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84 results for “Heterostructures”
Etching of Nitrides-NbN Heterostructures
<p>Niobium Nitride (NbN) is metallic at room temperature. NbN / III-N heterostructures are of interest for<br> new devices applications such as the Metal Base Transistor (MBT). Niobium Nitride etching in fluorine plasma is documented by Reactive Ion Etching (RIE). In this document we present the etching of a III-Nitride NbN heterostructure with fluorine<br> chemistry Inductively Coupled Plasma (ICP).</p>
Dataset supporting the paper "Molecular Approach for Engineering Interfacial Interactions in Magnetic/Topological Insulator Heterostructures. ACS Nano 14, 6285 (2020)"
<p>Dataset corresponding to theoretical calculations in the paper "Molecular Approach for Engineering Interfacial Interactions in Magnetic/Topological Insulator Heterostructures" ACS Nano 14, 6285 (2020), DOI: <a href="https://doi.org/10.1021/acsnano.0c02498">10.1021/acsnano.0c02498</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain the following files:</p> <ul> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>)</li> <li>.agr files: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).<br> </li> </ul>
Nanomechanical probing and strain tuning of the Curie temperature in suspended Cr2Ge2Te6-based heterostructures
<p>Data files for Figs. 1-5 of the article "Nanomechanical probing and strain tuning of the Curie temperature in suspended Cr<sub>2</sub>Ge<sub>2</sub>Te<sub>6</sub>-based heterostructures" published in <em>npj 2D Materials and Applications</em>, DOI: , URL: </p>
Resistive switching memories with enhanced durability enabled by mixed-dimensional perfluoroarene perovskite heterostructures
<p><span>Characterisation dataset for “</span><span>Resistive switching memories with enhanced durability enabled by mixed-dimensional perfluoroarene perovskite heterostructures”</span><span>, DOI:</span><span>10.1039/d4nh00104d</span><span>. Data for main and supporting figures provided as *.xlsx and *.txt files.</span></p> <p> </p> <p> </p> <p> </p>
Data on Quasi-1D Moiré superlattices in self-twisted two-allotropic antimonene heterostructures
<p><span> 1. LEED patterns collected for α-Sb and β-Sb phases deposited on W(110) substrate. The diffraction pattern acquired for a clean W(110) substrate with an electron energy of 46 eV and the μLEED patterns collected for α-Sb and β-Sb phases with electron energies of 43 eV and 23 eV, res</span></p> <p><span>E 2. LEEM images collected during deposition of Sb on W(110) substrate at 130 °<span>C. </span>All LEEM images were collected with an electron energy of 6.75 eV and <span>FOV = 10 μm</span>.</span></p> <p><span><span>3 3. </span></span><span>The set of micro LEED images showing isotropic character of the orientation of β-Sb inclusions on α-Sb layer in β-Sb/ α-Sb heterostructure.</span></p> <p><span><span>4 4. </span></span><span>μLEED patterns recorded for the α‑Sb phase and the β-Sb/α‑Sb heterostructure collected with electron energies of 43 eV and <a name="_Hlk160621262"></a>26 eV, respectively.</span></p>
Research data for "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations"
<p>This dataset supports the paper "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations". </p> <p><strong>Included Files:</strong></p> <ul> <li><strong>ocp_active.zip</strong>: Modified version of ocp (https://github.com/Open-Catalyst-Project/ocp) tailored for active learning applications.</li> <li><strong>deployed.pth</strong>: Pre-trained model used in the experiments.</li> <li><strong>chemiscopy_run.py</strong>: Script integrating the chemiscopy and nequip modules, designed for dataset visualization.</li> <li><strong>new_energy.py</strong>: Modified version of the nequip module, featuring a repulsive potential function.</li> <li><strong>test_datasets.extxyz</strong> & <strong>train_datasets.extxyz</strong>: The test and training datasets in extxyz format.</li> </ul> <p>How to use the modified version of the nequip module:</p> <p>To train this version of the potential function, it is recommended to use nequip<=0.5.6 (on Linux). The NequIP training files need to be updated as follows:</p> <pre><code>model_builders: - new_energy.EnergyModel - StressForceOutput min_bond_len: 1.8</code></pre> <p>Then run:</p> <p><code>export PYTHONPATH=${PYTHONPATH}:$PWD</code><br><code>nequip-train config.yml # Train the potential function</code><br><code>nequip-deploy build --train-dir nequipresultsdir build.pth # Deploy the trained model</code></p>
Time and momentum resolved characterization of hybrid plasmonic heterostructure Au/WSe2
<p>Dataset attached to paper titled "Observation of Multi-Directional Energy Transfer in a Hybrid Plasmonic-Excitonic Nanostructure" with time and momentum characterization of a 2D palsmonic heterostructure formed by Au nanoislands on bulk WSe2. It contains Angle-resolved photoemission spectroscopy (ARPES) and time-resolved ARPES data (trARPES.zip); femtosecond electron diffraction (FED) data (FED.zip); optical absorption spectroscopy data (Optical_absorbance.zip) and Transmission electron microscopy micrographs (TEM.zip).</p> <p>For <strong>trARPES.zip</strong>, the following table reports the grid of measurements and most important parameters:</p> <table> <tbody> <tr> <td><strong>Name</strong></td> <td><strong>Sample temperature (K)</strong></td> <td> <p><strong>Pump Wavelength (nm)</strong></p> </td> <td><strong>Pump Duration (fs)</strong></td> <td><strong>Material</strong></td> </tr> <tr> <td>trARPES_Metis_002.mpes.nxs</td> <td>300</td> <td>800</td> <td>35</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2124.mpes.nxs</td> <td>300</td> <td>800</td> <td>35</td> <td>WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2146.mpes.nxs</td> <td>70</td> <td>800</td> <td>35</td> <td>WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2197.mpes.nxs*</td> <td>70</td> <td>800</td> <td>35</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2198.mpes.nxs*</td> <td>70</td> <td>800</td> <td>35</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2212.mpes.nxs*</td> <td>300</td> <td>800</td> <td>35</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan2219.mpes.nxs*</td> <td>300</td> <td>800</td> <td>35</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan3159.mpes.nxs</td> <td>300</td> <td>1030</td> <td>200</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan3164.mpes.nxs**</td> <td>300</td> <td>1030</td> <td>200</td> <td>Au/WSe<sub>2</sub></td> </tr> <tr> <td>trARPES_Phoibos_Scan3185.mpes.nxs</td> <td>300</td> <td>1030</td> <td>200</td> <td>WSe<sub>2</sub></td> </tr> </tbody> </table> <p>*These scans are acquired with higher angular dispersion requiring separate scans for K and Sigma valleys.</p> <p>**Fluence scan.</p> <p><strong>FED.zip</strong> contains the following subfolders:</p> <ul> <li><em>Manuscript_Figure</em>: Experimental data and fit parameters depicted in Figure 4 of the main article.</li> <li><em>Analysis</em>: Additional information for the FED data including: raw data descriptions (delay, power, filename and more), Matlab scripts with comments, masks and backgrounds for image processing. The <em>Static_patterns</em> subfolder contains electron diffraction patterns of pure WSe<sub>2</sub> flakes and Au-covered WSe<sub>2</sub> flakes.</li> </ul> <p><strong>Optical_absorbance.zip</strong> contains the following subfolders & subfiles:</p> <ul> <li><em>without Au</em> & <em>with Au</em> containing all the optical measurements of pristine and Au-covered WSe<sub>2</sub> flakes, respectively.</li> <li><em>comparison_with_and_without_Au.xlsx</em> contains the analysis of the difference curves</li> <li><em>manuscript_figure.txt </em>contains the data that were used in Figure 1 of the main article.</li> </ul> <p> </p>
Two-dimensional Xene Heterostructures by Epitaxy
<p>The synthesis of new Xenes and their potential applications prototypes have achieved significant milestones so far. However, to date the realization of Xene heterostructures in analogy with the well-known van der Waals heterostructures remains an unresolved issue. Here, we introduce a Xene heterostructure concept based on the epitaxial combination of silicene and stanene on Ag(111), and demonstrate how one Xene layer enables another Xene layer of different nature to grow on top. We synthesized single-phase (4 x 4) silicene using stanene as a template, and managed to grow stanene on top of silicene on the other way around. In both heterostructures <em>in situ</em> and <em>ex situ</em> probes confirm layer-by-layer growth without intercalations and intermixing. Modelling via Density Functional Theory (DFT) shows that the atomic layers in the heterostructures are strongly interacting and hexagonal symmetry conservation in each individual layer is sequence-selective. Our results provide a substantial step towards currently missing Xene heterostructures and open the door to a new frontier of atomic-scale materials engineering. </p>
Supporting data for "Benchmarking the integration of hexagonal boron nitride crystals and thin films into graphene-based van der Waals heterostructures"
<p>Dataset for the publication "Benchmarking the integration of hexagonal boron nitride crystals and thin films into graphene-based van der Waals heterostructures"</p>
Dataset of the publication: Spin-crossover nanoparticles anchored on MoS2 layers for heterostructures with tunable strain driven by thermal or light-induced spin switching
<p>Dataset of the publication: </p> <div>Spin-crossover nanoparticles anchored on MoS2 layers for heterostructures with tunable strain driven by thermal or light-induced spin switching</div> <div> <div>https://doi.org/10.1038/s41557-021-00795-y</div> <div>R. Torres-Cavanillas, M. Morant-Giner, G. Escorcia-Ariza, J. Dugay, J. Canet-Ferrer, S. Tatay, S. Cardona-Serra, M. Giménez-Marqués, M. Galbiati, A. Forment-Aliaga, E. Coronado, <em>Nat Chem</em> <strong>2021</strong>, <em>13</em>, 1101.</div> </div>
Dataset of the publication: Hybrid Heterostructures of a Spin Crossover Coordination Polymer on MoS2: Elucidating the Role of the 2D Substrate. Small 2023, 19, e2304954.
<p><span> Dataset of the publication: Hybrid Heterostructures of a Spin Crossover Coordination Polymer on MoS2: Elucidating the Role of the 2D Substrate.</span></p> <p><span><span>A. Núñez-López, R. Torres-Cavanillas, M. Morant-Giner, N. Vassilyeva, R. Mattana, S. Tatay, P. Ohresser, E. Otero, E. Fonda, M. Paulus, V. Rubio-Giménez, A. Forment-Aliaga, E. Coronado, <em>Small</em> <strong>2023</strong>, <em>19</em>, e2304954.</span> </span></p> <p><span><span>doi: 10.1002/smll.202304954</span></span></p> <p><span><span><span>10.1002/smll.202304954</span><span>10.1002/smll.202304954<span>10.1002/smll.202304954</span></span></span></span></p>
Dataset of the publication: Strain Switching in van der Waals Heterostructures Triggered by a Spin-Crossover Metal–Organic Framework
<p>Dataset of the publication: Strain Switching in van der Waals Heterostructures Triggered by a Spin-Crossover Metal–Organic Framework</p> <p>DOI: 10.1002/adma.202110027</p> <p>Boix-Constant, Carla; Garcia-Lopez, Victor; Navarro-Moratalla, Efren; Clemente-Leon, Miguel; Zafra, Jose Luis; Casado, Juan; Guinea, Francisco; Manas-Valero, Samuel; Coronado, Eugenio</p> <p> Adv. Mater. 34, 2110027 (2022)</p>
Dataset of the publication: Probing the spin dimensionality in single-layer CrSBr van der Waals heterostructures by magneto-transport measurements
<p>Dataset of the publication: Probing the spin dimensionality in single-layer CrSBr van der Waals heterostructures by magneto-transport measurements</p> <p>DOI: 10.1002/adma.202204940</p> <p>C. Boix-Constant, S. Mañas-Valero, A. M. Ruiz, A. Rybakov, K. A. Konieczny, S. Pillet, J. J. Baldoví, E. Coronado</p> <p>Adv. Mater., 34, 2204940 (2022)</p>
Data for the article "Tuning Spin-Orbit Torques Across the Phase Transition in VO2/NiFe Heterostructure"
<p>Data for the article "Tuning Spin-Orbit Torques Across the Phase Transition in VO2/NiFe Heterostructure" (<a href="https://onlinelibrary.wiley.com/doi/full/10.1002/adfm.202111555">https://onlinelibrary.wiley.com/doi/full/10.1002/adfm.202111555</a> and <a href="http://arxiv.org/abs/2201.12984">http://arxiv.org/abs/2201.12984</a>)</p>
Data for: Quantum microscopy with van der Waals heterostructures
<p>Data repositiory for <em>Quantum microscopy with van der Waals heterostructures</em>.</p> <p>See README.txt in zip for details.</p>
Ultrafast data of "Near-Infrared Plasmon-Induced Hot Electron Extraction Evidence in an Indium Tin Oxide Nanoparticle/Monolayer Molybdenum Disulfide Heterostructure"
<p>Ultrafast differential transmission data:</p> <p>- Ito.txt : differential transmission map of indium tin oxide nanoparticles pumped at 1750 nm</p> <p>- Ito_Mos2.txt : differential transmission map of indium tin oxide nanoparticle / monolayer MoS2 heterojunction pumped at 1750 nm</p> <p>- MoS2_ir.txt : differential transmission map of monolayer MoS2 heterojunction pumped at 1750 nm</p> <p>- MoS2_vis.txt : differential transmission map of monolayer MoS2 heterojunction pumped at 500 nm</p> <p> </p> <p>In the matrix the first line is the vector of the delays in femtosecond, while the first raw is the vector of the wavelengths in nanometers.</p>
Data set of "Large superconducting diode effect in ion-beam patterned Sn-based superconductor nanowire/topological Dirac semimetal planar heterostructures"
<p><span>Superconductor/topological material heterostructures are intensively studied as a platform for topological superconductivity and Majorana </span><span>physics</span><span>. However, the high cost of nanofabrication and the difficulty of preparing high-quality interfaces between the two dissimilar materials are common obstacles that hinder the observation of intrinsic physics and </span><span>the </span><span>realisation of scalable topological devices and circuits. </span><span>Here, we demonstrate an innovative method to directly draw nanoscale superconducting </span><span><span>beta-tin (</span></span><span><span>β-Sn</span></span><span><span>)</span></span><span><span> patterns of any shape in the plane of a topological Dirac </span></span><span><span>semimetal</span></span><span><span> (TDS) </span></span><span><span>alpha-tin (</span></span><span><span>α-Sn</span></span><span><span>)</span></span><span><span> thin </span></span><span><span>film</span></span><span><span> by irradiating a focused ion beam (FIB</span></span><span><span>). We utilise</span></span><span><span> the property that α-Sn undergoes a phase transition to superconducting β-Sn upon heating by FIB. </span></span><span><span>In β-Sn nanowires embedded in a TDS α-Sn thin film, we observe large </span></span><span><span>non-reciprocal</span></span><span><span> superconducting transport, where the critical current changes by 69% upon reversing the current direction. The superconducting diode rectification ratio <em>η</em> reaches a maximum of 35% when the magnetic field is applied parallel to the current, </span></span><span><span>distinguishing</span></span><span><span> itself from all the previous reports</span></span><span><span>. Moreover, it</span></span><span><span> oscillates between alternate signs with increasing magnetic field strength. </span></span><span><span>The angular</span></span><span><span> dependence of <em>η</em> on the magnetic field and current directions is similar to that of the chiral anomaly effect in TDS α-Sn, suggesting that the </span></span><span><span>SDE</span></span><span><span> may occur at the α-Sn/</span></span><span><span>β</span></span><span><span>-Sn interfaces where the TDS α-Sn becomes superconducting by a proximity effect.</span></span><span><span> As superconducting TDSs are expected candidates for topological superconductivity and harboring Majorana bound states,</span></span><span><span> t</span></span><span><span>he ion-beam patterned Sn-based superconductor/TDS planar structures thus </span></span><span><span>show promise</span></span><span><span> as a universal platform for investigating novel quantum physics and devices based on topological superconducting circuits of any shape.</span></span></p>
Tailoring optical properties of 2D semiconductors in van der Waals heterostructures
<p>Dataset for the publication 'Tailoring the dielectric screening in WS<sub>2</sub>-graphene heterostructures'</p>
BeMAGIC_Organic/inorganic heterostructured (bilayered) multiferroic films
<p>BeMAGIC ITN (GA861145)_Organic/inorganic heterostructured (bilayered) multiferroic films. Results from ICN2, UAB and UCAM</p>
Gate-Tunable Spin Hall Effect in an All-Light-Element Heterostructure: Graphene with Copper Oxide
<p>Graphene is a light material for long-distance spin transport due to its low spin–orbit coupling, which at the same time is the main drawback for exhibiting a sizable spin Hall effect. Decoration by light atoms has been predicted to enhance the spin Hall angle in graphene while retaining a long spin diffusion length. Here, we combine a light metal oxide (oxidized Cu) with graphene to induce the spin Hall effect. Its efficiency, given by the product of the spin Hall angle and the spin diffusion length, can be tuned with the Fermi level position, exhibiting a maximum (1.8 ± 0.6 nm at 100 K) around the charge neutrality point. This all-light-element heterostructure shows a larger efficiency than conventional spin Hall materials. The gate-tunable spin Hall effect is observed up to room temperature. Our experimental demonstration provides an efficient spin-to-charge conversion system free from heavy metals and compatible with large-scale fabrication.</p>
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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.