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4 results for “van der Waals structures”
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>
Datesets and images of the publication "Probing crystallinity and grain structure of 2D materials and 2D-like van der Waals heterostructures by low-voltage electron diffraction" - DOI: 10.1002/pssa.202300148
<p>Datasets and images of the publication "Probing crystallinity and grain structure of 2D materials and 2D-like van der Waals heterostructures by low-voltage electron diffraction" - DOI: <a href="https://www.doi.org/10.1002/pssa.202300148">10.1002/pssa.202300148</a></p> <p>The Jupyter Notebooks for analyzing the datasets and generating all the figures are available at <a href="https://gitlab.com/JohMu/tds_hios_manuscript">https://gitlab.com/JohMu/tds_hios_manuscript</a>.</p> <p><strong>MoS<sub>2</sub> 4D-STEM dataset:</strong></p> <ul> <li>192x192 scan pixels</li> <li>200x200 camera pixels</li> <li>Acceleration voltage: 20kV</li> <li>Camera length: 10.56 mm</li> <li>Camera pixel size: 4x5.86 µm = 23.44 µm (original dataset with 4x4 binning)</li> <li>File location: Figure 2_3_S1.zip -> 230101205338_20kV_hexz0_camz-10_posi_003_good\scan_data_bin2_centered_crop-imgNx200.h5</li> <li>The original raw dataset (23 GB, 192x192 scan pixels, 800x800 camera pixels, camera pixel size: 5.86 µm), the scan reference dataset and the Jupyter Notebook for the shift-compensation is available from the author. The dataset uploaded here is binned by a factor of 4 and shift-compensated.</li> </ul> <p><strong>C60/MoS<sub>2</sub> 4D-STEM dataset:</strong></p> <ul> <li>113x113 scan pixels</li> <li>512x512 camera pixels</li> <li>Acceleration voltage: 20kV</li> <li>Camera length: 20.56 mm</li> <li>Camera pixel size: 5.86 µm</li> <li>File location: Figure 4.zip -> scan_data_scan113x113_gzip.h5</li> </ul> <p> </p>
Data set for "Electrical detection of the flat band dispersion in van der Waals field-effect structures"
<p>Data set for "Electrical detection of the flat band dispersion in van der Waals field-effect structures" paper published in doi:10.1038/s41565-023-01489-x</p>
Auto-resolving atomic structure at van der Waal interfaces using a generative model
<p>Dataset and model parameter for paper 'Auto-resolving atomic structure at van der Waal interfaces using a generative model'</p> <p>The dataset will be made public after the papers are accepted.</p> <p>Modified DRIT training data: xxx.tar.gz</p> <p>Modified DRIT Model parameter:modified_dirt_xxx.pth</p> <p>Stacking Pattern Analysing Model training data: xxx_als.tar.gz</p> <p>Bilayer ReS2 Stacking Pattern Analysing Model's parameter : res2_bs.pth</p> <p>MoS2 stacking pattern training data is subvolume compressed, please download all subvolumes to use this data set</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.