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16 results for “photocatalysis”
Visible light photocatalysis of 6pi-heterocyclization
<p>Photo‐mediated 6π cyclization is a valuable method for the formation of fused heterocyclic systems. Here we demonstrate that irradiation of cyclic 2‐aryloxyketones with blue LED light in the presence of an Ir<sup>III</sup> complex leads to efficient and high yielding arylation across a panoply of substrates by energy transfer. 2-Arylthioketones and 2‐arylaminoketones also cyclize effectively under these conditions. Quantum calculation demonstrates that the reaction proceeds via conrotatory ring closure in the triplet excited state. Subsequent suprafacial 1,4‐hydrogen shift and epimerization leads to the observed cis‐fused products.</p> <p>This data-set contains the output files from DFT calculations performed for this work, along with <a href="https://doi.org/10.5281/zenodo.595246">GoodVibes</a> thermochemistry outputs</p>
Thiosulfonylation of Unactivated Alkenes with Visible-Light Organic Photocatalysis
<p><strong>Origin of the data: </strong>Experimental spectroscopic measurements<br> <strong>Data Type: </strong>experimental measurements, open access supporting information</p> <p>The data are in CSV, DSW and FBSW format. Supporting information are supplied in PDF format.</p> <p>Data <strong>generated </strong>by instruments: </p> <p>Varian Cary 5E-UV-Vis-NIR spectrophotometer for UV-Vis measurements,<br> Varian Cary Eclipse fluorescence spectrophotomer for fluorescence quenching measurements.</p> <p><strong>Analytical and procedural information: </strong>Stern-Volmer fluorescence quenching experiments, UV-Vis measurements and Fluorescent Quantum Yield determination via ferrioxalate actinometry.</p> <p><strong>Definition of variables: </strong>Wavelength, Absorbance, Concentration<br> <strong>Units of measurement: </strong>nanometers (nm), moles-per-litre (mol/l)</p> <p><strong>Abbreviations: </strong><br> File names and data headers use the following abbreviations:</p> <ul> <li><strong>FQY </strong>refers to Fluorescence Quantum Yield determination experiments</li> <li><strong>Light </strong>refers to irradiated samples in the actinometry experiment, as detailed in the procedure in the supporting information.</li> <li><strong>Dark </strong>refers to non-irradiated samples in the actinometry experiment, as detailed in the procedure in the supporting information.</li> <li><strong>SVQuench </strong>refers to Stern-Volmer quenching experiments</li> <li><strong>RAxx </strong>refer to measurements related to allylbenzene. <strong>Xx </strong>is the amount of quencher in mol/l (05 should be intended as 0.5 mol/l and so on).</li> <li><strong>RTxx </strong>refer to measurements related to <em>S</em>-(4-methylphenyl) 4-methylbenzenethiosulfonate. <strong>Xx </strong>is the amount of quencher in mol/l as above.</li> <li><strong>RExx </strong>refer to measurements related to 1,2-dimethoxy-4-(prop-2-en-1-yl)benzene. <strong>Xx </strong>is the amount of quencher in mol/l as above.</li> <li><strong>RSxx </strong>refer to measurements related to styrene. <strong>Xx </strong>is the amount of quencher in mol/l.</li> <li><strong>RTFxx </strong>refer to measurements related to <em>S</em>-(4-fluorophenyl) 4-fluorobenzenethiosulfonate. <strong>Xx </strong>is the amount of quencher in mol/l as above.</li> <li><strong>MesAcrMe Xx </strong>refers to data related to catalyst 9-mesityl-10-methylacridinium. <strong>Xx </strong>is the amount of catalyst in mol/l as above.</li> <li><strong>DMC </strong>for measurements employing dimethylcarbonate as solvent.</li> <li><strong>ACN </strong>for measurements employing acetonitrile as solvent.</li> </ul>
Which bridge to cross, which mountain to climb – supramolecular photocatalysis outpacing conventional catalysis
<p>The file contains all raw data for the manuscript entitled "Which bridge to cross, which mountain to climb – supramolecular photocatalysis outpacing conventional catalysis" (i.e. Figs. 3-10).</p>
Raw data for Machine learning approach for photocatalysis: An experimentally validated case study of photocatalytic dye degradation
<p>Specification of affiliations:</p> <ul> <li>Hassan Ali - Centre of Polymer Systems</li> <li>Muhammad Yasir - Centre of Polymer Systems</li> <li>Hamza Ul Haq - Laboratory of Alternative Fuel and Sustainability, School of Chemical and Materials Engineering,</li> <li>Ali Can Guler - Centre of Polymer Systems</li> <li>Milan Masar - Centre of Polymer Systems</li> <li>Muhammad Nouman Aslam Khan - Laboratory of Alternative Fuel and Sustainability, School of Chemical and Materials Engineering,</li> <li>Michal Machovsky - Centre of Polymer Systems</li> <li>Vladimir Sedlarik - Centre of Polymer Systems</li> <li>Ivo Kuritka - Centre of Polymer Systems</li> </ul> <p> </p> <p>Raw data for the research paper. Information on the data collection are described in the manuscript. </p>
Benzaldehyde-Promoted (Auto)Photocatalysis under Visible Light: Pitfalls and Opportunities in Photocatalytic H2O2 Production
<p>Data to our study "Benzaldehyde-Promoted (Auto)Photocatalysis under Visible Light: Pitfalls and Opportunities in Photocatalytic H<sub>2</sub>O<sub>2</sub> Production"</p>
Datasets of evaluated Covalent Organic Frameworks for photocatalysis
<p>We developed a workflow to evaluate covalent organic frameworks (COFs) for photocatalysis. As an input, we chose the CURATED COFs (doi:<a href="https://doi.org/10.24435/materialscloud:z6-jn">10.24435/materialscloud:z6-jn</a>), a database of experimental COFs. We performed density functional theory (DFT) calculations, and post-processed the result with in-house codes available on GitHub (see <a href="https://github.com/bmourino/cof_photocatalysis">GitHub repository</a>). The dataset in cofs_descriptors.csv is the full dataset with all of our computed descriptors, and an application was developed to allow for interactively exploring the results (see <a href="https://github.com/bmourino/cofs_photocat_app">GitHub repository</a>). The bootstrapped_statistics.csv is the result of the statistical analysis with DABEST (Data Analysis with Bootstrap-coupled ESTimation, doi:<a href="https://doi.org/10.1038/s41592-019-0470-3">10.1038/s41592-019-0470-3</a>).</p>
Protected ultrathin cuprous oxide film for photocatalysis: Excitation and relaxation dynamics
<p>The main data analysis was done with Wavemetrics Igor Pro 7.08 using user-defined macros. Data files given in *.itx<br> format are human-readable text files that can be opened in Igor Pro. User-defined macros are available from the<br> authors upon reasonable request. Static spectra are measured with the proprietary "Croissant" software for the<br> channeltron analyzer and saved in human-readable *.plsp format, or SpecsLab Prodigy 4.60.1 for the 2D analyzer and<br> saved in the proprietary SPECS *.sle format or exported into *.itx format. Time-resolved spectra are measured with a<br> proprietary LabView program and exported in the binary HDF5 *.h5 file format.</p> <p><br> ******************************************** Fig. 1 LEED and He Ia ARPES ********************************************<br> LEED images taken with SBIG STF-8300 CCD Camera, the SBIG format is a 16-bit grayscale bitmap with metadata.<br> Fig. 1a: LEED image at 120 eV<br> LEED220210_120eV_Cu111_hBN_Cu2O.SBIG<br> Fig. 1b: LEED image at 48 eV<br> LEED220210_048eV_Cu111_hBN_Cu2O.SBIG</p> <p>other energies (not shown in the figure): see Fig. S2/S3</p> <p>Fig. 1c: He Ia spectrum second derivative as function of parallel momentum and binding energy<br> Spectra measured with VG ESCALAB 220 channeltron hemispherical analyzer by tilting the sample at two fixed azimuthal<br> angles and using a Gammadata VUV 5050 monochromated helium lamp. The azimuthal angles correspond to the M and K<br> directions, respectively, as determined by x-ray photoelectron diffraction of the Cu(111) surface. Measurement<br> parameters are given in the files.<br> Positive parallel momentum: M direction, VG2Z220628N015.plsp<br> Negative parallel momentum: K direction, VG2Z220628N016.plsp<br> Combined ARPES spectrum as a function of parallel momentum and binding energy: VG2Z220628N015_N016.itx<br> Second derivative along energy direction: VG2Z220628N015_N016d.itx; smoothed: VG2Z220628N015_N016d_smth.itx</p> <p><br> ************************************************ Fig. 2 He IIa ARPES ************************************************<br> All ARPES spectra measured with SPECS Phoibos 150 WAL hemispherical analyzer (2D detector) using SpecsLab Prodigy<br> software and non-monochromated helium lamp.</p> <p>Fig. 2a: Detail of He IIa spectrum measured on h-BN/Cu(111)<br> Full angle-resolved spectrum (intensity as function of angular coordinate and kinetic energy), summed over all energy<br> channels and scans, exported from SpecsLab Prodigy as Igor Text. All measurement parameters are given in the file.<br> Spectrum HeIIa h-BN Cu111 20201023.itx<br> Spectrum scale converted into parallel momentum and binding energy: Spectrum HeIIa h-BN Cu111 20201023 k2.itx</p> <p>Fig. 2b: Detail of He IIa spectrum measured on h-BN/Cu2O/Cu(111)<br> Full angle-resolved spectrum (intensity as function of angular coordinate and kinetic energy), summed over all energy<br> channels and scans, exported from SpecsLab Prodigy as Igor Text. All measurement parameters are given in the file.<br> Spectrum HeIIa h-BN Cu2O Cu111 20220211.itx<br> Spectrum scale converted into parallel momentum and binding energy: Spectrum HeIIa h-BN Cu2O Cu111 20220211 k2.itx</p> <p>Fig. 2c: Spectra integrated over given parallel momentum range<br> Intensity as a function of binding energy<br> Spectrum HeIIa h-BN Cu111 20201023 k2 042_092.txt<br> Spectrum HeIIa h-BN Cu2O Cu111 20220211 k2 041_091.txt</p> <p><br> ************************* Fig. 3 2PPE spectra of Cu(111), h-BN/Cu(111) and h-BN/Cu2O/Cu(111) *************************<br> Spectra measured with SPECS Phoibos 150 WAL hemispherical analyzer (2D detector) using SpecsLab Prodigy software and<br> exported as Igor Text. All measurement parameters are given in the files. 3eV wavelength was 412nm, p-polarized.<br> A -10V bias voltage was applied to the sample.<br> Cu(111) 2PPE: P=1mW, Cu111 2022-04-14_20h47m45s.itx<br> Cu(111) 3PPE: P=3mW, Cu111 2022-04-14_21h09m29s.itx<br> h-BN/Cu(111) 2PPE: P=1.0mW, 0.5mm entrance slit, Cu111 hBN Spectrum3eV_2B_ppol.itx<br> h-BN/Cu(111) 3PPE: P=0.4mW, 3.0mm entrance slit, Cu111 hBN Spectrum3eV_4B_ppol.itx<br> h-BN/Cu2O/Cu(111) 2PPE: P~0.1mW, Cu111 hBN Cu2O 2022-02-11_17h07m34s.itx<br> h-BN/Cu2O/Cu(111) 3PPE: P~0.1mW, Cu111 hBN Cu2O 2022-02-11_16h58m49s.itx</p> <p>************************************************* Fig. 4 Delay Scan *************************************************<br> Delay scans are recorded with proprietary LabView software and saved in binary HDF5 format as a 3D stack of<br> detector images (intensity as function of angular coordinate and kinetic energy) as a function of pump-probe delay.<br> Bias -5V, 3eV=413nm 0.3mW p-pol, 6eV=208nm 1nA p-pol, Ekin=11.9eV, Epass=20eV,<br> 1mm slit, exposure 10x500ms, 20 scans, 10fs steps<br> Raw data, 256 angular pixels x 348 energy pixels x 201 delays x 20 scans:<br> WAL_20220215_UZH_JB_dscan_040_0to9.h5<br> WAL_20220215_UZH_JB_dscan_040_10to19.h5<br> Sum of all scans (transposed):<br> WAL_20220215_UZH_JB_dscan_040_sum.h5<br> Cropped to active detector window and applied distortion correction and correct scaling:<br> dscan_20220215_040_data3Dcorrected.h5<br> Integrated over +-10° angular window: dscan040.itx<br> Background averaged over delay positions 0-19 subtracted and energy and delay scales corrected:<br> Fig. 4a: dscan040bgi0.itx<br> Delay scan with 50ps range and 0.2ps steps, not shown in figure but analyzed the same way: dscan041bgi.itx</p> <p>Fig. 4b: Intensity as a function of intermediate state energy<br> 50 fs, delay positions 40-50: dscan040t0mbg.txt<br> 1 ps, delay positions 140-150: dscan040t2mbg.txt<br> 10 ps, delay positions 55-65 in dscan041bgi: dscan041t3mbg.txt</p> <p>Fig. 4c: detector image obtained by averaging images at delay positions 40-50 and subtracting the background image,<br> then correcting the angular distortion by normalizing the intensity at the Fermi energy<br> dscan040image_diff0.itx</p> <p><br> ************************************************* Fig. 5 Fit Curves *************************************************<br> The Igor Pro batch fitting procedure was used with a custom fitting function to fit the delay scan dscan040bgi<br> binned in 0.1 eV intervals with index 0 at -0.3 eV.<br> The displayed curves have index 13 (1.0 eV), 6 (0.3 eV) and 4 (0.1 eV).</p> <p>Binned delay scan: dscan040bgi_pix.itx<br> Fit parameters: dscan040bgi_fitparams.txt<br> Fit result: dscan040bgi_pixRateFits.itx<br> Fast component: dscan040bgi_FastComponent.itx<br> Slow component: dscan040bgi_SlowComponent.itx</p> <p><br> ******************************************* Fig. 6 Fit Results Comparison *******************************************<br> Relaxation times are extracted from the batch fit results of different delay scans.<br> 3 nJ pump: dscan040bgi_fitparams.txt dscan_220215_040<br> 20 nJ pump: dscan010_BG4_fitparams.txt dscan220703_010<br> (data: dscan010_BG4.itx, binned: dscan010_BG4_pix.itx, fits: dscan010_BG4_pixFit.itx)<br> h-BN/Cu(111): dscan033_fitparams.txt<br> (binned data: dscan044_hBN_side_pix1.itx, fits: dscan033_hBN_side_pixFits.itx)<br> Lisowski et al.: LifetimesLisowski.txt<br> (data from M. Lisowski, P. A. Loukakos, U. Bovensiepen, and M. Wolf, Femtosecond Dynamics and Transport of Optically<br> Excited Electrons in Epitaxial Cu Films on Si(111)-7 x 7, Appl. Phys. A 79, 739 (2004))<br> Extrapolation: fit_LifetimesLisowski.txt, using power law tau=0.054797*E^(-1.1419)</p> <p><br> **************************************************** Fig. S1 XPS ****************************************************<br> Preparation 1 before oxidation: Preparation 1 after oxidation: Preparation 2 after oxidation:<br> B 1s: VG2Z220209N005.pesp B 1s: VG2Z220210N023.pesp B 1s: VG2Z220628N002.pesp<br> N 1s: VG2Z220209N006.pesp N 1s: VG2Z220210N024.pesp N 1s: VG2Z220628N003.pesp<br> C 1s: VG2Z220209N007.pesp C 1s: VG2Z220210N025.pesp C 1s: VG2Z220628N004.pesp<br> O 1s: VG2Z220209N008.pesp O 1s: VG2Z220210N026.pesp O 1s: VG2Z220628N005.pesp<br> Cu 2p:VG2Z220209N009.pesp Cu 2p:VG2Z220210N027.pesp Cu 2p:VG2Z220628N006.pesp</p> <p><br> **************************************************** Fig. S2 LEED ****************************************************<br> 48 eV: LEED220209_048eV_Cu111_hBN.SBIG<br> 70 eV: LEED220209_070eV_Cu111_hBN.SBIG<br> 100 eV: LEED220209_100eV_Cu111_hBN.SBIG<br> not shown in figure:<br> 40 eV: LEED220209_040eV_Cu111_hBN.SBIG<br> 120 eV: LEED220209_120eV_Cu111_hBN.SBIG</p> <p><br> **************************************************** Fig. S3 LEED ****************************************************<br> 40 eV: LEED220210_040eV_Cu111_hBN_Cu2O.SBIG<br> 48 eV: LEED220210_048eV_Cu111_hBN_Cu2O.SBIG<br> 70 eV: LEED220210_070eV_Cu111_hBN_Cu2O.SBIG<br> 100 eV: LEED220210_100eV_Cu111_hBN_Cu2O.SBIG<br> 120 eV: LEED220210_120eV_Cu111_hBN_Cu2O.SBIG<br> 150 eV: LEED220210_150eV_Cu111_hBN_Cu2O.SBIG</p> <p><br> **************************************************** Fig. S4 LEED ****************************************************<br> 40 eV: LEED220628_040eV_Cu111_hBN_Cu2O.SBIG<br> 48 eV: LEED220628_048eV_Cu111_hBN_Cu2O.SBIG<br> 70 eV: LEED220628_070eV_Cu111_hBN_Cu2O.SBIG<br> 100 eV: LEED220628_100eV_Cu111_hBN_Cu2O.SBIG<br> 110 eV: LEED220628_110eV_Cu111_hBN_Cu2O.SBIG<br> 140 eV: LEED220628_140eV_Cu111_hBN_Cu2O.SBIG<br> 180 eV: LEED220628_180eV_Cu111_hBN_Cu2O.SBIG<br> not shown in figure:<br> 120 eV: LEED220628_120eV_Cu111_hBN_Cu2O.SBIG<br> 150 eV: LEED220628_150eV_Cu111_hBN_Cu2O.SBIG</p> <p><br> ********************************************* Fig. S5 Work function maps *********************************************<br> Ekin=10.4eV, Epass=20eV, 6eV=208.5nm 0.2nA p-pol, 1mm slit, -5V bias, exposure 1x500ms, 0.1mm steps, 81x81 pixels<br> Preparation 1:<br> Data cube after lens correction and correct scaling: dscan_220221_003_data3Dcorrected.h5<br> Integrated over all angles and brought into raster format: dscan_220221_003_raster.h5<br> Work function map: dscan_220221_003_rasterWF.itx<br> Inset: Photograph of the sample after preparation 1, "Photograph hBN Cu2O Cu.png"<br> Preparation 2:<br> Data cube after lens correction and correct scaling: dscan_220704_011_data3Dcorrected.h5<br> Integrated over all angles: dscan_220704_011_raster.h5<br> Work function map: dscan_220704_011_rasterWF.itx</p> <p><br> ************************************************ Fig. S6 Delay Scans ************************************************<br> See description of Fig. 4 for processing details. Pump power was measured with a thermal powermeter and probe power<br> was measured with a Thorlabs SM05PD7A GaP-photodiode with 14.4 mA/W sensitivity at 208nm.<br> The thermal powermeter has an accuracy of +-0.1mW.<br> 1.0mW pump power at 100kHz repetition rate equals 10nJ pulse energy.<br> 1.0nA photodiode current equals approximately 70nW probe power or 0.7 pJ probe energy.</p> <p>Common settings: Bias voltage -5V, exposure time 20x500ms, 20 scans, 20fs steps, entrance slit size 1mm,<br> Pass energy 20eV, Kinetic energy 11.9 eV, pump wavelength 413nm, pump and probe beam are p-polarized.<br> Differing settings are written for each dataset.</p> <p>Fig. S6a: dscan_220215_040/dscan040bgi0.itx, processed raw data: dscan_220215_040_data3Dcorrected.h5<br> 0.3mW pump, 208nm 1.0nA probe, 10fs steps, exposure 10x500ms<br> Fig. S6b: dscan_220217_045/dscan045bgi.itx, processed raw data: dscan_220217_045_data3Dcorrected.h5<br> 0.3mW pump, 208nm 1.0nA probe, 10fs steps, Ekin=13.3eV, Epass=30eV, 7mm slit, 50 scans<br> Fig. S6c: dscan_220216_041/dscan041bgi.itx, processed raw data: dscan_220216_041_data3Dcorrected.h5<br> 0.3mW pump, 208nm 1.0nA probe, 200fs steps, exposure 10x500ms, 10 scans</p> <p><br> ************************************************ Fig. S7 Delay Scans ************************************************<br> Common settings: same as in Fig. S6</p> <p>Fig. S7a: dscan_220701_020/dscan020bgi0.itx, processed raw data: dscan_220701_020_data3Dcorrected.h5<br> 0.5mW pump, 209nm 0.9nA probe, 3mm slit<br> Fig. S7b: dscan_220712_029/dscan029_BG.itx, processed raw data: dscan_220712_029_data3Dcorrected.h5<br> 1.5mW pump, 209nm 1.0nA probe<br> Fig. S7c: dscan_220703_010/dscan010_BG4.itx, processed raw data: dscan_220703_010_data3Dcorrected.h5<br> 2.0mW pump, 209nm 0.9nA probe<br> Fig. S7d: dscan_220417_033/dscan033_hBN_side0.itx, processed raw data: dscan_220417_033_data3Dcorrected.h5<br> 1.0mW pump, 208nm 0.1nA probe, Ekin=11.8eV, 40 scans</p> <p><br> *********************************************** Fig. S8 Beam profiles ***********************************************<br> 8-bit CCD images were acquired with a Basler puA1280-54um CCD camera and Basler pylonViewer 5.0 acquisition software.<br> Sensor resolution: 1280x960, pixel size: 3.75x3.75 micrometers<br> 3 eV image: 10 microseconds exposure time, Spot3eV 10us 20mm.bmp<br> 6 eV image: 100 milliseconds exposure time, Spot6eV 100ms 20mm.bmp</p>
Monitoring of ciprofloxacin degradation by UV-A LED photolysis and photocatalysis under different scenarios
<p>The spreadsheet contains the HPLC integration peaks monitoring the photolytic and photocatalytic degradation of the antibiotic ciprofloxacin (CIP) in milliQ water. The initial concentration of CIP is 10 mg/L. In the spreadsheets is shown the obtainment of 1st order kinetic constant rates for different photoreactor designs using 2, 3, 4 or 6 UVA-LED strips around the reactor, distanced 10 or 15 mm from the reactor's walls. The influence of different controlled periodic illumination's duty cycle (0.50 and 0.75) is also shown. Calculations of EEO (electrical energy per order consumption) are also made for each reactor set up.</p> <p>The irradiance values for each photoreactor design calculated by an optical software is presented as planar projections of the cylindrical reactor. Images showing the radiant flux in the photoreactor's middle cross section obtained by the software are also shown</p> <p>Finally, a full factorial design of experiments is made to obtain a model of prediction of kinetic constant rates and EEO values. Predicted vs experimental values are plotted.</p>
Photocatalysis Ontology - Dataset and RO-Crates packages
<p>In this package are the datasets extracted from the Artleafs database, as well as the RO-Crate packages and the RDF dataset generated from them for the project to create RO-Crates using the PHCAT ontology. You can also find python scripts used to transform the extracted CSV data into a new RDF dataset allowing you to create more RO-Crate packages if desired.</p> <p><strong>-./data:</strong> contains the set of data extracted from the database in CSV format.</p> <p><strong>- ./resources:</strong> contains the generated RO-Crate packages as well as the mapping files used and the RDF subsets of each article.</p> <p><strong>- ./OutputPhotocatalysisMapping.ttl:</strong> is the file in turtle format in charge of storing the global RDF data set after the translation of the database data.</p> <p>- ./<strong>documentation: </strong>in this folder is the documentation in HTML format of W3C.</p> <p>The rest of the folders and files contain mapping rules and scripts used in the data transformation process. For more information check the following GitHub repository: https://github.com/oeg-upm/photocatalysis-ontology.</p> <p> </p>
raw data for the article "Direct Photoexcitation of EthynylBenziodoXolones: An Alternative to Photocatalysis for Alkynylation Reactions"
<p>Raw NMR, MS and IR data for the article "Direct Photoexcitation of EthynylBenziodoXolones: An Alternative to Photocatalysis for Alkynylation Reactions" published in Angewandte Chemie, International Edition, DOI: </p> <p>https://onlinelibrary.wiley.com/doi/10.1002/anie.202110257R1</p> <p>The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.</p>
Data to our paper "Enhancing Photocatalysis: Understanding the Mechanistic Diversity in Photocatalysts Modified with Single-Atom Catalytic Sites"
<p>Data to our paper "Enhancing Photocatalysis: Understanding the Mechanistic Diversity in Photocatalysts Modified with Single-Atom Catalytic Sites"</p>
Direct Decarboxylation of Trifluoroacetates Enabled by Iron Photocatalysis – NMR raw data
<div> <p>NMR raw data and HRMS of the compounds in the publication cited.</p> </div>
Turn-on of a ruthenium complex photocatalysis by DNA-templated ligation - Raw data
<p>Raw data from analyses reported in the publication</p>
Moisture-based green energy harvesting over 600 hours via photocatalysis-enhanced hydrovoltaic effect
<p>Source Date</p>
Exploring the Chemical Design Space of Metal-Organic Frameworks for Photocatalysis
<p>In this work, we employ a chemical insights-based diversity-driven approach to search for metal-organic framework (MOF) photocatalysts. With an in silico design based on chemical insights, we populated areas in the chemical design space related to MOFs with photocatalytic potential. We selected a balanced dataset of DFT-based photocatalytic descriptors computed for 314 MOFs, comprising our in silico structures, a diverse subset of the QMOF database, and experimental MOF photocatalysts. With such a balanced dataset, we could fine-tune supervised machine-learning models from literature that allowed us to draw insights into relevant areas in the chemical design space for photocatalysis and potential bottlenecks.<br>Among our in silico MOFs, a few motifs stood out, such as Au-pyrazolate, Ti clusters and rod-shaped metal nodes, and a particular MOF designed with the Mn4Ca cluster, which mimics the OER center in the photosystem II of photosynthesis.<br>Overall, by combining three pillars --- the design of potential MOF photocatalysts guided by chemical insights, the DFT evaluation of photocatalytic descriptors, and the machine-learning approach --- we were able to gain insights into structure-property relationship, and identify trends in the chemical design space that can open new avenues for advancing the field of photocatalysis.</p>
Selective ligand removal to improve accessibility of active sites in hierarchical MOFs for heterogeneous photocatalysis
<p>This file includes the source data for all experimental and theoretical data of the publication.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.