Atomic-scale mapping and quantification of local Ruddlesden-Popper phase variations

Kavli Affiliate: Darrell G. Schlom

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| Summary:

The Ruddlesden-Popper ($A_{n+1}B_{n}text{O}_{3n+1}$) compounds are a highly
tunable class of materials whose functional properties can be dramatically
impacted by their structural phase $n$. The negligible energetic differences
associated with forming a sample with a single value of $n$ versus a mixture of
$n$ makes the growth of these materials difficult to control and can lead to
local atomic-scale structural variation arising from small stoichiometric
deviations. In this work, we present a Python analysis platform to detect,
measure, and quantify the presence of different $n$-phases based on
atomic-resolution scanning transmission electron microscopy (STEM) images in a
statistically rigorous manner. We employ phase analysis on the 002 Bragg peak
to identify horizontal Ruddlesden-Popper faults which appear as regions of high
positive compressive strain within the lattice image, allowing us to quantify
the local structure. Our semi-automated technique offers statistical advantages
by considering effects of finite projection thickness, limited fields of view,
and precise sampling rates. This method retains the real-space distribution of
layer variations allowing for a spatial mapping of local $n$-phases, enabling
both quantification of intergrowth occurrence as well as qualitative
description of their distribution, opening the door to new insights and levels
of control over a range of layered materials.

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