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

Dataset doi link: https://doi.org/10.34863/amcp-4s12

Paper doi:
1: https://doi.org/10.1021/acs.nanolett.2c03893

Authors: Erin E. Fleck¹ Matthew R. Barone² Hari P. Nair² Nathaniel J. Schreiber² Natalie M. Dawley² Darrell G. Schlom^2,3,4 Berit H. Goodge¹ Lena F. Kourkoutis^1,3

Author affiliations:
¹: Department of Applied Engineering Physics - Cornell University
²: Department of Materials Science and Engineering - Cornell University
³: Kavli Institute at Cornell for Nanoscale Science
⁴: Leibniz-Institut für Kristallzüchtung

Example Python notebooks for basic implementation of the phase-lock-in method described in Goodge, et al. "Disentangling Coexisting Structural Order Through Phase Lock-In Analysis of Atomic-Resolution STEM Data”, Microscopy and Microanalysis (2022) [ https://doi.org/10.1017/S1431927622000125] and the image-based structural analysis described in Fleck, et al. “Atomic-Scale Mapping and Quantification of Local RuddlesdenPopper Phase Variations”, Nano Letters (2022) [https://doi.org/10.1021/acs.nanolett.2c03893], as well as raw HAADF-STEM images and complete notebooks used to produce the figures in Fleck, et al. with all relevant parameters (e.g., Fourier mask size, strain threshold, horizontal sampling).

Code
Item	Type	File
Python Cache	zipped folder	__pycache__.zip
Phase-Strain Basic	ipynb	Phase-Strain_Basic.ipynb
corrCROP_31-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1	tif	corrCROP_31-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1.tif
Click plot	py	clickplot.py
Walkthrough	ipynb	RP_Walkthrough.ipynb
RP Basic	ipynb	RP_Basic.ipynb
RP Analysis	ipynb	RP_Analysis.ipynb
corrCROP_07_3.6Mx_50x0.5us_1024px_0.9nAscreenI_50umC2_1	tif	corrCROP_07_3.6Mx_50x0.5us_1024px_0.9nAscreenI_50umC2_1.tif
corrCROP_07_3.6Mx_50x0.5us_1024px_0.9nAscreenI_50umC2_1	py	VizPLDs.py
Utils	py	utils.py
Pld	py	pld.py
27_SRO_5-1Mx_12us_1024px	tif	27_SRO_5-1Mx_12us_1024px.tif
Figure 1
Item	Type	File
06_3.6Mx_1x1us_4096px_50umC2_CL130mm_600pAscreen_1	tif	06_3.6Mx_1x1us_4096px_50umC2_CL130mm_600pAscreen_1.tif
RP_Fig1	ipynb	RP_Fig1.ipynb
Figure 2
Item	Type	File
08_2.55Mx_1x1us_4096px_50umC2_CL130mm_600pAscreen_1	tif	08_2.55Mx_1x1us_4096px_50umC2_CL130mm_600pAscreen_1.tif
RP_Fig2	ipynb	RP_Fig2.ipynb
Figure 3
Item	Type	File
Fig3_raw-strain	png	Fig3_raw-strain.png
Fig3a_corrCROP_29-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1	tif	Fig3a_corrCROP_29-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1.tif
RP_Fig3a	ipynb	RP_Fig3a.ipynb
Fig3b_corrCROP_29-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1	tif	Fig3b_corrCROP_29-rot_2.55Mx_50x0.25us_2048px_160mmCL_70umC2_0.5nA_mono30_spot9_1.tif
RP_Fig3b	ipynb	RP_Fig3b.ipynb
Figure 4
Item	Type	File
Fig4_raw-strain	png	Fig4_raw-strain.png
Figure 4a
Item	Type	File
42_SRO_3-6Mx_12us_1024px	tif	42_SRO_3-6Mx_12us_1024px.tif
RP_Fig4a	ipynb	RP_Fig4a.ipynb
Figure 4b
Item	Type	File
Python Cache	zipped folder	__pycache__.zip
Python Cache	zipped folder	RP_Fib4b.ipynb.zip
Click plot	py	clickplot.py
vizPLDs	py	vizPLDs.py
Utils	py	utils.py
Pld	py	pld.py
42_SRO_3-6Mx_12us_1024px	tif	42_SRO_3-6Mx_12us_1024px.tif
Figure 5
Item	Type	File
42_SRO_3-6Mx_12us_1024px	ipynb	RP_Fib5.ipynb
Fig5 Raw Strain	png	Fig5_raw-strain.png
42_SRO_3-6Mx_12us_1024px	tif	42_SRO_3-6Mx_12us_1024px.tif