Contributors: Griffin Walker
... Griffin Walker's demo, released in 2004. It's not mastered, please be kind.
Dataset for C-O bond activation using ultra-low loading noble metal catalysts on moderately reducible oxides
Contributors: Jiayi Fu, Jonathan Lym, Weiqing Zheng, Konstantinos Alexopoulos, Alexander Mironenko, Na Li, Jorge Anibal Boscoboinik, Dong Su, Ralph Webber, Dionisios Vlachos
... Selective C-O activation of complex multifunctional molecules is an essential step for many important chemical processes. Although reducible metal oxides are active and selective towards reductive C-O bond scission via the reverse Mars-van Krevelen mechanism, the most active oxides undergo bulk reduction during reaction. Here, we report a strategy for C-O bonds activation by surface doping moderately reducible oxides with ultra-low loading of noble metals. We demonstrate the principle using highly dispersed Pt anchored onto TiO2 for furfuryl alcohol conversion to methyl furan. A combination of density functional theory calculations, catalyst characterization (STEM, EPR, FTIR and XAS), kinetic experiments, and microkinetic modelling expose significant C-O activation rate enhancement, without either bulk catalyst reduction or unselective ring hydrogenation. A methodology is introduced to quantify various types of sites, revealing that the cationic redox Pt on TiO2 surface is more active than metallic sites for C-O bond activation.
Data for: Combination of numerical modelling and field measurments reveals strong regional control of slope on soil thickness and chemical weathering in subtropical Brazil
Contributors: Liesa Brosens, Benjamin Campforts, Jérémy Robinet, veerle vanacker, Sophie Opfergelt, Yolanda Ameijeiras-Mariño, jean minella, gerard govers
... This data repository contains 3 main files: 1) Excel tables with: - Input and results of the synthetic model runs (Table S3) - Input and results of model applied to sampling locations (Table S4) - Soil profile description for each sampled location 2) Map with the coordinates of the sampling locations (.gpx and .shp format) 3) Text file containing the spectra of the scanned regional samples in the Mid- Infrared region (MIR). Spectra are given as absorbance and already corrected for possible drift by dividing by the background samples
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Contributors: Raúl Roberto poppiel, Marilusa Pinto Coelho Lacerda, José Lucas Safanelli, Rodnei Rizzo, Manuel Pereira de Oliveira junior, Jean Jesus Novais, Jose Alexandre Dematte
... Maps of clay, silt and sand contents (g kg-1) were predicted at 0-20 cm, 20-60 cm and 60-100 cm depths intervals by random forest regression in Google Earth Engine. Gridded soil information covers a part of the Midwest Brazil, from 12° S to 20° S and from 45° W to 54° W, and is available with 250m resolution. The maps were cross-validated and had Coefficient of Determination ranging from 0.64 to 0.85 at all depth intervals.
Contributors: Hary Murcahyanto
... Data ini adalh data hasil wawancara penelitian alat Musik Trasisional Lombok "Selober" yang menjadi bahan kajian utama pada penelitian ini,
Contributors: Abdikaiym Zhiyenbek
... This dataset contains Aral Sea Basin boundary shapefiles and its sub-basins. The shapefiles are produced using data from HydroSHEDS project that provides watershed delineations at a global scale. Aral Sea basin has two major rivers, Syr-Darya and Amu-Darya, and their boundary shapefiles are included separately. Small sub-basins between these two major rivers were joined and merged to produce the Aral Sea Basin boundary.
Contributors: Andrea Vigliotti
... This is a static collection of the scripts needed to reproduce the examples of the paper: Vigliotti A., Auricchio F., "Automatic differentiation for solid mechanics", Archives of Computational Methods in Engineering, 2020, In the press DOI 10.1007/s11831-019-09396-y The same data are also availble from the following github repository: https://github.com/avigliotti/AD4SM.jl the above repository includes the AD4SM.jl package files and will be updated with new versions, new examples, bug corrections, etc. The scripts included in this data set are written in the Julia programming language and will need a working installation in order to run properly. Julia is an open-source, high-level, high-performance, dynamic programming language. Refer to the Julia language website for more information and downloads at https://julialang.org/ Following the content of the individual files: - adiff.jl : main module implementing the dual number algebra needed for the forward differentiation - materials.jl : module implementing the strain energy density functions for the different material models - elements.jl : module implementing the element integration rules, the functions for evaluating the deformation energy of the entire model, together with the Lagrange multipliers, and the solvers - example_01_non_linear_truss.jl : julia file for the first example 1 of the paper, this file produce as output the openscad model of the deformed truss for producing preety images - example_01_non_linear_truss.ipynb : jupyther notebook file for example 1 - example_02_Euler_beams.ipynb : julia file for the first example 2 of the paper - example_02_Euler_beams.jl : jupyther notebook file for example 2 - example_03_plane_stress.ipynb : jupyther notebook file for the first example 3 of the paper - example_03_plane_stress.jl : julia file for example 3 - example_04_AxSymDomain.ipynb : notebook file for example 4 - example_04_AxSymDomain.jl : julia file for example 4 - example_05_3DSpring.jl : julia file for example 5, this files produces output files readable with paraview - Pattern2D03FinerMesh02j.inp : input file for example 3 - AxSymDomainj.inp : input file for example 4 - 3DSpringHexaj.inp : input file for example 5 - polyhedron_hedges.scad : helper file to produce the openscad files for the deformed lattices of example 1 - description.txt : this file - step_to_reproduce.txt : the file with the steps to reproduce te ecamples
Data for: An analytical solution for buckling and vibration problems of delaminated doubly curved shells
Contributors: Zoltán Juhász, András Szekrényes
... Abaqus validation
Contributors: Hichem Omrani, Bilel Omrani, Benoit Parmentier, Marco Helbich
... Monitoring of air pollution is an important task in public health. Availability of data is often hindered by the paucity of the ground monitoring station network. We present here a new spatio-temporal dataset collected and processed from the Sentinel-5P remote sensing platform aiming at the monitoring of air pollution for public institutions. As an example application, we applied the full workflow to process measurements of Nitrogen dioxide (NO2) collected over the territory of mainland France from May 2018 to June 2019. The data stack generated is daily measurements at a 4×7km spatial resolution. The supplementary code package used to collect and process the data is made publicly available to ease the access and processing for any location and product. The dataset provided in this article is of value for policy-makers and health assessment. Please find the full dataset in a Dropbox shared repository using this link: https://drive.google.com/drive/folders/1t5vbQq1g0LtJa37Sc6NYoq45bkLP2EWp?usp=sharing The raw data file is zipped to save disk space. The original raw data have a size of 60 Gigabyte
Contributors: Gaetan Montero, Cécile Tannier, Isabelle Thomas
... Contributors: Gaëtan Montero, Cécile Tannier, Isabelle Thomas Date:2019-16-10 Description: This data set can be used to reproduce the analyses made by the authors in their paper “Morphological delineation of cities based on scaling properties of urban patterns: a comparison of three methods”. It contains 12 shapefiles that represent theoretical urban patterns and 4 shapefiles that can be used to delineate the morphological agglomeration of Brussels (Belgium). It also contains a R script to calculate the carrying capacity of a logistic percolation function. Description of each file 2_Figure_1: theoretical street network for testing the Natural Cities method 3_Figure_2: theoretical street network for the comparison of two variants of the Natural Cities method 4_Figure_3: theoretical street network to evaluate the effects of the spatial extent of the study area on the delineation of Natural Cities 5_Figure_5a: theoretical pattern for testing MorphoLim (building footprints) – dense urban core 6_Figure_5b: theoretical pattern for testing MorphoLim (building footprints) – less dense urban core 7_Figure_6: theoretical pattern (building footprints) to evaluate the effects of the geographic extent of the study area on the delineation with MorphoLim 8_Percolation_C_Calculation: R code to calculate the carrying capacity of a logistic function (Hierarchical Percolation) 9_Figure_7: theoretical street network for testing Hierarchical Percolation 10_Figure_8: theoretical polycentric street network for testing Hierarchical Percolation 11_Figure_9ac: theoretical urban pattern crossed by a large non built area (road intersections) 12_Figure_9b: theoretical urban pattern crossed by a large non built area (building footprints) 13_Figure_10ac: theoretical pattern where a built ribbon links two urban centres (roads intersections ) 14_Figure_10b: theoretical pattern where a built ribbon links two urban centres (building footprints) 15_Belgium_buildings: cadastral data of buildings (2D) for Belgium (© 2009 Administration Générale de la Documentation Patrimoniale) 16_Brabant_buildings: cadastral data of buildings (2D) for the province of Brabant (© 2009 Administration Générale de la Documentation Patrimoniale) 17_Belgium_roads: road network data come from the platform Geofabrik of OpenStreetMap (http://download.geofabrik.de, accessed 08/21/2018) for Belgium 18_Brabant_roads: Road network data come from the platform Geofabrik of OpenStreetMap (http://download.geofabrik.de, accessed 08/21/2018) for the province of Brabant.