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14 results for “two-dimensional materials”
Bandgap fluctuations and robustness in two-dimensional hyperuniform dielectric materials
<p>These are the data associated with the paper "Bandgap fluctuations and robustness in two-dimensional hyperuniform dielectric materials" published in <a href="http://doi.org/10.1364/OE.484232"><em>Optics Express</em> <strong>31</strong>, 18509 (2023)</a></p> <ul> <li>gapsFrequenciesAndWidths.h5: each line of the table lists the largest and second largest gap widths and frequencies in GHz for all 5000 samples studied in the paper <table align="center"> <thead> <tr> <th scope="col">Column</th> <th scope="col">Quantity</th> </tr> </thead> <tbody> <tr> <td>0</td> <td><span class="math-tex">\(\chi\)</span></td> </tr> <tr> <td>1</td> <td>largest gap frequency (GHz)</td> </tr> <tr> <td>2</td> <td>largest gap width (GHz)</td> </tr> <tr> <td>3</td> <td>second largest gap frequency (GHz)</td> </tr> <tr> <td>4</td> <td>second largest gap width (GHz)</td> </tr> </tbody> </table> </li> <li>DOS.h5: normalized density of states as a function of the frequency (GHz) averaged over all samples for all <span class="math-tex">\(\chi\)</span> values studied in the paper <table align="center"> <thead> <tr> <th scope="col">Column</th> <th scope="col">Quantity</th> </tr> </thead> <tbody> <tr> <td>0</td> <td><span class="math-tex">\(\chi\)</span></td> </tr> <tr> <td>1</td> <td>Frequency (GHz)</td> </tr> <tr> <td>2</td> <td>nDOS</td> </tr> </tbody> </table> <p> </p> </li> </ul>
Out-of-plane ferroelectricity and robust magnetoelectricity in quasi two-dimensional materials
<p>Thin film ferroelectrics have been pursued for capacitive and nonvolatile memory devices. They rely on polarizations that are oriented in an out-of-plane direction to facilitate integration and addressability with CMOS architectures. The internal depolarization field, however, formed by surface charges can suppress the out-of-plane polarization in ultrathin ferroelectric films that could otherwise exhibit lower coercive fields and operate with lower power. Here we unveil stabilization of a polar longitudinal optical (LO) mode in the <em>n</em>=2 Ruddlesden–Popper family that produces out-of-plane ferroelectricity, persists under open-circuit boundary conditions, and is distinct from hyperferroelectricity. Our first-principles calculations show the stabilization of the LO mode is ubiquitous in chalcogenides and halides and relies on anharmonic trilinear mode coupling. We further show that the out-of-plane ferroelectricity can be predicted with a crystallographic tolerance factor, and we use these insights to design a room-temperature multiferroic with strong magnetoelectric coupling suitable for magneto-electric spin-orbit transistors. </p>
Datasets of VAMAS TWA2 Project 33: Chemical characterization of graphene related two-dimensional materials by XPS
<p>The datasets contain excel-files of the XPS raw data of the participants of the interlaboratory comparison. Additionally, the protocol is added.</p>
Two-dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials
<p>This repo contains the supplementary data sets for the to-be-published paper entitled "Two-dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials".</p> <p> </p> <p>This repo contains the following data sets:</p> <p>1. CIF files for amorphous porous materials (activated carbon, hyper-cross-linked polymers, Kerogen, PIMs).</p> <p>2. Grand canonical Monte Carlo (GCMC) simulation results for single-component adsorption isotherms in ToBaCCo1.0 MOFs and in amorphous porous materials. Gas molecules include Kr, Xe, ethane, propane, butane, n-hexane, and 2,2-dimethylbutane.</p> <p>3. Textural properties of ToBaCCo1.0 MOFs and amorphous porous materials.</p> <p>4. Trained machine learning models. R code that can work with these ML models is hosted on <a href="https://github.com/snurr-group/2D-energy-histogram">GitHub</a>. </p>
Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 4/4
<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> <p>Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118</p> <h3>Contents</h3> <p>Trajectories of positions and forces with corresponding input files of systems with 550 water molecules on 2D materials:</p> <ul> <li>MoS2/water</li> <li>MoS2/MoS2/water</li> <li>graphene/MoS2/water</li> <li>MoS2/graphene/water</li> <li>MoS2/hBN/water</li> <li>hBN/MoS2/water</li> <li>graphene/water</li> <li>hBN/water</li> </ul>
Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 3/4
<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> <p>Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118</p> <h3>Contents</h3> <p>Trajectories of positions and forces with corresponding input files of systems with 550 water molecules on 2D materials:</p> <ul> <li>graphene/graphene/water</li> <li>hBN/hBN/water</li> <li>graphene/hBN/water</li> <li>hBN/graphene/water</li> </ul>
Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 1/4
<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> <p>Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118</p> <h3>Contents</h3> <p>Trajectories of positions and forces with corresponding input files of systems with 120 water molecules confined between 2D materials:</p> <ul> <li>graphene/water/graphene</li> <li>hBN/water/hBN</li> <li>graphene/graphene/water/graphene/graphene</li> <li>hBN/hBN/water/hBN/hBN</li> <li>graphene/hBN/water/hBN/graphene</li> <li>hBN/graphene/water/graphene/hBN</li> </ul> <p> </p>
Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 2/4
<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> <p>Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118</p> <h3>Contents</h3> <p>Trajectories of positions and forces with corresponding input files of systems with 120 water molecules confined between 2D materials:</p> <ul> <li>MoS2/water/MoS2</li> <li>MoS2/MoS2/water/MoS2/MoS2</li> <li>graphene/MoS2/water/MoS2/graphene</li> <li>MoS2/graphene/water/graphene/MoS2</li> </ul>
Out-of-plane ferroelectricity and robust magnetoelectricity in quasi two-dimensional materials
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Diffusive regimes in a two-dimensional chiral fluid - Supplementary Material
<p>Supplementary datasets and additional videos. Data files are included for the experiments corresponding to Figures 1(a), 2 and 4(a), they are stored in a compressed pickle format, they can be easily read in Python with:</p> <pre><code class="language-python">df = pd.read_pickle('path_to_file', compression='xz')</code></pre> <p>The experiment ids of the experimental data files correspond to the following cases:</p> <ul> <li>155e9e3bf635544e8ff7240c760bee7b: packing fraction 0.45, mean vorticity -0.12</li> <li>f509f3b902a7ada8064a9247404d7019: packing fraction 0.45, mean vorticity 0.03</li> <li>edc6f35457554fd45382f6becdf41d97: packing fraction 0.45, mean vorticity 0.26</li> </ul>
Nonunique fraction of Fock exchange for defects in two-dimensional materials
<p>This dataset contains the input and output files for the defect calculations as described in the paper "Nonunique fraction of Fock exchange for defects in two-dimensional materials".</p> <ol> <li>ws2.tar.gz: PBE and PBE0, monolayer WS<sub>2</sub></li> <li>ws2_bulk.tar.gz: PBE and PBE0, bulk WS<sub>2</sub></li> <li>ws2_bgw.tar.gz: G<sub>0</sub>W<sub>0</sub>, monolayer WS<sub>2</sub></li> </ol> <p> </p>
Quantitative Nanoscale Absorption Mapping: A Novel Technique To Probe Optical Absorption of Two-Dimensional Materials
<p>Two-dimensional semiconductors, in particular transition metal dichalcogenides and related heterostructures, have gained increasing interest as they constitute potential new building blocks for the next generation of electronic and optoelectronic applications. In this work, we develop a novel nondestructive and noncontact technique for mapping the absorption properties of 2D materials, by taking advantage of the underlying substrate cathodoluminescence emission. We map the quantitative absorption of MoS<sub>2</sub> and MoSe<sub>2</sub> monolayers, obtained on sapphire and oxidized silicon, with nanoscale resolution. We extend our technique to the characterization of the absorption properties of MoS<sub>2</sub>/MoSe<sub>2</sub> van der Waals heterostructures. We demonstrate that interlayer excitonic phenomena enhance the absorption in the UV range. Our technique also highlights the presence of defects such as grain boundaries and ad-layers. We provide measurements on the absorption of grain boundaries in monolayer MoS<sub>2</sub> at different merging angles. We observe a higher absorption yield of randomly oriented monolayers with respect to 60° rotated monolayers. This work opens up a new possibility for characterizing the functional properties two-dimensional semiconductors at the nanoscale.</p> <p> </p> <p>This dataset contains some of the raw data for Figures 1 and 2.</p>
Dataset and Code for the Paper "Reinforced Active Learning for CVD-Grown Two-Dimensional Materials Characterization"
<p>This repository contains the original data and code for the paper titled as "Reinforced Active Learning for CVD-Grown Two-Dimensional Materials Characterization" published on <em>IISE Transactions</em>.</p>
Magnetic two-dimensional material dataset
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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.