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564 results for “ABS”
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>
Ab initio umbrella sampling of an iodide ion at the aqueous graphene interface
<p>Ab initio molecular dynamics trajectories obtained with umbrella sampling of an iodide 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 MoS2 sheets
<p>Ab initio molecular dynamics trajectories of water confined between MoS2 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>
Äggersättningspulver. AB Kronjäst Mjölby.
Scan by [Christer Lindqvist](https://sketchfab.com/Pappac). Retopology by Niclas Ekholm. Source: Objaverse 1.0 / Sketchfab
Fuzzy Logic Control for ABS ESR 8
<p>Results of the Fuzzy Logic Control for ABS from the HIL test rig at TU Ilmenau.</p>
Speciation data for "Pressure-induced coordination changes in a pyrolitic silicate melt from ab initio molecular dynamics simulations"
<p>With <em>ab initio</em> molecular dynamics simulations on pyrolite melt, we examine the detailed changes in elemental coordination as a function of pressure and temperature. We consider the average coordination as well as the proportion and distribution of coordination environments at pressures and temperatures encompassing the conditions at which molten silicates may exist in present-day Earth and those of the Early Earth's magma ocean. At ambient pressure and 2000 K, we find that the average coordination of cations with respect to oxygen is 4.0 for Si-O, 4.0 for Al-O, 3.7 for Fe-O, 4.6 for Mg-O, 5.9 for Na-O and 6.2 for Ca-O. Although the coordination for iron with respect to oxygen is underestimated, the coordination number for all other cations are consistent with experiments. At the base of the upper mantle (~15 GPa and 2000 K), the average coordination for Si-O remains at 4.0, but increases to 4.1 for Al-O, 4.2 for Fe-O, 4.9 for Mg-O, 8.0 for Na-O and 6.8 for Ca-O. The coordination environment for Na-O remains approximately constant up to core-mantle boundary conditions (135 GPa and 4000 K), but increases to about 6 for Si-O, 6.5 for Al-O, 6.5 for Fe-O, 8 for Mg-O, 9.5 for Ca-O. Our results have implications for melt properties, such as viscosity, transport coefficients, thermal conductivities and electrical conductivities, and will help interpret experimental results on silicate glasses.</p> <p>Detailed speciation statistics for pyrolite melt were determined using <em>a</em><em>b initio</em> molecular dynamics simulations with the Vienna Ab Initio Simulation Package (VASP) (Kresse and Furthmuller, 1996). Simulations were performed with a time step of 0.5-2 femtoseconds for 10-50 picoseconds, depending on the temperature and density. The composition of the Bulk Silicate Earth was modeled with a pyrolite melt with the stoichiometry NaCa<sub>2</sub>Fe<sub>4</sub>Mg<sub>30</sub>Al<sub>3</sub>Si<sub>24</sub>O<sub>89</sub>. Bond distances were determined from the pair distribution functions, which describe the probability of finding an atom type at a given distance from the reference atom. We used the first peak in the pair distribution function to approximate the average bond length; the distance at which the first minimum occurs marks the radius of the first coordination sphere of atoms that are directly bonded to the reference atom. We used this value to define the bond criterion between two atom types. Additional computational details can be found in the manuscript.</p>
eol_data-2016-12-08 (EOL v2): split.tgz-ab
[eol_data-2016-12-08.tgz] is a big file. So we split them into four smaller chunks. You can download these four files below on your local and merge them to get [eol_data-2016-12-08.tgz]. This is the command to merge once you__ve downloaded all four parts: `$ cat split.tgz-* | tar xz` Once you get [eol_data-2016-12-08.tgz], extract it to get these four TSVs: * hierarchy_entries.tsv * data_objects.tsv * data_objects_additional_attribution.tsv * data_objects_taxon_concepts.tsv<p></p>2 of 4
Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters via Ab Initio Molecular Dynamics Simulations to Accurately Model Glycosaminoglycan Electrostatic Interactions
<p>To cite and for more details: Riopedre-Fernandez et al. <em>J. Chem. Inf. Model.</em> <strong>2024</strong>, 64 (18), 7122–7134. DOI: <a href="https://doi.org/10.1021/acs.jcim.4c00981">https://doi.org/10.1021/acs.jcim.4c00981</a></p> <p>The dataset includes molecular dynamics simulations of sulfated saccharides and their sulfated analogs in the presence of calcium cations in aqueous solution. Several force field parameter sets were compared (CHARMM36, GLYCAM06, AMOEBA, Drude) and new have been developed (prosECCo75 and GLYCAM-ECC75).</p> <p>The uploaded files contain the following simulation input files or/and simulation trajectories:</p> <p>1) Sulfated_Molecules_Umbrella_Sampling_AIMD: Umbrella sampling ab initio molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>2) Sulfated_Molecules_Umbrella_Sampling_FFMD: Umbrella sampling force field molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>3) Sulfated_Molecules_AWH_FFMD: Accelerated weight histogram force field molecular dynamics simulations of calcium interacting with both methylsufate and N-methylsulfamate in water.</p> <p>4) Disaccharides_FFMD: Unbiased force field molecular dynamics simulations of calcium-sulfated disaccharide aqueous solutions.</p> <p>UPD. Version 2.0 has updated one of the disaccharide-containing simulations (GLYCAM06, N-sulfation) due to incorrect calcium LJ parameters in the original upload.</p>
Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1$_0$ FeNi."
<p>Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1$_0$ FeNi", published in npj Comput. Mater. <strong>10</strong> 272 (2024).</p> <p>Version 2 contains additional results relating to Ni-rich systems.</p> <p>Version 3 contains data relating to vibrational considerations for the A1-L1$_0$ transition in equiatomic FeNi.</p> <p>Version 4 contains date pertaining to the Curie temperatures of the disordered, partially ordered, and fully ordered alloys considered in this work.</p>
Ab initio design of microbial communities from large-scale seed pools using deep learning and rapid ptimization
<h4>This repository contains the full results of our paper: <strong><em>Ab initio</em> design of microbial communities from large-scale seed pools using deep learning and rapid ptimization.</strong></h4> <p>Authors: Xiaoqing Jiang#, Jiaheng Hou#, Haoyu Zhang#, Jinyuan Guo, Shaohua Gu, Yulin Liao, Xinrun Yang, Peter X. Geng, Yiyan Zhou, Qian Guo, Chunhui Wang, Mo Li, Alexandre Jousset, Zhong Wei*, and Huaiqiu Zhu*</p> <p>The results including:</p> <p><strong>(1)</strong> <strong>GEM.tar.gz</strong>: The eBiota-GEM dataset, containing 21,514 Genome-Scale Metabolic Models (GEMs) constructed using CarveMe based on RefSeq complete genomes.</p> <p><strong>(2) Baterial_evaluation.tar.gz</strong>: The evaluation of the ability to uptake substrates and secret productions for all 21,514 GEMs.</p> <p><strong>(3) Community_results.tar.gz</strong>: The results calculated from eBiota-GEM includes various combinations for two-bacterial consortia, covering strain IDs, substrates, products, yields, dual-bacterial growth, single-bacterial growth, co-occurrence predictions, interactions and total production.</p> <p><strong>(4) DeepCooc_files.tar.gz</strong>: The parameter files of DeepCooc, required by eBiota platform.</p>
Triple-resolution of spectral phases via semi-relativistic ab-initio RABBITT simulations DATA & WORKFLOW
<p>This dataset contains the necessary atomic structure and input files to use the <a href="https://gitlab.com/Uk-amor/RMT/rmt">R-Matrix with Time-dependence code suite</a> (open source and freely available) to replicate the results presented in "Triple-resolution of spectral phases via semi-relativistic ab-initio RABBITT simulations".</p> <p>Additionally, the output photoelectron momentum spectra data output from the RMT simulations are provided, to allow replication of the post-processing and spectral phase extraction processes in the absence of access to a large HPC cluster.</p> <p>Finally, a link is provided to a <a href="https://gitlab.com/lukeroantree/argon_rabbitt_scripts">git repository</a> hosted on gitlab.com where post-processing, spectral phase extraction, and visualisation tools are available to operate on these momentum spectra, and an interactive example is provided via a webhosted (via mybinder) Python Jupyter notebook.</p>
amorphous carbon ab-initio calculation dataset
<p><strong>Description</strong></p> <p>This dataset was used in our manuscript titled “Persistent homology-based descriptor for machine-learning potential of amorphous structures” (arXiv:2206.13727 [cs.LG] <a href="https://arxiv.org/abs/2206.13727">https://arxiv.org/abs/2206.13727</a>).</p> <p><strong>Methods to generate the dataset</strong></p> <p>The amorphous carbon dataset was generated using ab initio calculations with VASP software. We utilized the LDA exchange-correlation functional and the PAW potential for carbon. Melt-quench simulations were performed to create amorphous and liquid-state structures. A simple cubic lattice of 216 carbon atoms was chosen as the initial state. Simulations were conducted at densities of 1.5, 1.7, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, and 3.5 g/cm<sup>3</sup> to produce a variety of structures. The NVT ensemble was employed for all melt-quench simulations, and the density was adjusted by modifying the size of the simulation cell. A time step of 1 fs was used for the simulations. For all densities, only the Γ points were sampled in the k-space. To increase structural diversity, six independent simulations were performed.</p> <p>In the melt-quench simulations, the temperature was raised from 300 K to 9000 K over 2 ps to melt carbon. Equilibrium molecular dynamics (MD) was conducted at 9000 K for 3 ps to create a liquid state, followed by a decrease in temperature to 5000 K over 2 ps, with the system equilibrating at that temperature for 2 ps. Finally, the temperature was lowered from 5000 K to 300 K over 2 ps to generate an amorphous structure.</p> <p>During the melt-quench simulation, 30 snapshots were taken from the equilibrium MD trajectory at 9000 K, 100 from the cooling process between 9000 and 5000 K, 25 from the equilibrium MD trajectory at 5000 K, and 100 from the cooling process between 5000 and 300 K. This yielded a total of 16,830 data points.</p> <p>Data for diamond structures containing 216 atoms at densities of 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, and 3.5 g/cm3 were also prepared. Further data on the diamond structure were obtained from 80 snapshots taken from the 2 ps equilibrium MD trajectory at 300 K, resulting in 560 data points.</p> <p>To validate predictions for larger structures, we generated data for 512-atom systems using the same procedure as for the 216-atom systems. A single simulation was conducted for each density. The number of data points was 2,805 for amorphous and liquid states.</p> <p><strong>Contents of each folder </strong></p> <p>・216atom_amorphous: Contains six xyz files generated from the trajectory of the melt-quench simulation.</p> <p>・216atom_crystal: Contains a single xyz file with data of diamond structures containing 216 atoms at densities of 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, and 3.5 g/cm3.</p> <p>・512atom_amorphous: Contains a single xyz file with data of 512-atom systems.</p> <p>・dataset_train_test_split: The training and test data used in the manuscript, constructed from splitting the entire 216atom_amorphous dataset.</p>
Data supporting Mixed-anion mixed-cation perovskite (FAPbI3)0.875(MAPbBr3)0.125: an ab initio molecular dynamics study
<p>Data of a molecular dynamics simulation of the mixed cation and mixed halide perovskite (FAPbI3)0.875(MAPbBr3)0.125 , as well as the end compounds FAPbI3 and MAPbBr3.</p> <p>Related article: </p> <p><em><strong>J. Mater. Chem. A</strong></em>, 2022,<strong>10</strong>, 9592-9603, <a href="https://doi.org/10.1039/D1TA10860C">https://doi.org/10.1039/D1TA10860C</a></p> <p>arXiv:2112.09795 [cond-mat.mtrl-sci] arXiv: 2112.09795 <a href="https://doi.org/10.48550/arXiv.2112.09795">https://doi.org/10.48550/arXiv.2112.09795</a></p>
Ab initio results for dolerophanite, Cu2OSO4
<p>Collection of ab initio (DFT) results for the magnetic exchange couplings in dolerophanite, Cu2OSO4. The data set also includes density of states (DOS) and Wannier projections used for evaluating and visualizing magnetic orbitals.</p>
Linear machine learning based force matching for amorphous silica: How close are the classical two-body potentials to ab initio calculations?
<p>Please later see our manuscript (in submission) for details.</p>
Electrofreezing of liquid water at ambient conditions - trajectories from ab initio molecular dynamics simulations
Open the record for dataset details and reuse information.
Structure and dynamics of liquid water from ab initio simulations: Adding Minnesota density functionals to Jacob's ladder
<p>Supporting data and analysis script for the work</p><p><i>Structure and dynamics of liquid water from ab initio simulations: Adding Minnesota density functionals to Jacob's ladder</i></p>
A Study of the Safety and Pharmacokinetics of a Human Monoclonal Antibody, VRCHIVMAB0115-00-AB (VRC01.23LS), Administered Intravenously or Subcutaneously to Healthy Adults
ClinicalTrials.gov study NCT05627258. IPD Sharing: NO. Countries: 1. Publications: 3.
Safety and Pharmacokinetics of a Human Monoclonal Antibody, VRC-EBOMAB092-00-AB (MAb114), Administered Intravenously to Healthy Adults
ClinicalTrials.gov study NCT03478891. IPD Sharing: NO. Countries: 1. Publications: 3.
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