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73 results for “zeolites”
Michael Deem's PCOD database of Predicted Zeolitic Structures
<p>These are the SLC 'good' sections of version 2.1 of <a href="https://mwdeem.org">Michael Deem</a>'s database of predicted zeolite structures. Version 1 was published in M. W. Deem, R. Pophale, P. A. Cheeseman, and D. J. Earl, ``Computational Discovery of New Zeolite-Like Materials,'' with cover image, <em>J. Phys. Chem. C</em> <strong>113</strong> (2009) 21353-21360. Version 2 was published in R. Pophale, P. A. Cheeseman, and M. W. Deem, "A Database of New Zeolite-Like Materials," <em>Phys. Chem. Chem. Phys.</em> <strong>13</strong> (2011) 12407-12412:</p> <p>"We here describe a database of computationally predicted zeolite-like materials. These crystals were discovered by a Monte Carlo search for zeolite-like materials. Positions of Si atoms as well as unit cell, space group, density, and number of crystallographically unique atoms were explored in the construction of this database. The database contains over 2.6 M unique structures. Roughly 15% of these are within +30 kJ mol<sup>−1</sup>Si of α-quartz, the band in which most of the known zeolites lie. These structures have topological, geometrical, and diffraction characteristics that are similar to those of known zeolites. The database is the result of refinement by two interatomic potentials that both satisfy the Pauli exclusion principle." <a href="https://doi.org/10.1039/C0CP02255A">https://doi.org/10.1039/C0CP02255A</a></p> <p>These files are also available at <a href="https://mwdeem.org/PCOD">https://mwdeem.org/PCOD</a></p> <p> </p>
Dataset: Dendritic nanoarchitecture imparts ZSM-5 zeolite with enhanced adsorption and catalytic performance in energy applications
<p>The development of zeolites possessing dendritic features represents a great opportunity for the design of novel materials with applications in a large variety of fields and, in particular, in the energy sector to afford its transition towards a low carbon system. In the current work, ZSM-5 zeolite showing a dendritic 3D nanoarchitecture has been synthesized by the functionalization of protozeolitic nanounits with an amphiphilic organosilane, which provokes the branched aggregative growth of zeolite embryos.<br> Dendritic ZSM-5 exhibits outstanding accessibility arising from a highly interconnected network of radially-oriented mesopores (3 – 10 nm) and large cavities (20 – 80 nm), which add to the zeolitic micropores, thus showing a well-defined trimodal pore size distribution. These singular features provide dendritic ZSM-5 with sharply enhanced performance in comparison with nano- and hierarchical reference materials when tested in a number of energy related applications, such as VOCs (toluene) adsorption (improved capacity), plastics (low-density polyethylene) catalytic cracking (boosted activity) and hydrogen production by methane catalytic decomposition (higher activity and deactivation resistance).</p>
Proton dissociation and delocalization under stepwise hydration of zeolite HZSM-5
<p>This is a data archive for the publication: </p><p>"Proton dissociation and delocalization under stepwise hydration of zeolite HZSM-5" John H. Hack, Xinyou Ma, Yaxin Chen, James P. Dombrowski, Nicholas H. C. Lewis, Chenghan Li, Harold H. Kung, Gregory A. Voth, and Andrei Tokmakoff. The Journal of Physical Chemistry C <strong>2023</strong> <i>127</i> (32), 16175-16186. DOI: 10.1021/acs.jpcc.3c03611</p>
Dataset of article: Synthesis of Dendritic ZSM‑5 Zeolite through Micellar Templating Controlled by the Amphiphilic Organosilane Chain Length
<p>Data used for preparation of the article : Synthesis of Dendritic ZSM‑5 Zeolite through Micellar Templating Controlled by the Amphiphilic Organosilane Chain Length</p> <p> Abstract of article: </p> <p>The synthesis of ZSM-5 zeolites by hydrothermal crystallization of protozeolitic nanounits functionalized with amphiphilic organosilanes of different chain length (Cn-N(CH3)2-(CH2)3-Si- (OCH3)3, n = 10, 14, 18 and 22) has been investigated. Well developed dendritic nanoarchitectures were achieved when using C14 and C18 organosilanes, exhibiting a radial and branched pattern of zeolitic nanounits aggregates. In contrast, although C10 and C22 organosilanes led to materials with hierarchical porosity, they lack of dendritic features. These differences have been linked to the formation of an amorphous mesophase at the gel preparation stage for the C14 and C18 samples, in which the surfactant micelles are covalently connected with the protozeolitic nanounits through siloxane bonds. The presence of the dendritic nanostructure positively impacts both the textural and catalytic properties of ZSM-5 zeolite. Thus, ZSM-5 (C14) and ZSM-5 (C18) samples exhibit the largest contribution of mesoporosity in terms of both surface area and pore volume. On the other hand, when tested as catalysts in the aldol condensation of furfural with cyclopentanone, which is an interesting reaction for the production of sustainable jet fuels, the highest catalytic activity is attained over the dendritic ZSM-5 materials due to their remarkable accessibility and balanced Brønsted/Lewis acidity.</p>
Fig. 1 in Use of sodium chloride and zeolite during shipment of Ancistrus triradiatus under high temperature
Fig. 1. Linear regression between the number of Ancistrus triradiatus that maintained the swimming axis and time of exposure to hyperosmotic saline solution for control and zeolite groups.
Catalytic Dehydrogenation of Ethane over Mn Oxide Supported on Zeolite Chabazite
<p>A new class of Mn-containing zeolites prepared by incipient wetness impregnation (IWI) have been found to catalyze the ethane dehydrogenation reaction with high selectivity (98%+). Preparation by IWI leads to the formation of Mn<sub>2</sub>O<sub>3</sub> nanoparticles on the external surface of the zeolite crystals and herein is shown that the primary active sites for the reaction are located on the surface of these particles. Propane dehydrogenation is also successfully catalyzed by this catalyst. Other Mn-zeolites (MFI and BEA) also have high reactivity and selectivity towards light alkane dehydrogenation.</p>
Influence of ion mobility on the redox and catalytic properties of Cu ions in zeolites
<ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements and related elaboration from Figure 7</li> <li>Files are with filename extensions: <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> <li>Normalized Cu K-edge XANES of a Cu-CHA sample (Si/Al = 5, Cu/Al = 0.3), collected during heating from RT to 350 °C under a He flow. In situ data were collected at the BM23 beamline of the European Synchrotron Radiation Facility (ESRF, Grenoble, France) in a Microtomo reactor cell</li> <li>Cu L<sub>3</sub>-edge TEY NEXAFS spectra of of a Cu-CHA sample (Si/Al = 5, Cu/Al = 0.3), collected during heating from RT to 350 °C under a He flow. In situ data were collected at the APE-HE beamline of Elettra Sincrotrone Trieste (Basovizza, Italy) in a dedicated ambient pressure cell.</li> <li><strong>Information on</strong>:</li> <li>specialized abbreviations: <strong>XANES</strong> – X-ray absorption near edge structure, <strong>TEY</strong> - Total Electron Yield, <strong>NEXAFS</strong> – near edge X-ray absorption fine structure, <strong>CHA</strong> - chabazite</li> </ul>
Supplementary data: A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR
<p><strong>Content:</strong></p> <p>This dataset provides supplementary data to "A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR". It contains trained Neural Network Potentials (NNP), energy and force data used for accuracy evaluation of the NNPs. Energy and forces are stored as ASE trajectory files (traj), readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE). In addition, this repository contains the generated training database with DFT (SCAN+D3(BJ)) energies and forces as SchNetPack1.0 database (SiAlOHNa.db) file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>. Also, the structure files used to calculate NMR properties are involved.</p> <ul> <li>"nnps.zip" - (pytorch) NNP model files (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>)</li> <li>"SiAlOHNa.db" - DFT (SCAN+D3(BJ)) training database as SchNetPack1.0 database file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li> <li>"error_stats.zip" - traj files storing energies/forces at the DFT (SCAN+D3(BJ)) and NNP level for all test simulations to calcuate energy/force errors</li> <li>"Structures_CHA17.zip" - the structures files of CHA(17). </li> </ul>
CO co-feeding effect in CH3Cl coupling over ZSM-5 zeolite: pressure twists the plot
<p>Dataset supporting the article 'CO co-feeding effect in CH3Cl coupling over ZSM-5 zeolite: pressure twists the plot', by Z. Zhang, M. Vanni, X. Wu, P. Hemberger, A. Bodi, S. Mitchell, and J. Pérez-Ramírez.</p>
Continuous rotation electron diffraction data for zeolite SSZ-27
<p><strong>Raw data for SSZ-27 (as-synthesized)</strong></p> <p>The directories labeled <strong>S**</strong> contain the raw data for the SSZ-27 phase, those labeled <strong>C**</strong> for the SSZ-26 impurity.</p> <p>Each directory contains the following:</p> <ul> <li>cred_log.txt, data collection log file</li> <li>SMV, Directory with data in SMV format and XDS processing output</li> <li>tiff, Directory with raw data in TIFF format</li> <li>tiff_image, Directory with defocused images showing the position of the crystal</li> <li>pets.pts, input file for PETS</li> <li>beam_centers.txt, a table with the position of the primary beam</li> </ul> <p>Then there are three other directories:</p> <ul> <li>XSCALE, contains the scaling results from the 14 SSZ-27 crystals that were used for the cluster analysis</li> <li>SSZ-26_cluster_1, contains the clustering results and refinement data for SSZ-26</li> <li>SSZ-27_cluster_4, contains the clustering results and refinement data for SSZ-27</li> </ul> <p>The data were collected using the software <a href="https://github.com/stefsmeets/instamatic">instamatic</a> and processed using <a href="http://xds.mpimf-heidelberg.mpg.de/">XDS</a>/<a href="https://github.com/stefsmeets/edtools">edtools</a>.</p>
ZEO-1, A Stable Zeolite Catalyst with Intersecting Three-Dimensional extralarge Plus Large Pores
<p>ZEO-1 is an aluminosilicate zeolite with a multidimensional system of interconnected extra-large pores. This aluminosilicate has a high silica content and a zeolitic, non-interrupted framework, with high thermal and hydrothermal stability. The pore system of ZEO-1 contains both 3D 16MR and large 3D 12MR channels with high interconnectivity that results in three types of supercages with four windows of 16MR and/or 12MR. </p>
Selectivity improvement of polysulfone-zeolite templated carbon membrane by annealing and coating treatment for CO2/CH4 and H2/CH4 separation
<p>Natural gas, which majorly consists of methane (CH4), is a renewable energy source widely used as fuel, as well as hydrogen (H2). However, in its production process of each gas containing other impurity gasses. Therefore, membrane technology is needed to separate the gasses from the impurities. Mixed Matrix Membrane (MMM) is a more promising membrane compared to the others. Zeolite Templated Carbon-based MMM offers a good separation performance because of ZTC's large surface area and well-defined pore structure. However, the interfacial void in MMM is challenging to be prevented, which contributes to the reduced separation performance. This study aims to enhance separation performance by modifying membrane surfaces using various methods. MMM PSF/ZTC modified by annealing at 120, 150, and 190 °C; coating using 0.01, 0.03, and 0.05 mol tetramethylorthosilicate (TMOS); and both combinations annealing at 190 °C and coating using 0.03 mol TMOS. MMM PSF/ZTC was successfully significantly improved CO2/CH4 selectivity by both combinations of annealed at 190 °C and coated 0.03 mol TMOS from 1.37 to 5.90 (331%) and H2/CH4 selectivity by coating with 0.03 mol TMOS from 4.58 to 65.76 (1378%). The enhancement of selectivity was due to structural changes of the membrane that was denser and smoother, which SEM and AFM observed. In this study, annealing and coating treatment are the methods that can use for improving the polymer matrix and filler particle adhesion.</p>
Elucidation of radical- and oxygenate-driven paths in zeolite-catalyzed conversion of methanol and methyl chloride to hydrocarbons
<p>Dataset corresponding to the publication:</p> <p><strong>Elucidation of radical- and oxygenate-driven paths in zeolite-catalyzed conversion of methanol and methyl chloride to hydrocarbons</strong></p> <p>Alessia Cesarini,<sup>1†</sup> Sharon Mitchell,<sup>1†</sup> Guido Zichittella,<sup>1†</sup>* Mikhail Agrachev,<sup>2</sup> Stefan P. Schmid,<sup>2</sup> Gunnar Jeschke,<sup>2</sup> Zeyou Pan,<sup>3</sup> Andras Bodi,<sup>3</sup> Patrick Hemberger,<sup>3</sup>* and Javier Pérez‑Ramírez<sup>1</sup>*</p> <p><sup>1</sup> Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland,</p> <p><sup>2</sup> Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland,</p> <p><sup>3</sup> Laboratory of Synchrotron Radiation and Femtochemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland,</p> <p><sup>†</sup>These authors contributed equally, listed alphabetically.</p> <p>*Corresponding author. E-mails: zguido@mit.edu, <a href="mailto:patrick.hemberger@psi.ch">patrick.hemberger@psi.ch</a>, jpr@chem.ethz.ch.</p>
Simultaneous Control of Aluminum Atoms and Defects in MOR Zeolite Framework by Post-Synthetic Treatments
<p><span>Input and output files used to calculate 27Al NMR chemical shifts in Quantum Espresso 6.5 for modernities with various defects and Al substitutions.</span></p>
Spin density studies of tetrahedral Cu(II) ions doped into porous zeolitic imidazolate frameworks
<p><strong>Description of the dataset:</strong></p> <ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements</li> <li>Files are with filename extensions: <strong>spc, par, dsc, dta, out, and oof</strong></li> <li>Information on <strong>origin of the data</strong>:</li> <li>The X-band continuous wave (CW) EPR spectroscopic measurements were generated by EMX spectrometer equipped with ER 4119 HS Resonator. The raw data extensions: spc and par.</li> <li>The Q-band pulsed EPR experiments (Davies and Mims ENDOR) were conducted using a Bruker Elexsys E580 spectrometer with a SuperQ-FT microwave bridge. The raw data extensions: dsc and dta.</li> <li>Periodic geometry optimizations were carried out by using the replicated data-parallel version of CRYSTAL17 code within the framework of Density Functional Theory (DFT) exploiting the hybrid B3LYP method. Molecular cluster calculations were carried out with ORCA (v5.0.2) code.</li> </ul> <ul> <li><strong>Folders are classified based on the type of measurement conducted.</strong></li> </ul> <ul> <li><strong>Additional Information </strong>: <ul> <li>specialized abbreviations: <strong>EPR</strong> – Electron Paramagnetic Resonance, <strong>ZIF</strong> – Zeolitic imidazolate frameworks, <strong>HYSCORE</strong>- Hyperfine sublevel correlation, <strong>ENDOR </strong>- Electron nuclear double resonance, <strong>EDFS </strong>- Echo-detected field sweep, <strong>ESEEM- </strong>electron spin echo envelope modulation, <strong>Act - </strong>activated.</li> <li>definitions of variables: <strong>magnetic field, pulse sequence, microwave power.</strong></li> <li>units of measurement: <strong>Gauss (G), milliTesla (mT), nanosecond(ns), microwave power (dB), Kelvin (K), Cu dopant percentage (%)</strong>.</li> <li>abbreviations on the data filename for pulsed EPR results: Dates, sample name, sample state, type of experiments (including the pulse delay tau or d1), temperature, number of scan, baseline correction if indicated.</li> </ul> </li> </ul>
Computed data for the paper "Deciphering Faujasite Zeolite Dealumination at the Atomic Scale" by Z. Wang, T. Jarrin, [...], G. Pirngruber, C. Chizallet, A. Lesage, https://doi.org/10.1021/acscatal.4c03036
<p>The presented data correspond to NMR calculations done with the VASP code, for models of zeolite faujasite (bulk and external surfaces, possibly with defects), silica, and amorphous silica-alumina surfaces. For details on the format of the files, see https://www.vasp.at/wiki/index.php/The_VASP_Manual. </p> <p>The date correspond to the following paper: <span><em>ACS Catal.</em></span> <span>2024</span><span>, 14</span><span>, 24</span><span>, 18442–18456,</span> https://doi.org/10.1021/acscatal.4c03036 </p>
Research data for the paper: Adsorption Desalination and Cation Exchange of NaCl and CaCl2-water solutions in LTA zeolites
<p>Adsorption isotherms data of water in LTA zeolites (LTA_Si, NaLTA, CaLTA and NaCaLTA) with 0 Salt, 7 molecs/uc NaCl, 21 molecs/uc NaCl, 7 molecs/uc CaCl2, 21 molecs/uc CaCl2.</p> <p>Water adsorption data in MFI zeolite for force field validation</p> <p>Raw data of Radial Distribution Functions (RDFs) in NaLTA (LTA4A), NaCaLTA (LTA5A), CaLTA (LTACa), distances between structure (Oa), extra framework cations (NaCAT, CaCAT), salt cation (Na, Ca), and water (Ospce)</p> <p> </p>
The Shape of Water in Zeolites and its Impact on Epoxidation Catalysis
<p><strong>The Shape of Water in Zeolites and its Impact on Epoxidation Catalysis</strong></p> <p>Daniel T. Bregante,<sup>1</sup> Matthew Chan,<sup>1</sup> Jun Zhi Tan,<sup>1</sup> E. Zeynep Ayla,<sup>1</sup> Christopher P. Nicholas,<sup>2,3</sup> Diwakar Shukla,<sup>1</sup> and David W. Flaherty<sup>1,*</sup></p> <p><em><sup>1</sup></em><em>Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61802</em></p> <p><em><sup>2</sup></em><em>Exploratory Materials and Catalysis Research, Honeywell UOP, Des Plaines, IL 60016</em></p> <p><em><sup>3</sup></em><em>C<sub>2</sub>P Sciences L3C, Evanston, IL 60202</em></p> <p><sup>*</sup>Corresponding Author: dwflhrty@illinois.edu</p> <p> </p> <p>Molecular dynamics simulations for zeolite framework studied in "<strong>The Shape of Water in Zeolites and its Impact on Epoxidation Catalysis". </strong></p> <p>Repository contains the last 100 nanoseconds of classical molecular dynamics equilibration, <em>ab initio</em> molecular dynamics trajectories, initial and final simulated zeolite structures, and scripts used for analyzing MD trajectories. </p>
Supporting data for "Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics"
<p>Supporting data for "<a href="https://www.nature.com/articles/s41467-023-36666-y">Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics</a>" by M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen and V. Van Speybroeck, <em>Nature Communications</em>, <strong>2023</strong>, 14, 1008.</p> <p>This dataset contains examples of input files, submission and analysis scripts to train and use a machine learning potential based on the Schnet architecture for the proton hopping reaction in the H-CHA zeolite. The complete DFT training set, obtained by unbiasing the forces printed by CP2K (with PLUMED coupling), is stored as extended xyz files in the folders DFT/A-B/training_data.xyz where A=1-3 and A<B<5. More details on the folder architecture can be found in the README.md file.</p>
Effect of temperature in methanol conversion to dimethyl ether (DME) and light hydrocarbons with beta zeolite
<p><span>Crystalline beta zeolite molecular sieve with SiO<sub>2</sub>/Al2O<sub>3</sub> molar ratio of 28.5 was synthesized by the hydrothermal crystallization method and examined for the methanol dehydration reaction. The micro-mesoporous beta zeolite was active between 250 and 450°C. Dimethyl ether (DME) was observed as the predominant product at all reaction temperatures, with a maximum selectivity of 47.9% at 300°C and a methanol turnover frequency (TOF<sub>MeOH</sub>) of 741.9 h-1. At increased reaction temperatures, the beta zeolite showed enhanced strong acid site fraction, promoting higher hydrocarbon formation following the olefin-based cycle. It was revealed that the crystallinity, porosity, and acidity of the beta zeolite change in the reaction environment. Amorphous carbon deposition occurred on beta zeolite, which involved the loss in crystallinity to some extent. The temperature increase showed a pore-broadening phenomenon at elevated temperature regions. The regeneration cycle test showed stable activity of regenerated beta zeolite for 280 h time-on-stream.</span></p>
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