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167 results for “Twist”
WES cropbioBonn WGGC CN Twist Exome vcf results
<p>Whole Exome Sequencing Data Analysis with <a href="https://github.com/tgstoecker/WES_WGGC_2021_AG_Schoof">https://github.com/tgstoecker/WES_WGGC_2021_AG_Schoof</a></p> <p>HG001/NA12878 Twist Exome, NovaSeq 6000</p>
Implementing electronic signatures of graphene and hexagonal boron nitride in twisted bilayer molybdenum disulfide
<p><strong>Abstract</strong></p> <p>Angeli and MacDonald reported a superlattice-imposed Dirac band in twisted bilayer molybdenum disulphide (tBL MoS2) for small twist angles towards the R_h^M (parallel) stacking. Using a hierarchical set of theoretical methods, we show that the superlattices differ for twist angles with respect to metastable R_h^M (0°) and lowest-energy H_h^h (60°) configurations. When approaching R_h^M stacking, identical domains with opposite spatial orientation emerge. They form a honeycomb superlattice, yielding Dirac bands and a lateral spin texture distribution with opposite-spin-occupied K and K’ valleys. Small twist angles towards the H_h^h configuration (60°) generate H_h^h and H_h^X stacking domains of different relative energies and, hence, different spatial extensions. This imposes a symmetry break in the moiré cell, which opens a gap between the two top-valence bands, which become flat already for relatively small moiré cells. The superlattices impose electronic superstructures resembling graphene and hexagonal boron nitride into trivial semiconductor MoS<sub>2</sub>.</p> <p>The data set published in this repository was used to create the preprint published at <strong>https://doi.org/10.26434/chemrxiv-2023-rx2fz</strong>.</p> <p><strong>Content of repository</strong></p> <ul> <li>"ReaxFF_structure_optimization.zip": contains the inputs and outputs for all structure optimizations for ML, BL, and tBL systems using the Reax force field, performed using LAMMPS.</li> <li>" bilayer_verification_ReaxFF_with_DFT.zip": contains the inputs and outputs for verifying the results of the Reax force field by running DFT geometry optimization and total energy calculations in FHI-aims for the high-symmetry bilayer stackings.</li> <li>"QATK_band_structures_and_eff_mass.zip": contains the inputs and outputs of all calculations done via QuantumATK (QATK), including calculations for ML, BL, and tBL systems on DFT and DFTB level of theory.</li> <li>"TB_fit.zip": contains the Python scripts and input data (DFTB band structure) used to fit the TB Hamiltonians as described in the Methods section and shown in the Supplementary Material.</li> <li>"effective_masses_from_bands.zip": contains the extraction of the effective hole masses from the bands calculated at the DFTB level of theory in QATK.</li> </ul>
Relaxation effects in twisted bilayer molybdenum disulfide: structure, stability, and electronic properties
<p><strong>Abstract</strong></p> <p>Manipulating the interlayer twist angle is a powerful tool to tailor the properties of layered two-dimensional crystals. The twist angle has a determinant impact on these systems' atomistic structure and electronic properties. This includes the corrugation of individual layers, formation of stacking domains and other structural elements, and electronic structure changes due to the atomic reconstruction and superlattice effects. However, how these properties change with the twist angle, <em>θ</em>, is not yet well understood. Here, we monitor the change of twisted bilayer (tBL) MoS<sub>2</sub> characteristics as a function of <em>θ</em>. We identify distinct structural regimes, each with particular structural and electronic properties. We employ a hierarchical approach ranging from a reactive force field through the density-functional-based tight-binding approach and density-functional theory. To obtain a comprehensive overview, we analyzed a large number of tBLs with twist angles in the range of <span class="math-tex">\(\theta=0.2^\circ\dots59.6^\circ\)</span>. Some systems include up to half a million atoms, making structure optimization and electronic property calculation challenging. For <span class="math-tex">\(13^\circ \lessapprox \theta \lessapprox 47^\circ\)</span>, the structure is well-described by a moiré regime composed of two rigidly twisted monolayers. At small twist angles (<span class="math-tex">\(\theta\leq3^\circ\)</span> and <span class="math-tex">\(57^\circ\leq\theta\)</span>), a domain-soliton regime evolves, where the structure contains large triangular stacking domains, separated by a network of strain solitons and short-ranged high-energy nodes. The corrugation of the layers and the emerging superlattice of solitons and stacking domains affects the electronic structure. Emerging predominant characteristic features are Dirac cones at <em>K</em> and kagome bands. These features flatten for <em>θ</em> approaching 0<sup>∘</sup> and 60<sup>∘</sup>. Our results show at which range of <em>θ</em> the characteristic features of the reconstruction, namely extended stacking domains, the soliton network, and superlattice, emerge and give rise to exciting electronics. We expect our findings also to be relevant for other tBL systems.</p> <p>DOI: 10.1088/2053-1583/aceb75</p> <p><strong>Overview</strong></p> <p>This repository contains calculation files, optimized structures, and visualization movies for studies of twisted-bilayer MoS<sub>2</sub>, focussing on structural properties and electronic structure. Each directory has its own README.md file with additional information, separated by what data is included and the method used.</p> <p><strong>Geometry optimization</strong></p> <ul> <li>Directory `calc_structure_optimization_ReaxFF`: calculation files of the structure optimization of all studied structures, done with ReaxFF.</li> <li>Directory `calc_structure_optimization_DFT`: validation calculation files of the ReaxFF-optimized structures using DFT optimization.</li> </ul> <p><strong>Electronic structure calculations</strong></p> <ul> <li>Directory `calc_electronic_properties_DFT`: calculation files of electronic structure calculations on the DFT level.</li> <li>Directory `calc_electronic_properties_DFTB`: calculation files of electronic structure calculations on the DFTB level</li> </ul> <p><strong>Results</strong></p> <ul> <li>Directory `structures_rigidly_twisted`: structure files in cif format of the rigidly twisted (flat) systems, labeled by their twist angle.</li> <li>Directory `structures_fully_optimized`: structure files in cif format of the fully ReaxFF-optimized systems, labeled by their twist angle.</li> <li>Directory `movies`: visualization of the change of the interlayer distance landscape and the strain fields with the twist angle.</li> <li>Additionally, the script `plot_interlayer_distance.py` is included, which was used to create the individual frames of the movie showing the interlayer distance.</li> </ul>
Data: A New Twist on the Light-Switch Effect: Controlling the fate of excited states with pH in a 4-hydroxythiazol-extended Ruthenium(II) dppz complex
<p>The peer-reviewed publication for this dataset has been published in <a href="https://doi.org/10.1021/acs.jpca.3c06179">J. Phys. Chem. A 2023, 127, 50, 10613–10620, DOI: 10.1021/acs.jpca.3c06179.</a> Please cite this when using the data.</p>
Direct magnetic imaging of fractional Chern insulators in twisted MoTe2
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Data from: Twist and chew: three dimensional tongue kinematics during chewing in macaque primates
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Twisted epitaxy of gold nanodiscs grown between twisted substrate layers of molybdenum disulfide
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Experimental data for "Localization of lattice dynamics in low-angle twisted bilayer graphene"
<p>This repository contains the experimental data related to the article "Localization of lattice dynamics in low-angle twisted bilayer graphene" and is provided to the reader under the “data availability” directive. the files have been organized on a per-figure basis.</p>
Strain fields in twisted bilayer graphene: Dataset 10 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_13.h5 : dataset s2-13 corresponding to mean angle of 0.16</p>
Strain fields in twisted bilayer graphene: Dataset 11 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_3.h5 : dataset s2-3 corresponding to mean angle of 1.1669</p>
Strain fields in twisted bilayer graphene: Dataset 6 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_2.h5 : dataset s2-2 corresponding to mean angle of 0.317</p>
Strain fields in twisted bilayer graphene: Dataset 4 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>02262020_15.h5 : dataset s1-15 corresponding to mean angle of 0.1203</p> <p>20200616_8.h5 : dataset s2-8 corresponding to mean angle of 0.663</p> <p>20200616_9.h5 : dataset s2-9 corresponding to mean angle of 0.6632</p>
Strain fields in twisted bilayer graphene: Dataset 12 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_4.h5 : dataset s2-4 corresponding to mean angle of 1.1897</p>
Strain fields in twisted bilayer graphene: Dataset 16 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_19.h5 : dataset s2-19 corresponding to mean angle of 0.16</p> <p>20200616_20.h5 : dataset s2-20 corresponding to mean angle of 0.16</p> <p>20200616_21.h5 : dataset s2-21 corresponding to mean angle of 0.16</p>
Strain fields in twisted bilayer graphene: Dataset 17 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_1.h5 : dataset s2-1 corresponding to mean angle of 0.2894</p> <p>20200616_23.h5 : dataset s2-23 corresponding to mean angle of 1.3067</p>
Strain fields in twisted bilayer graphene: Dataset 8 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_8.h5 : dataset s2-8 corresponding to mean angle of 0.7534</p>
Strain fields in twisted bilayer graphene: Dataset 3 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>02262020_18.h5 : dataset s2-10 corresponding to mean angle of 0.1355</p>
Strain fields in twisted bilayer graphene: Dataset 7 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_24.h5 : dataset s2-24 corresponding to mean angle of 1.3178</p> <p>20200616_25.h5 : dataset s2-25 corresponding to mean angle of 1.3468</p> <p>20200616_26.h5 : dataset s2-26 corresponding to mean angle of 1.3259</p>
Strain fields in twisted bilayer graphene: Dataset 2 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>02262020_10.h5 : dataset s1-10 corresponding to mean angle of 0.6272</p> <p>02262020_5.h5 : dataset s1-5 corresponding to mean angle of 1.2343</p> <p>02262020_8.h5 : dataset s1-8 corresponding to mean angle of 1.3672</p>
Strain fields in twisted bilayer graphene: Dataset 15 of 19
<p>See supplemental materials of Kazmierczak & Van Winkle et al for more information.</p> <p>20200616_14.h5 : dataset s2-14 corresponding to mean angle of 0.16</p>
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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)
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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.