Skip to main content
zenodoopen

Solvation Procedures Assessment of Borohydride Reduction of Carbon Dioxide

<p>Pathways, structures, gas-phase and solvation energies of aqueous borohydride reduction of carbon dioxide.</p> <p><strong>Contents</strong></p> <p><strong>data</strong></p> <p>Computational chemistry output files for gas-phase electronic energies, solvation energies, and QM/MM MD simulations are provided. They are organized by the method used to seek the reaction pathway.</p> <ul> <li>neb: contains computations involved with the g-SSNEB pathway from <a href="https://doi.org/10.1021/acs.jpcb.6b07606">Groenenboom and Keith</a>.</li> <li>gsm: contains computations either in preparation or execution of <a href="https://github.com/ZimmermanGroup/molecularGSM">growing string method (GSM)</a>&nbsp;calculations. The lego module of <a href="https://www.zhjun-sci.com/software-abcluster-download.php">ABCluster</a>&nbsp;was used to generate candidate starting structures.</li> <li>other: contains miscellaneous computations for additional analyses.</li> <li>scripts: contains all Python code used to generate&nbsp;<a href="https://github.com/OpenChemistry/chemicaljson">Chemical JSON</a>&nbsp;and CSV files.</li> <li>qmmm: contains <a href="https://www.msg.chem.iastate.edu/gamess/">GAMESS</a>&nbsp;QM/MM MD trajectories and <a href="http://membrane.urmc.rochester.edu/?page_id=126">WHAM</a>&nbsp;analyses.</li> </ul> <p>Note: the QM/MM MD data is in the zip with the &quot;qmmm&quot; suffix. Everything else is in the other zip.</p> <p><strong>figures</strong></p> <p>Contains Python scripts and figures made with matplotlib. Python files are named according to the data they use; for example, figure-neb.py&nbsp;is the code for figures that plot the various g-SSNEB pathways. Figures are organized according to where they appear: directly in the article (article/) or as supplemental information (si/).</p> <p><strong>structures</strong></p> <p>XYZ files relevant to this study organized by the chain-of-states method.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
8