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10 results for “surface reactivity”
Global Surface Reactive Nitrogen Concentration (NO2 and NH3)
<p>This datesets include global surface reactive nitrogen concentration (NO2 and NH3) using the OMI NO2 (2005-2016) and IASI NH3 (2008-2016). </p>
Research data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach"
<div><strong>Research Data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em></strong></div> <div> </div> <div>Dear reader,</div> <div> </div> <div>reasearch data are provided for the research article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em> (https://doi.org/10.1016/j.advwatres.2024.104763). The authors hope that the research data allows for a better understanding of the modeling workflow. The research data covers the following files:</div> <div> <ul> <li>Python scripts to create the models <ul> <li>Model scripts using FloPy (Bakker et al., 2016) are stored as .py files in './model_data/flopy_scripts/', named 'model_variant_vXYZ.py', where 'XYZ' is a wildcard for the model number. </li> <li>--> Note that model numbers correspond to the different model variants as referred to in the article, see overview below.</li> <li>The model scripts require postfix files, stored in './model_data/flopy_scripts/postfix/', a PHREEQC database file, stored in './model_data/flopy_scripts/template_database/', as well as spreadsheets that contain the initial concentrations as well as reaction rate parameters needed by PHT3D, stored as .xlsx files in './model_data/flopy_scripts/', to create the models.</li> <li>Note that the .xlsx files are used by PHT3D-FSP in the model scripts to generate relevant PHT3D input files (compare https://doi.org/10.5281/zenodo.7559750 for more details).</li> </ul> </li> <li>SEAWAT/PHT3D input files <ul> <li>Original SEAWAT and PHT3D input files, which were created with the corresponding model scripts previously (see step before).</li> <li>Input files are stored in './model_data/model_files/vXYZ/model_files/' for each model variant, where 'XYZ' is a wildcard for the model number.</li> <li>SEAWAT/PHT3D executables can directly run the model files files. Thus, the files don't need to be re-created via the previous step.</li> </ul> </li> <li>Model outputs <ul> <li>Model output data is stored as NumPy arrays in './model_data/model_files/vXYZ/npy_arrays/', where 'XYZ' is a wildcard for the model number.</li> <li>The script './model_data/flopy_scripts/template_output/pht3d_output_hpc_v006.py' was used to generate the output files.</li> <li>2-D species concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/species/', where 'XYZ' is a wildcard for the model number.</li> <li>Species min./max. concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/min_max/', where 'XYZ' is a wildcard for the model number.</li> <li>2-D water budget arrays (CH & WEL boundaries) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/budgets/', where 'XYZ' is a wildcard for the model number.</li> <li>Model discretization information (ncol, nrow, nlay etc.) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/discretization/', where 'XYZ' is a wildcard for the model number.</li> </ul> </li> <li>Figure files <ul> <li>Original figure files as well as the corresponding Python scripts to create the figures are stored in the subfolder'./figures'.</li> </ul> </li> </ul> <p>Numbering of the model variants is as follows:<br><br>v401 --> VAR-conservative<br>v402 --> VAR-OM<br>v403 --> VAR-C/I<br>v404 --> VAR-C/I/S<br>v405 --> VAR-C/I/P<br>v406 --> VAR-C/I/P/H<br>v407 --> VAR-C/I/P/V<br>v408 --> VAR-C/I/P-Co<br>v409 --> VAR-all<br>v410 --> VAR-all (no C)</p> </div> <div> </div> <div>Literature:</div> <div> </div> <div>Bakker, M., Post, V., Langevin, C.D., Hughes, J.D., White, J.T., Starn, J.J. and Fienen, M.N., 2016. Scripting MODFLOW model development using Python and FloPy. Groundwater, 54(5), pp.733-739. https://doi.org/10.1111/gwat.12413</div> <div> </div> <div>Seibert, S.L., Massmann, G., Meyer, R., Post, V.E.A., Greskowiak, J., 2024. Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2024.104763</div> <div> </div> <div><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Vincent E.A. Post (vincent@edinsi.nl), Rena Meyer (rena.meyer@uol.de) or Gudrun Massmann (gudrun.massmann@uol.de)</div>
WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions
<p>This repository houses electronic structure data and metadata generated as part of a computational chemistry case study, enabling full analysis of the paper "WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions" by Rohan Yuri Sanspeur, Javier Heras-Domingo, John R. Kitchin and Zachary Ulissi.</p>
Self-propagation of reactive Al/Ni multilayers with textured surface topography
<p>Reactive multilayer systems (RMS) were fabricated by magnetron sputtering deposition of Al and Ni nanolayers on a copper substrate with textured surface topography, the copper substrate was subsequently removed in order to obtain free-standing RMS. The morphology of the substrate surface impacted the microstructure of the produced RMS, therefore the RMS have a textured surface. The samples were papered with a surface texture in different orientations (0°, 45°, and 90°). Besides RMS with the same characteristics were prepared on Si wafer (flat surface) in order to compare the propagation behavior of the RMS with a textured surface and RMS with a relatively flat surface. During the ignition test, the propagation front was recorded by a High-Speed camera with a resolution of 50,000 fps. In the videos, it is possible to observe the effect of the textured surface of the RMS on the propagation front of the reaction.</p>
Controlling propagation velocity in Al/Ni reactive multilayer systems by periodic 2D surface structuring
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Computational Data: Accurately computed dimerization trends of ALD precursors and their impact on surface reactivity in area-selective atomic layer deposition
<p><span>The Lewis acidic nature of aluminum atoms in common precursors for the atomic layer deposition (ALD) of Al<sub>2</sub>O<sub>3</sub> can lead to dimerization. This study investigates whether these compounds predominantly exist as monomers or dimers under ALD conditions. Understanding dimerization is crucial for discussing precursor reactivities and other properties, especially in the context of area-selective ALD (AS-ALD). We employed a theoretical approach, incorporating conformer search, density functional theory, and coupled cluster calculations, to determine the dissociated dimer fraction for a range of precursors under typical ALD pressures and temperatures. The precursors studied include aluminum alkyls, chlorinated aluminum alkyls, dimethylaluminumisopropoxide (DMAI), and trisdimethylamidoaluminum (TDMAA). Our findings indicate that aluminum alkyls are completely dissociated over the whole parameter range, while DMAI and TDMAA form stable dimers. Chlorinated precursors were found to exist in both monomeric and dimeric forms depending on temperature and pressure.</span></p>
Inverse opals with reactive surface chemistry as sensors for aqueous pollutants
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Myelin oligodendrocyte glycoprotein reactive Th17 cells drive Janus Kinase 1 dependent transcriptional reprogramming in astrocytes and alter cell surface cytokine receptor profiles during experimental
GEO Series GSE262540. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Alkyne-functionalized cyclooctyne on Si(001) – reactivity studies and surface bonding from an energy decomposition analysis perspective
<p>The reactivity and bonding of an ethinyl-functionalized cyclooctyne on Si(001) is studied by means of density functional theory. This system is promising for the organic functionalization of semiconductors. Singly bonded adsorption structures are obtained by [2+2] cycloaddition reactions of the cyclooctyne or ethinyl group with the Si(001) surface. A thermodynamic preference for an adsorption with the cyclooctyne group in on-top position is found and traced back to minimal structural deformation of adsorbate and surface with the help of the energy decomposition analysis for extended systems (pEDA). Starting from singly bonded structures a plethora of reaction paths describing conformer changes and consecutive reactions with the surface are discussed. Strongly exothermic and exergonic reactions to doubly bonded structures are presented, while small reaction barriers highlight the high reactivity of the studied organic molecule on the Si(001) surface. Dynamic aspects of the competitive bonding of the functional groups are addressed by ab initio molecular dynamics calculations. Several trajectories to doubly bonded structures are obtained in agreement to calculations using the nudged-elastic band approach. However, our findings are in disagreement with experimental observations of a selective adsorption by the cyclooctyne moiety, which is critically discussed.</p>
Entecavir Prophylaxis for Hepatitis B Reactivation for CD20 Positive B-cell Lymphoma Patients With Resolved Hepatitis B (Negative Hepatitis B Surface Antigen, Positive Hepatitis B Core Antibody)
ClinicalTrials.gov study NCT05453435. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.