi-slice frozen-phonon simulations. When the atom column contains atoms of different chemical elements (mixed sites or partially occupied the order of these two different atoms (or atoms and vacancies) cannot be probed if one accounts for the mixed sites by using a weighted linear combination of elemental scattering factors. This is referred to as the Ôvirtual crystal approximation (VCA)Õ where a Ôvirtual atomÕ is used to describe all the atoms in the column. The order in atom columns has important consequences for chemical catalysis, optical films, thermal and electrical conductivity, mechanical stability and the general process of structure-composition-property optimization. The VCA approach results in significant errors when assigning a composition to an atom column in DF imaging when compared to calculating the contrast using explicit ordering and dynamical scattering theory. A scatter of intensities of up to 20% is observable when calculating explicit cation ordering in an atom column. We will advance ways to image beyond the VCA using atom-segregated ÔisophilicÕ configurations as starting models for novel mathematical approaches in machine learning and non-linear approximations. Using a Protochips Fusion Select device we attempt to observe in-situ the change of order in atom columns at different temperatures and under current load due to atom migration and provide input for optimization of functionalities and life times of materials used in devices and as catalysts. Furthermore, we want to advance bright field imaging as a tool to probe the order of lower Z elements like oxygen. The growing use of aberration-corrected STEM for materials science around the world (> 500 machines now) calls for a more quantitative and iconoclastic approach to imaging data - beyond the VCA.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 31, 2020
- Source ID
- W911NF2010318
Entities
People
- Michael Matthews
Organizations
- Army Contracting Command
- United States Army
- University of South Carolina