14 research outputs found
py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets
Scanning transmission electron microscopy (STEM) allows for imaging,
diffraction, and spectroscopy of materials on length scales ranging from
microns to atoms. By using a high-speed, direct electron detector, it is now
possible to record a full 2D image of the diffracted electron beam at each
probe position, typically a 2D grid of probe positions. These 4D-STEM datasets
are rich in information, including signatures of the local structure,
orientation, deformation, electromagnetic fields and other sample-dependent
properties. However, extracting this information requires complex analysis
pipelines, from data wrangling to calibration to analysis to visualization, all
while maintaining robustness against imaging distortions and artifacts. In this
paper, we present py4DSTEM, an analysis toolkit for measuring material
properties from 4D-STEM datasets, written in the Python language and released
with an open source license. We describe the algorithmic steps for dataset
calibration and various 4D-STEM property measurements in detail, and present
results from several experimental datasets. We have also implemented a simple
and universal file format appropriate for electron microscopy data in py4DSTEM,
which uses the open source HDF5 standard. We hope this tool will benefit the
research community, helps to move the developing standards for data and
computational methods in electron microscopy, and invite the community to
contribute to this ongoing, fully open-source project
Correlative analysis of structure and chemistry of LixFePO4 platelets using 4D-STEM and X-ray ptychography
Lithium iron phosphate (LixFePO4), a cathode material used in rechargeable
Li-ion batteries, phase separates upon de/lithiation under equilibrium. The
interfacial structure and chemistry within these cathode materials affects
Li-ion transport, and therefore battery performance. Correlative imaging of
LixFePO4 was performed using four-dimensional scanning transmission electron
microscopy (4D-STEM), scanning transmission X-ray microscopy (STXM), and X-ray
ptychography in order to analyze the local structure and chemistry of the same
particle set. Over 50,000 diffraction patterns from 10 particles provided
measurements of both structure and chemistry at a nanoscale spatial resolution
(16.6-49.5 nm) over wide (several micron) fields-of-view with statistical
robustness.LixFePO4 particles at varying stages of delithiation were measured
to examine the evolution of structure and chemistry as a function of
delithiation. In lithiated and delithiated particles, local variations were
observed in the degree of lithiation even while local lattice structures
remained comparatively constant, and calculation of linear coefficients of
chemical expansion suggest pinning of the lattice structures in these
populations. Partially delithiated particles displayed broadly core-shell-like
structures, however, with highly variable behavior both locally and per
individual particle that exhibited distinctive intermediate regions at the
interface between phases, and pockets within the lithiated core that correspond
to FePO4 in structure and chemistry.The results provide insight into the
LixFePO4 system, subtleties in the scope and applicability of Vegards law
(linear lattice parameter-composition behavior) under local versus global
measurements, and demonstrate a powerful new combination of experimental and
analytical modalities for bridging the crucial gap between local and
statistical characterization.Comment: 17 pages, 4 figure
Space Charge at Nanoscale: Probing Injection and Dynamic Phenomena Under Dark/Light Configurations by Using KPFM and C-AFM
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py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets
Scanning transmission electron microscopy (STEM) allows for imaging,
diffraction, and spectroscopy of materials on length scales ranging from
microns to atoms. By using a high-speed, direct electron detector, it is now
possible to record a full 2D image of the diffracted electron beam at each
probe position, typically a 2D grid of probe positions. These 4D-STEM datasets
are rich in information, including signatures of the local structure,
orientation, deformation, electromagnetic fields and other sample-dependent
properties. However, extracting this information requires complex analysis
pipelines, from data wrangling to calibration to analysis to visualization, all
while maintaining robustness against imaging distortions and artifacts. In this
paper, we present py4DSTEM, an analysis toolkit for measuring material
properties from 4D-STEM datasets, written in the Python language and released
with an open source license. We describe the algorithmic steps for dataset
calibration and various 4D-STEM property measurements in detail, and present
results from several experimental datasets. We have also implemented a simple
and universal file format appropriate for electron microscopy data in py4DSTEM,
which uses the open source HDF5 standard. We hope this tool will benefit the
research community, helps to move the developing standards for data and
computational methods in electron microscopy, and invite the community to
contribute to this ongoing, fully open-source project