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189 results for “thermodynamics”
Thermodynamic Evolution of Cerium Oxide Nanoparticle Morphology Using Carbon Dioxide Dataset
<p>Data supporting the publication "Thermodynamic Evolution of Cerium Oxide Nanoparticle Morphology Using Carbon Dioxide"</p> <p>DOI : <a href="https://doi.org/10.1021/acs.jpcc.0c07437">10.1021/acs.jpcc.0c07437</a></p> <p>URL : https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.0c07437</p> <p>Contained within are the the initial and final configurations from the VASP calculations.</p> <p>We used the Ce, O and C POTCAR.</p> <p>We used a KPOINT mesh of 2 x 2 x 1</p> <p>An example INCAR has been include.</p> <p> </p>
Dataset for "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena"
<p>This dataset was used to fit a general purpose machine-learning interatomic potential for Mo-Si alloys based on the Atomic Cluster Expansion (ACE) formalism. It supports the paper "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena".</p>
Contents for: Influence of Ionization on the Polytropic Index of the Solar Atmosphere within Local Thermodynamic Equilibrium Approximation
<p>This is the data used for the creation of the manuscript figures. Explanation about the data is in the "README.txt" file. Version 2 includes compressed archive file containing Fortran module files with subroutines and input data files for the calculations of the study.</p>
Thermodynamic parameters and elasticity data of phase D at high pressures and temperatures
<p>This dataset contains all the original data for figures in the article "Thermoelasticity of phase D and implications for low-velocity anomalies and local discontinuities at the uppermost lower mantle" submitted to American Mineralogist.</p>
The results of thermodynamic calculations for alloys presented in a paper published in Journal of Materials Research and Technology, 2023, 27, pp. 6182–6191
<p>Thermophysical data for the alloys developed within the project. The results have been published in ournal of Materials Research and Technology, 2023, 27, pp. 6182–6191.</p>
NOAA PSL thermodynamic profiles retrieved from a combination of active and passive remote sensors and numerical weather prediction models with the optimal estimation physical retrieval TROPoe at Platteville, CO, USA
<p>This dataset contains retrieved profiles of thermodynamic variables obtained using the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval from various combinations of input data collected by passive and active remote sensing instruments, in-situ surface platforms, and numerical weather prediction models deployed at the Platteville, CO, USA, site in fall 20221-winter 2022. Among the employed instruments are Microwave Radiometers (MWRs), Infrared Spectrometers (IRS), Radio Acoustic Sounding Systems (RASS), ceilometers, surface sensors, and information from the operational Rapid Refresh numerical weather prediction model.</p> <p>The dataset also includes 15 radiosounding launched for assessing the retrievals.</p> <p>For further information, please see:</p> <p>Bianco, L., Adler, B., Bariteau, L., Djalalova, I. V., Myers, T., Pezoa, S., Turner, D. D., and Wilczak, J. M.: Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2023-263, in review, 2024.</p>
Evaluating quantum alchemy of atoms with thermodynamic cycles: Beyond ground electronic states
<p>Data at the time of submission.</p>
Data Archive for "Nonequilibrium Statistical Thermodynamics of Multicomponent Interfaces"
<p>Selected data, including certain simulation output, analysis scripts, and processed data files used for figures.</p>
Removal of Crystal Violet (CV) in aqueous solution by Activated Carbon- Equilibrium, kinetic and Thermodynamic
<p>The quantitative kinetic and equilibrium adsorption parameters for Crystal Violet (CV) removed by commercial activated carbon (AC) were studied by UV visible absorption spectroscopy. (AC) with a high specific surface area (1250.320m2 /g) was characterized by the Brunauer-Emmett-Teller (BET) method and the zero charge point (pzc).The adsorptive properties of (AC) with (CV) was conducted at variable stirring speed , adsorbent dose, solution pH, initial (CV) concentrations, contact time and temperature using batch mode operation to find the optimal conditions for a maximum adsorption. The adsorption mechanism of CV onto (AC) was studied using the first pseudo order, second pseudo order and Elovich kinetic models. The kinetic was found to follow a pseudo-second order kinetic model. The equilibrium adsorption data for CV on AC were analyzed by the Langmuir, Freundlich, Elovich and Temkin models. The results indicate that the Langmuir model provides the best correlation (qmax = 35.71, 90.91 mg/g at 25 °C and 40 °C respectively).The adsorption isotherms at different temperatures have been used for the determination of thermodynamic parameters i.e. the free energy (ΔGo = -2.30 to -5.34 kJ/mol), enthalpy (ΔHo = 36.966 kJ/mol), entropy (ΔSo = 0.131 kJ/mol K) and activation energy (Ea) 40.208 kJ/mol of adsorption. The negative ΔGo and positive ΔHo values indicate that the overall adsorption is spontaneous and endothermic in nature</p>
Structural changes across thermodynamic maxima in supercooled liquid tellurium: a water-like scenario
<p>This dataset contains all numerical data used to produce the figures in the manuscript, arXiv:2201.06838 by P. Sun et al. (2022).</p> <p>Please see the README file for more information.</p>
Dataset for: Conformational and Thermodynamic Differences Underlying Wild-type and Mutant YEATS Domain Specificity for Epigenetic Marks
<p>The set of molecular dynamics trajectories generated and analyzed in the paper "Conformational and Thermodynamic Differences Underlying Wild-type and Mutant YEATS Domain Specificity for Epigenetic Marks." <strong>Citations should refer directly to the manuscript. </strong> The preprint version is available at: https://doi.org/10.1101/2022.07.14.500085</p> <p>The uploaded zip file "trajectory_data.zip" contains trajectories for the (1) apo (2) h3k27ac and (3) h3k9ac systems. In each directory is a subdirectory corresponding to the wild-type, deletion, and insertion mutations. In each of those subdirectories are 10 XTC files, which correspond to the trajectories for the 10 different simulations performed for each system, along with an AMBER-formated PRMTOP file. Solvent molecules were removed from each file, and trajectories were strided such that there is one frame per 500 ps. </p>
Dataset to "Local thermodynamic description of isothermal single-phase flow in simple porous media"
<p>This is the dataset presented in the article "Local thermodynamic description of isothermal single-phase flow in porous media" [1]. This dataset contains three files: "equilibrium.out", "equilibrium_bulk.out", and "flow.out". The first file contains data for equilibrium simulations of the porous medium, while the second file contains data for equilibrium simulations of bulk fluid, and the third file contains data for non-equilibrium simulations of the porous medium.</p> <p>[1] https://doi.org/10.1007/s11242-022-01844-x</p> <p><strong>In the file "equilibrium.out" the columns from left to right are</strong></p> <ol> <li>Temperature</li> <li>Standard deviation of the temperature</li> <li>Lattice constant</li> <li>Fluid chemical potential</li> <li>Potential energy</li> <li>Standard deviation of the potential energy</li> <li>Kinetic energy</li> <li>Standard deviation of the kinetic energy</li> <li>Fluid mass density</li> <li>Standard deviation of the fluid mass density</li> </ol> <p><strong>In the file "equilibrium_bulk.out" the columns from left to right are</strong></p> <ol> <li>Temperature</li> <li>Standard deviation of the temperature</li> <li>Fluid chemical potential</li> <li>Potential energy</li> <li>Standard deviation of the potential energy</li> <li>Kinetic energy</li> <li>Standard deviation of the kinetic energy</li> <li>Fluid mass density</li> <li>Standard deviation of the fluid mass density</li> <li>Trace of the mechanical pressure tensor divided by 3</li> <li>Standard deviation of the trace of the mechanical pressure tensor divided by 3</li> </ol> <p><strong>In the file "flow.out" the columns from left to right are</strong></p> <ol> <li>Temperature</li> <li>Standard deviation of the temperature</li> <li>Lattice constant</li> <li>Fluid chemical potential</li> <li>Passing probability of reflecting particle method (RPM)</li> <li>Mass flux</li> <li>Standard deviation of the mass flux</li> <li>Integral pressure gradient</li> <li>Standard deviation of the integral pressure</li> </ol>
Increasing the thermodynamic driving force of the phosphofructokinase reaction in Clostridium thermocellum
<p>Glycolysis is an ancient, widespread, and highly conserved metabolic pathway that converts glucose into pyruvate. In the canonical pathway, the phosphofructokinase (PFK) reaction plays an important role in controlling flux through the pathway. <em>Clostridium thermocellum</em> has an atypical glycolysis and uses pyrophosphate (PPi) instead of ATP as the phosphate donor for the PFK reaction. The reduced thermodynamic driving force of the PPi-PFK reaction shifts the entire pathway closer to thermodynamic equilibrium, which has been predicted to limit product titers. In this work, we replace the PPi-PFK reaction with an ATP-PFK reaction. We demonstrate that the local changes are consistent with thermodynamic predictions: the ratio of fructose 1,6-bisphosphate to fructose-6-phosphate increases, and the reverse flux through the reaction (determined by <sup>13</sup>C labeling) decreases. The final titer and distribution of fermentation products, however, do not change, demonstrating that the thermodynamic constraints of the PPi-PFK reaction are not the sole factor limiting product titer.</p>
Thermodynamics of the metal-insulator transition in the extended Hubbard model from determinantal quantum Monte Carlo
<p>This zip archive contains the DQMC data sets for the \beta=1/T resolved double<br> occupancy, internal energy per site, antiferromagnetic structure factor and<br> charge density wave structure factor obtained with the ALF Code.<br> The computations have been carried out on a square lattice at half filling for<br> the Hubbard model, the U-V model and the long-range Coulomb(LRC)-Hubbard model.<br> Every model is computed at fixed U/t=1.9.</p> <p>The naming convention of the csv-files is the following:<br> V0.0 = Hubbard model<br> V0.x = U-V model with V/t=0.x<br> Vcx.x = LRC-Hubbard model with V_C/t=x.x<br> <br> - dat_docc_{\Delta\tau}_V{x}.csv = double occupancy at \Delta\tau={0.05, 0.1, 0.2}<br> - dat_docc_{\Delta\tau}_V{x}_err.csv = corresponding statistical error<br> - dat_energy_0.1_V{x}.csv = internal energy at \Delta\tau=0.1<br> - dat_energy_0.1_V{x}_err.csv = corresponding statistical error<br> - dat_saf_0.1_V{x}.csv = antiferromagnetic structure factor at \Delta\tau=0.1<br> - dat_saf_0.1_V{x}_err.csv = corresponding statistical error<br> - dat_scdw_0.1_V{x}.csv = charge density wave structure factor at \Delta\tau=0.1<br> - dat_scdw_0.1_V{x}_err.csv = corresponding statistical error</p> <p>The structure of each file is to be read column-wise:<br> \beta, L=8, L=10, L=12, L=16, L=18, L=20</p> <p> </p>
The planted XY model: thermodynamics and inference
<p>Data and codes for figures in manuscript "The planted XY model: thermodynamics and inference"</p>
Dataset for A thermodynamic criterion for the formation of Circumplanetary disks
<p>This repository includes data to reproduce the Fiugres of the manuscript entitled "A thermodynamics criterion for the formation of circumplanetary disks"</p>
Thermodynamics of alkali feldspar solid solutions with varying Al–Si order: atomistic simulations using a neural network potential - Accompanying Data
<p>This dataset accompanies the manuscript: "Thermodynamics of alkali feldspar solid solutions with varying Al–Si order: atomistic simulations using a neural network potential". It contains:</p> <ul> <li>LAMMPS-data files of the relaxed 8x6x8 systems for the three ordering types across Na-K composition, </li> <li>template input files for the minimization and for the semi grand canonical Monte Carlo + molecular dynamics simulation,</li> <li>the training and testing data with and without the point charge correction,</li> <li>the neural network potential committee and a modified n2p2 source that is necessary for running the special weighted atom centered symmetry functions. </li> </ul> <p>The algorithm to create the Al-Si and Na-K disorder is hosted on <a href="https://github.com/alexgorfer/Alkali-feldspar-disorder-generator">https://github.com/alexgorfer/Alkali-feldspar-disorder-generator</a> instead.</p>
Thermodynamic (p, ρ, T) characterization of a reference high-calorific natural gas mixture when hydrogen is added up to 20 % (mol/mol)
<p>File: 1-s2.0-S0360319924017166-mmc1.docx</p> <p>This file (DOCX) is a supplementary file that contains the mixture preparation chart and auxiliary mixture validation data.</p> <p>File: 2024_IJHE_Results_Repository.xlsx</p> <p>This file (XLSX) contains tables with the density data of the systems investigated.</p> <p>File: 2024_IJHE_Manuscript_repository.docx</p> <p>This is an author-created, un-copyedited version of an article accepted for publication in the International Journal of Hydrogen Energy (2024, 70, 118-135). The editor of the Journal is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher-authenticated, Open-Access version is available online at: https://doi.org/10.1016/j.ijhydene.2024.05.028</p>
Thermophysical properties of hydrogen mixtures relevant for the development of the hydrogen economy: Review of available experimental data and thermodynamic models
<p>File: 1-s2.0-S096014812201271X-mmc1.docx</p> <p>This file (DOCX) contains additional figures associated with the hydrogen-containing systems.</p> <p>File: 1-s2.0-S096014812201271X-mmc2.xlsx</p> <p>This file (XLSX) contains tables with the coordinates of the VLE associated with the hydrogen-containing systems.</p> <p>File: 1-s2.0-S096014812201271X-mmc3.xlsx</p> <p>This file (XLSX) contains tables with the density data associated with the hydrogen-containing systems.</p> <p>File: 1-s2.0-S096014812201271X-mmc4.xlsx</p> <p>This file (XLSX) contains tables with the calorific data associated with the hydrogen-containing systems.</p> <p> </p> <p>File: 2022_Renewable Energy_Manuscript_repository.docx</p> <p>This is an author-created, un-copyedited version of an article accepted for publication in Renewable Energy (2022, 198, 1398-1429). The editor of the Journal is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher-authenticated, Open-Access version is available online at: https://doi.org/10.1016/j.renene.2022.08.096</p>
Thermodynamic characterization of the (H2 + C3H8) system significant for the hydrogen economy: Experimental (p, rho, T) determination and equation of-state modelling
<p>File: 2023_IJHE_Manuscript_repository.docx</p> <p>This is an author-created, un-copyedited version of an article accepted for publication in the International Journal of Hydrogen Energy (2023, 48 (23), 8645-8667). The editor of the Journal is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher-authenticated, Open-Access version is available online at: https://doi.org/10.1016/j.ijhydene.2022.11.170<br><br>File: 2023_IJHE_Results_Repository.xlsx</p> <p>This is the MS Excel data file of the paper. </p> <p> </p> <p> </p>
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Allen Brain Atlas
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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.