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103 results for “metal–organic framework”
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>
Characterization Data for the Manuscript: "Unraveling Metal Effects on CO2 Uptake in Pyrene-based Metal-Organic Frameworks through Integrated Lab and Computer Experiments"
<p>This entry contains characterization data for the manuscript "Unraveling Metal Effects on CO2 Uptake in Pyrene-based Metal-Organic Frameworks through Integrated Lab and Computer Experiments".</p>
Dataset for "Fine-Tuning A Robust Metal–Organic Framework Towards Enhanced Clean Energy Gas Storage"
<p>Dataset covering the DFT simulations performed for the journal article "Fine-Tuning A Robust Metal–Organic Framework Towards Enhanced Clean Energy Gas Storage"</p>
Raw data files for the manuscript entitled "Hybridization of Synthetic Humins with a Metal–Organic Framework for Precious Metal Recovery and Reuse"
<p>Datasets for the data presented in the manuscript entitled "Hybridization of Synthetic Humins with a Metal–Organic Framework for Precious Metal Recovery and Reuse" published in ACS Applied Materials and Interfaces.</p>
Dataset for "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"
<p>Dataset belonging to publication "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"</p>
Dataset for "An air-stable Cu(I) metal-organic framework for hydrogen storage"
<p>Dataset for "An air-stable Cu(I) metal-organic framework for hydrogen storage"</p> <p>Raw data set of the electronic structure calculations and inputs for the GCMC calculations relating to above publication.</p>
Heterogenized Molecular Rhodium Phosphine Catalysts within Metal–Organic Frameworks for Alkene Hydroformylation
<p>Supplementary information for associated publication</p>
Upcycling a Plastic Cup: One-Pot Synthesis of Lactate Containing Metal Organic Frameworks from Polylactic Acid
<p>Data supporting publication: <strong>Upcycling a plastic cup: one-pot synthesis of lactate containing metal organic frameworks from polylactic acid</strong>, Benjamin Slater, So-On Wong, Andrew Duckworth, Andrew J. P. White, Matthew R. Hill and Bradley P. Ladewig, Chen. Commun. (2019), DOI: <a href="https://doi.org/10.1039/c9cc02861g">10.1039/c9cc02861g</a>. </p> <p>Includes raw data for XRD spectra for all materials, CIF file and checkCIF file.</p> <p>v2 includes additional high-resolution photos and diagrams supporting the publication</p>
Experimental evidence for the incorporation of two metals at equivalent lattice positions in mixed metal organic frameworks. Dataset related to publication. Version: 1
<p>Experimental evidence for the incorporation of two metals at equivalent lattice positions in mixed metal organic frameworks. Dataset related to publication. Version: 1</p>
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>
Polymer-assisted modification of metal-organic framework MIL-96 (Al): influence on particle size, crystal morphology and perfluorooctanoic acid (PFOA) removal
<p>Dataset supporting publication.</p> <p><strong>Polymer-assisted modification of metal-organic framework MIL-96 (Al): influence of HPAM concentration on particle size, crystal morphology and removal of harmful environmental pollutant PFOA</strong></p> <p>Chemosphere, <a href="https://doi.org/10.1016/j.chemosphere.2020.128072">https://doi.org/10.1016/j.chemosphere.2020.128072</a></p> <p>Preprint available from ChemRxiv, <a href="https://doi.org/10.26434/chemrxiv.12262010.v2">https://doi.org/10.26434/chemrxiv.12262010.v2</a></p> <p><strong>Abstract</strong></p> <p>A new synthesis method was developed to prepare an aluminum-based metal organic framework (MIL-96) with a larger particle size and different crystal habits. A low cost and water-soluble polymer, hydrolyzed polyacrylamide (HPAM), was added in varying quantities into the synthesis reaction to achieve >200% particle size enlargement with controlled crystal morphology. The modified adsorbent, MIL-96-RHPAM2, was systematically characterized by SEM, XRD, FTIR, BET and TGA-MS. Using activated carbon (AC) as a reference adsorbent, the effectiveness of MIL-96-RHPAM2 for perfluorooctanoic acid (PFOA) removal from water was examined. The study confirms stable morphology of hydrated MIL-96-RHPAM2 particles as well as a superior PFOA adsorption capacity (340 mg/g) despite its lower surface area, relative to standard MIL-96. MIL-96-RHPAM2 suffers from slow adsorption kinetics as the modification significantly blocks pore access. The strong adsorption of PFOA by MIL-96-RHPAM2 was associated with the formation of electrostatic bonds between the anionic carboxylate of PFOA and the amine functionality present in the HPAM backbone. Thus, the strongly held PFOA molecules in the pores of MIL-96-RHPAM2 were not easily desorbed even after eluted with a high ionic strength solvent (500 mM NaCl). Nevertheless, this simple HPAM addition strategy can still chart promising pathways to impart judicious control over adsorbent particle size and crystal shapes while the introduction of amine functionality onto the surface chemistry is simultaneously useful for enhanced PFOA removal from contaminated aqueous systems.</p>
Long-Term Stable Metal Organic Framework (MOF) Based Mixed Matrix Membranes for Ultrafiltration
<p><strong>Preprint available here:</strong> Al-shaeli, Muayad; Smith, Stefan J. D.; Jiang, Shanxue; Wang, Huanting; Zhang, Kaisong; Ladewig, Bradley P. (2020): Long-Term Stable Metal Organic Framework (MOF) Based Mixed Matrix Membranes for Ultrafiltration. ChemRxiv. Preprint. <a href="https://doi.org/10.26434/chemrxiv.13399367.v1">https://doi.org/10.26434/chemrxiv.13399367.v1</a></p> <p>Published manuscript: Muayad Al-Shaeli, Stefan J.D. Smith, Shanxue Jiang, Huanting Wang, Kaisong Zhang, Bradley P. Ladewig,<br> Long-term stable metal organic framework (MOF) based mixed matrix membranes for ultrafiltration,<br> Journal of Membrane Science, 2021, 119339, <a href="https://doi.org/10.1016/j.memsci.2021.119339">https://doi.org/10.1016/j.memsci.2021.119339</a></p> <p><strong>Abstract</strong></p> <p>In this study, novel mixed matrix membranes (MMMs) were synthesized by adding metal organic frameworks (MOFs) (UiO-66 and UiO-66-NH<sub>2</sub>) to pristine and sulfonated polyethersulfone (PES). The differing synthetic method resulting in MMM where additives were grafted to the matrix polymer, or formed a natural interface, allowing the impact of these MMM features to be investigated. The composite membranes were characterised by FTIR, PXRD, water contact angle, porosity, pore size, etc. Membrane performance was investigated by water permeation flux, flux recovery ratio, fouling resistance and anti-fouling performance. The stability test was also conducted for all the prepared mixed matrix membranes. A higher reduction in the water contact angle was observed after adding both MOFs to the PES and sulfonated PES membranes compared to pristine PES membranes. An enhancement in membrane performance was observed by embedding the MOFs into PES membrane matrix, with flux increased remarkably (565 LMH for PES+UiO-66-NH<sub>2</sub> at 5% loading and 487.1 LMH for SPES-UiO-66(10% binding) while the BSA rejection was still kept at a high level. By adding the MOFs into PES matrix, the flux recovery ratio was increased greatly (more than 99% for most mixed matrix membranes). The mixed matrix membranes showed higher resistance to protein adsorption compared to pristine PES membranes. After immersing the membranes in water for 3 months, 6 months and 12 months, both MOFs were stable and retained their structure. This study indicates that UiO-66 and UiO-66-NH<sub>2</sub> are great candidates for designing long-term stable mixed matrix membranes (MMMs) for applications in water and wastewater treatment.</p>
Data from: Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal–organic framework
<p>In nature, nonheme iron-containing enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although scientists have long sought to mimic this reactivity, the enzyme-like activation of dioxygen to form high-spin iron(IV)=O species remains an unrealized goal in synthetic chemistry. Here, we report a metal–organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with dioxygen at low temperatures to form high-spin iron(IV)=O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kβ x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of dioxygen, the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.</p>
Solid-state $^{13}$C-NMR spectroscopic determination of sidechain mobilities in zirconium-based metal-organic frameworks
<p>This Dataset contains the raw data contained in the figures of our journal article in <i>Magnetic Resonance</i>: <a href="https://doi.org/10.5194/mr-2023-13">https://doi.org/10.5194/mr-2023-13</a>.</p>
Room-temperature quantum coherence of entangled multiexcitons in a metal-organic framework
<p><span>Singlet fission (SF) can generate an exchange-coupled quintet triplet pair state</span><span> </span><sup><span>5</span></sup><span>TT, which could lead to the realization of quantum computing and quantum sensing using entangled multiple qubits even at room temperature. However, the observation of the quantum coherence of <sup>5</sup>TT has been limited to cryogenic temperatures, and the fundamental question is what kind of material design will enable its room-temperature quantum coherence. Here we show that the quantum coherence of SF-derived <sup>5</sup>TT in a chromophore-integrated metal-organic framework (MOF) can be over hundred nanoseconds at room temperature. The subtle motion of the chromophores in ordered domains within the MOF leads to the enough fluctuation of the exchange interaction necessary for <sup>5</sup>TT generation, but at the same time does not cause severe <sup>5</sup>TT decoherence. Furthermore, the phase and amplitude of quantum beating can be controlled by molecular motion, opening the way to room-temperature molecular quantum computing based on multiple quantum gate control.</span></p>
Engineering Machine Learning features to predict adsorption of carbon dioxide and nitrogen in metal-organic frameworks
<p>This repository contains CIF files for metal-organic frameworks and Grand canonical Monte Carlo (GCMC) simulation results for the article <em>Engineering Machine Learning features to predict adsorption of carbon dioxide and nitrogen in metal-organic frameworks</em> by Zijun Deng and Lev Sarkisov.</p>
Raw data files for "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" manuscript
<p>Raw data files for a manuscript "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" published in Chemical Science. <a href="https://doi.org/10.1039/D2SC01041K">https://doi.org/10.1039/D2SC01041K</a></p> <p>The files are organized by manuscript figure names and are in a simple text or CSV format. The headers contain the necessary information such as column designations, units, etc.</p> <p> </p> <p> </p> <p> </p>
Graph Neural Network for Metal Organic Framework Potential Energy Approximation
<p>Data set consists of 50,000 different configurations for the Metal Organic Framework (MOF) FIGXAU. Was generated by randomly modifying the positions of the atoms and doing an SCF relaxation on each configuration.</p>
Supplementary Data for "Exploring the Chemical Space of Metal–Organic Frameworks with rht Topology for High Capacity Hydrogen Storage"
<p>This dataset includes optimization and simulation inputs, optimized structures, building blocks, computed hydrogen uptakes and textural properties of the metal–organic frameworks that correspond with work in "Exploring the Chemical Space of Metal–Organic Frameworks with rht Topology for High Capacity Hydrogen Storage" (DOI: 10.1021/acs.jpcc.4c00638).</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>
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