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669 results for “ATOM”
Data-driven Household Load Flexibility Modelling: Shiftable Atomic Load
<p>This is flexibility model for shiftable atomic loads (i.e. washing machine, dryers and dish washers). The model is based on real 1-minute level measurements from real households over period of time. The details of the model are described in [R]. The model is implemented in Excel for cloth washing machines weekday consumption and flexibility scenario and all the required data is included for modelling the other equipment.</p> <p>[R] Degefa, M.Z., Sæle, H., Petersen, I. and Ahcin, P., 2018, October. Data-driven Household Load Flexibility Modelling: Shiftable Atomic Load. In <em>2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)</em> (pp. 1-6). IEEE.</p> <p><a href="https://ieeexplore.ieee.org/document/8571836">https://ieeexplore.ieee.org/document/8571836</a></p>
Extended Data: Structure-dependence of the atomic-scale mechanisms of Pt electrooxidation and dissolution
<p><strong>Abstract:</strong></p> <p>Platinum dissolution and restructuring due to surface oxidation are primary degradation mechanisms that limit the lifetime of Pt-based electrocatalysts for electrochemical energy conversion. Here, we studied well-defined Pt(100) and Pt(111) electrode surfaces by in situ high-energy surface X-ray diffraction, on-line inductively coupled plasma mass spectrometry, and density functional theory calculations, to elucidate the atomic-scale mechanisms of these processes. The locations of the extracted Pt atoms after Pt(100) oxidation reveal distinct differences from the Pt(111) case, which explains the different surface stability. The evolution of a specific stripe oxide structure on Pt(100) produces unstable surface atoms which are prone to dissolution and restructuring, leading to one order of magnitude higher dissolution rates.</p> <p><strong>Contents of this repository:</strong></p> <p><strong>1. SXRD data:</strong></p> <p>The experiments for the acquisition of the raw SXRD data were performed at the the European Synchrotron Radiation Facility, Grenoble, France at the beamlines ID31 and ID03. We thank H. Isern and T. Dufrane for the help during the SXRD experiments.</p> <ul> <li>tomo_tomo.spec is the file with the X-ray diffraction metadata for the CTR scans. It is a plain text file.</li> <li>Each HESXRD dataset is saved in a folder, which denotes the potential (e.g. 1V0.zip). The png-image files are previews of the corresponding dataset. The individual raw cbf files can be opened by pyMCA or silx. From python, the images can be accessed using the fabio library.</li> <li>calibration.zip contains the pyFAI calibration files and a list with indexed Bragg reflections for the UB matrix calculation</li> <li>CTRs_parameters.zip contains the averaged CTR structure factors used for the structual analysis as well as files with the atomic coordinates of the refined structural model.</li> <li>steps.zip contains the full datasets from the potential step experiments in Fig. 1e.</li> </ul> <p><strong>2. DFT:</strong></p> <ul> <li>CONTCARs.zip contains the atomic coordinates of the optimized computational models.</li> </ul> <p> </p> <p> </p>
Source Data - Ilzhofer et al. - Phase coherence in out-of-equilibrium supersolid states of ultracold dipolar atoms
<p>Source data for following publication:</p> <p>"Phase coherence in out-of-equilibrium supersolid states of ultracold dipolar atoms" (2019)</p> <p>P. Ilzhofer and M. Sohmen and G. Durastante and Claudia Politi and A. Trautmann and G. Morpurgo and T. Giamarchi and L. Chomaz and M. Mark and F. Ferlaino</p> <p>Institut f ̈ur Quantenoptik und Quanteninformation, ̈Osterreichische Akademie der Wissenschaften, 6020 Innsbruck, Austria</p> <p>Institut f ̈ur Experimentalphysik und Zentrum f ̈ur Quantenoptik,Universit ̈at Innsbruck, Technikerstraße 25, 6020 Innsbruck, Austria</p> <p>DQMP, University of Geneva, 24 Quai Ernest-Ansermet, CH-1211 Geneva, Switzerland</p>
Atom probe characterisation of segregation driven Cu and Mn–Ni–Si co-precipitation in neutron irradiated T91 tempered-martensitic steel - data
<p>Data for 'Atom probe characterisation of segregation driven Cu and Mn–Ni–Si co-precipitation in neutron irradiated T91 tempered-martensitic steel' paper (<a href="https://doi.org/10.1016/j.mtla.2020.100946">https://doi.org/10.1016/j.mtla.2020.100946</a>) </p>
hnRNPA1* and hSUMO-hnRNPA1* all-atom MD trajectories and protein-water rescaling MD trajectories
<pre>All-atom trajectories of hnRNPA1* and hSUMO-hnRNPA1* with varying NaCl concentrations back-mapped from CG simulations. CG trajectories of hnRNPA1* and hSUMO-hnRNPA1* with varying PW-rescaling parameter lambda (theta in file names). Supporting data for "Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation".</pre> <pre> </pre>
Atomic resolution X-ray crystal structure of cisplatin bound to hen egg white lysozyme stored for 5 years ‘on the shelf’
<p>These are the raw diffraction images for crystals 1 and 2 underpinning PDBe code 5LXW.</p>
Data presented in "Three-dimensional Doppler, polarization-gradient, and magneto-optical forces for atoms and molecules with dark states"
<p>These are the data presented in our paper "Three-dimensional Doppler, polarization-gradient, and magneto-optical forces for atoms and molecules with dark states" which has been accepted for publication in the New Journal of Physics (as of 07 November 2016).</p>
Data for Properties of Kinetic Transition Networks for Atomic Clusters and Glassy Solids
<p>Databases of minima and transition states for Morse clusters, in two and three dimensions at a variety of ranges.</p>
Atomic Cluster Expansion for a General-Purpose Interatomic Potential of Magnesium
<p>This collection contains files associated with Physical Review Materials. "Atomic cluster expansion for a general-purpose interatomic potential of magnesium" (2023) paper:</p><p>- ACE potentials for magnesium.</p><p>-Active set inverted (ASI) for the ACE potential</p><p>- Magnesium DFT-PBE dataset computed with FHI-aims and that was used for fitting Atomic Cluster Expansion potential for magnesium.</p>
Transferability of atomic energies from alchemical decomposition - additional data
<p>Additional data to the paper "Transferability of atomic energies from alchemical decomposition"</p><p><a href="https://doi.org/10.48550/arXiv.2311.04784">https://doi.org/10.48550/arXiv.2311.04784</a></p><p>Atomic energies of selected QM9 compounds calculated with different decomposition schemes (alchemy, IQA and IBO/IAO).</p><p>Code to generate the input-file and the rescaled pseudopotential files for DFT calculations with fractional core charges with the CPMD program and to calculate alchemical atomic energies from the CPMD output.</p><p> </p>
Dataset/Models for: Active learning accelerated exploration of the single atom local environments in multimetallic systems for oxygen electrocatalysis
<p>This is the datasets and trained models for the work "Active learning accelerated exploration of the single atom local environments in multimetallic systems for oxygen electrocatalysis", by Hoje Chun, Jaclyn R. Lunger, Jeung Ku Kang, Rafael Gómez-Bombarelli, and Byungchan Han. Folder named Models contains the trained models of "m-PaiNN" and "per-site PaiNN". Folder named Dataset contains the torch dataset and Dataset_raw contains the raw Density Functional Theory (DFT) dataset parsed in format of pymatgen Structure. Some structures (868) in the search space are missing due to the lost track of the geometry optimization during the initial dataset curation.</p>
Partial Atomic Model of the Tailed Lactococcal Phage TP901-1 as Predicted by AlphaFold2
Open the record for dataset details and reuse information.
Data Repository for Nanoscale magnetism and magnetic phase transitions in atomically thin CrSBr
<p><span>Data repository for: Nanoscale magnetism and magnetic phase transitions in atomically thin CrSBr</span></p> <p><span><span>This data repository contains the raw data as measured on the experimental setup, simulations, analysis scripts and plotting scripts to reproduce the plots shown in the manuscript’s figures.</span></span></p> <p><span><span>Code for plotting: Matlab R2021b<br>The raw data is either stored as MatLab structs (.mat) or accessible through the .json files.</span></span></p> <p><span><span>See ReadMe.txt for more information.</span></span></p>
Dataset for the manuscript "Realization of an atomic quantum Hall system in four dimensions", arXiv:2210.06322
<p>Dataset for the manuscript "Realization of an atomic quantum Hall system in four dimensions", arXiv:2210.06322</p>
Models (atmospheric and atomic) for the P-CORONA code together with some sample runs.
<p>The dataset comprises some sample example runs with all necessary input parameters and corresponding outputs expected from P-CORONA, along with a few atomic and atmospheric models. Description of the files included is given in the README.txt file.</p> <p>The P-CORONA code can be obtained at <a href="https://gitlab.com/polmag/P-CORONA">https://gitlab.com/polmag/P-CORONA</a> and its documentation at <a href="https://polmag.gitlab.io/P-CORONA/">https://polmag.gitlab.io/P-CORONA/</a></p> <p>The version of P-CORONA used to generate this dataset (which corresponds to the commit #85d7552 in <a href="https://gitlab.com/polmag/P-CORONA">https://gitlab.com/polmag/P-CORONA</a>) can be found at: <a href="https://doi.org/10.5281/zenodo.15195460">https://doi.org/10.5281/zenodo.15195460</a></p>
All-atom molecular dynamics simulations of incomplete ATP synthase rotor rings with unusually high stoichiometry predicted by the AlphaFold2-based method
<p>The trajectories of all-atom MD simulations of <span>AlphaFold2 4, 11, 16 or 18-mer structures of the subunit <em>c</em> from<br></span><span><em>Candidatus Kryptonium thompsoni</em></span><span> (CKt_Nmer_lipid_mix_CHM36m_303K_500ns) and <br></span><span><em>Thalassoglobus polymorphus </em>(Tp_Nmer_lipid_mix_CHM36m_303K_500ns), and <br>AlphaFold2 11-mer structure of the subunit <em>c</em> from <em>Spinacia oleracea</em> (So_11mer-c20_POPC_CHM36m_303K_300ns) </span><span>in a lipid bilayer.</span></p> <p><span>Simulations have been performed using the CHARMM36m force field, running with the GROMACS 2022 package.</span></p>
Generalized biomolecular modeling and design with RoseTTAFold all-atom
<p>Although AlphaFold2 (AF2) and RoseTTAFold (RF) have transformed structural biology by enabling high-accuracy protein structure modeling, they are unable to model covalent modifications or interactions with small molecules and other non-protein molecules that can play key roles in biological function. Here, we describe RoseTTAFold All-Atom (RFAA), a deep network capable of modeling full biological assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given the sequences of the polymers and the atomic bonded geometry of the small molecules and covalent modifications. Following training on structures of full biological assemblies in the Protein Data Bank (PDB), RFAA has comparable protein structure prediction accuracy to AF2, excellent performance in CAMEO for flexible backbone small molecule docking, and reasonable prediction accuracy for protein covalent modifications and assemblies of proteins with multiple nucleic acid chains and small molecules which, to our knowledge, no existing method can model simultaneously. By fine-tuning on diffusive denoising tasks, we develop RFdiffusion All-Atom (RFdiffusionAA), which generates binding pockets by directly building protein structures around small molecules and other non-protein molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and optically active bilin molecules with potential for expanding the range of wavelengths captured by photosynthesis. We anticipate that RFAA and RFdiffusionAA will be widely useful for modeling and designing complex biomolecular systems.</p>
Supplemental data and figures behind: Atom scale element and isotopic investigation of 25Mg-rich stardust from a H-burning supernova
<p>We have discovered a presolar olivine from ALH 77307 with the highest <sup>25</sup>Mg isotopic composition measured in a silicate to date (δ<sup>25</sup>Mg = 3025.1‰ ± 38.3‰).<strong> </strong>Its isotopic compositions challenge current stellar models, with modelling of Mg, Si and O showing a closest match to formation in a supernova where hydrogen ingestion occurred in the pre-supernova phase. Presolar grains within primitive astromaterials retain records of processes and environmental changes throughout stellar evolution. However, accessing these records has proved challenging due to the average grain size (~150 nm) of presolar silicates, their sensitivity to extraction agents and instrumental restrictions, limiting the range of isotopic and chemical signatures which can be studied per grain volume. Here, we present the first known detailed, geochemical study of a presolar silicate from a H-burning supernova, studied in 3D without contributions to the analysis volume and at unprecedented spatial resolutions (< 1 nm), essential for constraining physical and chemical processes occurring within this recently proposed stellar environment. From our results, we infer either; [1] condensation within an environment depleted of heavy elements compatible with the olivine lattice under the pressure and temperature conditions during condensation. [2] during periods of limited mixing either near the end of the pre-supernova phase or from a collapse so rapid localised pockets of different gas compositions formed.</p>
A nanoparticle stored with an atomic ion in a linear Paul trap
<p>Radiofrequency traps are used to confine charged particles but are only stable for a narrow range of charge-to-mass ratios. Here, we confine two particles---a nanoparticle and an atomic ion---in the same radiofrequency trap although their charge-to-mass ratios differ by six orders of magnitude. The confinement is enabled by a dual-frequency voltage applied to the trap electrodes. We introduce a robust loading procedure under ultra-high vacuum and characterize the stability of both particles. It is observed that slow-field micromotion, an effect specific to the dual-field setting, plays a crucial role for ion localization and will be important to account for when engineering controlled interactions between the particles.</p>
Probing structural superlubricity of two-dimensional water transport with atomic resolution.
<p>Here lies the tabulated data used to create the Figures for the Science manuscript ado1544 titled "Probing structural superlubricity of two-dimensional water transport with atomic resolution".</p>
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