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51 results for “Electron transfer”
Dataset for Activation of Glassy Carbon Surfaces by Alkaline Anodization Enhances Dopamine Adsorption and Electron-Transfer Kinetics
<p>This dataset provides the raw data to the manuscript</p><p><strong>"Activation of Glassy Carbon Surfaces by Alkaline Anodization Enhances Dopamine Adsorption and Electron-Transfer Kinetics"</strong></p><p>published in ChemElectroChem</p><p>Specifically, the following measurements are provided:</p><ul><li>Scanning electrochemical cell microscopy (SECCM). Cyclic voltammetry (E, i) data for each location across the sample. 5 cycles.</li><li>Chronoamperometry (i, t) for the anodization process.</li><li>Atomic Force Microscopy (AFM) topography.</li><li>Raman microscopy</li><li>X-ray photoelectron spectroscopy (XPS)</li><li>Scanning electron microscopy (SEM)</li></ul>
Radiation damage hot spots formed by two-step electron transfer mediated decay of solvated ions - data
<p>Data set pertaining to the manuscript "Radiation damage hot spots formed by two-step electron transfer mediated decay of solvated ions", accepted for publication in Nature Chemistry.</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07, see<br> https://www.nexusformat.org/<br> https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br> NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br> * nexpy (distributed with python)<br> * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br> 1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data') if applicable.<br> 2. As-measured data ('raw').</p> <p>Files with extension .csv are comma-separated ascii-files, designed to be opened with a spreadsheet programme.</p> <p><br> The following files are provided:</p> <p>Photoemission data pertaining to ETMD measurements:<br> alcl3-K-etmd.h5 (ETMD after Al K-shell photoionization)<br> alcl3-L23-etmd.h5 (ETMD after Al L-shell photoionization)</p> <p>Calculated energies of the ETMD final states after 1s ionization. The energies were calculated at the CAS-CI/cc-pVDZ level. The states were shifted so that the lowest-energy state corresponds to the LC-ωPBE/aug-cc-pVTZ and aug-cc-pCVTZ value obtained in a polarizable continuum:<br> Dataset_ETMD_after_1s_ionization.csv<br> Dataset_ETMD_after_2p_ionization.csv</p> <p>Geometrical coordinates of the clusters that were used for energy calculation:<br> clusters.dat<br> clusters_small.dat</p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p> <p> </p> <p>Version history:</p> <p>v3 - Al L2,3 data: Orientation of the analyser hemisphere corrected. Direction of the linear polarization vector added. All other data unchanged.<br> v2 - cluster coordinates added, all other data unchanged.<br> v1 - initial upload.</p>
Data: Steering photoinduced electron transfer in intramolecular photocatalysts by peripheral ligand control
<p>The data presented herein is analysed and showcased within the <i>ChemRxiv</i> article titled "<i>Steering photoinduced electron transfer in intramolecular photocatalysts by peripheral ligand control</i>" (<a href="10.26434/chemrxiv-2023-vspb5"><strong>DOI </strong></a><a href="https://doi.org/10.26434/chemrxiv-2023-vspb5"><strong>10.26434/chemrxiv-2023-vspb5</strong></a>). Kindly acknowledge and cite this article when referencing or utilizing the provided data.</p>
Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics
<p>Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics.</p> <p>Including the simulation input parameter file and the necessary output data to plot each figure in the article. </p>
Understanding Electron Transfer Reactions using Constrained Density Functional Theory: Complications due to Surface Interactions
<p>For reproducing the results presented in "<strong>Hashemi, A., Peljo, P., & Laasonen, K. (2022). Understanding Electron Transfer Reactions using Constrained Density Functional Theory: Complications due to Surface Interactions</strong>", this database provides the input files and CDFT-AIMD trajectory information. Please refer to the publication if you wish to use these data.</p> <p>---------------------------------------**************************************************************************-------------------------------------------------</p> <p><em>This study was financed by the Horizon 2020 Framework Programme CompBat with project number 875565. We also thank CSC-IT Center for Science Ltd. and Aalto Science-IT project for generous grants of computer time.</em><br> -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>The content of a directory is shown in a tree-like format:</strong><br> ├── 1DMDQ<br> │ ├── 1_md<br> │ │ ├── dft-common-params.inc<br> │ │ ├── dmdq-md-pos-1.xyz<br> │ │ ├── md.inp<br> │ │ ├── pos.xyz<br> │ │ ├── submit.sh<br> │ │ └── subsys.inc<br> │ ├── 2_cdftaimd<br> │ │ ├── state_a<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ ├── state_b<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ └── subsys.inc<br> │ │ └── state_c<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── cdft_md.bash<br> │ │ ├── cdft_md.inp<br> │ │ ├── dft-common-params.inc<br> │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ └── subsys.inc<br> │ └── 3_cdft_wH2O_sccs<br> │ ├── state_a<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ ├── state_b<br> │ │ ├── b_to_a.tar.gz<br> │ │ └── b_to_c.tar.gz<br> │ └── state_c<br> │ ├── framePrint.py<br> │ ├── input_files<br> │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── dft-common-params.inc<br> │ │ ├── energy_cdft.inp<br> │ │ ├── energy_mixed_cdft.inp<br> │ │ └── subsys.inc<br> │ └── README<br> ├── 2MeVi<br> │ ├── 1_md<br> │ │ ├── dft-common-params.inc<br> │ │ ├── md.inp<br> │ │ ├── mevi-md-pos-1.xyz<br> │ │ ├── pos.xyz<br> │ │ ├── submit.sh<br> │ │ └── subsys.inc<br> │ ├── 2_cdftaimd<br> │ │ ├── state_a<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ └── subsys.inc<br> │ │ ├── state_b<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ └── state_c<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── cdft_md.bash<br> │ │ ├── cdft_md.inp<br> │ │ ├── dft-common-params.inc<br> │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ ├── frame.xyz<br> │ │ └── subsys.inc<br> │ └── 3_cdft_wH2O_sccs<br> │ ├── state_a<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ ├── state_b<br> │ │ ├── b_to_a<br> │ │ │ ├── framePrint.py<br> │ │ │ ├── input_files<br> │ │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ │ ├── dft-common-params.inc<br> │ │ │ │ ├── energy_cdft.inp<br> │ │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ │ └── subsys.inc<br> │ │ │ └── README<br> │ │ └── b_to_c<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ └── state_c<br> │ ├── framePrint.py<br> │ ├── input_files<br> │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── dft-common-params.inc<br> │ │ ├── energy_cdft.inp<br> │ │ ├── energy_mixed_cdft.inp<br> │ │ └── subsys.inc<br> │ └── README<br> ├── 3OHVi<br> │ ├── 1_md<br> │ │ ├── dft-common-params.inc<br> │ │ ├── md.inp<br> │ │ ├── ohvi-md-pos-1.xyz<br> │ │ ├── pos.xyz<br> │ │ ├── submit.sh<br> │ │ └── subsys.inc<br> │ ├── 2_cdftaimd<br> │ │ ├── state_a<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ ├── state_b<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ └── state_c<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── cdft_md.bash<br> │ │ ├── cdft_md.inp<br> │ │ ├── dft-common-params.inc<br> │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ ├── frame.xyz<br> │ │ └── subsys.inc<br> │ └── 3_cdft_wH2O_sccs<br> │ ├── state_a<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ ├── state_b<br> │ │ ├── b_to_a<br> │ │ │ ├── framePrint.py<br> │ │ │ ├── input_files<br> │ │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ │ ├── dft-common-params.inc<br> │ │ │ │ ├── energy_cdft.inp<br> │ │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ │ └── subsys.inc<br> │ │ │ └── README<br> │ │ ├── b_to_a.tar.gz<br> │ │ ├── b_to_c<br> │ │ │ ├── framePrint.py<br> │ │ │ ├── input_files<br> │ │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ │ ├── dft-common-params.inc<br> │ │ │ │ ├── energy_cdft.inp<br> │ │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ │ └── subsys.inc<br> │ │ │ └── README<br> │ │ └── b_to_c.tar.gz<br> │ └── state_c<br> │ ├── framePrint.py<br> │ ├── input_files<br> │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── dft-common-params.inc<br> │ │ ├── energy_cdft.inp<br> │ │ ├── energy_mixed_cdft.inp<br> │ │ └── subsys.inc<br> │ └── README<br> ├── 4dBR5<br> │ ├── 1_md<br> │ │ ├── dft-common-params.inc<br> │ │ ├── dmdq-md-pos-1.xyz<br> │ │ ├── md.inp<br> │ │ ├── pos.xyz<br> │ │ ├── submit.sh<br> │ │ └── subsys.inc<br> │ ├── 2_cdftaimd<br> │ │ ├── state_a<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ ├── state_b<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ └── state_c<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── cdft_md.bash<br> │ │ ├── cdft_md.inp<br> │ │ ├── dft-common-params.inc<br> │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ ├── frame.xyz<br> │ │ └── subsys.inc<br> │ └── 3_cdft_wH2O_sccs<br> │ ├── state_a<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ ├── state_b<br> │ │ ├── b_to_a.tar.gz<br> │ │ └── b_to_c.tar.gz<br> │ └── state_c<br> │ ├── framePrint.py<br> │ ├── input_files<br> │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── dft-common-params.inc<br> │ │ ├── energy_cdft.inp<br> │ │ ├── energy_mixed_cdft.inp<br> │ │ └── subsys.inc<br> │ └── README<br> ├── 52HNQ<br> │ ├── 1_md<br> │ │ ├── dft-common-params.inc<br> │ │ ├── hnq-md-pos-1.xyz<br> │ │ ├── md.inp<br> │ │ ├── pos.xyz<br> │ │ ├── submit.sh<br> │ │ └── subsys.inc<br> │ ├── 2_cdftaimd<br> │ │ ├── state_a<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ ├── state_b<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── cdft_md.bash<br> │ │ │ ├── cdft_md.inp<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ │ ├── frame.xyz<br> │ │ │ └── subsys.inc<br> │ │ └── state_c<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── cdft_md.bash<br> │ │ ├── cdft_md.inp<br> │ │ ├── dft-common-params.inc<br> │ │ ├── frame-cdft-pos-total.xyz.tar.gz<br> │ │ ├── frame.xyz<br> │ │ └── subsys.inc<br> │ └── 3_cdft_wH2O_sccs<br> │ ├── state_a<br> │ │ ├── framePrint.py<br> │ │ ├── input_files<br> │ │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ │ ├── becke_twoconstraints.inc<br> │ │ │ ├── dft-common-params.inc<br> │ │ │ ├── energy_cdft.inp<br> │ │ │ ├── energy_mixed_cdft.inp<br> │ │ │ └── subsys.inc<br> │ │ └── README<br> │ ├── state_b<br> │ │ ├── b_to_a.tar.gz<br> │ │ └── b_to_c.tar.gz<br> │ └── state_c<br> │ ├── framePrint.py<br> │ ├── input_files<br> │ │ ├── 1_energy_cdft_STATE1.bash<br> │ │ ├── 2_energy_cdft_STATE2.bash<br> │ │ ├── 3_energy_cdft_mixed.bash<br> │ │ ├── becke_twoconstraints.inc<br> │ │ ├── dft-common-params.inc<br> │ │ ├── energy_cdft.inp<br> │ │ ├── energy_mixed_cdft.inp<br> │ │ └── subsys.inc<br> │ └── README<br> └── 6_n_H2O_effect_mevi<br> ├── 08h2o<br> │ ├── framePrint.py<br> │ ├── README<br> │ ├── state_a.tar.gz<br> │ └── state_b.tar.gz<br> ├── 10h2o<br> │ ├── framePrint.py<br> │ ├── README<br> │ ├── state_a.tar.gz<br> │ └── state_b.tar.gz<br> ├── 20h2o<br> │ ├── framePrint.py<br> │ ├── README<br> │ ├── state_a.tar.gz<br> │ └── state_b.tar.gz<br> ├── 40h2o<br> │ ├── framePrint.py<br> │ ├── README<br> │ ├── state_a.tar.gz<br> │ └── state_b.tar.gz<br> ├── 97h2o<br> │ ├── framePrint.py<br> │ ├── README<br> │ ├── state_a.tar.gz<br> │ └── state_b.tar.gz<br> └── fig3.png</p> <p>74 directories, 301 files<br> -------------------------------------------------------<br> There are 6 directories: 1DMDQ, 2MeVi, 3OHVi, 4dBR5, 52HNQ, 6_n_H2O_effect_mevi. Except for "6_n_H2O_effect_mevi", we see 3 subdirectories named 1_md, 2_cdftaimd, and 3_cdft_wH2O_sccs. The input files and AIMD trajectories can be found in 1_md. While 2_cdftaimd contains the CDFT-AIMD input files and trajectories. To reproduce snapshots and input files of 3_cdft_wH2O_sccs, follow the README files in the subdirectories.</p> <p>The directory "6_n_H2O_effect_mevi" contains the number of water effects (Figure 3 of the publication). Users are guided by README files once again. </p>
Photoinduced Electron Transfer in Multicomponent Truxene- Quinoxaline Metal−Organic Frameworks
<ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>ARACAT_WP4_20200825_ULEI_03_60min_MUF77_OME_100K </strong>folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt formats.</li> </ul> </li> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>MUF7_OME – </strong>NC-MUF-7_dbc-dpq-OMe MOF, <strong>MUF7_OME – </strong>MUF-7_dbc-dpq-OMe MOF, <strong>MUF7_dpq – </strong>MUF-7_dbc-dpq MOF<strong> MUF77_paq – </strong>MUF-7_dbc-paq MOF</li> <li>_100K – measured at 10 K</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
Dataset to accompany publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes"
<p>This dataset accompanies the publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes" published in Nano Letters. The data can be used to reproduce the original plots in figures 2-4 in the main text and all original plots in figures S1-S13 in the supporting information. All files are in .xlsx and easily readable. <br>The abstract for the associated paper is as follows:<br>Exploring nonequilibrium hot carriers from plasmonic metal nanostructures is a dynamic field in optoelectronics, with applications including photochemical reactions for solar fuel generation. The hot carrier injection mechanism and the reaction rate are highly impacted by the metal/molecule interaction. However, determining the primary type of the reaction and thus the injection mechanism of hot carriers has remained elusive. In this work, we reveal an electron injection mechanism deviating from a purely outer-sphere process for the reduction of ferricyanide redox molecule in a gold/p-type gallium nitride (Au/p-GaN) photocathode system. Combining our experimental approach with ab-initio simulations, we discover that an efficient inner-sphere transfer of low-energy electrons leads to an enhancement in the photocathode device performance in the interband regime. These findings provide important mechanistic insights, showing our methodology as a powerful tool for analyzing and engineering hot-carrier-driven processes in plasmonic photocatalytic systems and optoelectronic devices.</p>
Excitation energy transfer and vibronic coherence in intact phycobilisomes — multidimensional electronic spectroscopy data set and MATLAB and Julia analysis code
<p>Data sets used in the article "Excitation energy transfer and vibronic coherence in intact phycobilisomes" by Sil et al. The phycobilisomes were isolated from the short-filament mutant (SF33) of <em>Fremyella diplosiphon</em> UTEX 481 (also known as <em>Tolypothrix</em> sp. PCC 7601). Multidimensional electronic spectroscopy was performed with 6.7 fs mid-visible pulses (520–700 nm) using a pump–probe optical configuration using adaptive pulse shaping techniques. In addition to the full set of two-dimensional spectra and analysis files generated using global and target modeling and analysis of coherences (3DES oscillation maps), we provide here a linear absorption spectrum with phycobiliprotein component analysis as well as a set of 2D excitation–emission fluorescence spectra of intact and broken phycobilisome preparations. </p> <p>Sil, S.; Tilluck, R. W.; Mohan TM, N.; Leslie, C. H.; Rose, J. B.; Domínguez-Martín, M. A.; Lou, W.; Kerfeld, C. A.; Beck, W. F. Excitation energy transfer and vibronic coherence in intact phycobilisomes. Nat. Chem. (2022), DOI: 10.1038/s41557-022-01026-8.</p> <p><a href="https://urldefense.com/v3/__https://www.nature.com/articles/s41557-022-01026-8__;!!HXCxUKc!yaVwTZFk8T-j3ROhygpOGW5Xy_E2wQvf-QgNGr9FZZbp4oNpfp_ZmhkdWYLdg2mKSDP8yYrNAZs$">https://www.nature.com/articles/s41557-022-01026-8</a></p> <p> </p> <p> </p>
Elastic electron scattering cross sections of ethanol in the energy range 30 eV to 800 eV: Differential (DCS), Integral (ICS) and Momentum Transfer Cross Sections (MTCS)
<h3>Cross section datasets on the elastic electron scattering of ethanol from our publication Eur. Phys. J. D 77, 52 (2023)</h3> <p>The elastic differential cross sections (DCS) are given in the energy range 30-800 eV in the full angular range: 30°-150° experimental, 0°-25° and 155°-180° extrapolated experimental data using the IAM-SCAR+I model.</p> <p>The integral elastic (ICS) and momentum transfer cross sections (MTCS) are given for energies 60-800 eV.</p> <p>Additional information can be found in the README.txt or the publication.</p>
Data from the manuscript: "Few-femtosecond electron transfer dynamics in photoionized donor-pi-acceptor molecules"
Open the record for dataset details and reuse information.
Electrochemical data plotted in A. Fasano, C. Guendon, A. Jacq-Bailly, A. Kpebe, J. Wozniak, C. Baffert, M. del Barrio, V. Fourmond, M. Brugna, C. Léger , « A chimeric NiFe hydrogenase heterodimer to assess the role of the electron transfer chain in tuning the enzyme's catalytic bias and oxygen tolerance », J. Am. Chem. Soc. 145, 36, 20021–20030 (2023). doi: 10.1021/jacs.3c06895
<p>Text file of all the electrochemical data shown in the following paper: A. Fasano, C. Guendon, A. Jacq-Bailly, A. Kpebe, J. Wozniak, C. Baffert, M. del Barrio, V. Fourmond, M. Brugna, C. Léger , « A chimeric NiFe hydrogenase heterodimer to assess the role of the electron transfer chain in tuning the enzyme's catalytic bias and oxygen tolerance », J. Am. Chem. Soc. 145, 36, 20021–20030 (2023). <a href="dx.doi.org/10.1021/jacs.3c06895" target="_blank" rel="noopener">doi: 10.1021/jacs.3c06895</a></p>
Data set: Modeling of Electron-Transfer Kinetics in Magnesium Electrolytes: Influence of the Solvent on the Battery Performance
<p>Dataset of the continuum simulations generated and used within the paper "<span>Modeling of Electron-Transfer Kinetics in Magnesium Electrolytes: Influence of the Solvent on the Battery Performance</span>", published in ChemSusChem (<span>2021</span><span>, </span><span>14 (21)</span><span>, 4820-4835, DOI: <span>10.1002/cssc.202101498</span></span>).</p> <p><span>The performance of rechargeable magnesium batteries is strongly dependent on the choice of electrolyte. The desolvation of multivalent cations usually goes along with high energy barriers, which can have a crucial impact on the plating reaction. This can lead to significantly higher overpotentials for magnesium deposition compared to magnesium dissolution. In this work we combine experimental measurements with DFT calculations and continuum modeling to analyze magnesium deposition in various solvents. Jointly, these methods provide a better understanding of the electrode reactions and especially the magnesium deposition mechanism. Thereby, a kinetic model for electrochemical reactions at metal electrodes is developed, which explicitly couples desolvation to electron transfer and, furthermore, qualitatively takes into account effects of the electrochemical double layer. The influence of different solvents on the battery performance is studied for<br>the state-of-the-art magnesium tetrakis(hexafluoroisopropyloxy)borate electrolyte salt. It becomes apparent that not necessarily a whole solvent molecule must be stripped from the</span> <span>solvated magnesium cation before the first reduction step can take place. For magnesium reduction it seems to be sufficient to have one coordination site available, so that the magnesium cation is able to get closer to the electrode surface. Thereby, the initial desolvation of the magnesium cation determines the deposition reaction for mono-, tri- and tetraglyme, whereas the influence of the desolvation on the plating reaction is minor for diglyme and<br>tetrahydrofuran. Overall, we can give a clear recommendation for diglyme to be applied as solvent in magnesium electrolytes</span>.<br><br></p>
Long-distance electron transfer along redox gradients in the subsurface
<p>Electron transfer (ET) is the fundamental process of life and element cycling. In the subsurface, the distance of ET determines its influencing area, normally as short as nanometers or micrometers. Here we provide direct evidence from column experiments that ET can last over 10 cm along the redox gradient in sediment columns, through a long-distance ET chain constituted by a series of short-distance electron hopping reactions involving with microbes and redox-active species like iron ions (and/or minerals) and natural organic matters. Microbial processes contribute largely under biologically active conditions, while chemical processes are important under extremely acidic/alkaline and cold conditions. Microbial and chemical processes synergistically mediate the long-distance ET process, with an estimated electron flux of 6.73 μmol e<sup>-</sup>/cm<sup>2</sup> per day. This long-distance ET represents an overlooked but important background process influencing subsurface biogeochemical processes and remediation activities.</p>
Ion-Pair Dynamics upon Photoinduced Electron Transfer Monitored by Pump-Pump-Probe Spectroscopy
<p>The files contain all the data that are shown in the figures of the main text and of the supporting information of the article:</p> <p>Beckwith, J.; Lang, B.; Grilj, J.; Vauthey, E. Ion-Pair Dynamics upon Photoinduced Electron Transfer Monitored by Pump-Pump-Probe Spectroscopy. J. Phys. Chem. Lett. 10 (2019), 10.1021/acs.jpclett.9b01431</p>
Trapped-Ion Quantum Simulation of Electron Transfer Models with Tunable Dissipation
<p>This package includes the data, the theory, and the source code to plot both in Mathematica to reproduce the figures of the paper.</p>
The kinetics and energetics of electron transfer to dimer radical cations
<p>Data files associated with publication titled "The kinetics and energetics of electron transfer to dimer radical cations" <em>J. Phys. Chem. B</em> 2023, 127, 13, 2881–2886</p>
Zinc(II) Complexes with Triplet Charge-Transfer Excited States Enabling Energy-Transfer Catalysis, Photoinduced Electron Transfer, and Upconversion
<p>Raw data to the graphs of the publication</p>
Cryogenic electron ptychographic single particle analysis with wide bandwidth information transfer
<p>Advances in cryogenic transmission electron microscopy have revolutionised the determination of many macromolecular structures at atomic or nearatomic resolution. This method is based on conventional defocused phase contrast imaging. However, it has limitations of weaker contrast for small biological molecules embedded in vitreous ice, in comparison with cryo-ptychography, which shows increased contrast. Here we report a single-particle analysis based on the use of ptychographic reconstruction data, demonstrating that three dimensional reconstructions with a wide information transfer bandwidth can be recovered by Fourier domain synthesis. Our work suggests future applications in otherwise challenging single particle analyses, including small macromolecules and heterogeneous or flexible particles. In addition structure determination in situ within cells without the requirement for protein purification and expression may be possible.</p>
Single-electron-charge transfer into putative Majorana and trivial modes in individual vortices
<p>Supporting data for Jian-Feng Ge, et al. “Single-electron-charge transfer into putative Majorana and trivial modes in individual vortices”.</p> <p>The following data files are used for the following figures.</p> <p> Fig. 1 a Illustration figure, no data used<br> b NbSe2_04_220202_0184.txt<br> c FeTeSe_08_210604_0614.txt</p> <p> Fig. 2 a NbSe2_04_220202_0133_raw.txt<br> b NbSe2_04_220202_dIdV_0033_0037_raw.txt<br> c NbSe2_04_220202_0133_raw.txt<br> d NbSe2_04_220202_0133_deconv.txt<br> e NbSe2_04_220202_dIdV_0033_0037_deconv.txt<br> f NbSe2_04_220202_0133_deconv.txt</p> <p> Fig. 3 a FeTeSe_08_210604_0188_raw.txt<br> b FeTeSe_08_210604_dIdV_0121_0122_raw.txt<br> c FeTeSe_08_210604_0188_raw.txt<br> d FeTeSe_08_210604_0188_deconv.txt<br> e FeTeSe_08_210604_dIdV_0121_0122_deconv.txt<br> f FeTeSe_08_210604_0188_deconv.txt</p> <p> Fig. 4 a 220210_NbSe2_04_2.3K_spectrum_06_08.txt<br> b qeff_NbSe2.txt<br> c 210622_FeTeSe08_2.3K_spectrum_06_04.txt<br> d qeff_FeTeSe.txt</p> <p>Supplementary Fig. 1 a PbtipPb111.txt<br> b PbtipAu111.txt<br> c Pbtipfits.txt</p> <p>Supplementary Fig. 2 a Illustration figure, no data used<br> b linecut_raw.txt<br> c linecut_deconv.txt<br> d peak_pos.txt<br> e peak_amp.txt</p> <p>Supplementary Fig. 3 a NbSe2_04_220202_0098_raw.txt<br> b NbSe2_04_220202_0098_c_33_31_a_63_0_raw.txt<br> c NbSe2_04_220202_0098_raw.txt<br> d 220210_NbSe2_04_2.3K_spectrum_04_03.txt<br> e NbSe2_04_220202_0098_deconv.txt<br> f NbSe2_04_220202_0098_c_33_31_a_63_0_deconv.txt<br> g NbSe2_04_220202_0098_deconv.txt<br> h 220210_NbSe2_04_2.3K_spectrum_04_03_qeff.txt<br> i NbSe2_04_220202_0172_raw.txt<br> j NbSe2_04_220202_0098_c_33_35_a_0_63_raw.txt<br> k NbSe2_04_220202_0172_raw.txt <br> l 220210_NbSe2_04_2.3K_spectrum_10_11.txt<br> m NbSe2_04_220202_0172_deconv.txt<br> n NbSe2_04_220202_0098_c_33_35_a_0_63_deconv.txt<br> o NbSe2_04_220202_0172_deconv.txt<br> p 220210_NbSe2_04_2.3K_spectrum_10_11_qeff.txt</p> <p>Supplementary Fig. 4 a FeTeSe_08_210604_0355_raw.txt<br> b FeTeSe_08_210604_0355_c_26_30_a_63_0_raw.txt<br> c FeTeSe_08_210604_0355_raw.txt<br> d 210622_FeTeSe08_2.3K_spectrum_15_14.txt<br> e FeTeSe_08_210604_0355_deconv.txt<br> f FeTeSe_08_210604_0355_c_26_30_a_63_0_deconv.txt<br> g FeTeSe_08_210604_0355_deconv.txt<br> h 210622_FeTeSe08_2.3K_spectrum_15_14_qeff.txt<br> i FeTeSe_08_210604_0463_raw.txt<br> j FeTeSe_08_210604_0463_c_26_27_a_0_0_raw.txt<br> k FeTeSe_08_210604_0463_raw.txt <br> l 210622_FeTeSe08_2.3K_spectrum_27_24.txt<br> m FeTeSe_08_210604_0463_deconv.txt<br> n FeTeSe_08_210604_0463_c_26_27_a_0_0_deconv.txt<br> o FeTeSe_08_210604_0463_deconv.txt<br> p 210622_FeTeSe08_2.3K_spectrum_27_24_qeff.txt</p> <p>Supplementary Fig. 5 a 220210_NbSe2_04_2.3K_spectrum_06_08_qeff.txt<br> b 210622_FeTeSe08_2.3K_spectrum_06_04_qeff.txt</p> <p>Supplementary Fig. 6 a FeSeTe_07_180716_0309_topo.txt<br> b FeSeTe_07_180716_0309_ring.txt<br> c FeTeSe_08_210604_0355_raw.txt<br> d 180809_FeSeTe7_ring_2.5MOhm_3K_map_04.txt<br> e 180907_FeSeTe7_Pbtip_10MOhm_3K_spectra_24.txt<br> f 180907_FeSeTe7_Pbtip_10MOhm_3K_spectra_24_qeff.txt<br> <br> Supplementary Fig. 7 qeff_vs_qpcontrib.py</p> <p>Supplementary Fig. 8 a FeTeSe_10_211111_didv_FB.txt<br> b FeTeSe_10_211111_didv_FB_ratio_sim.txt</p> <p>Supplementary Fig. 9 220810_NbSe2_06_2.3K_spectrum_01_19.txt</p> <p>Supplementary Fig. 10 a NbSe2_05_220503_dIdV_0017.txt<br> b 220510_NbSe2_05_2.3K_spectrum_01.txt</p>
Doping of molecular semiconductors through proton-coupled electron transfer
<p>Doping of molecular semiconductors through proton-coupled electron transfer was conducted. Doping levels, electronic properties, and thin film structures of doped polymeric semiconductors were evaluated through conductivity, UV-Vis-NIR absorption, photoelectron yield, x-ray photoelectron, and x-ray diffraction measurements, where proton-coupled electron transfer reaction enable precise control of doping levels depending on pH of doping solutions under ambient conditions.</p>
ScienceDex guides
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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.