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97 results for “boronization”

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zenodo36/100

Tungsten Trioxide Adsorption on hexagonal boron nitride in acidic electrolyte

<p>Progressive adsorption of ((WO)<sub>3</sub>)<sub>3</sub>&nbsp;clusters in initially vacant pores of hexagonal boron nitride 2D-crystal. Electrochemical Scanning Tunneling microscopy images taken with tungsten tips in 0.1M H<sub>2</sub>SO<sub>4.&nbsp;</sub>Seen in time-lapse images. Recording of these images commences as soon as tunnelling is established, strong effects of noise are still present. Time stamp in seconds.</p>

opencc-by-4.0Dec 2020View details →
zenodo36/100

How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles study

<p>The dataset contains the necessary information&nbsp;to reproduce the phonon-defect scattering rates and the phonon thermal conductivity of cubic boron arsenide (BAs) upon doping, via the almaBTE software.</p> <p>Input files contain:</p> <p>1) Interatomic force constants for the pristine BAs, required to extract the phonon band structure and the intrinsic scattering processes;</p> <p>2) Unit cell POSCAR;</p> <p>3) Interatomic force constants for the C, Ge and Si impurities, required to compute the phonon-defect scattering rates beyond the mass-only approximation.</p> <p>Output files contain:</p> <p>1) Phonon-defect scattering rates (mass-only approximation, bond-only approximation, total) for charged and neutral impurities;</p> <p>2) Thermal conductivity at 300 K as function of the impurity concentration.</p> <p>&nbsp;</p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Tailoring the Emission Wavelength of Color Centers in Hexagonal Boron Nitride for Quantum Applications

<p>Dataset for&nbsp;all studied defects (sorted by type and by wavelength) in terms of electronic transition type, transition energy, wavelength, and lattice deformation.</p>

opencc-by-4.0Jul 2022View details →
zenodo36/100

Boron elemental and isotopic determination via the BF diatomic molecule using high-resolution continuum source graphite furnace molecular absorption spectrometry

<p>This dataset contains the raw data corresponding to the figures of the publication DOI: 10.1039/d3ja00420a</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Boron isotope pH calibration of a larger benthic nummulitid foraminifer using LA-MC-ICPMS

<p>This repository is associated with the Submission of the manuscript entitled: &quot;Boron isotope pH calibration of a larger benthic nummulitid foraminifer using LA-MC-ICPMS&quot; submitted to the Geochimica et Cosmochimica-Acta journal.</p> <p>This repository contains the supplementary materials and the data for all figures associated with the manuscripts.</p>

opencc-by-4.0Aug 2023View details →
zenodo36/100

Memristive circuits based on multilayer hexagonal boron nitride for millimetre wave radiofrequency applications - Source data

<p>Source data for the paper "Memristive circuits based on multilayer hexagonal boron nitride for radiofrequency and millimetre wave applications"</p> <p>Find online at:</p> <p>https://doi.org/10.1038/s41928-024-01192-2</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Gaussian Approximation Potential for C-doped Boron Nitride

<p>This is an GAP potential for amorphous boron nitride samples. It is trained based on datasets generated with ab-initio molecular dynamics and DFT. It can be used with pair_style quip command.&nbsp;</p>

opencc-by-4.0Dec 2022View details →
zenodo36/100

Dataset from J. Am. Chem. Soc. paper: Off-Stoichiometric Restructuring and Sliding Dynamics of Hexagonal Boron Nitride Edges in Conditions of Oxidative Dehydrogenation of Propane

<p>Dataset of the article &quot;Off-Stoichiometric Restructuring and Sliding Dynamics of Hexagonal Boron Nitride Edges in Conditions of Oxidative Dehydrogenation of Propane&quot; accepted in J. Am. Chem. Soc.</p> <p>- armchair.db: The ASE database&nbsp;of all unique surface states from the grand canonical genetic algorithm (GCGA) searches of the restructured armchair edge of h-BN.</p> <p>- zigzag.db: The ASE database&nbsp;of all unique surface states from the GCGA&nbsp;searches of the restructured zigzag edge of h-BN.</p> <p>Other key info such as DFT-calculated energies and magnetic moments are included in the metadata of each entry in the ASE databases.</p> <p>GCGA searches are performed using the workflow in the GOCIA package (https://github.com/zishengz/gocia)</p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

Data for paper "Designing a Boron Nitride Polyethylene Composite for Shielding Neutrons"

<p>Data set for the paper "Designing a Boron Nitride Polyethylene Composite for Shielding Neutrons" published in Applied Physics Letters Materials (<a href="http://doi.org/10.1063/5.0163377">https://doi.org/10.1063/5.0163377</a>). In this paper, we explore the three different ways to distribute boron-10 within HDPE. These three configurations are called: (1) blended, (2) ideal layered, and (3) manufacturable. Refer to the manuscript for details of these configurations.</p> <p>For the <strong>blended configuration</strong>, we have uploaded the feather files, which contain all the information that was tracked in Geant4. We have processed the ROOT files, outputted directly from Geant4, into feather files, which include the energy of each particle at the entry and exit surface of the shielding composite along with the particle type and interaction type. The feather files can be easily read into Python using pandas:</p> <pre><code>pd.read_feather(filename)</code></pre> <p>The feather files are labeled as "blended_B10enrich_seed1_processed_*.ftr". Each feather file contains information from ~10 ROOT files. The key information from these feather files, such as the number of neutrons and gammas exiting the shielding composite and effective dose ratio, is saved in a pickle file, called "blended_B10enrich_binned_seed1_compressed.pickle". The pickle files can be read into Python using:</p> <pre><code>with open(filename, 'rb') as pickle_file: dictionary = pickle.load(pickle_file)</code></pre> <p>For the <strong>ideal layered configuration</strong>, there are ~100 feather files that are available upon request. The corresponding pickle files for the ideal layered configuration are uploaded, see "layered_B10enrich_binned_compressed.pickle", which can be read into Python using the code provided above.&nbsp;</p> <p>For the <strong>manufacturable configuration</strong>, there are ~236 feather files that are ~2 GB each. To reduce the number of files uploaded to this repository, we have only uploaded the pickle files for this configuration (see "manufacturable_B10enrich_binned_compressed_*.pickle").</p> <p>Please contact the authors if you have additional questions (Advik Vira, avira@gatech.edu, or Phillip First, first@gatech.edu).</p>

opencc-by-4.0Aug 2023View details →
dryad36/100

Data from: Gallium-catalyzed boron-assisted recycling of silicone waste yields key chlorosilanes

Open the record for dataset details and reuse information.

publicApr 2025View details →
zenodo32/100

Dataset for Cyclopentadithiophene polymers synthesised via Suzuki-Miyaura polymerisation of MIDA boronate esters

<p>NMR and GPC files (raw and processed data) of compounds and experiments described in the Title publication.</p>

opencc-by-4.0Mar 2020View details →
dryad32/100

Preparation of Phosphorus doping modification of porous boron nitride and its adsorption characteristics for heavy metals in flue gas

Boron nitride, known as "white graphene", have attracted extensive attention to the fields of adsorption, catalysis and hydrogen storage due to their excellent chemical properties. In this paper, the phosphorus doped boron nitride material (P-BN), was successfully prepared by red phosphorus as a dopant for the preparation of porous boron nitride precursors, the phosphorus content in P-BN was adjusted by the addition rate of phosphorus. The tendency of specific surface area of P-BN increased firstly and then decreased with the increasing of phosphorus addition rate, and the maximum specific surface area was 837.08m2/g when the phosphorus addition rate was 0.50. The P-BN, prepared by the experimental, used as an adsorbent had been proved its adsorption capacity for heavy metal flue gas. In particular, P-BN had a stronger adsorption selectivity for Zinc compared with other heavy metals, and the adsorption capacity of P-BN for Zinc reached 5~38 times higher than that of other heavy metals. However, the maximum adsorption capacities of P-BN for Zinc and Copper in the single heavy metal atmosphere were 69.45mg/g and 53.80mg/g, respectively.

opencc-zeroAug 2020View details →
dryad32/100

Geometric structure and electronic properties of boron-substituted silicene

<p>The essential properties of monolayer silicene greatly enriched by boron substitutions are thoroughly explored through first -principles calculations. Delicate analyses are conducted on the highly non-uniform Moire superlattices, atom-dominated band structures, charge density distributions and atom- &amp; orbital-decomposed van Hove singularities. The hybridized 2pz-3pz and [2s, 2px, 2py]-[3s, 3px, 3py] bondings, with orthogonal relations, are obtained from the developed theoretical framework. The red-shifted Fermi level and the modified Dirac cones/π bands/σ bands are clearly identified under various concentrations and configurations of guest atoms. Our results demonstrate that the charge transfer leads to the non-uniform chemical environment that creates diverse electronic properties.<br>  </p>

opencc-zeroOct 2020View details →
zenodo32/100

Boron balls

<p>XYZ coordinates for all-boron fullerenes</p>

opencc-by-4.0Jan 2017View details →
zenodo32/100

Figure S1: Nutrient concentration of lettuce (Lactuca sativa 'Rex') plants grown at different total incident light levels in deep water culture hydroponics. Lines show multiple regression analysis results, indicating no significant interactions. Each data point represents one plant. N = nitrogen, P = phosphorus, K = potassium, Ca = calcium, Mg = magnesium, S = sulfur, B = boron, Cu = copper, Fe = iron, Mn = manganese, and Zn = zinc.

Open the record for dataset details and reuse information.

opencc-by-4.0Mar 2024View details →
zenodo32/100

Programmable Selective Acylation of Saccharides Mediated by Carbene and Boronic Acid

<p>This folder /final_xyz_structures/ contains the DFT-optimized geometries (in .xyz format together with the gas-phase energy, E) accompanying the paper</p> <p>&quot;Programmable Selective Acylation of Saccharides Mediated by Carbene and Boronic Acid&quot;</p> <p>Where conformers occur, they are always named from the lowest Gibbs energy to the highest in ascending order from c1 (sometimes omitted), c2, c3, ...<br> &nbsp;</p>

opencc-by-4.0Mar 2022View details →
zenodo32/100

Magnetic imaging with spin defects in hexagonal boron nitride

<p>Data relative to the publication arXiv:2207.10477</p>

opencc-by-4.0Jul 2022View details →
zenodo32/100

Atomic resolution high-angle annular dark field scanning transmission electron microscopy imaging of WSe2 encapsulated within hexagonal boron nitride

Open the record for dataset details and reuse information.

opencc-by-4.0Jun 2024View details →
zenodo32/100

Datasets supplementing journal article "A novel synthesis route with large-scale sublattice asymmetry in boron doped graphene on Ni(111)" in Surfaces and Interfaces 2024

<p>These are the datasets related to the publication "A novel synthesis route with large-scale sublattice asymmetry in boron doped graphene on Ni(111)", Surfaces and Interfaces 51 (2024) 104700 (<a href="https://doi.org/10.1016/j.surfin.2024.104700">https://doi.org/10.1016/j.surfin.2024.104700</a>).</p> <p>STM raw (.sm4, .mtrx) and analysed (.gwy) data can be opened with open source Gwyddion software (http://gwyddion.net/).</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

(DATA) Exploring the potential of boron-nitride nanobelts in environmental applications: greenhouse gases capture

<ul> <li>Input structures.</li> <li>Scrip to run all the calculations.</li> <li>Output files from several calculations.</li> </ul>

opencc-by-4.0Feb 2024View details →

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dandi-nwb
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Last verified 2026-04-30Open record

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.

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OpenNeuro

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