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8 results for “electrochemical redox”
Advanced Redox Electrochemical Capacitor Diode (CAPode) based on Parkerite (Ni3Bi2S2) with High Rectification Ratio for Iontronic Applications
<p>Recently, CAPodes were introduced as a new type of capacitive diode analogues. This device realizes unidirectional charging of ultracapacitors based on ion sieving mechanisms. Here, we present a new redox CAPode system in which hydroxide ions react with nickel bismuth sulfide on nickel foam as a battery-like electrode. This redox reaction leads to a high capacitance in a specific polarization window. However, for reversed bias this Faradaic electrode becomes inactive as it does not react with potassium cations, resulting efficient blocking. By adapting counter electrode materials, mass loading, utilized substrates, and electrolyte concentrations a very high rectification ratio (<em>R<sub>I</sub></em> = 37 and <em>R<sub>II</sub></em> = 0.96 at 10 mV s<sup>-1</sup>) was achieved, significantly surpassing the performance of other reported redox-type CAPodes. Moreover, this system shows an outstanding long-term stability of a rectification retention of 90% for <em>R<sub>II</sub></em> over 5000 repolarization cycles. Additionally, operando electrochemical measurements provide deep insights into the charge/discharge mechanism leading to a rationalization of the proposed concept. The integrated device, tested in logic gate circuits such as AND and OR gates, shows prospective results in ionologic applications.</p>
Electrochemical data shown in A. Fasano, A. Jacq-Bailly, J. Wozniak, V. Fourmond, and C. Léger, « Catalytic Bias and Redox-Driven Inactivation of the Group B FeFe Hydrogenase CpIII », ACS Catalysis (2024). doi: 10.1021/acscatal.4c01352
<p>Text file of all the electrochemical data shown in the following paper: A. Fasano, A. Jacq-Bailly, J. Wozniak, V. Fourmond, and C. Léger, « Catalytic Bias and Redox-Driven Inactivation of the Group B FeFe Hydrogenase CpIII », ACS Catalysis (2024). <a href="dx.doi.org/10.1021/acscatal.4c01352" target="_blank" rel="noopener">doi: 10.1021/acscatal.4c01352</a></p>
Electrochemical Biosensing of Tuberculosis using CRISPR-Cas12a and redox-probe modified oligonucleotide
<p>We have submitted the manuscript in HELIYON </p> <p><span>Manuscript. Number: HELIYON-D-24-20798R3 </span></p> <p>Title: An electrochemical biosensor for the detection of tuberculosis specific DNA with CRISPR-Cas12a and redox-probe modified oligonucleotide. </p> <p>The dataset used in that study is available here. </p>
Operando magnetic resonance imaging for mapping of temperature and redox species in thermo-electrochemical cells
<p>Raw data for our publication "Operando magnetic resonance imaging for mapping of temperature and redox species in thermo-electrochemical cells", including imaging files (Paravision), ASCII, MATLAB and EC Lab data files organised corresponding to each figure in the paper and supplementary information.</p>
Videos of electrochemiluminescence response for paper "Direct visualization of reactant transport in forced convection electrochemical cells and its application to Redox Flow Batteries"
<p>Videos showing the real time electrochemiluminescent light production in a serpentine flow field of a redox flow battery type system. The two videos show the difference when only an ITO electrode is used compared to when an ITO and carbon paper electrode is used.</p>
Data file for paper: Javier Rubio-Garcia; Anthony R J Kucernak, and Alexandra Charleson, "Direct visualization of reactant transport in forced convection electrochemical cells and its application to Redox Flow Batteries, Electrochemistry Communications, 2018
<p>Excel Data file containing the data presented in the figures of the paper:</p> <p>Javier Rubio-Garcia; Anthony R J Kucernak, and Alexandra Charleson, "Direct visualization of reactant transport in forced convection electrochemical cells and its application to Redox Flow Batteries</p> <p>Electrochemistry Communications, 2018,</p> <p>DOI:10.1016/j.elecom.2018.07.002</p> <p>Please cite the above reference if you wish to use this data</p>
Dataset for the paper "Electrochemical and Spectroscopic Characterisation of Organic Molecules with High Positive Redox Potentials for Energy Storage in Aqueous Flow Cells", DOI:10.1039/d4ya00366g
<table> <tbody> <tr> <td>The data in this spreadsheet was used to produce the figures in the paper</td> </tr> <tr> <td>Authors:</td> <td>Christopher G. Cannon, Peter A. A. Klusener, Nigel P. Brandon, and Anthony R. J. Kucernak</td> </tr> <tr> <td>Title:</td> <td>Electrochemical and Spectroscopic Characterisation of Organic Molecules with High Positive Redox Potentials for Energy Storage in Aqueous Flow Cells</td> </tr> <tr> <td>Journal:</td> <td>Energy Advances</td> </tr> <tr> <td>DOI:</td> <td>DOI:10.1039/d4ya00366g</td> </tr> <tr> <td>Please cite the above reference if you wish to use this data</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>DOI of data:</td> <td><span>10.5281/zenodo.13712672</span></td> </tr> </tbody> </table>
Density Functional Theory and Machine Learning for Electrochemical Square-Scheme Prediction: An Application to Quinone-type Molecules Relevant to Redox Flow Batteries
<p>The uploaded data contains (i) "<strong>01_Data</strong>" optimized molecular structure in XYZ format and the primary attributes and SMILES, (ii) "<strong>02_Datasets</strong>" datasets used in the publication, and (iv) "<strong>03_pynb_script</strong>" a Jupyter-Notebook. The <strong>01_Data </strong>directory contains more than 8000 subdirectories. Each is for a molecule that undergoes a two-proton two-electron transfer reaction. In each subdirectory, one finds the following files:</p> <p>(1) directories named corresponding to the ones in Figure 1 of the paper. Inside each, there are geometries and properties in XYZ and CSV format, respectively.</p> <p>(2)<strong> "freeEnergy.dat" </strong>contains the free energy of different states.</p> <p>(3) <strong>"schemesquare.dat" </strong>has the parameters of the electrochemical scheme of square representation.</p> <p>├── A<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── A1-<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── A2-<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH1+<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH1-<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH2<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH21+<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── AH22+<br> │ ├── info.csv<br> │ └── pos.xyz<br> ├── <strong>freeEnergy.dat</strong><br> └── <strong>schemesquare.dat</strong><br> ******************************************************<br> The new version (v1.1) contains some updates around:<br> (i) The DFT calculations workflow in a folder called "<strong>04_workflow_of_DFT</strong>"</p> <p> The Gaussian input files have been explained in the "README" file.</p> <p>(ii) The Python scripts for data extraction have been added and can be found in "<strong>05_how_to_extracted_data</strong>"</p> <p>(iii) We explained how to compute the Purbaix diagram in great detail "<strong>06_how_to_compute_Pourbaix_diagram</strong>/"</p> <p>All these changes/improvements were applied/made following the Referee of Digital Discovery Journal. Here, we would like to thank him/her.</p>
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