This dataset allows to investigate phase contrast methods for 4D scanning transmission electron microscopy, such as ptychography. A synthetic dataset has been simulated, based on an SrTiO3 unit cell as a starting point. Then, a five by five super cell was created by repetition. Two artificial spatial frequencies were added to the phase grating, one with a wavelength of a single unit cell and one with a wavelength of the super cell. To eliminate dynamical scattering, a 4D-STEM simulation with 20 × 20 scan points per unit cell was performed using only one slice with a thickness of one unit cell along electron beam direction [001]. Files conf_01.mat: HDF5 file with the phase grating. Data extraction and plot of the phase grating.ipynb: J...
Recent advances in high-speed pixelated electron detectors have substantially facilitated the implem...
The arrival of direct electron detectors (DEDs) with high frame rates in the field of scanning trans...
In this study we explore the possibility to use deep learning for the reconstruction of phase images...
This dataset allows to investigate phase contrast methods for 4D scanning transmission electron micr...
This dataset can be used to test various analysis methods for high-resolution 4D STEM, including pha...
We report the application of focused probe ptychography using binary 4D datasets obtained using scan...
Ptychography has been shown to be an efficient phase contrast imaging technique for scanning transmi...
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a technique where a full two...
The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transm...
4D-STEM data frequently requires a number of calibrations in order to make accurate measurement: for...
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a technique where a full two...
Overview This repository contains 2 example 4D-STEM datasets format from the paper "Phase Object R...
4D-STEM, in which the 2D diffraction plane is captured for each 2D scan position in the scanning tra...
In Part I of this series of two papers, we demonstrated the formation of a high efficiency phase-con...
151 pagesThe development of fast pixelated direct electron detectors allows the collection of full s...
Recent advances in high-speed pixelated electron detectors have substantially facilitated the implem...
The arrival of direct electron detectors (DEDs) with high frame rates in the field of scanning trans...
In this study we explore the possibility to use deep learning for the reconstruction of phase images...
This dataset allows to investigate phase contrast methods for 4D scanning transmission electron micr...
This dataset can be used to test various analysis methods for high-resolution 4D STEM, including pha...
We report the application of focused probe ptychography using binary 4D datasets obtained using scan...
Ptychography has been shown to be an efficient phase contrast imaging technique for scanning transmi...
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a technique where a full two...
The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transm...
4D-STEM data frequently requires a number of calibrations in order to make accurate measurement: for...
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a technique where a full two...
Overview This repository contains 2 example 4D-STEM datasets format from the paper "Phase Object R...
4D-STEM, in which the 2D diffraction plane is captured for each 2D scan position in the scanning tra...
In Part I of this series of two papers, we demonstrated the formation of a high efficiency phase-con...
151 pagesThe development of fast pixelated direct electron detectors allows the collection of full s...
Recent advances in high-speed pixelated electron detectors have substantially facilitated the implem...
The arrival of direct electron detectors (DEDs) with high frame rates in the field of scanning trans...
In this study we explore the possibility to use deep learning for the reconstruction of phase images...