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194 results for “Solvent”
Supporting Information for "Solvent modulated specific ion effects: PNIPAM brushes in non-aqueous electrolytes"
<p>This deposition contains the data and analysis (Jupyter notebooks) detailed in <em>Solvent modulated specific ion effects: PNIPAM brushes in non-aqueous electrolytes</em>. All Jupyter notebooks have also been converted into PDF files for ease of viewing.</p> <p> </p> <p>All data and code (notebooks) required to reproduce the analysis can be found within the “supporting_data_analysis.zip” archive. This archive contains three sub-directories:</p> <ul> <li>Ellipsometry <ul> <li>Data directories containing all raw ellipsometry data for the ‘thick’ and ‘thin’ PNIPAM brushes.</li> <li>Spatial maps of the polymer brush used for spectroscopic ellipsometry data analysis: “surface_map.png”.</li> <li>“refellips_Spectroscopic_SL.ipynb” notebook to reproduce the analysis of the hydrated (solid-liquid) ‘thin’ polymer brush. Relevant plotting tools can be found in the <a href="https://github.com/refnx/refellips">refellips repo</a>.</li> <li>“Ellipsometry_logistical_fitting.ipynb” notebook and “water_results.csv” file for the demonstration of the extraction of a thermotransition temperature from an ellipsometry dataset. </li> <li>“refellips_Spectroscopic_SL_VFP.ipynb” notebook to reproduce the analysis of the hydrated (solid-liquid) ‘thick’ polymer brush.</li> </ul> </li> <li>Neutron_reflectometry <ul> <li>Data directory containing all relevant reduced reflectivity profiles from the Platypus reflectometer at ANSTO.</li> <li>“refnx_dry.ipynb” and “refnx_solvent.ipynb” notebooks required to reproduce the analysis pertaining to a dry polymer brush and a solvated brush, respectively.</li> <li>Additional code required to model the hydrated polymer brush and various plotting tools can be in the <a href="https://github.com/igresh/refnxtoolbox">refnxtoolbox repo</a>.</li> </ul> </li> </ul>
Structural Characterization of amphiphilic co-networks in selective and non-selective solvents using 1H-NMR and SAXS
<p>We investigate structural properties of model amphiphilic co-networks made by heterocomplementary end-linking of tetra-PEG tetra-PCL star polymers in selective and non-selective solvent using small-angle X-ray scattering, NMR diffusometry and double-quantum magic-angle spinning (DQ MAS) NMR techniques.<br><br>Here, the data used is made accessible</p>
Data related to the publication "Efficient molecular dynamics simulations of deep eutectic solvents with first-principles accuracy using machine learning interatomic potentials"
<p>The training data sets, the trained machine learning models, and input scripts for the training and molecular dynamics simulations.</p>
Supplementary materials for Phylogenomics and genetic analysis of solvent-producing Clostridium species
Open the record for dataset details and reuse information.
A green extraction design for enhancing flavonoid compounds from the Ixora javanica flowers using a deep eutectic solvent
<p>In this study, an environmentally friendly extraction method for flavonoid compound from <em>Ixora javanica</em> as a new raw material candidate for herbal medicine and cosmetics, was developed. The objectives of the present work were to provide recommendations for the optimal extraction conditions and to investigate the effects of any extraction parameters on flavonoid yields from the <em>I. javanica</em> flower. The extraction process was performed using deep eutectic solvent (DES) (choline chloride and propylene glycol at molar ratio of 1:1) and ultrasound-assisted extraction (UAE) method. Both single-factor and response surface analyses using three-level and three-factor Box Behnken designs were conducted to obtain the optimum flavonoid concentrations. The results showed that the optimum extraction conditions for total flavonoids featured an extraction time of 40 min, 25% water content in DES, and a solid-to-liquid ratio of 1:25 g/mL. An extract obtained under optimum extraction conditions showed higher total flavonoid yields than an ethanolic extract which was used for comparison. Scanning electron microscope (SEM) images demonstrated that both of the solvents also showed different effects on the outer surface of the <em>I. javanica</em> flower during extraction process. In sum, our work succeeded in determining the optimum conditions for total flavonoids in the <em>I. javanica</em> flower using a green extraction method.</p>
RNA Ensembles From Solvent Accessibility Data: Application to the SAM-I Riboswitch Aptamer Domain
<p>SASA-derived ensembles of the -SAM and +SAM states of the SAM-responsive riboswitch.</p>
Wavefunction for the lithium electride ROGDAS in a continuum solvent water
<p>Wavefunction for the lithium electride ROGDAS in a continuum solvent water at the wB97XD/6-31+G9d)/SCRF=water level</p>
Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"
<p>This dataset contains three archives. The first archive, full_dataset.zip, contains geometries and free energies for nearly 44,000 solute molecules with almost 9 million conformers, in 42 different solvents. The geometries and gas phase free energies are computed using density functional theory (DFT). The solvation free energy for each conformer is computed using COSMO-RS and the solution free energies are computed using the sum of the gas phase free energies and the solvation free energies. The geometries for each solute conformer are provided as ASE_atoms_objects within a pandas DataFrame, found in the compressed file dft coords.pkl.gz within full_dataset.zip. The gas-phase energies, solvation free energies, and solution free energies are also provided as a pandas DataFrame in the compressed file free_energy.pkl.gz within full_dataset.zip. Ten example data splits for both random and scaffold split types are also provided in the ZIP archive for training models. Scaffold split index 0 is used to generate results in the corresponding publication. </p><p>The second archive, refined_conf_search.zip, contains geometries and free energies for a representative sample of 28 solute molecules from the full dataset that were subject to a refined conformer search and thus had more conformers located. The format of the data is identical to full_dataset.zip.</p><p>The third archive contains one folder for each solvent for which we have provided free energies in full_dataset.zip. Each folder contains the .cosmo file for every solvent conformer used in the COSMOtherm calculations, a dummy input file for the COSMOtherm calculations, and a CSV file that contains the electronic energy of each solvent conformer that needs to be substituted for "EH_Line" in the dummy input file.</p>
Supplementary information: Specific versus Nonspecific Solvent Interactions of a Biomolecule in Water [Dataset]
<p><strong>Data availability</strong><strong> to the manuscript </strong><em>"</em>Specific versus Nonspecific Solvent Interactions of a Biomolecule in Water<em>"</em> by <strong>Lanhai He, Lukáš Tomaník, Sebastian Malerz, Florian Trinter, Sebastian Trippel, Michal Belina, Petr Slavíček, Bernd Winter, and Jochen Küpper</strong>, pubulished at<em> JPCL </em></p> <p>The dataset contains the complete x-ray photoelectron-emission spectra of indole<sub>aq</sub> in a liquid microjet. The uploaded files include:</p> <ul> <li>Valence band PES data (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0053VB.ibw">May02_0053VB.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0058VB_background.ibw">May02_0058VB_background.ibw</a>),</li> <li>core level PES data (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0045C1s.ibw">May02_0045C1s.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0049N1s.ibw">May02_0049N1s.ibw</a>),</li> <li>Auger PES pectra (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0052CAuger.ibw">May02_0052CAuger.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0057CAuger.ibw">May02_0057CAuger.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0056NAuger.ibw">May02_0056NAuger.ibw</a>)</li> <li>rough-scanned full spectra (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0046Full.ibw">May02_0046Full.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0047Full.ibw">May02_0047Full.ibw</a>).</li> </ul> <p>In addition, a python script (Read_ibw_file.py) has been uploaded, which can be used to read raw PES data files in .ibw format and export the intergraded PES data as a .txt file.</p>
Supporting materials for: pKa Prediction in Non-Aqueous Solvents
<p>This repository includes datasets and supplementary materials for the manuscript: "pKa Prediction in Non-Aqueous Solvents" by Jonathan W. Zheng, Emad Al Ibrahim, and William H. Green. <strong>Citations should refer directly to the manuscript:</strong></p> <blockquote> <p>Zheng, J. W., Al Ibrahim, E., Kaljurand, I., Leito, I., & Green, W. H. (2024). pKa Prediction in Non-Aqueous Solvents. <em>Journal of Computational Chemistry (2024), </em>doi:10.1002/jcc.27517</p> </blockquote> <p>This compilation includes the predicted and experimental pKa values for all compounds studied in the corresponding work, as well as .xyz files corresponding to all conformers used in the COSMO-RS calculations. </p> <p>For the <strong>.csv </strong>files, column <code>pKa_exp</code> corresponds to the originally-reported experimental value whereas <code>pKa_OK</code> corresponds to the corrected value.</p> <p>The data from <strong>low_error_solvent_preds.csv</strong> and <strong>high_error_solvent_preds.csv</strong> and <strong>unreliable_solvent_preds.csv</strong> are formatted in part based on their compilation in the source manuscript: <em>Busch, M., Ahlberg, E., Ahlberg, E., & Laasonen, K. (2022). How to Predict the pKa of Any Compound in Any Solvent. ACS Omega, 7(20), 17369-17383.</em></p> <p> </p> <ul> <li>Note on version Aug. 28, 2024: fixed erroneous SMILES for several of the benzoic acids in the test set.</li> <li>Note on version Nov. 18, 2024: updated many of the values in the training and test sets, excluding some values and correcting others. SMILES (and corresponding .xyz files) for two values in the test set were updated. </li> </ul>
Metadata of "Solvent-free Reactions for the Synthesis of Indolenine-based Squaraines and Croconaines: Comparison of Thermal Heating, Mechanochemical Milling, and IR Irradiation"
<p>Metadata of "Solvent-free Reactions for the Synthesis of Indolenine-based Squaraines and Croconaines: Comparison of Thermal Heating, Mechanochemical Milling, and IR Irradiation"</p>
Supporting Data for Electrolyte-Induced Instability of Colloidal Dispersions in Nonpolar Solvents (J. Phys. Chem. Lett., doi:10.1021/acs.jpclett.7b01685)
<p>Raw data: interaction force curves (separation [m], force [N], error force [N]) and small-angle neutron scattering curves (Q [1/Å], I(Q) [1/cm], error I(Q) [1/cm]).</p>
Supporting data for "Charging Poly(methyl Methacrylate) Latexes in Nonpolar Solvents: Effect of Particle Concentration" (Langmuir, doi:10.1021/acs.langmuir.7b02257)
<p>Raw data:</p> <p>- Electrophoretic mobilities as a function of particle concentration (Volume fraction phi [unitless, volume per volume], mu [m^2/(V s)], error mu [m^2/(V s]).</p> <p>- Small-angle neutron scattering curves (Q [1/Å], I(Q) [1/cm], error I(Q) [1/cm]).</p> <p>- Small-angle X-ray scattering curves (Q [1/Å], I(Q) [unitless, instrument intensity divided by fit scale]).</p>
Water Solvent Reorganization upon Ultrafast Resonant Stimulated X‑ray Raman Excitation of a Metalloporphyrin Dimer
<p><strong>Abstract</strong></p> <p>We propose an X-ray Raman pump - X-ray diffraction probe scheme to follow solvation dynamics upon charge migration in a solute molecule. The X-ray Raman pump selectively prepares a valence electronic wavepacket in the solute, while the probe provides information on the entire molecular ensemble. A combination of Molecular Dynamics (MD) and <em>ab initio</em> quantum chemistry simulations is applied to a Zn-Ni porphyrin dimer in water. Using time-resolved X-ray diffraction and pair distribution functions, solvation shell dynamics are extracted.</p> <p><strong>Datasets for the plots</strong></p> <p>data_rdf: Contains RDF data in netcdf4 (readable by xarray) and averaged CSV files.</p> <p>data_sfac: Contains scattering data in netcdf4 (readable by xarray) and averaged CSV files.</p> <p>data_ener: Contains CP2K energy file data for all reference and production runs.</p> <p>data_cdf: Contains csv data files for cumulative distribution function.</p> <p>data_sdf: Contains the cubes files for spatial distribution function.</p> <p>python_codes: Contains python code snippets for recreating figures from the above datasets.</p>
Solvent-triggered shape change in gradient-based 4D printed bilayers: case study on semi-crystalline polymer networks
<p>This dataset comes from the following paper:</p> <p>Lorenzo Bonetti, Aron Cobianchi, Daniele Natali, Stefano Pandini, Massimo Messori, Maurizio Toselli, Giulia Scalet, Solvent-triggered shape change in gradient-based 4D printed bilayers: case study on semi-crystalline polymer networks, Soft Matter, 2024. <a href="https://doi.org/10.1039/D4SM00304G" target="_blank" rel="noopener">https://doi.org/10.1039/D4SM00304G</a></p> <p>It contains:</p> <ul> <li>"Notes.pdf" describing all the files uploaded</li> <li>.xls files of the experimental data</li> <li>. m of the theoretical computations</li> </ul>
Green Extraction of depsidones and depsides from H. physodes using Natural Deep Eutectic Solvents
Open the record for dataset details and reuse information.
Dataset for 'Chaperone Solvent Assisted Assembly of Polymers at the Interface of Two Immiscible Liquids'
<p><span>The authors acknowledge financial support from the Research Grants Council of Hong Kong (Project No.21304421), the National Natural Science Foundation of China (Project No. 22003053), the Natural Science Foundation of Guangdong Province, China (Project No. 2023A1515011457),</span><span> </span><span>the Natural Science Foundation of Sichuan Province, China (Project No. 2023NSFSC0312), CityU Strategic Interdisciplinary Research Grant (Project No. 2020SIRG035), and</span><span> Hong Kong Institute for Advanced Study. The authors also thank OpenAI for editing.</span></p>
Determination of secondary species in solution through pump-selective transient absorption spectroscopy and explicit-solvent TDDFT
<p>Explicit and implicit solvent TDDFT of alizarin and tautomers of alizarin in methanol. Transient electronic absorption spectroscopy of alizarin in methanol at different pH values. </p>
High performance cation exchange membranes synthesized via in-situ emulsion polymerization without organic solvents and corrosive acids
<p>Dataset supporting journal publication:</p> <p><strong>Abstract:</strong> The synthesis of cation exchange membranes (CEMs) usually involves using organic solvents and/or sulfonation process. In this study, green and scalable synthesis of high performance CEMs is achieved without organic solvents and sulfonation. The synthesis is carried out via in-situ polymerization of lithium styrene sulfonate in porous support. Different preparation procedures are developed and optimized. Functional sulfonate groups were successfully loaded onto and into the membrane support, as verified by FTIR. Besides, water plays an important role during membrane synthesis. By reducing the amount of water used, the ratio of functional polymers to membrane support in the synthesized CEMs is increased. Therefore, the synthesized CEMs show increased ion exchange capacity (IEC). This is significant because it means that high IEC can be achieved without introducing cation exchange resins to the membranes. Finally, the synthesized membranes demonstrate high desalination performance. This new methodology may shed new light on preparing CEMs in an efficient and eco-friendly way.</p>
Computer-aided design of optimal environmentally benign solvent-based adhesive products
<p>The files contain all the product design problems implemented in GAMS for this publication. All models were run on a single core of a dual 8 core Intel(R) Xeon(R) CPU E5-2650 machine at 3.52 GHz with 125GB of memory.</p> <p> </p> <p><strong>Abstract</strong></p> <p>In this work, a general systematic methodology for the design of optimal adhesive products with low environmental impact is presented. The proposed approach integrates computer-aided design tools and Generalised Disjunctive Programming to formulate and solve the product design problem. Key design decisions in product design (number of ingredients, identity of compounds and their proportions) are optimised simultaneously. This methodology is applied to the design of solvent-based acrylic adhesives, which are commonly used in construction. First, optimal product formulations are determined with the aim to minimize toxicity. This reveals that that high performance can be achieved by investigating different number of components as well as by optimising all ingredients simultaneously rather than sequentially. The relation between two competing objectives is then explored by obtaining a set of Pareto optimal solutions. This leads to significant trade-offs and large areas of discontinuity driven by discrete changes in the list of optimal product ingredients.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.