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opencc-by-4.0Jan 2022View details →

MAPO-18 Catalysts for the Methanol to Olefins Process: Influence of Catalyst Acidity in a High-Pressure Syngas (CO + H2) Environment

Supplementary Material:  Catalyst characterization (XRD, SEM–EDS, N2 physisorption, IR spectroscopy, and propylamine-TPD), catalyst performance, and DFT calculations

opencc-by-4.0Nov 2021View details →

Discovering indium as hydrogen production booster for a Cu/SiO2 catalyst in steam reforming of methanol

Indium is  as an effective H2 production promoter in a Cu/SiO2 catalyst for the steam reforming of methanol. We prepared silica-supported Cu-In catalyst via a urea-assisted co-precipitation method that showed a higher H2 productivity compared to the monometallic catalyst and a H2/CO2 molar ratio of almost 3 at 493 K. By means of XPS, XRPD and HRTEM-EDX along with H2 and CO-TPR, H2O-TPD, and N2O titrations, supported by computational modeling, the superior performances were attributed to an easier H2O activation due to lower oxidation state of the Cu, resulting from the electron density transfer from the InOx phase. Here are available: Hydrogen Temperature Programmed Reduction data; Carbon Monoxide Temperature Programmed Reduction data; Water Temperature Programmed Desorption data; Nitrogen Physisorption data.

opencc-by-4.0Feb 2022View details →

ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions

Datasets supporting the publication 'ZnO-Promoted Inverse ZrO2–Cu Catalysts for CO2-Based Methanol Synthesis under Mild Conditions': catalyst evaluation data (Excel), XRD (Origin), crystallite sizes, Cu surface area, CO2 uptake, H2-TPR, CO2-TPD, CO-DRIFTS profiles (CSV)

opencc-by-4.0Mar 2022View details →

A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation

Thermocatalytic CO2 hydrogenation to methanol is an attractive decarbonization technology to combat climate change while producing a valuable platform chemical and energy carrier. However, predicting the performance of catalytic systems for this process remains a challenge. Herein, we present a machine learning framework to predict catalyst performance from experimental descriptors. A database of Cu-, Pd-, In2O3-, and ZnO-ZrO2-based catalysts with 1425 datapoints is compiled from literature and subjected to data mining. Accurate ensemble-tree models (R2 > 0.85) are developed to predict the methanol space-time yield (STY) from 12 descriptors, where the significance of space velocity, pressure, and metal content is revealed. The model prediction and its insights are experimentally validated, with a root mean squared error of 0.11 gMeOH h−1 gcat−1 between the actual and predicted methanol STY. The framework is purely data-driven, interpretable, cross-deployable to other catalytic processes, and serves as an invaluable tool for guided experiments and optimization.

opencc-by-4.0Oct 2024View details →

Enhanced Catalytic Performance of a Single-Atom Cu on Mo2C toward the CO2/CO Hydrogenation to Methanol: A First-Principles Study_dataset

Dataset of inputs and outputs concerning mechanisms, bader charge analysis, frequency analysis and model used in the study namely: Enhanced Catalytic Performance of a Single-Atom Cu on Mo2C toward the CO2/CO Hydrogenation to Methanol: A First-Principles Study published on Cat. Sci. Technol. (DOI: 10.1039/d4cy00703d).

opencc-by-4.0Jun 2023View details →

Dataset for Process design within planetary boundaries: Application to CO2 based methanol production

Dataset for the journal article: Process design within planetary boundaries: Application to CO2 based methanol production

Atomic resolution X-ray diffraction images for methanol dehydrogenase from Methylobacterium extorquens.

Atomic resolution X-ray diffraction images for methanol dehydrogenase from Methylobacterium extorquens collected at ESRF (Grenoble, France) using beamline ID29 in May 2002 with an ADSC detector. The diffraction resolution for the first pass is approximately 1.1 - 1.2 Angstroms and a second pass was collected to recoup the reflections that were overloaded in the first pass. More details of the data collection are in the included scanned notes and log files.

opencc-by-4.0Apr 2024View details →

Reactivity Switch of Platinum with Gallium: From Reverse Water Gas Shift to Methanol Synthesis

The development of efficient catalysts for the hydrogenation of CO2 to methanol using “green” H2 is foreseen to be a key step to close the carbon cycle. In this study, we show that small and narrowly distributed alloyed PtGa nanoparticles supported on silica, prepared via a surface organometallic chemistry (SOMC) approach, display notable activity for the hydrogenation of CO2 to methanol, reaching 7.2 mol h-1 molPt-1 methanol formation rate with a 54% intrinsic CH3OH selectivity. This reactivity sharply contrasts with what is expected for Pt, which favors the reverse water gas shift reaction, albeit with a poor activity (2.6 mol h-1 molPt-1). In situ XAS studies indicate that ca. 50% of Ga is reduced to Ga0 yielding alloyed PtGa nanoparticles, while the remaining 50% persist as isolated GaIII sites. The PtGa catalyst slightly dealloys under CO2 hydrogenation conditions and displays redox dynamics with PtGa-GaOx interfaces, responsible for promoting both CO2 hydrogenation activity and methanol selectivity. Further tailoring the catalyst interface by using a carbon support in place of silica enables to improve the methanol formation rate by a factor of ~5.

opencc-by-4.0Sep 2013View details →

Fig. 3 in Efficacy of eugenol and the methanolic extract of Condalia buxifolia during the transport of the silver catfish Rhamdia quelen

Fig. 3. The net ion (Na+, Cl- and K+) fluxes measured for the transport of Rhamdia quelen in plastic bags with eugenol and with the methanolic extract of Condalia buxifolia added to the water. The values are the means ± SEM. The different letters indicate significant differences between the treatments for the same ion (P<0.05).

opencc-by-4.0Sep 2013View details →

Fig. 1 in Efficacy of eugenol and the methanolic extract of Condalia buxifolia during the transport of the silver catfish Rhamdia quelen

Fig. 1. Time to reach the light sedation stage in Rhamdia quelen juveniles of two different weight classes exposed to the methanolic extract of Condalia buxifolia. The following equations were fitted to the data: For fish weighing 1.50 ± 0.02 g; y = 209.629 e0.015 x; r2 =0.996. For fish weighing 165.7 ± 22.5 g; y = 2039.020 e0.017 x; r2 =0.999. Where x = the concentration of the methanolic extract of C. buxifolia (µL L-1) and y = time for sedation(s).

Fig. 2 in Insecticidal activity of the methanol extract of Pronephrium megacuspe (Thelypteridaceae) and its active component on Solenopsis invicta (Hymenoptera: Formicidae)

Fig. 2. The effect of methanol extract, ethyl acetate fraction, and compound 26 293 (phenol-3-O-beta-D-glucoside) from Pronephrium megacuspe on the walking ability of 294 Solenopsis invicta micrergates. Each data point represents the mean ± SE of 3 replicates. Each 295 replicate contained 10 tested ants. CK = control.

Fig. 3 in Insecticidal activity of the methanol extract of Pronephrium megacuspe (Thelypteridaceae) and its active component on Solenopsis invicta (Hymenoptera: Formicidae)

Fig. 3. The effect of methanol extract, ethyl acetate fraction, and compound 26 298 (phenol-3-O-beta-D-glucoside) from Pronephrium megacuspe on the clinging ability of 299 Solenopsis invicta macrergates. Each data point represents the mean ± SE of 3 replicates. Each 300 replicate contained 10 tested ants. CK = control.

Fig. 1 in Insecticidal activity of the methanol extract of Pronephrium megacuspe (Thelypteridaceae) and its active component on Solenopsis invicta (Hymenoptera: Formicidae)

Fig. 1. The effect of methanol extract, ethyl acetate fraction, and compound 26 288 (phenol-3-O-beta-D-glucoside) from Pronephrium megacuspe on the walking ability of 289 Solenopsis invicta macrergates. Each data point represents the mean ± SE of 3 replicates. Each 290 replicate contained 10 tested ants. CK = control.

opencc-by-4.0Sep 2024View details →

Coarse-grained methanol trajectory

This dataset is a supplement to the paper "Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks," available at https://arxiv.org/abs/2406.12112.  To create this dataset, an all-atom trajectory of liquid methanol was generated using the GROMOS 54A7 force field and the LAMMPS software package.  The coarse-grained mapping described in the aforementioned paper was applied to the trajectory; the resulting positions, velocities, and forces are provided here. Additionally, the periodic cell is reported, as well as values of the radial distribution function calculated using the coarse-grained positions. For completeness, mass and species arrays are also included. The original all-atom trajectory was generated using a Nosé-Hoover thermostat at 700 K. After equilibration, 50,000 timesteps of 1 fs were computed and every 500th frame recorded. The resulting 100 frames were used to generate this dataset. The data is stored in a single Numpy .npz file, which contains eight arrays:  <table> <tbody> <tr> <td>key</td> <td>shape</td> <td>size (bytes)</td> <td>data units</td> </tr> <tr> <td>cells</td> <td>(100, 3, 3)</td> <td>7200</td> <td>Å</td> </tr> <tr> <td>forces</td> <td>(100, 1024, 3)</td> <td>2457600</td> <td>kcal/mol/Å</td> </tr> <tr> <td>masses</td> <td>(100, 1024)</td> <td>819200</td> <td>amu</td> </tr> <tr> <td>positions</td> <td>(100, 1024, 3)</td> <td>2457600</td> <td>Å</td> </tr> <tr> <td>rdf_bins</td> <td>(300,)</td> <td>2400</td> <td>Å</td> </tr> <tr> <td>rdf_values</td> <td>(300,)</td> <td>2400</td> <td>unitless</td> </tr> <tr> <td>species</td> <td>(100, 1024)</td> <td>819200</td> <td>unitless</td> </tr> <tr> <td>velocities</td> <td>(100, 1024, 3)</td> <td>2457600</td> <td>Å/ps</td> </tr> </tbody> </table>   Total size of file: 9.03 MB

opencc-by-4.0May 2023View details →

Dataset for Unified acidity of liquid chromatography mobile phases with methanol and acetonitrile

Dataset for article "Unified acidity of liquid chromatography mobile phases with methanol and acetonitrile". Here we report the data of 78 reversed-phase liquid chromatography-mass spectrometry mobile phases that were determined by potential differences in a symmetric cell with two glass electrode half-cells and almost ideal ionic liquid triethylamylammonium bis((trifluoromethyl)sulfonyl)imide [N2225][NTf2] salt bridge with multiple overlapping measurements. In addition, for 45 of these mobile phases, the potential difference between a glass and a double junction reference electrode were measured. Procedures used with Keysight B2987A Electrometer are given in <a href="https://dx.doi.org/10.17504/protocols.io.n92ld9dj8g5b/v2">dx.doi.org/10.17504/protocols.io.n92ld9dj8g5b/v2</a>  and <a href="https://dx.doi.org/10.17504/protocols.io.byh2pt8e">dx.doi.org/10.17504/protocols.io.byh2pt8e</a>. For other instruments, the procedures differ by software and instrument connections.

opencc-by-4.0Jun 2023View details →

Data set for the journal article: Social life cycle assessment of green methanol and benchmarking against conventional fossil methanol

Single File containing: <ul> <li>Green Methanol Inventories: numerical data as displayed in Figure 4, Main social life cycle inventory data of the green methanol system. </li> <li>Conventional Methanol Inventories: numerical data as displayed in Figure 5, Main social life cycle inventory data of the conventional methanol system. </li> <li>Supplementary information: Diagrams and tables describing teh flowsheet of the simulations used in this work: <ul> <li> Green methanol production process (flowsheet and stream table) </li> <li> Syngas production through Steam Methane Reforming (flowsheet and stream table) </li> <li> Conventional methanol production process (flowsheet and stream table) </li> </ul> </li> </ul>

opencc-by-4.0Aug 2023View details →

Theory-guided development of homogeneous catalysts for the reduction of CO2 to formate, formaldehyde, and methanol derivatives

The stepwise catalytic reduction of carbon dioxide (CO2) to formic acid, formaldehyde, and methanol opens non-fossil pathways to important platform chemicals. The present article aims at identifying molecular control parameters to steer the selectivity to the three distinct reduction levels using organometallic catalysts of earth-abundant first-row metals. A linear scaling relationship was developed to map the intrinsic reactivity of 3d transition metal pincer complexes to their activity and selectivity in CO2 hydrosilylation. The hydride affinity of the catalysts was used as a descriptor to predict activity/selectivity trends in a composite volcano picture, and the outstanding properties of cobalt complexes bearing bis(phosphino)triazine PNP-type pincer ligands to reach the three reduction levels selectively under different reaction conditions could thus be rationalized. The implications of the composite volcano picture were successfully experimentally validated with selected catalysts, and the challenging intermediate level of formaldehyde could be accessed in over 80% yield with the cobalt complex 6. The results underpin the potential of tandem computational-experimental approaches to propel catalyst design for CO2-based chemical transformations.