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6 results for “Metal-Organic Framework (MOF)”
Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset
<p>High-throughput computational screening of metal-organic frameworks rely on the availability of<strong><em> </em></strong>atomic coordinate files which can be used as input to simulation software packages. CoRE MOF Datasets are derived from Cambridge Structural Database (CSD) and also from the World Wide Web.</p> <p><strong>Nomenclatures:</strong></p> <p>LCD (Largest Cavity Diameter), PLD (pore limiting diameter), LFPD (Largest Sphere along the Free Path), ASA (Accessible Surface Area), NASA (Non-accessible surface area), AV_VF (Void Fraction, 0 - 1), NAV (Non Accessible Volume)</p> <p><strong>Dataset Directory Organization</strong></p> <p>CoREMOF2019_public_v2.zip: dataset with CR and NCR classifications</p> <p>1. CR dataset: computaion-ready (<em>N</em> = 10,367)</p> <ul> <li> ASR: all solvent removed (<em>N</em> = 6,603)</li> <li> FSR: free solvent removed (<em>N</em> = 3,764)</li> </ul> <p>2. NCR: not computaion-ready (<em>N</em> = 8,714)</p> <ul> <li> ASR: all solvent removed (<em>N</em> = 5,417) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (<em>N</em> = 2,597)</li> <li>Chen_Manz: NCR determined by Chen_Manz (<em>N</em> = 958)</li> <li>mofchecker: NCR determined by mofchecker (<em>N</em> = 1,859)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (<em>N</em> = 3)</li> </ul> </li> <li> FSR: free solvent removed (<em>N</em> = 3,297) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (<em>N</em> = 1,646)</li> <li>Chen_Manz: NCR determined by Chen_Manz (<em>N</em> = 463)</li> <li>mofchecker: NCR determined by mofchecker (<em>N</em> = 1,185)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (<em>N</em> = 3)</li> </ul> </li> </ul> <p>2. NCR_detail.xlsx: details of all structures by mofchecker and Chen_Manz for each NCR cases</p> <p><strong>November, 24 2024</strong></p> <ul> <li>Re-ordering of folders such that top level directory is based on computation-ready and not-computation ready classification.</li> </ul> <p><strong>November, 13 2024</strong></p> <ul> <li>Classification of Computation-Ready (CR) and Not Computation-Ready (NCR) Structures based on <a href="https://pubs.rsc.org/en/content/articlelanding/2020/ra/d0ra02498h">Chen & Manz</a> (RSC Adv., 2020,10, <a>26944-26951</a>) and <a href="https://github.com/kjappelbaum/mofchecker">MOFChecker </a>program by <a href="https://github.com/kjappelbaum">Kevin M. Jablonka</a>)</li> <li>ML-predicted DDEC6 partial atomic charges based on <a href="https://github.com/mtap-research/PACMAN-charge">PACMAN</a></li> </ul> <p><strong>Acknowledgements</strong></p> <ul> <li>This reserach is supported by the National Research Foundation of Korea (No. 2016R1D1A1B3934484, NRF-2020R1C1C1010373, RS-2024-00449431)</li> <li>This research is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-17ER16362 (Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulations, Machine Learning, and Experiment)</li> </ul>
DFT-optimized Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2014
<p>There are two folders inside the zipped file:</p> <p>- 838 structures (without DDEC partial atomic charges)</p> <p>- 502 structures (with DDEC partial atomic charges)<br> </p> <p> </p>
Predicting Partial Atomic Charges in Metal-Organic Frameworks: An Extension to Ionic MOFs
<p>This dataset is associated with the study <em>"Predicting Partial Atomic Charges in Metal-Organic Frameworks: An Extension to Ionic MOFs."</em> Detailed instructions for installation, usage, and example scripts for the PACMOF2 models can be found on our GitHub <a href="https://github.com/snurr-group/pacmof2">repository</a>.</p> <div> <div> <div> <div> <p>The dataset includes the following files:</p> <ul> <li><strong>DDEC6_data.zip</strong>: Contains the crystal structures of MOFs with DDEC6 partial charges.</li> <li><strong>PACMOF2_prediction_cifs.zip</strong>: Contains the crystal structures of MOFs with DDEC6 charges as predicted by the PACMOF2 models.</li> <li><strong>PACMOF2_ionic.gz</strong>: A machine learning model designed to predict charges in ionic MOFs with a non-zero formal charge.</li> <li><strong>PACMOF2_neutral.gz</strong>: A machine learning model designed to predict charges in neutral MOFs.</li> </ul> <p>For more details about each file, please refer to the accompanying <code>README.md</code> file.<br><br><br>Updates: <br>- September 2024 (version 1.0.1): Added README.md file.</p> </div> </div> </div> </div>
Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2014 DDEC Database
<p>~2,900 structures CoRE MOF 2014 structures with DDEC partial atomic charges. </p> <p> </p>
Precision-Engineered Metal-Organic Frameworks (PE-MOFs)
<p>This Zenodo record hosts the computationally predicted structures of 94,823 Precision-Engineered Metal-Organic Frameworks (PE-MOFs), designed using a fine-tuned Reverse Topological Approach (RTA). The structures are provided as part of a large-scale effort to systematically explore the vast combinatorial design space of metal and organic building units (BUs), pairing them based on geometric signatures and topological compatibility.</p> <p>These structures are optimized and curated for applications such as post-combustion CO2 capture.</p> <p>In this repository, you will find:</p> <p>Fully optimized structures of PE-MOFs: cif files provided in standard formats compatible with molecular simulation tools for further analysis and exploration.<br>Note: This Zenodo record only provides the computational structures. For the accompanying code, tools, and data used to generate these structures, please visit the GitHub repository here. https://github.com/xiaoyu961031/Fine-tuned-RTA</p> <p>If you use this dataset in your work, please cite our related publication:<br>Wu, X., Jiang, J. (2024). Precision-engineered metal-organic frameworks: Fine-tuning reverse topological structure prediction and design. Chemical Science, 2024, DOI: 10.1039/D4SC05616G </p>
Pore-engineered metal-organic frameworks (MOFs) for efficient delivery of diverse functional macromolecular cargoes
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