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109 results for “Electron Diffraction”
Raw ultrafast electron diffraction data of photoexcited nitrobenzene
<p>Raw gas phase ultrafast electron diffraction dataset of the molecule nitrobenzene after photoexcitation at 266 nm.</p> <p>The file "20180629_1619.zip" contains a folder structure with images of the detector background.</p> <p>The file"20180929_1630.zip" contains a folder structure with images of the diffraction patterns.</p> <p>The folder structure is as follows: Each scan of the pump-probe delay steps is in a separate folder "scanxxx" with xxx being the scan number. Each of these scan folders contains two subfolders, "I0" and "images-ANDOR1". The diffraction patterns of each delay step are contained in the latter folder. The filename has the following structure: ANDOR2_delay-x-y_z_a_0001.tif with x being the order of the delay step in which it was obtained, y being the delay stage position in mm, z being the date, and a being the time of data acquisition.</p> <p> </p>
Electron Diffraction (MicroED) Datasets for C16H21FN5OS - D-malate (Glacios TEM with a CETA-D)
<p>Electron diffraction datasets collected from a chiral pharmaceutical compound cocrystallized with D-malic acid.</p> <p> </p> <p>Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services)</p> <p>Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode)</p> <p>Collection Software: Leginon (Cheng, et. al. 2021)*</p> <p>Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, nano probe mode, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded)</p> <p>Grid: Ted Pella 01840</p> <p>Sample: C<sub>16</sub>H<sub>21</sub>FN<sub>5</sub>OS • D-malate, (N‐(5‐{[(3R)‐3‐[(5‐fluoropyrimidin‐2‐yl)methyl]piperidin‐1‐yl]methyl}‐1,3‐thiazol‐2‐yl)acetamide • D-malate, 483.51 g/mol</p> <p>Structure: CCDC 2132512</p> <p> </p> <p>* Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value.</p> <p> </p> <p>A data processing tutorial is available for processing data collected with this setup using DIALS: </p> <p><a href="https://dials.github.io/documentation/tutorials/3DED/Biotin.html">https://dials.github.io/documentation/tutorials/3DED/Biotin.html</a></p>
Indomethacin Polymorph δ Revealed to be Two Plastically Bendable Crystal Forms by 3D Electron Diffraction: Correcting a 47-Year-Old Misunderstanding
<p>Raw electron diffraction data of indomethacin polymorphs <span class="math-tex">\(δ\)</span> and <span class="math-tex">\(θ\)</span> obtained via solution and melt crystallization, respectively. Single crystals were grown using microdroplet melt crystallization and crushed to give microcrystals suitable for electron diffraction. Data were collected using a JEOL JEM-2100 LaB6 TEM operated at 200 kV and equipped with a Timepix hybrid pixel detector.</p> <p> </p>
Electron Diffraction (MicroED) Datasets for Ipragliflozin L-Proline (Glacios TEM with a CETA-D)
<p>Electron diffraction datasets collected from ipragliflozin L-proline, a chiral pharmaceutical cocrystal.</p> <p> </p> <p>Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services)</p> <p>Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode)</p> <p>Collection Software: Leginon (Cheng, et. al. 2021)*</p> <p>Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded)</p> <p>Grid: Ted Pella 01840</p> <p>Sample: Ipragliflozin (C<sub>21</sub>H<sub>21</sub>FO<sub>5</sub>S, (2S,3R,4R,5S,6R)-2-{3-[(1-benzothiophen-2-yl)methyl]-4-fluorophenyl}-6-(hydroxymethyl)oxane-3,4,5-triol) and L-proline (C<sub>5</sub>H<sub>9</sub>NO<sub>2, </sub>(2S)-pyrrolidine-2-carboxylic acid)</p> <p>Structure: CCDC 2174023</p> <p> </p> <p>* Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value.</p> <p> </p> <p>A data processing tutorial is available for processing data collected with this setup using DIALS: </p> <p><a href="https://dials.github.io/documentation/tutorials/3DED/Biotin.html">https://dials.github.io/documentation/tutorials/3DED/Biotin.html</a></p> <p> </p> <p>Funding: NIH/NIGMS grant number 1R44GM140666</p>
Data from: Electron backscatter diffraction (EBSD) analysis of maniraptoran eggshells with important implications for microstructural and taphonomic interpretations
Open the record for dataset details and reuse information.
Scanning electron diffraction - Cellulose
<p>Raw scanning electron diffraction data (SED) acquired from cellulose nanofibers (CNF) and nanocrystal (CNC). The CNFs are of Tunicate origin and the CNC is extracted from bacteria.</p> <p>The data can be read and processed using e.g. the open-source Python library pyXem 0.10.0 available from:<br> https://zenodo.org/record/3667613#.XzKk--exWUl</p>
Data from: Microcrystal Electron Diffraction (MicroED) Structure Determination of a Mechanochemically Synthesized Co-crystal not Affordable from Solution Crystallization
<p>Solid-state grinding can provide “mechano-distinctive” cocrystals that are not accessible from solutions. Herein, we demonstrate the structure determination of a powdered mechano-distinctive cocrystal of 2-aminopyrimidine and succinic acid in a 2:1 molar ratio using microcrystal electron diffraction.</p>
Data from Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction
<p><strong>Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in low signal-to-noise and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O<sub>3</sub>. Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.</strong></p>
The nanoscale ordering of cellulose in a hierarchically structured hybrid material revealed using scanning electron diffraction
<p>Scanning Electron Diffraction data and Python Notebooks used for data analysis of cellulose nanofiber orientation in the cell walls of composite material, transparent wood. The notebooks can be used to create Figures 1c, 3a and 5d in publication "The nanoscale ordering of cellulose in a hierarchically structured hybrid material revealed using scanning electron diffraction".</p> <p> </p>
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