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194 results for “solvent”
Dataset for "Modeling Dipolar Nonprotogenic Solvents with PC-SAFT-Type Equations of State: Pure Substance Properties"
<p>Dipolar nonprotogenic solvents (DNS) are important chemical substances used across a wide range of applications, including renewable green solvent media, sustainable energy sources, and as efficient solvents for fabricating and processing semiconductive materials used in organic photovoltaics. Therefore, for efficient solvent screening or process design, a description and prediction of the thermodynamic properties of DNS using thermodynamic models is essential. This dataset contains calculation results of four different modeling strategies within the PC-SAFT equation of state for pure-substance properties of six DNSs: gamma-valerolactone, propylene carbonate, acetonitrile, dihydrolevoglucosenone, 1-methyl-2-pyrrolidone, and sulfolane. The modeling strategies differ in the treatment of the strong dipolar interactions of DNSs. The pure-substance properties include liquid density, vapor pressure, enthalpy of vaporization, and residual isobaric liquid heat capacity. The PC-SAFT performance was analyzed and evaluated based on the calculated data. Additionally, the dataset includes input files for quantum mechanical calculations of optimal molecular geometries and dipole moments of the considered DNSs using Gaussian 16 software.</p>
Aquamarine: Quantum-Mechanical Exploration of Conformers and Solvent Effects in Large Drug-like Molecules
<p>Open challenges in computational drug design include the understanding and accurate description of solvent effects as well as collective dispersion interactions for realistic drug-like molecules. Both interactions profoundly influence the conformational stability of drug molecules and, consequently, the determination of other important quantum-mechanical (QM) observables. In this context, we here introduce the Aquamarine (AQM) dataset -- an extensive QM dataset that contains the structural and electronic information -- of 59,786 low-and high-energy conformers of 1,653 molecules containing up to 54 non-hydrogen atoms (including C, N, O, F, P, S and Cl). To gain insights into the solvent effects, we have carried out QM calculations of structures and properties in gas phase and in an aqueous solution modeled with implicit solvent. AQM contains over 40 global (molecular) and local (atom-in-a-molecule) physicochemical properties (including ground-state and response properties) per molecular structure computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD supplemented with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By treating both molecule-solvent and dispersion interactions, the AQM dataset can help understand the impact of both interactions in structure-property and property-property relationships of realistic drug-like molecules. Therefore, we propose the AQM dataset as a benchmark for current state-of-the-art machine learning methods for property prediction as well as for the <em>de novo</em> generation of large and flexible (solvated) molecules with pharmaceutical and biological relevance.</p>
The effect of solvent on convectively-driven silica particle assembly: Decoupling surface tension,viscosity, and evaporation rate
<p>Dataset associated with 'The effect of solvent on convectively-driven silica particle assembly: Decoupling surface tension, viscosity, and evaporation rate’.</p> <p>The data is based on the figures below, published in the linked article (see the doi).</p> <p><strong>- Figure 1. S</strong>egmented and raw images of dip-coated films. <strong>(images, .TIF)</strong></p> <p><strong>- Figure 2. </strong>Calculated surface coverages <strong>(data, .csv)</strong></p> <p><strong>- Figure 3. </strong>Rheology on SiO<sub>2</sub>-iPrOH-Glycerol mixtures & SEM micrographs of particle films. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure 4. </strong>SEM micrographs of silica helices films. <strong>(images, .TIF)</strong></p> <p><strong>- Figure S1. </strong>Measured evaporated masses of each solvent as a function of time. <strong>(data, .csv)</strong></p> <p><strong>- Figure S2. </strong>TEM micrographs of SiO2 seeds and measured particle diameters. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure S3. </strong>TEM micrographs of SiO particles and measured particle diameters. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure S4. </strong>Calculated solvent fractions as a function of time. <strong>(data, .csv)</strong></p> <p><strong>- Figure S5.</strong> Rheology of i-PrOH-glycerol mixtures.<strong> (data, .csv)</strong></p>
Stability Increase of Phenolic Acid Decarboxylase by a Combination of Protein and Solvent Engineering Unlocks Applications at Elevated Temperatures
<p>Enzymatic decarboxylation of biobased hydroxycinnamic acids gives access to phenolic styrenes for adhesive production. Phenolic acid decarboxylases are proficient enzymes that have been applied in aqueous systems, organic solvents, biphasic systems, and deep eutectic solvents, which makes stability a key feature. Stabilization of the enzyme would increase the total turnover number and thus reduce the energy consumption and waste accumulation associated with biocatalyst production. In this study, we used ancestral sequence reconstruction to generate thermostable decarboxylases. Investigation of a set of 16 ancestors resulted in the identification of a variant with an unfolding temperature of 78.1 °C and a half-life time of 45 h at 60 °C. Crystal structures were determined for three selected ancestors. Structural attributes were calculated to fit different regression models for predicting the thermal stability of variants that have not yet been experimentally explored. The models rely on hydrophobic clusters, salt bridges, hydrogen bonds, and surface properties and can identify more stable proteins out of a pool of candidates. Further stabilization was achieved by the application of mixtures of natural deep eutectic solvents and buffers. Our approach is a straightforward option for enhancing the industrial application of the decarboxylation process.</p>
Solute particle near a nanopore: influence of size and surface properties on the solvent-mediated forces: ftDFT code
<p>This is the complete ftDFT code used to generate the results reported in our Nov 2017 Nanoscale article "Solute particle near a nanopore: influence of size and surface properties on the solvent-mediated forces",DOI: 10.1039/C7NR07218J. </p>
Data for Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents
<div> <p>Full set of data related to the publication "Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents", published in ACS Nano with DOI:<a title="https://doi.org/10.1021/acsnano.4c01950" href="https://doi.org/10.1021/acsnano.4c01950">10.1021/acsnano.4c01950</a></p> <p> Full details on data treatment and logging are included in the file "DataLogging.pdf". All data use ASCII encoding in delimited .txt files.</p> <p> </p> </div>
Concentration-, Temperature- and Solvent-Dependent Self-Assembly: Merocyanine Dimerization as a Showcase Example for Obtaining Reliable Thermodynamic Data
<p><strong>Abstract:</strong> Mathematical models for the concentration-, temperature- and solvent-dependent analysis of self-assembly equilibria are derived for the most simple case of dimer formation, to highlight the assumptions these models and the thus determined thermodynamic parameters are based on. The three models were applied to UV/Vis absorption data for the dimerization of a highly dipolar merocyanine dye in 1,4-dioxane. Isothermal titration calorimetry (ITC) dilution experiments were performed as an independent reference technique. While the concentration-dependent analysis is according to our studies the most reliable method, also the less time-consuming temperature-dependent evaluation can give accurate results in the present example, despite small thermochromic effects. In contrast, the strong negative solvatochromism of the merocyanine tampers with the results from the solvent-dependent evaluation. Even though the studies presented in this work are limited to the monomer-dimer equilibrium of a dipolar dye, the basic principles can be transferred to other chromophores and different self-assembly models, including those for supramolecular polymerization.</p>
Raw data for the article: High-throughput computational solvent screening for lignocellulosic biomass processing
<p>This data set contains the raw data for the article "High-throughput computational solvent screening for lignocellulosic biomass processing" published in <em>Chemical Engineering Journal</em>, DOI: <a href="https://doi.org/10.1016/j.cej.2022.139476">https://doi.org/10.1016/j.cej.2022.139476</a></p>
The influence of the properties of inorganic solvents on the hydrodynamic diameter of TiO2 nanoparticles
<p>In this model the property of a nanomaterial is predicted not on the basis of descriptors characterizing the chemical composition of nanoparticles or physical properties of the initial nanoforms, but on the basis of descriptors describing the dispersion medium (pH, IP, D3_HeteroNonMetals) and the property of nanoparticles dependent on it (Potential ζ). </p> <p>The observed small size of the hydrodynamic diameter of TiO2 in solvents of strong acids and bases compared to other solvents may indicate stronger repulsive interactions between nanoparticles than in the case of other systems. Moreover, in the case of salt solutions, the observed large size of the hydrodynamic diameter of TiO2 may be the result of a thicker electrical layer surrounding the particles in the dispersion system.</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff96)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff96 and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff99SB-ildn)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff99SB-ildn and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Input Data for "Molecular Lignin Solubility and Structure in Organic Solvents"
<p>Input structures for a manuscript, along with selected output data and structures. This directory structure contains a cut-down copy of the directories used to generate the simulation data and the analysis. In order to make this fit into the 50GB Zenodo limit, it was constructed with the following tar command: `tar -zcvf ligninsolvationstudy.tar.gz --exclude="*BAK" --exclude="*#" --exclude="*xtc" --exclude="*gro" --exclude="*log" --exclude="*[0-9].out" --exclude="*npz" --exclude="*pkl" --exclude="*npy" --exclude="*png" --exclude="*bmim*" --exclude="*old" --exclude="*dcd" --exclude="*tmp" --exclude="*xst" --exclude="*edr" --exclude="*txt" --exclude="*state_prev.cpt" LigninSolvation`, which intentionally excludes large files. The full dataset is available upon request.</p> <p><strong>Directory Descriptions</strong></p> <p><strong>BuildSolventBoxes</strong> contains the scripts and inputs needed to make the solvent boxes suitable for use with the VMD solvate plugin.<br> <strong>BuildSystems</strong> assembles the lignin polymers and solvates them into a complete simulation system. Depends on the outputs from [LigninBuilder](https://github.com/jvermaas/LigninBuilder).<br> <strong>Equilibrium</strong> has all the equilibrium trajectories and the scripts needed to set them up.<br> <strong>FEP</strong> has the free energy perturbation calculation key outputs (the fepout files) and the scripts needed to set up the calculation and analyze them.</p> <p>The scripts are <em>mostly</em> python scripts, but some are also in tcl, and have the appropriate file endings. GROMACS run input files (.tpr) and namd configuration files (.namd) may also be of general interest.</p>
Solvent Engineered Synthesis of SnO Nanoparticles for High-Performance Anodes
<p>Batteries are the most abundant form of electrochemical energy storage. Lithium and sodium ion batteries account for a significant portion of the battery market, but high-performance electrochemically active materials still need to be discovered and optimized for these technologies. Recently, tin(II) oxide (SnO) has emerged as a highly-promising battery electrode. In this work, we present a facile synthesis method to produce SnO nanoparticles whose size and shape can be tailored by changing the solvent nature. We study the complex relationship between wet chemistry synthesis conditions and resulting nanoparticle morphology. Furthermore, high-level electronic structure theory, including dispersion corrections to account for van der Waals forces, are employed to augment our understanding of the underlying chemical mechanisms. The electronic vacuum alignment and surface energies are determined, allowing the prediction of the thermodynamically-favoured crystal shape (Wulff construction) and surface-weighted work function. Finally, the synthesized nanomaterials were tested as Li-ion battery anodes, demonstrating significantly enhanced electrochemical performance for morphologies obtained from specific synthesis conditions. </p> <p>Open-access publication in npj 2D Mater & Appl <a href="https://rdcu.be/cgdWZ">here</a>.</p>
Dataset for "A QM-CAMD approach to solvent design for optimal reaction rates"
<p>Dataset accompanying "A QM-CAMD approach to solvent design for optimal reaction rates". </p> <p>All Gaussian09 files for Step 2 of the proposed QM-CAMD algorithm</p> <p>Sample GAMS file for Step 4</p> <p>Excel spreadsheet containing a summary of results for all 3 case studies</p>
Supplementary materials for Phylogenomics and genetic analysis of solvent-producing Clostridium species
<p>The genus <em>Clostridium</em> is a large and diverse group within the Bacillota (formerly Firmicutes), whose members can encode useful complex traits such as solvent production, gas-fermentation, and lignocellulose breakdown. We describe 270 genome sequences of solventogenic clostridia from a comprehensive industrial strain collection assembled by Professor David Jones that includes 194 <em>C. beijerenckiI, </em>57 <em>C. saccharobutylicum</em>, 4 <em>C. saccharoperbutylacetonicum</em>, 5 <em>C. butyricum</em>, 7 <em>C. acetobutylicum</em>, and 3 <em>C. tetanomorphum </em>genomes. We report methods, analyses and characterization for phylogeny, key attributes, core biosynthetic genes, secondary metabolites, plasmids, prophage/CRISPR diversity, cellulosomes and quorum sensing for the 6 species. The expanded genomic data described here will facilitate engineering of solvent-producing clostridia as well as non-model microorganisms with innately desirable traits. Sequences could be applied in conventional platform biocatalysts such as yeast or <em>Escherichia coli </em>for enhanced chemical production. Recently, gene sequences from this collection were used to engineer <em>Clostridium autoethanogenum</em>, a gas-fermenting autotrophic acetogen, for continuous acetone or isopropanol production<em>, </em>as well as butanol, butanoic acid, hexanol and hexanoic acid production. </p>
Solvent sites detection from molecular dynamics in mixed solvents
<p>In this zip file, you will find 3 molecular dynamics (MDs) that were run using the AMBER molecular dynamics package (https://ambermd.org/), and the necessary scripts to obtain the solvent sites.</p> <p>The MDs correspond to the kinase and rubredoxin domains of protein kinase G from Mycobacterium tuberculosis. </p> <p> </p> <p> </p>
Solute-solvent clusters
Changed <ul> <li>Reorganized <code>solute</code> and <code>solute.solvent</code> to <code>heterogeneous</code> and <code>homogeneous</code>.</li> <li>Moved selected ABCluster structures into the <code>abc</code> folders instead of having them separate.</li> </ul> Added <ul> <li>Methanol 20mers from Pires & Deturi (DOI: <a href="https://doi.org/10.1021/ct600348x">10.1021/ct600348x</a>) and Yao et al (DOI: <a href="https://doi.org/10.1063/1.4973380">10.1063/1.4973380</a>).</li> <li>Packmol generated structures of 30h2o, 112h2o, 140h2o, 30mecn, 39mecn, 30meoh, 50meoh, and 62meoh.</li> <li>ORCA MP2/def2-TZVP energy+gradient calculation of Yoo et al. boat-b 16mer.</li> <li>Methanol 4-6mer minima from Boyd et al. (DOI: <a href="https://doi.org/10.1021/ct6002912">10.1021/ct6002912</a>) with MP2/def2-TZVP engrads.</li> <li>Acetonitrile 4-6mer minima from Malloum et al. (DOI: <a href="https://doi.org/10.1002/qua.26222">10.1002/qua.26222</a>) with MP2/def2-TZVP engrads.</li> <li>Water 16mer minima from Yoo et al. (DOI: <a href="https://doi.org/10.1021/jz101245s">10.1021/jz101245s</a>) with RI-MP2/def2-TZVP engrad.</li> <li>Water 4-6mer minima from Temelso et al. (DOI: <a href="https://doi.org/10.1021/jp2069489">10.1021/jp2069489</a>) with MP2/def2-TZVP engrads.</li> <li>20 Angstrom box of water from GROMACS solvate.</li> </ul> Removed <ul> <li>Moved 12h2o.su.etal monomers, dimers, and trimers to <a href="https://github.com/keithgroup/mbgdml-h2o-meoh-mecn-engrads">another repository</a>.</li> </ul>
TERMINUS WP5: Chain Extension Kinetics for Solvent-Free Adhesive Components
<p>In two-component polyurethane (PUR) adhesives, polyols and isocyanates are reacted to produce binding media.In order to obtain a Solvent-Free prepolymer as one of PUR components, an excess of macrodiols can be reacted with diisocyanates.The addition reaction between OH and NCO functional groups is frequently called “Chain-Extension”.PUR polymerization rarely follows classical kinetic theories, therefore, experimental study was carried out to monitor the rate of polymerization.Small specimens of the reaction mixture were periodically withdrawn during the course of Chain Extension.The amount of isocyanates was measured by titration.Four different macrodiols and two diisocyanates were tested at several temperatures and concentrations.Some data on two reactions from previous Dataset 5-1 “Adhesive_Chain_Extension_WP5” is also included to broaden the range of studied temperatures. Collected data can be used for future kinetic studies of both Solvent-Based and Solvent-Free PUR adhesives.</p>
Alanine dipeptide in an implicit solvent at 300K
<p>This dataset has been introduced in the article <a href="https://arxiv.org/abs/2208.01893">Midgley, et al.: Flow Annealed Importance Sampling Bootstrap, 2022</a>.</p> <p>It contains samples from the Boltzmann distribution of alanine dipeptide in an implicit solvent, which have been generated with a Replica Exchange Molecular Dynamics (REMD) simulation. The ff96 with an OBC GBSA implicit solvent was used.</p> <p>The REMD uses 21 replicas starting at a temperature of 300K and increasing the temperature by an increment of 50K. The replicas are exchanged every 200 iterations and use the state at each multiple of 1000 time steps as samples. Many of these simulations were in parallel with different seeds. We let the system equilibrate for <span class="math-tex">\(2\times10^5\)</span> iterations and run the simulation subsequently for <span class="math-tex">\(2\times10^6\)</span> iterations.</p> <p>The data is split into a training set, which consists of <span class="math-tex">\(10^6\)</span> samples; a validation set consisting of <span class="math-tex">\(10^6\)</span> samples as well; and a test set with <span class="math-tex">\(10^7\)</span> samples.</p> <p>The data is provided as raw <span class="math-tex">\((x,y,z)\)</span>-coordinates, stored as *.h5 files, and transformed to internal coordinates, stored as *.pt files.</p> <p>More details about the data and how to use it are given in our <a href="https://github.com/lollcat/fab-torch">GitHub repository</a> and <a href="https://arxiv.org/abs/2208.01893">paper</a>.</p>
Raw Data to "Prediction of acid pKa values in the solvent acetone based on COSMO-RS"
<p>This data is a supplement to the publication entitled "Prediction of Acid pKa Values in the Solvent Acetone based on COSMO-RS" in the Journal of Computational Chemistry (DOI:10.1002/jcc.26864). The data includes initial starting structures as inputs for conformer searches using COSMOconf (versions 2020 and 2021) in combination with TURBOMOLE (version 7.3). The corresponding output files serve as inputs for the calculation of Gibbs free energies using COSMO-RS as provided by COSMOtherm.</p> <p>Additional information on the file structure is given in the README file.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.