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666 results for “Diffraction”
Synchrotron X-ray Diffraction Results - Measuring Bulk Crystallographic Texture from Differently-Orientated Ti-6Al-4V Samples
<p>A dataset of crystallographic texture results for both α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phases, measured from six differently orientated Ti-6Al-4V (Ti-64) samples, using two different analysis techniques of synchrotron X-ray diffraction (SXRD) data. The texture results are produced from two refinement methods for fitting intensities from SXRD pattern images; an established Rietveld refinement method using the software package <a href="http://maud.radiographema.eu">MAUD (Materials Analysis Using Diffraction)</a> and a new Fourier-based peak fitting method from the <a href="https://pypi.org/project/continuous-peak-fit/">Continuous-Peak-Fit</a> Python package. The texture results were also compared with electron backscatter diffraction (EBSD) measurements from a single sample orientation. The SXRD and EBSD textures were analysed using <a href="https://mtex-toolbox.github.io">MTEX</a> to enable a direct comparison of the pole figures, orientation distribution functions (ODFs) and numerical values for the texture indices. The SXRD texture is calculated from each of the six different sample orientations, a combination of the six sample orientations, and in a batch processing method for calculating spatially-resolved texture variation from 387 individual X-Y stage-scan SXRD measurements across one of the samples. The texture variation measured using stage-scan SXRD is directly compared with EBSD, by splitting up the EBSD map into an equivalent grid matrix using an automated script in MTEX.</p> <p><strong>Material </strong></p> <p>The Ti-64 material used in this study was pre-rolled to 87.5% reduction at 915ºC and then air-cooled to develop a characteristic texture. The run numbers from the experiment reference six different sample orientations, according to their alignment with the original rolling directions (RD – rolling direction, TD – transverse direction, ND – normal direction), and alignment with the horizontal (X) and vertical (Y) axes of the synchrotron detector.</p> <p><strong>MAUD / MTEX Analysis</strong></p> <p>The α and β phase texture for each of the six different sample orientations was calculated using MAUD, included in this <a href="https://doi.org/10.5281/zenodo.7311323">analysis dataset</a>, which produced ODFs in the form of text files. The texture files were analysed in MTEX using scripts from the <a href="https://github.com/LightForm-group/MAUD-batch-analysis">MAUD-batch-analysis</a> package, for plotting of the pole figures and ODF slices, along with calculation of pole figure maxima, ODF maxima and texture indices. The same procedure was used to analyse texture from all six orientations together; using MTEX to fit a single ODF text file. And a series of ODF text files were analysed to calculate texture variation from an X-Y stage scan of Sample 1 (103845). Two different ODF resolutions of 5º and 15º were initially used to fit the texture in MAUD, with the same ODF resolution applied to analyse the data in MTEX. However, an ODF resolution of 15° was found to reproduce the most reasonable texture strength intensity values, with the closest match to the EBSD results.</p> <p><strong>Continuous-Peak-Fit / MTEX Analysis </strong></p> <p>The lattice plane intensities for 21 α and 4 β phase peaks were extracted from the Continuous-Peak-Fit analysis, included in this <a href="https://doi.org/10.5281/zenodo.7311323">analysis dataset</a>, and saved as text files in the form of pole figures. The lattice intensity text files were analysed in MTEX using scripts from the <a href="https://github.com/LightForm-group/continuous-peak-fit-analysis">continuous-peak-fit-analysis</a> package, to plot pole figures and ODF slices, and to calculate pole figure maxima, ODF maxima and texture indices. The same procedure was used to analyse texture from all six orientations together, along with combinations of different sample orientations, by fitting combined lattice intensity text files in MTEX. And a series of lattice intensity text files were analysed to calculate texture variation from the X-Y stage scan of Sample 1 (103845). Lattice plane intensity distributions which had been normalised to a Ti-64 powder sample measurement were also analysed, to see if this had any effect on the texture intensities. Nevertheless, the powder-corrected texture was found to exactly match the raw intensity measurements. Three different ODF resolutions of 5º, 10º and 15º were initially used to fit the texture in MTEX. However, a kernel half-width of 10° was found to produce optimal data fitting, for highly accurate texture strength intensity values.</p> <p><strong>EBSD / MTEX Analysis </strong></p> <p>The indexed α-phase EBSD measurements were recorded over an area of around 100 mm<sup>2</sup>, with an equivalent sized map of β-phase orientations reconstructed from the data. Both the α and the β phase maps were analysed using the <a href="https://github.com/LightForm-group/MTEX-texture-block-analysis">MTEX-texture-block-analysis</a> package, which was used to split up the map into 387 individual square sections, with equivalent dimensions to the SXRD stage-scan measurement grid. For each of the 387 sections, MTEX was used to plot pole figures and ODF slices, and to calculate pole figure maxima, ODF maxima and texture indices.</p> <p><strong>Texture Variation Comparison</strong></p> <p>The texture values calculated from the SXRD stage scan measurements, with the two analysis methods, were used for a direct comparison with the texture variation recorded using EBSD. This analysis was recorded in the <a href="https://github.com/LightForm-group/texture-strength-comparison">texture-strength-comparison</a> package. The results show differences in texture variation across the piece depending on the method used to analyse the SXRD data. The Continuous-Peak-Fit analysis method shows the closest match with EBSD, producing clear texture intensity spikes for the different α and β lattice plane pole figure intensities, ODF maxima and texture indices, at the centre of the piece. The results were also used to develop SXRD maps showing the distribution of texture intensities across the sample.</p> <p><strong>Metadata </strong></p> <p>An accompanying YAML text file contains associated processing metadata for the SXRD and EBSD analyses, recording information about the different packages used to process the data, along with details about the different files contained within this results dataset.</p>
Single crystal X-ray diffraction data for Rhizobium radiobacter N-carbamoyl-beta-alanine amidohydrolase
<p>Single crystal X-ray diffraction data for Rhizobium radiobacter N-carbamoyl-beta-alanine amidohydrolase collected from crystals produced as below:</p> <p>Purified recombinant RrCβAA was concentrated to 15 mg/mL using a 10 kDa MWCO centrifugal concentrator (Vivaspin) and subjected to sitting drop vapor diffusion crystallization screening with commercial screens from Molecular Dimensions and Hampton Research. Drops of 100 nL protein plus 100 nL well solution were set up against wells containing 70 L of crystallisation solutions. After two weeks crystals were found in xxx condition. An optimisation screen based on this condition was set up in 24 well plates by varying the PEG1500 concentration and MMT buffer pH. Drops of 1 μL protein and 1 μL well solution were set up on plastic cover slips over wells containing 1 ml crystallisation solution. Crystals grew in a well solution containing 23 % (w/v) PEG1500 and 100 mM MMT pH 6.0. Crystals were harvested with a LithoLoop (Molecular Dimensions Limited) and transferred to a cryoprotection solution of well solution supplemented with 50 % PEG400. Cryoprotected crystals were flash cooled in liquid nitrogen. </p>
IODP Expedition 376 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Diffraction data for complex of vancomycin with N-acetyl-D-Ala-D-Ser
<p>Raw diffraction images collected for a single crystal of the glycopeptide antibiotic vancomycin bound to N-acetyl-D-Ala-D-Ser (HDF5 format). Measured at beam line 17-ID-1 (AMX), NSLS-II, in December 2021, using an Eiger 9M detector. Other relevant metadata can be found in the file XDS.INP.</p>
IODP Expedition 385 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
IODP Expedition 396 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Predicting Pulsed Laser Deposition SrTiO3 Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction - sample treated_213nm
<p>RHEED intensity image dataset of sample "<strong>treated_213nm"</strong> in work "Predicting Pulsed Laser Deposition SrTiO<sub>3 </sub>Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction."</p>
Simulation of convergent-beam low-energy electron diffraction on Si(001) reconstructions
<p>Research results based upon this code and data are published at <a href="http://doi.org/10.1016/j.apsusc.2019.05.274">http://doi.org/10.1016/j.apsusc.2019.05.274</a>.</p> <p>The image simulation of convergent beam low energy electron diffraction (CBLEED) patterns are used to determine the sensitivity of CBLEED to atomic-scale displacements of several reconstructed variants of the Si(001) surface. The CAVATN code is used to determine the dynamical LEED intensities as a function of the incident electron energy (E<sub>i</sub>), angle (theta, phi) and at each of the miller indices (h,k), up to the third order. The CBLEED code then maps these intensities into reciprocal space, allowing the visualisation of CBLEED patterns to be made as a function of incident electron energy (E<sub>i</sub>). The data files for the CBLEED simulations are stored in a .txt format, with an accompanying .png image displaying the result of the simulation. This data is then analysed to determine the sensitivity of CBLEED patterns to small atomic displacements.</p> <p><strong>CAVATN code:</strong> Relevant documentation, electron beam files and the crystal structure files are all included. The CAVATN dynamical LEED package, developed from the CAVLEED code, is also included, where the code employs the muffin-tin potential approximation and involves a set of phase shifts for each atom type (which are treated as spherically symmetric scatterers in a crystal) that can be evaluated using phase shift calculation packages or tables. In the simulations performed here, complex phase shifts were used to simulate temperature dependent scattering effects at T = 293<em>K</em>. The inner potential is treated as energy independent and is split into real U<sub>or</sub> = 5 <em>eV </em>and imaginary U<sub>oi</sub> = 10 <em>eV </em>parts to respectively treat refraction (via the vacuum and muffin-tin zero difference) and absorption (due to in- elastic processes). Multiple scattering between atoms within a layer is calculated using the chain method and the multiple scattering between layers is included by the renormalized forward scattering perturbation method to evaluate the wave amplitudes of diffracted beams at the surface, and hence the intensities of the LEED pattern.</p> <p><strong>CBLEED code:</strong> The dynamical CBLEED package is included as ‘cbleed_analysis_script.py’, where the CBLEED patterns are simulated by uniformly partitioning the convergent cone into square areas as shown in Figure 1. An incident electron beam is located at the centre of these squares and defined directionally by and . Each of the incident electron beams of the sampled convergent cone was then used as input to the dynamical LEED program CAVATN, so that the corresponding multiply scattered intensities could be determined and mapped into reciprocal space. All the output data files from the CBLEED code is available for the following structures in the ‘output’ folder; Si(001)-1x1-ideal, Si(001)-2x1-symmetric, Si(001)-2x1-buckled, Si(001)-2x1-dH (for dimer height displacements) and Si(001)-2x1-dL (for dimer length displacements). The data for the sensitivity to atomic-scale displacements is included in the ‘sensitivity_output’ folder, which determines both the partial and whole pattern sensitivities.</p>
IODP Expedition 354 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Electron Diffraction (MicroED) Datasets for Aspirin (Glacios TEM with a CETA-D)
<p>Electron diffraction datasets collected from aspirin.</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: C<sub>9</sub>H<sub>8</sub>O<sub>4</sub>, 2-acetoxybenzoic acid, 180.16 g/mol</p> <p>Structure: CCDC 2260060</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>
Electron Diffraction (MicroED) Datasets for C20H13O4P (Glacios TEM with a CETA-D)
<p>Electron diffraction datasets collected from a chiral pharmaceutical compound.</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: C<sub>20</sub>H<sub>13</sub>O<sub>4</sub>P, (R)-(-)-1,1-Binaphthyl-2,2’-diyl hydrogenphosphate, 348.29 g/mol</p> <p>Structure: CCDC 2260063</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>
Electron Diffraction (MicroED) Datasets for Ipragliflozin (Glacios TEM with a CETA-D)
<p>Electron diffraction datasets collected from a chiral pharmaceutical compound.</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: C<sub>21</sub>H<sub>21</sub>FO<sub>5</sub>S, (1<em>S</em>)-1,5-anhydro-1-<em>C</em>-{3-[(1-benzothiophen-2-yl)methyl]-4-fluorophenyl}-D-glucitol, 404.45 g/mol</p> <p>Structure: CCDC 2260059</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>
IODP Expedition 362 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p> <p>Updated 26 June 2020 to include additional raw data files in supplementary materials. </p>
Datasets for Work "Predicting Pulsed-Laser Deposition SrTiO3 Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction"
<p>RHEED raw dataset and Gaussia fitting parameter dataset for samples "treated_213nm", "treated_81nm" and "untreated_162nm" in the work "Predicting Pulsed Laser Deposition SrTiO<sub>3 </sub>Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction."</p>
IODP Expedition 369 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
ptychographic_diffraction_image_sets_20211026
<p>121 spiral scans with 963 images each</p> <p>using a medipix3 detector with 55 um pixelsize and at 1.55 m downstream of the samples</p> <p>step size is 50 nm per scan with 0.4 s exposure time</p> <p>beam position is included in positions.csv</p> <p> </p>
Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images - dataset
<p>This dataset includes 4 files with segmentation results for 4 different ODT reconstructions of SH-SY5Y neuroblastoma cell. The segmentation results contain:</p> <ol> <li>3D binary masks of biological cells obtained through Cellpose [1] and <a href="https://github.com/biopto/ODT-SAS.git">ODT-SAS</a>;</li> <li>3D binary masks of organelles: nucleoli and lipid structures (LS) obtained through slice-by-slice manual segmentation and ODT-SAS.</li> </ol> <p>All files are .*mat files.</p> <p>The files <em>REC_SH-SY5Y_1.mat, REC_SH-SY5Y_2.mat</em> and<em> REC_SH-SY5Y_3.mat</em> consist of 7 variables:</p> <p>RECON – tomographic reconstruction of SH-SY5Y neuroblastoma cell;<br> n_imm – refractive index of object immersion medium;<br> dx – object space sample size in XY [<span class="math-tex">\(\mu m\)</span>];<br> rayXY – xy-coordinates of illumination vectors;</p> <p>maskManual – table with manually determined 3D binary masks of organelles;<br> maskCellpose – 3D binary mask of biological cell obtained through Cellpose;<br> maskODTSAS – table with 3D binary masks of biological cell and their organelles obtained through ODT-SAS.</p> <p>File <em>REC_SH-SY5Y_4.mat</em> includes masks for the ODT-SAS and Cellpose segmentation of three closely packed cells and consists of 5 variables: RECON, n_imm, dx, maskCellpose and maskODTSAS.<br> <br> Access a particular 3D binary mask from 'maskManual' and 'maskODTSAS' tables, using the following names: 'Cell', 'Nucleoli', 'LS'.<br> For example:</p> <pre><code>cellMask = maskODTSAS.Cell{1};</code></pre> <p><br> [1] Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. Nature methods, 18(1), 100-106.</p> <p> </p>
IODP Expedition 382 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Microdialysis on-chip crystallization of HEWL and Thaumatin and in situ X-ray diffraction studies
<p>This deposition includes the mtz and pdb files for HEWL and Thaumatin crystal structures included in the article "Microdialysis on-chip crystallization of soluble and membrane proteins with the MicroCrys platform and in situ X-ray diffraction case studies". </p>
IODP Expedition 392 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
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OpenNeuro
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