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Supporting Data for "Thermal Transport Through CTAB- and MTAB-Functionalized Gold Interfaces using Molecular Dynamics Simulations"
<p>This gzipped tar archive contains initial configurations and parameters used for the simulations in the manuscript:</p> <p>"Thermal Transport Through CTAB- and MTAB-Functionalized Gold Interfaces using Molecular Dynamics Simulations", by Sydney A. Shavalier, and J. Daniel Gezelter</p> <p>A note on naming conventions. All simulations have filenames with with two numbers - one that signifies simulation replica (1-5), and another that signified which step of equilibration/RNEMD was being performed. For example, lowmtab111_3opt4 would signify the third simulation replica of a low coverage MTAB system and a (111) gold facet, which was on its fourth equilibration step after optimization.</p> <p>The OpenMD simulation engine utilizes a number of file extensions that are present in this archive:</p> <p><strong>.omd</strong> : A combined MetaData and configuration file that is used to start a simulation <br><strong>.frc</strong> : a force field parameter file<br><strong>.eor</strong> : an 'end of run' or final configuration (same format as .omd)<br><strong>.stat</strong> : status file with instantaneous information about energies, temperatures, etc. These are generally large and have not been included, as they can be regenerated easily from the .omd file.<br><strong>.report </strong>: a post-simulation file containing thermodynamic averages from the .stat file<br><strong>.dump</strong> : a full trajectory file containing positions and velocities sampled at a 'sampleTime' specified in the .omd file. These are generally very large and have not been included, as they can be regenerated from the .omd file.<br><strong>.rnemd</strong> : Contains spatial information about temperatures, densities, etc. for simulations run under reverse non-equilibrium molecular dynamics</p> <p>Other data analyis or utility file extensions:</p> <p><strong> .pack</strong> : Files for creating systems with Packmol<br><strong> .z</strong> : Density \rho(z) for specific selected atom types<br><strong> .r </strong> : Density \rho(r) for specific selected atom types<br><strong> .p2z</strong> : Legendre Polynomial Correlation using z as reference axis<br><strong> .p2r</strong> : Legendre Polynomial Correlation using radial vector as reference axis<br> <strong>.chargez</strong> : Charge density as a function of z-axis<br> <strong>.charger</strong> : Charge density as a function of radius<br> <strong>.agr</strong> : Grace graphing package data<br><strong> .xyz </strong> : XYZ (Cartesian) coordinates for visualization<br> </p> <p>The archive is organized as follows:</p> <p> ./CTAB/111: Simulations of Au(111) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/111/RNEMD<br> ./CTAB/110: Simulations of Au(110) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/110/RNEMD<br> ./CTAB/100: Simulations of Au(100) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/100/RNEMD<br> ./MTAB/111: Simulations of Au(111) functionalized with MTAB <br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/111/RNEMD<br> ./MTAB/110: Simulations of Au(110) functionalized with MTAB<br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/110/RNEMD<br> ./MTAB/100: Simulations of Au(100) functionalized with MTAB <br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/100/RNEMD<br> ./MTAB/NP/R10: Simulations of Au Nanoparticles (r = 10 angstroms),<br> functionalized with MTAB<br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/NP/R10/RNEMD</p> <p>Systems that were run with metal polarizability turned on have 'fq' as part of their filenames.</p>
Data repository for the paper: Sharp front tracking with geometric interface reconstruction
<h1>Data repository for the paper</h1> <h1><em>Sharp front tracking with geometric interface reconstruction</em></h1> <p> </p> <p>This repository consists of the results data for the paper "Sharp front tracking with geometric interface reconstruction" by Christian Gorges, Fabien Evrard, Robert Chiodi, Berend van Wachem and Fabian Denner. The simulation results stored in this repository have the following data format:</p> <ul> <li> <p>.txt files consisting the raw data used for the plots in the results chapter of the paper</p> </li> <li> <p>.pvtu and .vtu files containing the front mesh data for the rising bubble simulations (Paraview is an exemplary software to view the front mesh data)</p> </li> <li> <p>.py files containing python scripts serving as examples on how to use and plot the raw data of the .txt files</p> </li> </ul> <p>The main folders of this repository are named as the sections in the results chapter of the paper. For instance, the folder translating_droplet contains the data of the "Translating droplet" section. Within the main folders, sub folders contain the raw data for the specific simulations. The naming style of the raw data files and the subfolders for each section is explained in the following.</p> <p><em>stationary_droplet</em>: This main folder contains subfolders for all Laplace numbers simulated. "La_120" corresponds to a Laplace number of 120. The file names of the .txt files within the subfolders consist of the Laplace number, followed by the front tracking method and the d/dx ratio. If roughness smoothing is used it also consists of "WithRoughnessSmoothing". For example "La_120_ClassicFT_ddx_52.txt" consists of the data for a Laplace number of 120, the classic front tracking method and a d/dx ratio of 52. The content in the .txt files is the following: "%e,%e,%e,%e,%e,%e,%e\n" which corresponds to "Physical time, Physical time / \tau_{mu}, Kinetic energy, RMS velocity, Max velocity, Ca_{max}, U_sigma".</p> <p><em>translating_droplet</em>: This main folder contains subfolders for all Laplace numbers simulated. "La_120" corresponds to a Laplace number of 120. The file names of the .txt files within the subfolders consist of the Laplace number, followed by the front tracking method and the d/dx ratio. If roughness smoothing is used it also consists of "WithRoughnessSmoothing". For example "La_120_ClassicFT_ddx_52.txt" consists of the data for a Laplace number of 120, the classic front tracking method and a d/dx ratio of 52. The content in the .txt files is the following: "%e,%e,%e,%e,%e,%e,%e\n" which corresponds to "Physical time, Physical time / \tau_{mu}, Kinetic energy, RMS velocity, Max velocity, Ca_{max}, U_sigma".</p> <p><em>oscillating_droplet</em>: This main folder contains subfolders for all droplet viscosities simulated. "mu_d_05" corresponds to a droplet viscosity of 0.5. The file names of the .txt files within the subfolders consist of the droplet viscosity, followed by the front tracking method and the d/dx ratio. If roughness smoothing is used it also consists of "WithRoughnessSmoothing". For example "mu_d_05_ClassicFT_ddx_52.txt" consists of the data for a droplet viscosity of 0.5, the classic front tracking method and a d/dx ratio of 52. The content in the .txt files is the following: "%f,%f,%e\n" which corresponds to "Physical time, \tau, r".</p> <p><em>rising_bubbles</em>: This main folder contains subfolders for all rising bubble cases simulated. "Case_1_Classic" corresponds to a case 1 simulated with the classic front tracking method. The .txt files within the subfolders consist of the physical time, followed by the non-dimensional time and the Reynolds number. The .zip files contain the .pvtu and .vtu files for the front meshes.</p> <p>The python scripts have been tested with Python 3.11.5.</p> <p>This project has received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), grant number 420239128, and from the European Unions's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101026017. This work was supported by the US Department of Energy through the Los Alamos National Laboratory. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of U.S. Department of Energy (Contract No. 89233218CNA000001).</p>
Test models and test results to evaluate CAD assembly modules capabilities to generate component interfaces
<p>Set of 3D CAD assembly models in STEP AP 203 format.</p> <p>Assembly test models are devoted to evaluations of interfaces between components. The interfaces can be of type surface, rectilinear contacts, circular contacts, or point contacts.</p> <p>Test results obtained from some commercially available CAD assembly modules are given as a set of tables organized in accordancce with contact categories (surface, rectilinear, circular, point).</p> <p>The content and use of the test models are described into the pdf document: Test models and test results to evaluate CAD assembly modules capabilities to generate component interfaces.</p> <p> </p>
Data and code for the publication "Tracking microplastics across the streambed interface: Using laser-induced fluorescence to quantitatively analyze microplastic transport in an experimental flume"
<p>This archive contains datasets and codes that were used in the publication "Tracking microplastics across the streambed interface: Using laser-induced fluorescence to quantitatively analyse microplastic transport in an experimental flume".</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>
mCRL2 models, requirements and test logs for the EULYNX Point interface case study
<p>mCRL2 models and mu-calculus formulas for the EULYNX Point Interface. Models and requirements are made in the context of the FormaSig project. Data is made available for replication purposes.</p> <p>REQ_P_001, REQ_P_001_1 and REQ_P_002 are requirements for the point specific mCRL2 model point_spec.mcrl2</p> <p>Remaining .mcf files are requirements for the generic PDI interface pdi_spec.mcrl2</p> <p>Artifacts relating to testing are:</p> <ul> <li>An mCRL2 model, mbt.mcrl2</li> <li>A rename file to rename internal actions to tau, rename_file.re</li> <li>Partial state space associated to mbt.mcrl2, partial_state_space.aut</li> <li>The weak-trace bisim reduced version of the state space, partial_state_space_reduced.aut</li> <li>Testing logs, test-logs.zip</li> <li>The source code of the simulator and the testing tools, Simulator code.zip</li> </ul>
Homogenized anisotropic thermal conductivity on microstructure of binary composite with thermally imperfect diffuse interface
<p>This dataset contains supplementary data and utilities of the publication "A diffuse-interface model of anisotropic interface thermal conductivity and its application in thermal homogenization of composites" (<a href="https://doi.org/10.1016/j.scriptamat.2022.114537">Yang, 2022</a>).</p> <p>We performed thermal homogenization on microstructures with three types of inclusion geometries, in which ones with oval-shaped and fiber-shaped inclusions were read from characterized/generated digital microstructures, and ones with irregular-shaped inclusions were imported from the phase-field additive manufacturing simulations <a href="https://doi.org/10.1002/gamm.202100017">(Zhou, 2021)</a>. Si-Hf-N was chosen as the composite material system with β-Si<sub>3</sub>N<sub>4</sub> as the sole matrix phase and HfN as the sole inclusion phase. Direct homogenization method with the linear temperature BCs (see Supplementary Note 3 of the publication) was adopted.</p> <p>This dataset documents homogenized anisotropic thermal conductivity of corresponding microstructure as a tensor with normalized interface thermal resistance varying from 10<sup>-8</sup> to 10<sup>12</sup>. Voxelized digital microstructures and utilities for visualizing the overall thermal anisotropy are also attached.</p> <table> <tbody> <tr> <td>Properties</td> <td>Value</td> <td>Dimension</td> <td>Description</td> </tr> <tr> <td><span class="math-tex">\(k_\mathrm{(i)}\)</span></td> <td>90</td> <td><span class="math-tex">\(\mathrm{W~m^{-1}~K^{-1}}\)</span></td> <td>Thermal conductivity of HfN inclusion (<a href="https://10.1016/j.mtphys.2020.100256">Li, 2020</a>)</td> </tr> <tr> <td><span class="math-tex">\(k_\mathrm{(m)}\)</span></td> <td>180</td> <td><span class="math-tex">\(\mathrm{W~m^{-1}~K^{-1}}\)</span></td> <td>Thermal conductivity of β-Si<sub>3</sub>N<sub>4</sub> matrix (<a href="https://10.1016/s0955-2219(98)00258-1">Li, 1999</a>)</td> </tr> <tr> <td><span class="math-tex">\(\ell\)</span></td> <td>5</td> <td><span class="math-tex">\(\mathrm{nm}\)</span></td> <td>Diffuse interface width</td> </tr> <tr> <td><span class="math-tex">\((X,Y,Z)\)</span></td> <td>(500,500,500)</td> <td><span class="math-tex">\(\mathrm{nm}\)</span></td> <td>Simulation domain size</td> </tr> </tbody> </table> <p><strong>Notice:</strong> The digital microstructure has been voxelized, which can be loaded by default as a 200x200x200 numpy array (see utilities.ipynb). In order to perform the homogenization, interface smoothening is required, i.e., to generate diffuse interfaces. In this work, we smoothened the interface by operating transient Allen-Cahn calculation with finite timesteps. See Supplementary Note 4 of the publication for more information.</p>
Epistasis at the SARS-CoV-2 RBD Interface and the Propitiously Boring Implications for Vaccine Escape
<p>This repository includes:</p> <p> </p> <p>SI Appendix</p> <p>GISAID Acknowledgements</p> <p>An example resfile</p> <p>RosettaScripts .xml files</p> <p>Complex conformations (50 each) for WT/Delta/Gamma/Omicron; antibody (NAb) and receptor (ACE2)</p>
Data set for publication: Interfacial Deposition of Titanium Dioxide at the Polarized Liquid– Liquid Interface
<p>The attached files are the raw data used to write the manuscript (.txt; .csv; .jpg): Interfacial Deposition of Titanium Dioxide at the Polarized Liquid– Liquid Interface</p>
Research Data For "Structure and Interactions at the Mg(0001)/Water Interface: An ab initio Study" Paper
<p>This folder contains data used in the paper "Structure and Interactions at the Mg/Water Interface: An ab initio Study". Some details on the structure are as follows:</p> <p>The folder "figures" contains data to create various figures in the main paper.</p> <p>The folder "md_traj" contains the molecular dynamics trajectory. The file "traj.exyz" is a standard format which can be opened with various software. "traj.json" contains the same information in an in-house format used by the author. The "thermo_data.json" contains various thermodynamics properties over the simulation, such as temperatures and kinetic energies. Units are femtoseconds, Angstrom, electron-volts and Kelvin.</p> <p>The folders "mg_plus_clusters"/"mg_plus_monomer"/"misc_reference_structs" contain geometries for various structures used in the paper (in *.exyz format). These also contain *.json files; these contain information on how the calculations were carried out in a format used by the author (they are small files primarily included for the benefit of the author).</p> <p> </p>
Post-deposition annealing and interfacial ALD buffer layers of Sb2Se3/CdS stacks for reduced interface recombination and increased open-circuit voltages
<p>Data for the article:</p> <p>Post-deposition annealing and interfacial ALD buffer layers of Sb2Se3/CdS stacks for reduced interface recombination and increased open-circuit voltages</p>
User Interface Logs for SmartRPA
<p>This dataset contains the User Interface (UI) logs used for testing SmartRPA in the range of the paper "Reactive Synthesis of Software Robots in RPA from User Interface Logs".</p>
Raw data of manuscript "Tapered fibertrodes for opto-electrical neural interfacing in small brain volumes with reduced artefacts"
<p>This dataset contains the raw data for the paper titled "Tapered fibertrodes for opto-electrical neural interfacing in small brain volumes with reduced artefacts".</p>
Data From: Evolution of woody plants to the land‐sea interface: The atypical genomic features of mangroves with atypical phenotypic adaptation
<p><span>How plants adapt and diverge in extreme environments is a key question of plant evolution and ecology. Mangrove invasion of intertidal environments is facilitated by adaptive phenotypes such as aerial roots, salt-secreting leaf, and viviparity, and genomic mechanisms including whole genome duplication and transposable element number reduction. However, a number of mangroves lack these typical phenotypes. The question we ask is whether these phenotypically atypical mangroves also have distinct genomic features? The sibling mangrove species <em>Lumnitzera littorea</em> and <em>Lumnitzera racemosa</em> provide a model to study this question. We sequenced and assembled their genomes to chromosome level, together with a closely related species <em>Combretum micranthum</em>. While most mangroves have small genomes, the genomes of both <em>Lumnitzera </em>species are large (1443 and 1317 Mb) and carry a high proportion of repeat sequences (~75%). Moreover, <em>Lumnitzera</em> species have not undergone post-gamma whole-genome duplications. Their genome size increased mainly due to the expansion of repeat sequences in their ancestors. However, <em>Lumnitzera </em>genomes have reduced transposable elements by constraining the proliferation of new LTR-RTs. Meanwhile, the two species have more gene families contracted than expanded, and some gene families with reversed size change may underlie their differentiation in root morphology and local distribution. We identified 86 chromosomal inversions, five of which are measured between 6.5 and 12.8 megabases. A number of genes located in these inversions function in pigment biosynthesis, a process likely involved in flower color differentiation between the <em>Lumnitzera </em>species. We conclude that the mangroves with atypical phenotypes also have atypical genomic evolution.</span></p>
Heterogeneous cavitation from atomically smooth liquid-liquid interfaces
<p>Original research data on "Heterogeneous cavitation from atomically smooth liquid-liquid interfaces"</p> <p> </p> <p>Magnetic beads: diameter 4.5 µm<br> Framerate 5x10^6 fps<br> scale: 1px = 1.45 µm</p> <p>PFOB: 1-Bromoheptadecafluorooctane<br> Framerate 5x10^6 fps<br> scale: 1px = 1.60 µm</p> <p>4H-PFOB: 1H,1H,2H,2H-Perfluorooctyl bromide<br> Framerate 5x10^6 fps<br> scale: 1px = 1.23 µm</p> <p>"Luminity": Perfluteren 150 µl/ml<br> Framerate 5x10^6 fps<br> scale: 1px = 1.60 µm</p> <p>single_Interface: 4H-PFOB (left;laser impact) and water (right)<br> Framerate 5x10^6 fps<br> scale: 1px = 1.33 µm</p> <p>multi_cav: PFOB droplets<br> Framerate 5x10^6 fps<br> scale: 1px = 1.34 µm</p>
Ab initio umbrella sampling of a potassium ion at the aqueous graphene interface
<p>Ab initio molecular dynamics trajectories obtained with umbrella sampling of a potassium ion at the aqueous graphene interface, where in each trajectory the ion is at a different height from the graphene sheet.</p> <p>This repository contains supplementary data supporting the findings of the paper:</p> <p>L. Joly, R. H. Meissner, M. Iannuzzi, G. Tocci, "Osmotic Transport at the Aqueous Graphene and hBN Interfaces: Scaling Laws from a Unified, First-Principles Description", ACS Nano, 15, 9, 15249–15258 (2021), DOI: 10.1021/acsnano.1c05931.</p>
Ab initio molecular dynamics trajectories of liquid water at the interface with hBN sheets
<p>Ab initio molecular dynamics trajectories of water confined between hBN sheets for different confinement widths and system sizes.</p> <p>This repository contains data supporting the findings of the paper: </p> <p>G. Tocci, M. Bilichenko, L. Joly, M. Iannuzzi, <em>Ab initio</em> nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction, Nanoscale, 12, 10994-11000 (2020). DOI: 10.1039/D0NR02511A.</p>
Ab initio molecular dynamics trajectories of liquid water at the interface with graphene sheets
<p>Ab initio molecular dynamics trajectories of water in contact with graphene sheets for different confinement widths and system sizes</p> <p>This repository contains data supporting the findings of the paper: </p> <p>G. Tocci, M. Bilichenko, L. Joly, M. Iannuzzi, <em>Ab initio</em> nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction, Nanoscale, 12, 10994-11000 (2020). DOI: 10.1039/D0NR02511A.</p>
Ab initio umbrella sampling of a potassium ion at the aqueous hBN interface
<p>Ab initio molecular dynamics trajectories obtained with umbrella sampling of a potassium ion at the aqueous hBN interface, where in each trajectory the ion is at a different height from the hBN sheet.</p> <p>This repository contains supplementary data supporting the findings of the paper:</p> <p>L. Joly, R. H. Meissner, M. Iannuzzi, G. Tocci, "Osmotic Transport at the Aqueous Graphene and hBN Interfaces: Scaling Laws from a Unified, First-Principles Description", ACS Nano, 15, 9, 15249–15258 (2021). DOI: 10.1021/acsnano.1c05931</p>
Ab initio umbrella sampling of an iodide ion at the aqueous hBN interface
<p>Ab initio molecular dynamics trajectories obtained with umbrella sampling of an iodide ion at the aqueous hBN interface, where in each trajectory the ion is at a different height from the hBN sheet.</p> <p>This repository contains supplementary data supporting the findings of the paper:</p> <p>L. Joly, R. H. Meissner, M. Iannuzzi, G. Tocci, "Osmotic Transport at the Aqueous Graphene and hBN Interfaces: Scaling Laws from a Unified, First-Principles Description", ACS Nano, 15, 9, 15249–15258 (2021). DOI: 10.1021/acsnano.1c05931</p>
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