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22 results for “band gap”
Supplementary dataset: Phoamtonic designs yield sizeable 3D photonic band gaps
<p>Supplementary Dataset of the publication "<a href="http://www.pnas.org/content/116/47/23480">Phoamtonic designs yield sizeable 3D photonic band gaps</a>" by the same authors:</p> <p>M. A. Klatt, P. J. Steinhardt, S. Torquato. <em>Proc. Natl. Acad. Sci. U.S.A.</em> <strong>116</strong>:23480–23486 (2019)<br> <a href="https://doi.org/10.1073/pnas.1912730116">https://doi.org/10.1073/pnas.1912730116</a></p> <p>Database S1 "Gap maps": Raw data of the gap maps listing the gap--mid-gap ratios together with the corresponding rod radii, volume fractions, or dilectric contrast.</p> <p>Database S2 "Configurations": All triply-periodic nets and networks analyzed in this study. The readme file explains the file formats.</p> <p>Database S3 "Parameters and Data": All parameters for the photonic calculations, raw output and post-processed data sets.</p>
Training Machine-Learned Density Functionals on Band Gaps
<p>This dataset contains atomic structures and molecular orbitals (computed with DFT using the PBE functional) for the systems studied in the paper "<a href="https://doi.org/10.1021/acs.jctc.4c00999">Training Machine-Learned Density Functionals on Band Gaps</a>." The <a href="https://github.com/mir-group/CiderPress">CiderPress code</a> can be used to analyze the data.</p> <p>Please see the README.md file for more details on the dataset, and refer to the original paper for details on methodology and funding acknowledgments.</p>
Revised direct band gap and band parameters for AlP: hybrid-functional first-principles calculations vs. experiment
<p>Raw data and plotting scripts associated with the paper:<br><br>Cónal Murphy, Eoin P. O'Reilly and Christopher A. Broderick, "Revised direct band-gap and band parameters for AlP: hybrid-functional first-principles calculations vs. experiment", <em>APL Mater.</em> (2024) (undergoing revision)<br><br>Tyndall National Institute, Lee Maltings, Dyke Parade, University College Cork, Cork T12 R5CP, Ireland<br>School of Physics, University College Cork, Cork T12 YN60, Ireland</p>
Dataset for study "Band gap engineering by cationic substitution in Sn(Zr1-xTix)Se3 alloy for bottom sub-cell application in solar cells"
<p>This dataset contains raw and processed data that were used to for the study entilted "Band gap engineering by cationic substitution in Sn(Zr1-xTix)Se3 alloy for bottom sub-cell application in solar cells". </p>
Gap dendrometer band measurements at the Coweeta Hydrologic Laboratory from 1992 to 2000 (Circumference measurements)
Tree mortality at small spatial scales represents background levels of forest disturbance in the southern Appalachians, and is the dominant and most frequent initiator of change in terrestrial ecosystems. Large-scale and rare episodic events (i.e., hurricanes, ice, etc.) may do more to influence tree replacement and stand composition in the long-run than do small scale tree mortality events. What is the ecological significance of small scale mortality events with respect to biotic and abiotic responses? We experimentally created typical (<300 m2) canopy gaps (girdling and herbicides) at two elevations in Rhododendron and non-Rhododendron areas. The measurements in this study included automated micro-environmental measurements (air and soil temperature), photosynthetically active radiation, %WC, hemispherical photography, dendrometer bands and repeated measurements, population dynamics and seedling physiology, in situ closed core N mineralization and nitrification, and small and large mammal seed and plant herbivory using exclosures. Here are some specific questions relating to this study. How are microclimate and nutrient (N) cycling affected by small scale canopy removal? What are the physiological and productivity responses of advanced regeneration? What is the productivity response of non-gap-maker trees (dominants, co-dominant, and saplings)? What strategy for recovery is most likely (seedling recruitment, sapling ingrowth, canopy closure)? How do all of the above relate to/regulate each other? What is the effect of elevation on response? How do responses differ in Rhododendron versus non-Rhododendron areas?
GNN Models and results for the paper "Band-gap regression with architecture-optimized message-passing neural networks"
<p>Contains files with model parameters for random search and reference models, as well as the converted AFLOW dataset, in graphs form. Corresponds to results in <a href="https://arxiv.org/pdf/2309.06348.pdf">https://arxiv.org/pdf/2309.06348.pdf</a>.</p> <p>Model predictions along with AUID identifiers are located in result_combined.zip, band gap (egap) and formation energy (ef) predictions are from the PaiNN ensemble, band gap classification is done by MPEU model.</p> <p>New results include PaiNN NAS models.</p> <p>Compatible source code can be found at <a href="https://github.com/tisabe/jraph_MPEU/tree/v1.0.0">jraph_MPEU GitHub repository</a>.</p>
Data: Non-utopian optical properties computed of a tomographically reconstructed real photonic band gap crystal
<p>This repository contains the scripts and data used for the manuscript "Non-utopian optical properties computed of a tomographically reconstructed real photonic band gap crystal'' by LJ Corbijn van Willenswaard, S Smeets, N Renaud, M Schlottbom, JJW van der Vegt and WL Vos</p> <p>This dataset contains the following:</p> <ul> <li>The starting slice of the X-ray holotomagraphy dataset</li> <li> All data generated that is used in the paper including: <ul> <li>X-ray processing results</li> <li>Raw results from the computations</li> <li>Post processed results that are the basis of the manuscript</li> </ul> </li> <li>All scripts that were used to automate this process</li> <li>A copy of: <ul> <li>Nanomesh repository (for x-ray processing)</li> <li>hpgem & DGMax source code (for the computations)</li> </ul> </li> </ul> <p>A more detailed readme is included with the data.</p>
Selective dynamic band gap tuning in metamaterials using graded photoresponsive resonator arrays
<p>Raw Data for figures:</p> <p>Fig. 2: Dispersion diagrams for non-illuminated (off) and illuminated (on) pillars of different heights (hp). hp1 = 7 mm, hp2 = 9 mm, hp3 = 11 mm, hp4 = 13 mm; p = 0 (1) for purely in- (out-of-plane) behavior</p> <p>Fig. 4: Computed transmission spectrum of a finite structure. a) Numerically simulated transmission spectrum for the considered 8-pillar specimen, both without ("Laser off") and with laser illumination ("Laser on 7th pillar").</p> <p>Fig. 5: Transmission spectrum of the finite structure considered experimentally. a) Measured spectra before (blue) and after (red) illumination of pillar 1. Band gaps are highlighted in light blue and numbered from I to IV; b) Corresponding colour map representing transmission vs. frequency and time (vertical axis) when switching laser illumination on (t = 700 s) and off (t = 2300 s); c) same as a), with illumination of pillar 6; d) same as b), with illumination on pillar 6.</p> <p>Fig. 6: Dynamic modulation of signal frequencies (f1 = 21.5 kHz, f2 = 71.5 kHz) in a graded pillar structure. The different temporal intervals depict tunable suppression and enhancement of specific frequencies through selective pillar illumination.</p>
Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se)
<p>The structural, electrical, and optical properties of a series of six layered oxychalcogenides with general formula Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> where <em>M</em> = Ga, Sc, or In and <em>Ch</em> = S or Se have been investigated. From this set we report the structure and properties of Sr<sub>2</sub>GaO<sub>3</sub>CuSe for the first time, as well as the full structural details of Sr<sub>2</sub>ScO<sub>3</sub>CuSe, which have not previously been available. A systematic study of the suitability of all the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> phases as <em>p</em>-type conductors has been carried out, after doping with both sodium and potassium to a nominal composition of <em>A</em><sub>0.05</sub>Sr<sub>1.95</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em>, (<em>A</em> = Na or K), to increase the hole carrier concentration. Density functional theory calculations were used to determine the electronic band structure and predict the transport properties, while optical properties were determined using UV-vis spectroscopy, and structures confirmed using Rietveld refinement against powder X-ray diffraction data. Room temperature conductivity measurements were carried out on both pristine samples and doped samples, eighteen compositions in total, using four-point probe measurements. We found that the most conductive sample wasK<sub>0.05</sub>Sr<sub>1.95</sub>GaO<sub>3</sub>CuSe, with a measured conductivity of 0.46 Scm<sup>−1</sup>, collected from a sintered pellet. We have also been able to identify a relationship between the conductivity and the geometry of the copper chalcogenide layer within the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> series of compounds. As this geometry can be controlled through the material composition, the identification of this structure-property relationship highlights a route to selection and identification of materials with even higher conductivities.</p> <p> </p> <p>This repository contains the computational research data generated for *Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se).</p> <p> </p> <p>## Folder Architecture</p> <p>The folders contain the structures relaxed with hybrid functionals (HSE06), the band structure and the uniform DOS and AMSET calculations for each system.</p> <p> </p> <p> </p>
Dataset for "Role of electron-phonon coupling and thermal expansion on band gaps, carrier mobility, and interfacial offsets in kesterite thin-film solar cells"
<p>Dataset for "Role of electron-phonon coupling and thermal expansion on band gaps, carrier mobility, and interfacial offsets in kesterite thin-film solar cells"</p>
Dataset for "Open-Circuit Voltage Deficit in Cu2ZnSnS4 Solar Cells by Interface Band Gap Narrowing"
<p><strong>Files in "ExchangeCorrelation": POSCAR_material_Exc</strong></p> <p><em>material</em></p> <ul> <li>CdS </li> <li>CZTS = Cu2ZnSnS4</li> <li>CZTSe = Cu2ZnSnSe4</li> </ul> <p><em>Exchange-correlation functionals</em></p> <ul> <li>PBE</li> <li>RP = revised PBE</li> <li>PBEsol</li> <li>AM05</li> <li>SCAN</li> <li>HSE06</li> <li>6_6: PBE+U (U= 6 eV for Cu d and Zn d)</li> <li>8_8: PBE+U (U= 8 eV for Cu d and Zn d)</li> </ul> <p><strong>Files in "Interface"</strong></p> <p>POSCAR_S_fixed: CZTS/CdS interface, CdS layers were fully relaxed.<br> POSCAR_S_PBE_U: CZTS/CdS interface, the atomic coordinates were relaxed using PBE+U<br> POSCAR_S_SCAN_U: CZTS/CdS interface, the atomic coordinates were relaxed using SCAN+U<br> POSCAR_Se_fixed: CZTSe/CdS interface, CdS layers were fully relaxed.<br> POSCAR_Se_PBE_U: CZTSe/CdS interface, the atomic coordinates were relaxed using PBE+U<br> POSCAR_Se_SCAN_U: CZTSe/CdS interface, the atomic coordinates were relaxed using SCAN+U</p>
Accurate Determination of the Uniaxial Complex Refractive Index and the Optical Band Gap of Polymer Thin Films to Correlate their Absorption Strength and Onset of Absorption
<p>The uploaded datasets contain complex refractive indices of polymer thin films and a glass substrate and are published in connection with the following article:</p> <p>Kamptner, Scharber, Schiek.<br>Accurate Determination of the Uniaxial Complex Refractive Index and the Optical Band Gap of Polymer Thin Films to Correlate their Absorption Strength and Onset of Absorption.<br>ChemPhysChem 2024.</p> <p><a href="https://doi.org/10.1002/cphc.202400233">https://doi.org/10.1002/cphc.202400233</a></p> <p> </p> <p><strong>F8BT</strong> (or PFBT): Poly(9,9-dioctylfluorene-alt-benzothiadiazole).</p> <p><strong>MDMO-PPV</strong> (or OC1C10-PPV): Poly-[2-(3,7-dimethyloctyloxy)-5-methyloxy]-para-phenylene-vinylene.</p> <p><strong>PBDB-T-2F</strong> (or PBDB-T-F, PBDB-TF, PM6): Poly[(2,6-(4,8-bis(5-(2-ethylhexyl-3-fluoro)thiophen-2-yl)-benzo[1,2-b:4,5-b’]dithiophene))-alt-(5,5-(1’,3’-di-2-thienyl-5’,7’-bis(2-ethylhexyl)benzo[1’,2’-c:4’,5’-c’]dithiophene-4,8-dione)].</p> <p><strong>PDCBT</strong>: Poly[2,2''''-bis[[(2-butyloctyl)oxy]carbonyl][2,2':5',2'':5'',2'''-quaterthiophene] -5,5'''-diyl].</p> <p><strong>PTB7</strong>: Poly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1,2-b:4,5-b']dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl]].</p> <p><strong>ZZ50</strong> (or c-PCPDTBT): Poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b']dithiophene)-alt-4,7(2,1,3-benzothiadiazole)].</p> <p><strong>float glass</strong> objective slide (Marienfeld) "tin" and "air" side.</p>
Validaded Spectral Gaps and Bands for the Critical Almost Mathieu Operator
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Expert-annotated dataset for band gap prediction
<p>Here we present the dataset for "Toward Accurate Interpretable Predictions of Materials Properties within Transformer Language Models" (<a href="https://doi.org/10.48550/arXiv.2303.12188">arXiv:2303.12188</a>).</p> <p>The <strong>dataset_annotated.json</strong> file is organized as follows:</p> <pre><code class="language-python">{ "JARVIS-DFT id": { "text": "text description of material generated within the Robocrystallographer library", "tokens": "sequence of tokens generated by the MatBERT tokenizer", "rationales": "rationales proposed by a domain expert", "label": "label predicted by the MatBERT model", }, ...: ..., }</code></pre> <p> </p>
Observation of carrier cooling in direct band gap hexagonal silicon-germanium
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Band gap formation in commensurate twisted bilayer graphene/hBN moiré lattices
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Band gaps and a few properties more of metals, metal oxides and carbon materials
<p>We achieved to create a database of electronic structure properties of bulk materials (metals, metal oxides, carbon) with a good relative accuracy compared to experimental values and minimal computational cost using density functional theory and semi-empirical quantum mechanical methods.</p>
Transport spectroscopy of ultraclean tunable band gaps in bilayer graphene
<p>Dataset for the Publication "Transport spectroscopy of ultraclean tunable band gaps in bilayer graphene"</p> <p>Abstract:</p> <p>"The importance of controlling both the charge carrier density and the band gap of a semiconductor cannot be overstated, as it opens the doors to a wide range of applications, including, e.g., highly-tunable transistors, photodetectors, and lasers. Bernal-stacked bilayer graphene is a unique van-der-Waals material that allows tuning the band gap by an out-of-plane electric field. <br> Although the first evidence of the tunable gap was already found ten years ago, it took until recent to fabricate sufficiently clean heterostructures where the electrically induced gap could be used to fully suppress transport or confine charge carriers.<br> <br> Here, we present a detailed study of the tunable band gap in gated bilayer graphene characterized by temperature-activated transport and finite-bias spectroscopy measurements. The latter method allows comparing different gate materials and device technologies, which directly affects the disorder potential in bilayer graphene. We show that graphite-gated bilayer graphene exhibits extremely low disorder and as good as no subgap states resulting in ultraclean tunable band gaps up to 120 meV. The size of the band gaps are in good agreement with theory and allow complete current suppression making a wide range of semiconductor applications possible."</p>
Band gap of the III-V semiconductors as a function of lattice parameter
<p><strong>Copyright notice 1</strong>: reuse of this figure must be accompanied by appropriate attribution to Miguel Caro's PhD thesis as follows:</p> <blockquote> <p>Caro, Miguel A. Theory of elasticity and electric polarization effects in the group-III nitrides. PhD Thesis, University College Cork (2013).</p> </blockquote> <p><strong>Copyright notice 2</strong>: you may modify this figure as long as the text stating the copyright ownership on the left lower corner of the figure is not removed. This applies for the usage cases not covered by the attached CC license, e.g., commercial use, cf. "notice 3" below.</p> <p><strong>Copyright notice 3</strong>: if you wish to use this figure for commercial purposes, contact the author directly.</p> <p><strong>Description</strong>:</p> <p>This figure shows the band gap <span class="math-tex">\(E_\text{g}\)</span> of the technologically important III-V binaries as a function of lattice parameter (in-plane lattice parameter in the case of WZ nitrides). Solid circles indicate a direct gap material while empty circles indicate an indirect gap. The curves show the band gap for some of the ternaries, where solid lines indicate direct gap and dashed lines indicate indirect gap. The data for the cubic III-Vs has been taken from Ref. [1], except for ZB nitrides, which is from Ref. [2]. The data for the WZ nitrides is from Wu's review paper [3]. The band gap of the ZB ternaries has been calculated as the minimum of the gaps at <span class="math-tex">\(\Gamma\)</span>, <span class="math-tex">\(X\)</span> and <span class="math-tex">\(L\)</span> from the respective band gap bowing parameters provided in Refs. [1,2], using an interpolation with bowing parameter (Eq. (3.8) of Miguel Caro's thesis). The variation of <span class="math-tex">\(E_\text{g}\)</span> with composition for the WZ nitride ternaries has been calculated using the same equation from the bowing parameters recommended by Wu [3]. See Chapter 3 of Miguel Caro's thesis for a discussion on III-N bowing parameters, AlInN in particular. A linear interpolation (Végard's law) is assumed for the lattice parameters of the ternaries.<br> All data is for the zero-temperature limit <span class="math-tex">\(T = 0\)</span>.</p> <p>[1] I. Vurgaftman, J. R. Meyer, and L. R. Ram-Mohan. Band parameters for III-V compound semiconductors and their alloys. J. Appl. Phys., 89:5815, 2001.</p> <p>[2] I. Vurgaftman and J. R. Meyer. Band parameters for nitrogen-containing semiconductors. J. Appl. Phys., 94:3675, 2003.</p> <p>[3] J. Wu. When group-III nitrides go infrared: New properties and perspectives. J. Appl. Phys., 106:011101, 2009.</p>
Revealing flat bands and hybridization gaps in a gated twisted bilayer graphene device with microARPES
<p>Igor binary waves and optical image that underpin the figures in the manuscript.</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)
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DANDI Archive for NWB datasets
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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.