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Dataset results
13 results for “Electron efficiency”
Cryo-4D-STEM datasets on cells and cellular organelles for demonstrating a dose-Efficient cryo-EM technique: tilt-Corrected Scanning Transmission Electron Microscopy
<p>This upload contains three 4D-STEM datasets in .raw format for demonstrating a dose-efficient cryo-EM technique for thick samples: tilt-corrected Scanning Transmission Electron Microscopy (tcBF-STEM). The dataset dimension is 128130256*256. Data were acquired on vitrified intact E.coli cells and isolated human cell organelles. This upload also contains the EFTEM images in .mrc acqired in the same ROI as the 4D-STEM dataset. </p> <p>It also contains analysis of the manuscript's Fig 3 and Ext. data fig 8. </p>
Dataset for Using Your Beam Efficiently: Reducing Electron-dose in the STEM via Flyback Compensation
<p>Experimental scanning transmission electron microscopy dataset for the paper "Using Your Beam Efficiently: Reducing Electron-dose in the STEM via Flyback Compensation"</p>
Graph of phase shift $\Delta P_0$ vs electron trapping efficiency parameter $\beta $
<p>Graph of phase shift $\Delta P_0$ vs electron trapping efficiency parameter $\beta $, taking rest of parameters as $\varepsilon =0.1$, $\phi _m=1$, $\alpha =3.5 $, $\mu =0.56$ and $\nu=0.44$. The upper curve for $q =0.25$ (red line), middle one for $q=0.5$ (green line) and lower one is $q= 0.75 $ (blue line).</p>
Efficiency of terahertz undulator radiation from short electron bunches moving in the field of permanently magnetized helices
<p>The motion and radiation of short dense bunches of ultrarelativistic electrons produced by laser-driven accelerators and moving in an undulator in the form of magnetized helices have been studied. Simulations demonstrate the possibility of generating wideband THz pulses with energies of hundreds of microjoules and relatively high efficiency in regimes close to the group synchronism of electrons with the waveguide mode.</p>
An efficient method for higher heating value estimation of municipal solid wastes electronic supplementary material
<p><span><span>To facilitate the disposal of municipal solid wastes (MSWs) via thermo-chemical approaches, the accurate measurement of MSWs' higher heating value (HHV) plays a key role. This study aims to forecast the HHV of MSWs using the optimized multi-variate grey model (OBGM (1, N)) due to its high accuracy under the condition of scanty data. Results show that POBGM (1, 5) with proximate analysis data is the most accurate model with the least error of 5.41% MAPE (mean absolute percentage error). This model also illustrates that ash is the most important factor affecting HHV due to its significant fraction in MSWs, followed by volatiles, fixed carbon and water contents, respectively. With prediction interval (PI) method, most of the actual data can be included by using the 95% confidence intervals.</span></span></p>
Efficient implementation of molecular CCSD gradients with Cholesky-decomposed electron repulsion integrals
<p>Initial and optimized geometries from the manuscript "Efficient implementation of molecular CCSD gradients with Cholesky-decomposed electron repulsion integrals"</p>
Dataset for deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation
<p>Dataset files of atomic structures and Hamiltonian matrices of graphene, MoS<sub>2</sub>, bilayer graphene and bilayer bismuthene.</p> <p>Please note that the DFT results in this dataset were calculated using OpenMX. This means that if you want to use a DeepH model trained on this dataset to calculate properties, you need to use the <a href="https://github.com/mzjb/overlap-only-OpenMX">overlap calculated using OpenMX</a>. The orbital information required for overlap calculations can be found in the <a href="https://www.nature.com/articles/s43588-022-00265-6">paper</a>.</p>
Numerical data supporting the publication "Accurate and gate-efficient quantum Ansätze for electronic states without adaptive optimization"
<p>Numerical data and plotting scripts for regenerating figures in the article "Accurate and gate-efficient quantum ansätze for electronic states without adaptive optimisation".</p> <p>See README for more details.</p>
Efficiency comparison of photonic and electronic phase matching for comb generation
<p>Spectral analysis raw data for measurements of the comb generated from PM using optical ( 1551_001.SPE ) or electric ( 1551_000.SPE ) phase matching. Measurements carried out in the framework of WP5 of H2020 project ULTRAWAVE at the Nanophotonics Technology Center (NTC) of Universitat Politecnica de Valencia (Spain).</p>
Efficiency of Electronic Multimedia Intervention With the Cardiac Implantable Electronic Device.
ClinicalTrials.gov study NCT05688540. IPD Sharing: NO. Countries: 1. Publications: 1.
An efficient method for higher heating value estimation of municipal solid wastes electronic supplementary material
Open the record for dataset details and reuse information.
WEEE-dismantling trial: Investigation on increasing resource efficiency and environmental protection for the recycling of small household electrical and electronic devices
<p>In the frame of the FORCE-project, Aurubis AG and Stadtreinigung Hamburg (the city of Hamburg’s municipal waste management service) carried out a trial to investigate the recycling advantages of manually pre-dismantling small electrical and electronic devices compared to non-dismantled devices. For this purpose, Stadtreinigung Hamburg dismantled a 10 t test charge of waste electrical and electronic devices and separated plastic, iron, nonferrous metal (NF metal), and aluminum to the greatest possible extent. The fractions were sampled, evaluated, and compared with another 10 t test charge of unhandled (mechanically shredded) devices.<br> Based on the results, the benefits for environmental protection and resource conservation were investigated through an ecological assessment, and an economic efficiency analysis of manual predismantling was carried out as well. Because manual pre-dismantling has proven to be economically inefficient under the current conditions, suggestions for future device design were developed – based on examples of individual product groups – to improve the economic efficiency of manual dismantling<br> and also possibly enable additional metals to be recovered in a cost-efficient manner in the future.</p> <p>Overview of the results<br> - Device-specific – small electrical and electronic devices from collection group 5 (CG 5):<br> o Breakdown of the different device types<br> o Manual dismantling process (dismantling time)<br> o Pollutant content in the electrical and electronic devices<br> o Assessment of difficulties that arose during manual dismantling<br> o Non-ferrous metal percentages for the device type at hand</p> <p>- Charge-specific (manual dismantling vs. mechanical shredding):<br> o Percentages of the material fractions plastic, iron, NF metal, aluminum, and residual material<br> (wood, fabric) for both charges (manually dismantled and mechanically shredded)<br> o Economic efficiency analysis of manual dismantling<br> o Ecological comparison of manual dismantling and mechanical shredding<br> o Suggestions for Design for Recycling</p>
Dataset for efficient modelling of ionic and electronic interactions by resistive memory- based reservoir graph neural network
<p>Dataset for training the resistive memory-based reservoir graph neural network.</p> <p>In the atomic force calculation experiment, <span lang="EN-HK"><span>a Li</span><sub>3</sub><span>PO</span><sub>4</sub><span> dataset is derived from the melting and quenching trajectory via AIMD simulations. The training, validation, and testing datasets consist of 40,000, 5,000, and 5,000 samples, respectively. </span></span></p> <p><span lang="EN-HK"><span>In the Hamiltonian calculation, a dataset </span><span lang="EN-HK">of various graphene (72 atoms) configurations are generated by AIMD simulations at room temperature, with Hamiltonian data calculated via the OpenMX code</span><span lang="EN-HK">.</span><span lang="EN-HK"> <span>The training, validation, and testing datasets consist of 270, 90, and 90 samples (including atomic structure and Hamiltonian matrix), respectively.</span></span></span></p> <p>Code: https://github.com/hustmeng/RGNN.git</p> <p>1-Atomic_force_dataset.zip and 2-Hamiltonian_dataset.zip are original data.</p> <p>3-Graph_atomic_force.zip and 4-Graph_training_Hamiltonian.zip are graphs. </p> <p> </p> <p>References:</p> <p> </p> <p>1. C.W. Park, M. Kornbluth, J. Vandermause, C. Wolverton, B. Kozinsky, J.P. Mailoa, Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture, npj Comput. Mater. 7(1) (2021) 73. https://github.com/ken2403/gnnff.git</p> <p>2. H. Li, Z. Wang, N. Zou, M. Ye, R. Xu, X. Gong, W. Duan, Y. Xu, Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation, Nat. Comput. Sci. 2(6) (2022) 367-377. https://github.com/mzjb/DeepH-pack.git</p> <p>3. D. Pfau, J.S. Spencer, A.G.D.G. Matthews, W.M.C. Foulkes, Ab initio solution of the many-electron Schrödinger equation with deep neural networks, Phys. Rev. Res. 2(3) (2020) 033429. https://github.com/google-deepmind/ferminet.git</p> <p> </p>
ScienceDex guides
Understand access before you commit
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)
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.