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235 results for “Lattices”
Determinant Quantum Monte Carlo data for the Hubbard model on the half filled square lattice, on a (U,B)-grid
<p>Data generated with QUEST 1.4.9. For documentation see these two homepages:<br> Original homepage: http://quest.ucdavis.edu/<br> Newest version available at: https://code.google.com/archive/p/quest-qmc/</p> <p>The simulations are done at half filling on a square lattice, with the following parameters:</p> <ul> <li>Lattice sizes: 4x4, 6x6, 8x8, 10x10, 12x12, periodic boundary conditions</li> <li>Trotter discretizations: 0.1 and 0.2</li> <li>Inverse temperature beta = 10.0</li> <li>48 values for the on-site interaction U from 0.0 to 10.0</li> <li>48 values for the magnetic field (in z-direction) B from 0.0 to 4.0</li> <li>10000 warmup sweeps, 30000 measurement sweeps</li> </ul> <p>The following data from equal time measurements are available:</p> <ul> <li>Charge-Charge Correlation (next neighbors)</li> <li>Greens Function (n.n.)</li> <li>Magnetization</li> <li>Double Occupancy</li> <li>Kinetic Energy</li> <li>Total Energy</li> <li>Spin-Spin Correlation (n.n.)</li> <li>Spin-Spin Correlation (only ZZ) (n.n.)</li> <li>Ferromagnetic Structure Factor (ZZ)</li> <li>Antiferromagnetic Structure Factor (ZZ)</li> </ul> <p>The data are available as a hdf5 archive. The python script 'extract.py' illustrates the access with h5py. Relevant QUEST input parameters are provided in the group 'parameters' within the archive.</p> <p>All calculated quantities are averaged over multiple consecutive simulations, which is why the data is not presented in the usual QUEST output. This was necessary due to limited walltime on the used supercomputer.</p> <p>The authors acknowledge the North-German Supercomputing Alliance (HLRN) for providing computing resources via project number hbp00046 that have contributed to these results.</p>
Formation of Néel Type Skyrmions in an Antidot Lattice with Perpendicular Magnetic Anisotropy
<p>Open access data set for manuscript "Formation of Néel Type Skyrmions in an Antidot Lattice with Perpendicular Magnetic Anisotropy" published in Physical Review B, 100, 144435 (2019)</p>
Research data supporting "Mechanical properties of semi-regular lattices"
<p>Research data supporting "Mechanical properties of semi-regular lattices" published in Materials & Design in 2022. This dataset includes:</p> <ul> <li>Processed data plotted in Figure 11 (Fig11.xlsx).</li> <li>Processed data plotted in Figure 19 (Fig19.xlsx).</li> <li>Finite element models used to compute the elastic and shear moduli of each semi-regular lattice. These can be opened with the commercial software Abaqus CAE version 2023 (periodic_boundary_model.cae).</li> </ul>
Research data supporting "The fracture toughness of demi-regular lattices"
<p>Research data supporting "The fracture toughness of demi-regular lattices" published in <em>Scripta Materialia</em> in 2023. This dataset includes:</p> <ul> <li>Processed data plotted in Figures 2 and 4 (Figs.xlsx).</li> <li>Python scripts used to generate the finite element models (*.py files). These have to be used with the commercial software Abaqus CAE.</li> </ul>
Research data supporting "Fracture toughness of semi-regular lattices"
<p>Research data supporting "Fracture toughness of semi-regular lattices" published in <em>International Journal of Solids and Structures</em> in 2023. This dataset includes:</p> <ul> <li>Processed data plotted in Figures 4, 5, 6, 10, and A2 (*.xlsx files).</li> <li>Raw data plotted in Figure 8 (Fig 8.xlsx).</li> <li>CAD files for all test specimens (*.STL files).</li> <li>Python scripts used to generate the finite element models (*.py files). These have to be used with the commercial software Abaqus CAE.</li> </ul>
Data of "Effect of sample dimensions on the stiffness of PA12 Lattice materials fabricated using Powder Bed Fusion"
<div> </div> <div> <pre>Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data) title = "Effect of sample dimensions on the stiffness of PA12 Lattice materials fabricated using Powder Bed Fusion", journal = "Additive Manufacturing", pages = " ", year = "2024", issn = "", doi = "https://doi.org/10.1016/j.addma.2024.104382", author = "L. Cobian, E. Maire, J. Adrien, U. Freitas, J.P. Fernandez-Blazquez, M.A. Monclus, J. Segurado"</pre> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 862015</p> </div>
Raw data to "Order-by-disorder in the antiferromagnetic $J_1$-$J_2$-$J_3$ transverse-field Ising model on the ruby lattice"
<p>This directory contains the data used to generate the results in the work "Order-by-disorder in the antiferromagnetic $J_1$-$J_2$-$J_3$ transverse-field Ising model on the ruby lattice" [1].</p> <p>To get an overview of the organization of the directory and a description of the data we recommend the README.txt file.</p> <p>[1]: A. Duft et al., Order-by-disorder in the antiferromagnetic $J_1$-$J_2$-$J_3$ transverse-field Ising model on the ruby lattice. arXiv:2312.12941</p>
Dataset for the research paper "Computational and experimental investigation of thermally auxetic multi-metal lattice structures produced by Laser Powder Bed Fusion"
<p>The aim of this study is to investigate the potential of tailoring the structural thermal expansion properties of a multi-metal re-entrant lattice structure made of 316L stainless steel and CuCr1Zr copper alloy. Several geometric configurations with different layout of parent materials were designed and tested for their ability to thermally expand at elevated temperature. The study showed that one of the geometric configurations with the chosen material layouts allows to exceed the expansion range that can be achieved by both parent materials. The prediction of the finite element analysis was thus confirmed by experimental measurements. In addition, the influence of manufacturing imperfections in the form of geometric deviations and non-optimal material deposition was also investigated, and the results showed that this has a significant influence on the overall expansion. In conclusion, it was found that it is possible to tailor multi-metal lattice structures to a specific expansion, but the disadvantages associated with manufacturing must first be eliminated.</p>
Development and Comparison of Model-Based and Data-Driven Approaches for the Prediction of the Mechanical Properties of Lattice Structures
<p>This dataset comes from the following paper:</p> <p>Chiara Pasini, Oscar Ramponi, Stefano Pandini, Luciana Sartore, Giulia Scalet, Development and Comparison of Model-Based and Data-Driven Approaches for the Prediction of the Mechanical Properties of Lattice Structures, J. of Materi Eng and Perform, 2024. <a href="https://doi.org/10.1007/s11665-024-10199-x">https://doi.org/10.1007/s11665-024-10199-x</a></p> <p>It contains:</p> <ul> <li>"Notes.pdf" describing all the files uploaded</li> <li>. m of the neural network</li> <li>. inp of the Abaqus finite element simulations</li> </ul>
Data for "Artificial out-of-plane Ising antiferromagnet on the kagome lattice with very small further neighbour couplings"
<p>Open access data and small scripts for the Figures of Colbois, Hofhuis, Luo, Wang, Hrabec, Heyderman and Mila, PRB 2021 (please cite upon using this data).</p> <p>Each folder contains a specific README file regarding its content. Here is only a short summary of the various folders contents:</p> <ol> <li>Colbois_Hofhuis_Micromagnetics_FurtherNeighbourInteractions_DATA : raw data from the micromagnetic simulations with MuMax</li> <li>Colbois_Micromagnetics_FurtherNeighbourInteractions_Analysis : Mathematica and Jupyter notebooks for the analysis of the micromagnetic simulations results and the creation of the corresponding Figures.</li> <li>Hofhuis_MFMandTIF_DATA : raw images and data for the spin configurations for the various samples of the experiment.</li> <li>Luo_Wang_Hofhuis_Protocols : text files describing the protocols for the sample fabrication and for the demagnetization process.</li> <li>Colbois_ExperimentalConfigurations_ANALYSIS : results and figures of the analysis of the data in Hofhuis_MFMandTIF_DATA.</li> <li>Colbois_MCandTNdata_J1 : data and analysis for the nearest neighbour model in zero field.</li> <li>Colbois_TNdata_J1-h : data and analysis for the nearest neighbour model in a field</li> <li>Colbois_J1J2_Data : MC data for all the plots related to the J1-J2 model</li> <li>Colbois_J1J2J3ph_Data : MC correlations data for the 1/3 magnetisation plateau, and magnetisation data for all fields.</li> </ol> <p> </p> <p> </p> <p> </p> <p> </p>
Influence of feature size and shape on corrosion of 316L lattice structures fabricated by laser powder bed fusion
<p><strong>An open dataset for the paper with the same title: "<em>Influence of feature size and shape on corrosion of 316L lattice structures fabricated by laser powder bed fusion</em>". </strong></p> <p><strong>The dataset contains, for example, 3D models, original and analyzed microCT data, video visualizations, tensile testing .csv files, microscopy images, and code resources. Selected works are presented as part of the paper.</strong></p> <p><strong>Abstract:</strong></p> <p><em>Laser powder bed fusion (LPBF) has become an established method for manufacturing end-use metal components. Exploiting the geometric freedom of additive manufacturing (AM) offers broad possibilities for part optimization and enables performance enhancements across industry sectors. However, part shape and feature size have been found to locally affect residual stresses, melt pool cooling rates, microstructure, and thus the mechanical properties of </em><em>components. Even though the mesoscale structure can locally induce microstructural changes, there are no prior studies on how it influences corrosion. </em><em>Using AM-produced, optimized parts in critical applications necessitates a better understanding of their long-term performance. In this study, lattice structures were used to probe the influence of feature size and shape on corrosion susceptibility and its spatial localization.</em></p> <p><em>The susceptibility of submillimeter LPBF-fabricated 316L stainless steel </em><em>lattice structures to corrosion was investigated by conducting a 21-day immersion corrosion test in an aqueous 3.5wt% NaCl solution. Schoen gyroid and Schwarz </em><em>diamond triply periodic minimal surface lattices were manufactured with three unit cell sizes and wall thicknesses (0.867, 0.515, and 0.323 mm). The nominal surface and cross-sectional areas were the same for the two geometries. X-ray microcomputed tomography (microCT) scans before and after the corrosion test were compared for volumetric losses. <em>In addition, the </em>mechanical properties and microstructure of the samples were evaluated.</em></p> <p><em>As part of the study, a workflow to register, index, and analyze volumetric changes of consecutive microCT image stacks was developed. The method is fully reported and applicable to time-lapse studies with microCT. Three out of five of the 0.323 mm wall thickness lattices displayed visually aggressive pitting. Based on the microcomputed tomography data, the mass losses were localized either in the entrapped powder particles or partially melted surface globules. Corrosion did not occur in the dense base material. The total mass losses ranged from 8 to 19 mg. Despite visual indications to support a higher corrosion susceptibility for the smallest lattice sizes, the mass loss values did not confirm this conclusion. The tensile test results did not provide any clear indications of latent corrosion effects on mechanical properties.</em></p> <p> </p> <p><em>Version 1.1: 'Microstructure.zip' was revised. Metallographic preparation and Beraha II etching was redone for selected samples. New images and grain size (and grain distribution) measurements were added.</em></p> <p><em>Version 1.2: 'CT_Data_Heatmap_example.zip' was added. </em></p>
Dataset to run the NeuralFRG software for the t-t' Hubbard model on the square lattice "Phys. Rev. Lett. 129, 136402 (2022)"
<p>This hdf5 repository contains the fRG vertices for the t-t' Hubbard model on the square lattice required to reproduce the results shown in the publication</p> <p>Di Sante et al., Phys. Rev. Lett. 129, 136402 (2022)</p> <p>by means of the NeuralFRG software (https://github.com/BITMAPdds/NeuralFRG).</p> <p>A train-test split can be performed with:</p> <p>python3 train_validation_split.py NeuralFRG_train_and_validation_data.h5 --verbose</p> <p>and training can be started with:</p> <p>python3 train.py path/to/file_train.h5 (...) #Additional flags here</p>
Role of electronic correlations in the kagome-lattice superconductor LaRh3B2
<p>Here are reported some input and DFT results concerning the paper "Role of electronic correlations in the kagome-lattice superconductor LaRh3B2", published in Phys. Rev. B on 06/02/2023.</p> <p>The theoretical contribution to the work was mainly related to a phononic study of the system at hand, which have been performed using the Quantum Espresso package. Among the files you can then find the phonon density of states, as well as the phonon dispersion.<br> Also, are reported the electron-phonon interaction coefficients, lambda, for different values of the broadening.</p> <p>You can also find the geometry of the system, in VASP format (POSCAR) as well as the electronic band structure, computed with VASP. </p>
Spin-wave spectra in antidot lattice with inhomogeneous perpendicular magnetic anisotropy
<p>Data for "Spin-wave spectra in antidot lattice with inhomogeneous perpendicular magnetic anisotropy"</p> <p>https://aip.scitation.org/doi/abs/10.1063/5.0128621</p>
Data and code for "Tuning the lattice thermal conductivity in van-der-Waals structures through rotational (dis)ordering"
<p>This record contains neuroevolution potential (NEP) models for C, BN, and MoS<sub>2</sub> that have been constructed to model the potential energy surfaces of these materials in the presence of interlayer rotations. It also contains databases with the results from density functional theory calculations that were used for constructing the NEP models.</p> <p><strong>Databases</strong><br> The <code>*.db</code> files are databases with the results from density functional theory (DFT) calculations. These are sqlite databases in ase format, see <a href="https://wiki.fysik.dtu.dk/ase/tutorials/tut06_database/database.html">here</a> for more information. The <code>demo-database-access.py</code> script illustrates the most basic access.</p> <p><strong>Models</strong><br> The neuroevolution potential (NEP) models described in the publication can be found in the <code>nep-*.txt</code> files. They can be used in conjunction with the <a href="https://gpumd.org">GPUMD package</a>. The <a href="https://calorine.materialsmodeling.org">calorine package</a> provides a Python interface to GPUMD.</p> <p><strong>Primitive structures</strong><br> Several primitive structures in extended xyz format can be found in the <code>*.xyz</code> files. These structures have been relaxed using the NEP models included here. The <code>demo-for-using-structures-and-models.py</code> script illustrates how to access the structures and models.</p>
Insights on the coupling between vibronically active molecular vibrations and lattice phonons in molecular nanomagnets
<p>Spin–lattice relaxation is a key open problem to understand the spin dynamics of single-molecule magnets and molecular spin qubits. While modelling the coupling between spin states and local vibrations allows to determine the more relevant molecular vibrations for spin relaxation, this is not sufficient to explain how energy is dissipated towards the thermal bath. Herein, we employ a simple and efficient model to examine the coupling of local vibrational modes with long-wavelength longitudinal and transverse phonons in the clock-like spin qubit [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup>. We find that in crystals of this polyoxometalate the vibrational mode previously found to be vibronically active at low temperature does not couple significantly to lattice phonons. This means that further intramolecular energy transfer <em>via</em> anharmonic vibrations is necessary for spin relaxation in this system. Finally, we discuss implications for the spin–phonon coupling of [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup> deposited on a MgO (001) substrate, offering a simple methodology that can be extrapolated to estimate the effects on spin relaxation of different surfaces, including 2D materials.</p>
Pneumatic elastostatics of multi-functional inflatable lattices: Realization of extreme specific stiffness with active modulation and deployability
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Data for: Characterization, comparison, and optimization of lattice light sheets (Part 3/3)
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Data for: Characterization, comparison, and optimization of lattice light sheets (Part 2/3)
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Data for: Characterization, comparison, and optimization of lattice light sheets (Part 1/3)
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