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24 results for “Neutron scattering”
Small Angle Neutron Scattering (SANS) virtual experiments at KWS-1
<p>Small Angle Neutron Scattering (SANS) virtual experiments at KWS-1, FRM-II dataset. Intended for Machine learning purposes. Data generated by performing simulations in <a href="https://www.mcstas.org/">McStas</a> with the <a href="https://www.sasview.org/docs/user/qtgui/Perspectives/Fitting/models/index.html">SasView small angle scattering form factor models</a> describing the sample interaction. Two parameter spaces are varied sistematically: form factor model parameters and instrument configuration parameters. For more detailed information, read the <code>README.md</code> file of this database.</p> <p>The database contains 46 SANS form factor models under different instrument configurations. All data is uploaded in <code>hdf5</code> files, and the corresponding metadata in <code>.csv</code> files. Description of what each instrument configuration means (sample-detector distance, collimation, incident wavelength) and which model is used is contained in the metadata file. </p> <p>Each array is the result of the position sensitive detector output in neutron intensity (float values). A Dataset loader for Pytorch may be found <a href="https://github.com/jorobledo/hdf_loader_pytorch" target="_blank" rel="noopener">in GitHub</a> and is intended for Machine Learning purposes.</p>
Supporting data for "Quantifying the Strength of a Salt Bridge by Neutron Scattering and Molecular Dynamics"
<p>Supporting data for the following published paper: Mason, Jungwirth, Duboué-Dijon, 2019, JPhysChemLett, 10, 3254-3259</p> <p>Contains both data from neutron scattering measurements and input simulation files necessary for reproduction of the work.</p>
Dataset from the paper entitled "Complex structure of molten FLiBe (2 LiF – BeF2) examined by experimental neutron scattering, X-ray scattering, and deep neural network-based molecular dynamics"
<p>Dataset from the paper entitled "Complex structure of molten FLiBe (2 LiF – BeF2) examined by experimental neutron scattering, X-ray scattering, and deep neural network-based molecular dynamics". These data include experimental total scattering measurements and molecular dynamics simulations on the molten structure of FLiBe. </p>
Dataset of the publication: Probing Short-Range Correlations in the van der Waals Magnet CrSBr by Small-Angle Neutron Scattering
<p>Dataset of the publication: Probing Short-Range Correlations in the van der Waals Magnet CrSBr by Small-Angle Neutron Scattering</p> <p>DOI: 10.1002/smsc.202400244</p> <p>A. Rybakov, C. Boix-Constant, D. Alba Venero, H. S. J. van der Zant, S. Mañas-Valero, E. Coronado</p> <p>Small Science, 4, 8, 2400244 (2024)</p>
INSPIRED: Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design
<p>INSPIRED is a graphic user interface (GUI) that performs rapid prediction and calculation of phonons and inelastic neutron scattering (INS) spectra. It consists of three modules. The "Predictor" module uses a symmetry-aware neural network (coupled with an autoencoder) [1-3] to perform direct prediction of total/partial phonon density of states and powder 1D/2D INS spectra from a given structure. The "DFT database" module uses pre-calculated force constants from density functional theory (DFT) [4] to perform INS simulations for single crystals and powders (for the crystals available in the database). The "MLFF" module uses pre-trained universal force fields [8-12] to perform structural optimization, phonon calculation, and INS simulations for single crystals and powders for any given crystal. The predicted/calculated results are saved in CSV files and can be visualized with the GUI. INSPIRED is developed to be a convenient tool for INS experimental planning, steering, and quick data analysis.</p> <p>This repository contains two files as an update to the previous version:</p> <p>1. A tarball file (dftdb.tar.gz) containing the DFT database (currently with 12734 crystals)</p> <p>2. A VirtualBox appliance file (inspired_vm.ova) to run INSPIRED as a virtual machine.</p> <p>The ML model file (model.tar.gz) remains the same and can be obtained from the previous version.</p> <p>Instructions on how to use these files, as well as the rest part of the software, can be found on the <a href="https://github.com/cyqjh/inspired">GitHub page</a>. </p>
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
<p>Files uploaded here are related to the paper titled "Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data". Here we investigate how generative adversarial networks can be used to match simulated- and experimental INS data.</p>
Research data for "Revisiting neutron scattering data from deuterated milk" (Food Hydrocolloids, doi:10.1016/j.foodhyd.2020.106511)
<p>USANS and SESANS data used for the analysis in this paper. Data are either two- or three-column data (as specified below). Data were extracted from the figures in the papers using the macOS application GraphClick.</p> <p>USANS and SANS data were originally published in "Protein aggregate structure under high pressure" by Andrew J. Jackson and Duncan J. McGillivray (<em>Chem. Commun.</em>, 2011, <strong>47</strong>, 487-489, doi:10.1039/C0CC02314K). USANS data are three-column *.txt files [Q in Å<sup>–1</sup>, I(Q) in cm<sup>–1</sup>, uncertainty in I(Q) in cm<sup>–1</sup>]. SANS data (numbered 1, 2, and 3 to denote different instrument configurations) are two-column *.txt files [Q in Å<sup>–1</sup>, I(Q) in cm<sup>–1</sup>].</p> <p>SESANS data were originally published in "Milk Gelation Studied with Small Angle Neutron Scattering Techniques and Monte Carlo Simulations" by Léon F. van Heijkamp, Ignatz M. de Schepper, Markus Strobl, R. Hans Tromp, Jouke R. Heringa, and Wim G. Bouwman (<em>J. Phys. Chem. A</em>, 2010, <strong>114</strong>, 2412–2426, doi:10.1021/jp9067735). SESANS data are three-column *.csv files [Z in Å, normalized SESANS signal in cm<sup>–1</sup> Å<sup>–2</sup>, uncertainty in normalized SESANS signal in cm<sup>–1</sup> Å<sup>–2</sup>].</p>
Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering
<p>The repository contains the data presented in the figures in the manuscript entitled <br> "Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering".</p> <p>Requests for further information can be directed to the corresponding authors Victor Ukleev (victor.ukleev 'at' psi.ch).</p>
simlation of Li diffusion via neutron scattering
<p>don't even open</p>
A database of synthetic inelastic neutron scattering spectra from molecules and crystals
<p>This database contains simulated inelastic neutron scattering (INS) spectra for 10,000+ inorganic crystals and 20,000+ organic molecules. The INS database for inorganic crystals is based on the phonon database at Kyoto University by Atsushi Togo (http://phonondb.mtl.kyoto-u.ac.jp/). The INS database for organic molecules is based on the QM8 dataset (http://quantum-machine.org/datasets/).</p> <p>Entry lists can be found in crystals.dat and molecules.dat. After unzipping the tar.gz files, data for each structure model can be found in a subfolder. </p> <p>For the inorganic crystal database, each subfolder contains five files: a structure.cif file for the crystal structure, a vis_inc_0K.csv file containing the simulated VISION/TOSCA spectra, a powder_2Dmesh_coh_0K.csv file containing the simulated powder S(Q,E), a vis_nwdos.csv file containing the neutron weighted PDOS, a vis_dos.csv file containing the true PDOS, and a gamma_modes.xyz file containing the displacements of gamma point phonons for visualization (with Jmol, http://jmol.sourceforge.net/).</p> <p>For the QM8 molecular database, there are five files in each subfolder: an INFO-* file containing the SMILES string as well as the IUPAC name (if available) for this molecule, a *.com file containing the input for Gaussian simulation (which also contains the atomic coordinates), a *vis_inc_0K.csv file containing the simulated INS spectra, a *.xyz file containing the atomic displacement of each vibrational modes (can be visualized with Jmol), and a *modes.csv file containing the calculated INS intensity for each normal mode. </p> <p>A python script (plot_ins.py) to plot the INS data files is provided<br> Usage: plot_ins.py *.csv {-s [1,2] -x [0:100] -y [0:100] -z [0:2.5]}<br> -s : spectrum index, -x/y/z : range to plot </p> <p><br> The manual for the OCLIMAX software used for INS simulations is also provided for reference.</p>
Data from: Particle dynamics of nanoplastics suspended in water with soil microparticles: Insights from small angle neutron scattering (SANS) and ultra-SANS
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Data from: Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)
Terrestrial nanoplastics (NPs) pose a serious threat to agricultural food production systems due to the potential harm of soil-born micro- and macroorganisms that promote soil fertility and ability of NPs to adsorb onto and penetrate into vegetables and other crops. Very little is known about the dispersion, fate and transport of NPs in soils. This is because of the challenges of analyzing terrestrial NPs by conventional microscopic techniques due to the low concentrations of NPs and absence of optical transparency in these systems. Herein, we investigate the potential utility of small-angle neutron scattering (SANS) and Ultra SANS (USANS) to probe the agglomeration behavior of NPs prepared from polybutyrate adipate terephthalate, a prominent biodegradable plastic used in agricultural mulching, in the presence of vermiculite, an artificial soil. SANS with the contrast matching technique was used to study the aggregation of NPs co-dispersed with vermiculite in aqueous media. We determined the contrast match point for vermiculite was 66% D 2 O / 33% H 2 O. At this condition, the signal for vermiculite was ~50-100%-fold lower that obtained using neat H 2 O or D 2 O as solvent. According to SANS and USANS, smaller-sized NPs (50 nm) remained dispersed in water and did not undergo size reduction or self-agglomeration, nor form agglomerates with vermiculite. Larger-sized NPs (300-1000 nm) formed self-agglomerates and agglomerates with vermiculite, demonstrating their significant adhesion with soil. However, employment of convective transport (simulated by ex situ stirring of the slurries prior to SANS and USANS analyses) reduced the self-agglomeration, demonstrating weak NP-NP interactions. Convective transport also led to size reduction of the larger-sized NPs. Therefore, this study demonstrates the potential utility of SANS and USANS with contrast matching technique for investigating behavior of terrestrial NPs in complex soil systems.
Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition"
<p>Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition".</p> <p>neutron_data.zip --> neutron data in .nxspe form. S(Q,E) calculated using the DAVE software. Includes logbook spreadsheet. </p> <p>Training_Data.xyz --> xyz file containing training data used to generate Allegro machine learning forcefield in the paper</p> <p>nh3_pimd.deploy --> Trained Allegro model to that can be used in LAMMPS and RXMD software a ML forcefield </p> <p>POSCAR_UNIT_CELL_AMMONIA --> NH3 unit cell in solid phase in POSCAR format that can be read by the VASP software used to perform the DFT simmulations.</p>
Dataset: Uncovering Obscured Phonon Dynamics from Powder Inelastic Neutron Scattering using Machine Learning
<p>Dataset of simulated and experimental spectra for the manuscript: Uncovering Obscured Phonon Dynamics from Powder Inelastic Neutron Scattering using Machine Learning. </p> <p>The data.zip contains all the simulated spectra and labels.</p> <p>The dataset.zip contains the divided subsets for training, validation and testing purposes, as well as the experimental dataset.</p>
DFT data from article "Oxide Ion Mobility in V- and P-doped Bi2O3-Based Solid Electrolytes: Combining Quasielastic Neutron Scattering with Ab Initio Molecular Dynamics"
<p>DFT data from article: "Oxide Ion Mobility in V- and P-doped Bi2O3-Based Solid Electrolytes: Combining Quasielastic Neutron Scattering with Ab Initio Molecular Dynamics" (<span><a href="https://pubs.acs.org/doi/full/10.1021/acs.chemmater.2c03103">https://pubs.acs.org/doi/full/10.1021/acs.chemmater.2c03103</a>). Published by 'creators' listed above. </span></p>
Circular dichroism spectroscopic and small-angle neutron scattering analysis of alpha-synuclein and bacteriorhodopsin in bicontinuous microemulsions
<p>The membrane proteins (MPs) alpha-synuclein (ASYN) and bacteriorhodopsin (BR) were readily incorporated into bicontinuous microemulsions (BMEs) formed by two microemulsion systems: water/heptane/Aerosol-OT (AOT)/CK-2,13 and water/dodecane/sodium dodecyl sulfate (SDS)/1-pentanol. (CK-2,13 is an alkyl ethoxylate possessing two alkyl tail groups of carbon chain length 2 and 13 and an average degree of ethoxylation of 5.6.) MPs were encapsulated in BMEs through preparation of Winsor-III systems at optimal salinity, with the anionic surfactants AOT and SDS providing the driving force for extraction. Dissolution of ASYN in BMEs greatly increased the former's alpha-helicity, similar to ASYN's behavior in the presence of biomembranes, while BME- and vesicle-encapsulated BR possessed similar secondary structure. Small-angle neutron scattering (SANS) results clearly demonstrated the direct interaction of MPs with the surfactants, resulting in a decrease of surface area per volume for surfactant monolayers due to decreased<span> surfactant efficiency. The SANS signal for ASYN was isolated through the use of neutron contrast matching for the surfactants through partial deuteration of water and oil</span><span><span>, one of the first reports</span></span><span> of contrast matching </span><span><span>for</span></span><span> BMEs in the literature. The SANS results of the contrast matched sample reflected similar aggregation for ASYN in BMEs as was reported previously for vesicles and SDS solution. </span><span><span>This study</span></span><span> demonstrate</span><span><span>s</span></span><span> the potential use of BMEs as MP host systems for conducting biochemical reactions such as the conversion of sunlight into adenosine triphosphate (ATP) by BR and studyi</span>ng fundamental behavior of MPs, such as the role of ASYN dysfunction in Parkinson's disease, as well as for isolation and purification of MPs via Winsor-III -based extraction.</p>
Circular dichroism spectroscopic and small-angle neutron scattering analysis of alpha-synuclein and bacteriorhodopsin in bicontinuous microemulsions
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Data from: Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)
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Research data supporting "Effect of Formulation Method, Lipid Composition and PEGylation on Vesicle Lamellarity: A Small-Angle Neutron Scattering Study"
<p>Research data supporting the paper:</p> <p>Nele V. et al., Langmuir (2019), DOI: 10.1021/acs.langmuir.8b04256</p>
Supporting Data for "Spin-echo small-angle neutron scattering (SESANS) studies of diblock copolymer nanoparticles" (Soft Matter, doi:10.1039/c8sm01425f)
<p>SAXS [Q / Å^{-1}, I(Q) / Arb. unit, error I(Q) / Arb. unit] data as *.dat files</p> <p>SESANS [Columns labeled] data as *.ses files</p>
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OpenNeuro
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