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36 results for “Reaction mechanism”
HyUSPRe Report & Data on 'New experimental data on reactions between H2 and well cement and effects on fluid flow and mechanical properties of well cement
<p>In this study, new experimental data is presented of the effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties of oil well (class G) cement, relevant for underground hydrogen storage operations. Changes in mechanical properties (Young’s modulus, Poisson’s ratio and ultimate strength) have been analyzed using unconfined compressive strength (UCS) tests and confined cyclic loading tests on class G cement samples that were unreacted (cured for 3 days at 80°C) and exposed to lime-saturated brine and N<sub>2</sub> or H<sub>2</sub> for 1 and 2 months. Changes in cement mineralogy were analyzed by XRD analysis of the unreacted and exposed samples. The mechanical properties of elastic modulus and Poisson’s ratio are within the expected range of an oil well cement. Differences in Young’s modulus, Poisson’s ratio and ultimate strength are limited between unreacted, N<sub>2</sub>-exposed and H<sub>2</sub>-exposed samples, when comparing UCS tests or confined cyclic loading tests. Repeated UCS tests seem to indicate that the variation in Young’s modulus and ultimate strength increases after N<sub>2</sub> and H<sub>2</sub> exposure, but this observation needs to be confirmed in additional tests. During cyclic axial loading of confined cement samples, irreversible (plastic) deformation (compaction) occurs that affect static Young’s modulus. Also, effects of exceeding yield and failure strength on Young’s modulus are observed. Dynamic Young’s moduli and Poisson’s ratios derived from acoustic velocity measurements during confined cyclic tests show limited variation, in particular if static and dynamic Young’s modulus are compared. The mineralogical changes as identified using XRD analysis suggest minor changes between unexposed and H<sub>2</sub>- and N<sub>2</sub>-exposed samples, although XRD patterns indicate some minerals that could not be identified. The main conclusion is that effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties and mineralogical changes of class G cement is limited compared to unreacted or N<sub>2</sub> exposed samples for the investigated conditions. There is no indication that changes in mechanical properties of cement are such that cement integrity of wells used for underground hydrogen storage will be significantly affected. It should be emphasized that this conclusion is based on experiments on one type of cement (class G) and a limited set of conditions. In particular, additional tests to assess the reproducibility of current results and tests on samples that were exposed longer to H<sub>2</sub> and N<sub>2</sub> are of interest. Detailed effects of changing properties for the durability and integrity of wells can be derived by performing a parameter sensitivity analysis with well integrity modelling for the range in mechanical properties measured in this study.</p>
Catalytic Rules and Validation Results for "EzMechanism: An Automated Tool to Propose Catalytic Mechanisms of Enzyme Reactions"
<p>Dataset containing the "Rules of Enzyme Catalysis" as created during the development of EzMechanism and the validation results of the software. For more information see https://www.biorxiv.org/content/10.1101/2022.09.05.506575v1, and the M-CSA website in https://www.ebi.ac.uk/thornton-srv/m-csa/</p>
Dataset for "From CO2 to Solid Carbon: Reaction Mechanism, Active Species, and Conditioning the Ce-Alloyed GaInSn Catalyst"
<p>Experimental raw data for the article "<em>From CO<sub>2</sub> to Solid Carbon: Reaction Mechanism, Active Species, and Conditioning the Ce-alloyed GaInSn Catalyst</em>", published in <em>Journal of Physical Chemistry C </em>(2024). DOI:10.1021/acs.jpcc.4c05482.</p> <p>The data set is organized according to the publication's figures. XPS data given here is the raw data without binding energy calibration. For the manuscript, binding energies in a series of samples were calibrated by taking the strongest peak, where no chemical shift was to be expected, as a reference.</p>
Image segmentation masks for curved arrows on molecular images from chemical reaction mechanism images
<p>The dataset presented herein is designed as a ground truth for image segmentation tasks focused on noise extraction in Optical Chemical Structure Recognition (OCSR) processes. It comprises 73 manually extracted and annotated images from real reaction mechanism images, along with 5320 synthetic molecular images generated using RDKit, each featuring computer-drawn curved arrows on random locations on the molecular image pertinent to their respective tasks. Curved arrows are prevalent in chemical reaction mechanism images and significantly impact the accuracy of molecular identity recognition. This dataset aims to enhance OCSR tasks by enabling the pretreatment of molecular images to remove noise, thereby improving molecular recognition accuracy.</p>
Kinetic Insights into Glycerol Electrooxidation on Nickel: Current-Dependent Product Distribution and Reaction Mechanism
<p>## FILE DESCRIPTION<br>--------------<br>### Figure 1<br>- Fig1a.txt : Cyclic voltammetry of a Ni-based electrode in 0.1 M LiOH and 50 mM glycerol, measured at 5 mV s^-1. <br>- Fig1b.txt : IS spectra obtained at 1.50 V vs RHE in 0.1 M LiOH and 0.1 M LiOH + 50 mM glycerol.<br>- Fig1c.txt : Chronopotentiometric curves at 1 mA cm^-2, 3 mA cm^-2, 5 mA cm^-2 during 2 hours in 0.1 M LiOH + 50 mM glycerol.</p> <p>### Figure 2<br>- Fig2a.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1 mA cm^-2.<br>- Fig2b.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 3 mA cm^-2.<br>- Fig2c.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 5 mA cm^-2.<br>- Fig2d.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 10 mA cm^-2.<br>- Fig2e.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 1 mA cm^-2.<br>- Fig2f.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 3 mA cm^-2.<br>- Fig2g.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 5 mA cm^-2.<br>- Fig2h.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 10 mA cm^-2.</p> <p>### Figure 3<br>- Fig3a.txt : Rate constant comparison at varying current densities applied for the formation of formate, glycolate, glycerate, tartronate and oxalate with its error bar.</p> <p>### Figure 4<br>- Fig4a.txt : Differential optical density (m∆O.D) taken at the maximum absorption peak as a function of potential applied in a solution of 0.1 M LiOH and LiOH 0.1 M + 50 mM glycerol in different regions (capacitive, NiOOH formation and GEOR and OER).<br>- Fig4b.txt : Rate law plot for glycerol and LiOH considering current density as a function of the normalized differential absorption (m∆O.D).</p> <p>### Figure S3<br>- FigS3.txt : X-ray diffraction (XRD) analysis </p> <p><br>### Figure S4<br>- FigS4a.txt : Cyclic Voltammetries in different electrolytes.</p> <p>### Figure S5<br>- FigS5a.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.53 V vs RHE.<br>- FigS5b.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.62 V vs RHE.<br>- FigS5c.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.78 V vs RHE.</p> <p>### Figure S6<br>- FigS6a.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 1 mA cm^-2.<br>- FigS6b.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 3 mA cm^-2.<br>- FigS6c.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 5 mA cm^-2.</p> <p>### Figure S7<br>- FigS7a.txt : UV-Vis absorbance spectra as a function of applied potentials in 0.1 M LiOH.<br>- FigS7b.txt : Chronoamperometry measurement without glycerol.<br>- FigS7c.txt : UV-Vis absorbance spectra as a function of applied potentials in 0.1 M LiOH + 50 mM glycerol.<br>- FigS8d.txt : Chronoamperometry measurement with glycerol.</p> <p>### Figure S8<br>- FigS8a.txt : Differential UV-Vis spectra of pre-catalytic (species formed in capacitive and NiOOH formation region) in 0.1 M LiOH.<br>- FigS8b.txt : Differential UV-Vis spectra of catalytic species (formed in OER and GEOR region) in 0.1 M LiOH.<br>- FigS8c.txt : Differential UV-Vis spectra of pre-catalytic species in 0.1 M LiOH + 50 mM glycerol. <br>- FigS8d.txt : Differential UV-Vis spectra of catalytic species in 0.1 M LiOH + 50 mM glycerol.<br>- FigS8e.txt : Steady state J-V curve with the onset for OER (Oxygen Evolution Reaction) and GEOR (Glycerol Electrooxidation Reaction) indicated.</p> <p>### Figure S9<br>- FigS9.txt : Rate law plot for glycerol and LiOH considering current density (j) as a function of the normalized differential absorption (m∆O.D).</p>
Discrete Feature Representations of CHO Reaction Mechanisms as Quasireaction Subgraphs
<p>This data set contains 194778 quasireaction subgraphs extracted from CHO transition networks with 2-6 non-hydrogen atoms (CxHyOz, 2 <= x + z <= 6).</p> <p>The complete table of subgraphs (including file locations) is in CHO-6-atoms-subgraphs.csv file. The subgraphs are in GraphML format (http://graphml.graphdrawing.org) and are compressed using bzip2. All subgraphs are undirected and unweighted. The reactant and product nodes (initial and final) are labeled in the "type" node attribute. The nodes are represented as multi-molecule SMILES strings. The edges are labeled by the reaction rules in SMARTS representation. The forward and backward reading of the SMARTS string should be considered equivalent.</p> <p>The generation and analysis of this data set is described in<br> D. Rappoport, Statistics and Bias-Free Sampling of Reaction Mechanisms from Reaction Network Models, 2023, submitted. Preprint at ChemrXiv, DOI: 10.26434/chemrxiv-2023-wltcr</p> <p>Simulation parameters<br> - CHO networks constructed using polar bond break/bond formation rule set for CHO.<br> - High-energy nodes were excluded using the following rules:<br> (i) more than 3 rings, (ii) triple and allene bonds in rings, (iii) double bonds at<br> bridge atoms,(iv) double bonds in fused 3-membered rings.<br> - Neutral nodes were defined as containing only neutral molecules.<br> - Shortest path lengths were determined for all pairs of neutral nodes.<br> - Pairs of neutral nodes with shortest-path length > 8 were excluded.<br> - Additionally, pairs of neutral nodes connected only by shortest paths passing through<br> additional neutral nodes (reducible paths) were excluded.</p> <p>For background and additional details, see paper above.</p>
Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies
<p>Abstract</p> <p>Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production.</p> <p>Computational Details</p> <p>AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary<br> conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28 ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep<br> the simulation temperature at 300 K.</p> <p>Please see the corresponding article for more details.</p>
Data for Automatic Mechanism Generation Involving Kinetics of Surface Reactions with Bidentate Adsorbates
<p>Data and scripts for the preprint "Automatic Mechanism Generation Involving Kinetics of Surface Reactions with Bidentate Adsorbates".</p>
DFT Calculated xyz and log Files in Support of "Reaction Mechanism of Pd-catalyzed "CO-free" Carbonylation Reaction Uncovered by In situ Spectroscopy: The Formyl Mechanism"
<p>Theoretically calculated xyz and log files for hydrogen, carbon monoxide, carbon dioxide, methane, methanol, methyl formate, butene, methyl pentanoate and multiple Pd-dtbpx complexes (dtbpx = 1,2-Bis(di-<em>tert</em>-butylphosphino)xylene) which catalyze the addition of HCOOMe/CO onto butene to form methyl pentanoate.</p> <p>All quantum chemical simulations were performed using the Gaussian16 software. The ground state equilibrium structures and electronic properties were obtained at the density functional (DFT) level of theory utilizing the B3LYP XC functional.The def2-SVP basis set as well as the respective core potentials were applied for all atoms. A subsequent vibrational analysis was carried out for each optimized ground state structure to verify that a minimum on the potential energy (hyper‑)surface (PES) was obtained. All calculations were performed including D3 dispersion correction with Becke-Johnson damping.</p> <p>An analogous computational setup was applied for the optimization of transition states (TSs), while an initial guess in the vicinity of the saddle point was at first obtained via the Nudged Elastic Band (NEB) method as implemented in pysisyphus with xtb.<sup> </sup>Thereafter, the TSs were obtained in Gaussian16 via the Berny algorithm, followed by a vibrational analysis to verify that a first-order saddle point on the PES was obtained.</p>
Development of predictive models of the kinetics of a hydrogen abstraction reaction combining quantum-mechanical calculations and experimental data
<p>The files contain the electronic structure calculations for all the levels of theory tested in this work.</p>
Elucidating the reaction mechanism of SO2 with Cu-CHA catalysts for NH3-SCR by X-ray absorption spectroscopy
<p>Dataset related to the article with the same title and authors:</p><p>https://pubs.rsc.org/en/content/articlelanding/2023/SC/D3SC03924B#fn1</p><p>dat files corresponding to the spectra reported in the article. See the article for the description of the procedures and of high and load loading catalysts</p><p> </p><p> </p>
The proteolytic cleavage of TLR8 Z-loop by furin protease - molecular recognition, reaction mechanism and role of water molecules DATASET_v2
<p>The dataset comprises:<br>i) AlphaFold-Multimer predictions for TLR8LRR-furin complex<br>ii) The optimised structures of QM cluster models for reactant (RE), intermediate1-3 (INT1-INT3), and product (PROD)<br>iii) The optimised structures of QM/MM model for RE, INT1-INT3, PROD<br>iv) Input structures used in MD simulations and parameterization files for non-standard residues for RE, INT1-INT3, PROD<br>v) PyMOL sessions from AQUA-DUCT calculations for RE, INT1-INT3, PROD</p>
Dataset for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries
<p>A dataset for publication Datase for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries including all relevant data used in the manuscript. Information on how to use the dataset are included in the readme file.</p>
Understanding the Nitrogen Reduction Reaction Mechanism on CuFeO2 Photocathodes
<p>This is a data set for the corresponding research article. It provides the necessary input files and optimized geometries to reproduce or extend this data set. The folders are uploaded on GitLab (project ID: 62597469). There are two versions one is for windows users (.zip) and the other for Linux users (*.tar.gz). Information on how to navigate through the folder structure is described in the README.md file in the dataset folder.</p> <p>The work was funded by the DFG through the priority program SPP-2370 (project id 502202153) and project 501805371, and through the collaborative research center SFB-1316 (project 327886311). </p> <p>Further questions or remarks can be sent to this dataset's creator (julian.bessner@uni-ulm.de).</p>
Reaction Mechanism of the PET Degrading Enzyme PETase Studied with DFT/MM Molecular Dynamics Simulations
<p>Raw simulations of the acylation step by PETase on a PET dimer model substrate, ran with CP2K 6.1 software at the PBE:AMBER level. Details can be found in the original manuscript (<a href="https://doi.org/10.1021/acscatal.1c03700">https://doi.org/10.1021/acscatal.1c03700</a>): Molecular topology in AMBER Parameter Topology format and Trajectories in CHARMM binary coordinate format DCD.</p> <p>RESIDUE LIST:<br> GLY57<br> TYR58<br> SER131<br> MET132<br> TRP156<br> ASP177<br> SER178<br> ILE179<br> ALA180<br> HID208<br> MOL262</p> <p>VMD selection:<br> (name CA C O HA2 HA3 and resname GLY and resid 57) or (name N CA CB H HA HB2 HB3 and resname TYR and resid 58) or (name CA C O OG CB HA HB2 HB3 HG and resname SER and resid 131) or (name N CA SD CE CB CG H HA HB2 HB3 HG2 HG3 HE1 HE2 HE3 and resname MET and resid 132) or (name CB CG CD1 CD2 CE2 CE3 NE1 CZ2 CZ3 CH2 HB2 HB3 HD1 HE1 HE3 HZ2 HZ3 HH2 and resname TRP and resid 156) or (name CG OD1 OD2 CB HB2 HB3 and resname ASP and resid 177) or (name C O and resname SER and resid 178) or (name N CA C O CG2 CD1 CB CG1 H HA HB HG12 HG13 HG21 HG22 HG23 HD11 HD12 HD13 and resname ILE and resid 179) or (name N CA H HA and resname ALA and resid 180) or (name CB CG CD2 ND1 CE1 NE2 HB2 HB3 HD1 HD2 HE1 and resname HID and resid 208) or (name C1 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C2 C20 C3 C4 C5 C6 C7 C8 C9 H1 H10 H11 H12 H13 H14 H15 H16 H17 H2 H3 H4 H5 H6 H7 H8 H9 O1 O2 O3 O4 O5 O6 O7 O8 O9 and resname MOL and resid 262)</p> <p>PYMOL selection:<br> (name CA+C+O+HA2+HA3 & resn GLY & resi 57) | (name N+CA+CB+H+HA+HB2+HB3 & resn TYR & resi 58) | (name CA+C+O+OG+CB+HA+HB2+HB3+HG & resn SER & resi 131) | (name N+CA+SD+CE+CB+CG+H+HA+HB2+HB3+HG2+HG3+HE1+HE2+HE3 & resn MET & resi 132) | (name CB+CG+CD1+CD2+CE2+CE3+NE1+CZ2+CZ3+CH2+HB2+HB3+HD1+HE1+HE3+HZ2+HZ3+HH2 & resn TRP & resi 156) | (name CG+OD1+OD2+CB+HB2+HB3 & resn ASP & resi 177) | (name C+O & resn SER & resi 178) | (name N+CA+C+O+CG2+CD1+CB+CG1+H+HA+HB+HG12+HG13+HG21+HG22+HG23+HD11+HD12+HD13 & resn ILE & resi 179) | (name N+CA+H+HA & resn ALA & resi 180) | (name CB+CG+CD2+ND1+CE1+NE2+HB2+HB3+HD1+HD2+HE1 & resn HID & resi 208) | (name C1+C10+C11+C12+C13+C14+C15+C16+C17+C18+C19+C2+C20+C3+C4+C5+C6+C7+C8+C9+H1+H10+H11+H12+H13+H14+H15+H16+H17+H2+H3+H4+H5+H6+H7+H8+H9+O1+O2+O3+O4+O5+O6+O7+O8+O9 & resn MOL & resi 262)</p>
Encapsulation Enhances the Catalytic Activity of C-N Coupling: Reaction Mechanism of a Cu(I)/Calix[8]arene Supramolecular Catalyst - XYZ Structure files
<p>XYZ Structures corresponding to DOI: 10.1002/cctc.202200662</p>
Supporting Information for the Journal Article "The electrostatic potential as a descriptor for the protonation propensity in automated exploration of reaction mechanisms"
<p>This dataset contains the supporting information published together with the article "The electrostatic potential as a descriptor for the protonation propensity in automated exploration of reaction mechanisms" (<a href="https://doi.org/10.1039/C9FD00061E"><em>Faraday Discuss.</em>, <strong>2019</strong>, <em>220</em>, 443</a>).</p>
Mechanisms of the reaction of elemental sulfur and polysulfides with cyanide and phosphines
<p>Gaussian 16 output files for all computed structures for "<strong>Mechanisms of the reaction of elemental sulfur and polysulfides with cyanide and phosphines</strong>".</p> <p><em>Chemistry - A European Journal, <strong>2023</strong>, </em>e202203906. DOI: 10.1002/chem.202203906</p>
Acceleration of Diels-Alder reactions by mechanical distortion
<p>Challenges in quantifying how force affects bond formation have hindered the widespread adoption of mechanochemistry. Here, parallel tip-based methods are used to determine reaction rates, activation energies, and activation volumes of force-accelerated [4+2] Diels-Alder cycloadditions between surface-immobilized anthracene and four dienophiles that differ in electronic and steric demand. The rate dependences on pressure are unexpectedly strong, and significant differences are observed between the dienophiles. Multiscale modeling demonstrates that, in proximity to a surface, mechanochemical trajectories ensue that are distinct from those observed solvothermally or under hydrostatic pressure. These results provide a framework for anticipating how experimental geometry, molecular confinement, and directed force contribute to mechanochemical kinetics.</p>
Acceleration of Diels-Alder reactions by mechanical distortion
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