345 Works

A Combined First Principles Study of the Structural, Magnetic, and Phonon Properties of Monolayer CrI3

Daniel Staros, Guoxiang Hu, Juha Tiihonen, Ravindra Nanguneri, Jaron T. Krogel, M. Chandler Bennett, Olle G. Heinonen, Panchapakesan Ganesh & Brenda Rubenstein

Data for Correlation Symmetry Analysis of Electron Nanodiffraction from Amorphous Materials

Shuoyuan Huang, Carter Francis, Jittisa Ketkaew, Jan Schroers & Paul M. Voyles
Data for "Correlation Symmetry Analysis of Electron Nanodiffraction from Amorphous Materials" by Shuoyuan Huang, Carter Francis, Jittisa Ketkaew, Jan Schroers, Paul M. Voyles. Data consist of experimental electron nanodiffraction patterns from metallic glasses. Experimental data were collected on Pd40Ni10Cu27P20 metallic glass nanowires with a 2 nm diameter, 200 kV electron probe beam on a Titan STEM using a Gatan US1000 CCD camera. The nanowires were 41 ± 3 nm thick. Jupyter notebooks demonstrate analysis of...

Neutron Structure Factor of Glassy Silica and Jade Glass

Ying Shi, Jörg Neuefeind, Mathieu Bauchy, Qi Zhou & Binghui Deng
Room temperature reduced neutron structure factor of glassy silica and Jade Glass measured by Time-of-flight (TOF) neutron scattering. The measurements were performed on the Nanoscale-Ordered Materials Diffractometer (NOMAD) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory.

Solidification of an Al-12.6wt%Cu alloy cooled from 627.9 C to 623.8 C

Kate L. M. Elder, Tiberiu Stan, Yue Sun, Xianghui Xiao & Peter W. Voorhees
Reconstruction of X-ray projections collected as an Al-12.6wt%Cu alloy was cooled from 627.9 C to 623.8 C at a cooling rate of 1 C/min. The experiment shows dendritic growth as the sample solidifies.

Solidification of an Al-12.6wt%Cu alloy cooled from 623.6 C to 621.8 C

Kate L. M. Elder, Tiberiu Stan, Yue Sun, Xianghui Xiao & Peter W. Voorhees
Reconstruction of X-ray projections collected as an Al-12.6wt%Cu alloy was cooled from 623.6 C to 621.8 C at a cooling rate of 0.5 C/min. The experiment shows dendritic growth as the sample solidifies.

SEM images of sDSA morphologies

Gregory S. Doerk, Aaron Stein & Kevin G. Yager
Scanning electron microscope (SEM) images collected on a combinatorial samplel used in an autonomous SAXS mapping experiment. The sample is a selective directed self-assembly (sDSA) combinatorial sample. Sample was a grid of lithographically-defined chemical patterns (varying pitch and dose) with a blend of block copolymer materials cast on top.

Foundry - Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning

Bing Huang, O. von Lilienfeld, Jaron T Krogel & Anouar Benali
This dataset contains summary inputs and outputs generated for the Paper "Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning" By B. Huang, O. Anatole von Lilienfeld, J. T. Krogel and A. Benali. Included in the dataset are energies for 1175 molecules calculated with varying methods, associated error calculations, and molecular structures in XYZ and pymatgen Molecule formats. Raw data for these calculations are available at https://doi.org/10.18126/hxlp-v732

High-Throughput DFT Dataset of Halide Perovskite Alloys

Arun Mannodi-Kanakkithodi, Maria K.Y. Chan, Jiaqi Yang & Panayotis Manganaris
This dataset contains DFT computations on 550 halide perovskite compounds, 90 of which are pure ABX3 compositions and the remaining involve mixing/alloying at the A, B or X sites. Computation folders include geometry optimization using GGA-PBE and HSE06, optical absorption calculations, vacancy defect calculations, and dielectric constant calculations. Machine learning models were trained using this data to accelerate the prediction of stability and optoelectronic properties of a combinatorial perovskite dataset. One publication is currently under...

A Materials Dataset for Elastomeric Foam Impact Mitigating Materials

Alexander K Landauer, Orion L Kafka, Newell H Moser & Aaron M Forster
The database includes data for structure-properties relationships and mechanical modeling of elastic impact protection foams from a variety of imaging (micro-computed tomography, digital image correlation) and force-sensing instruments (dynamic mechanical analysis, universal test system) under a wide range of experimental conditions and modes. The data repository includes directories for: dynamic mechanical analysis raw data, results, and analysis tools; intermediate rate (servo-hydraulic UTS based) raw data including 2D digital image correlation (DIC) images, results, and analysis...

A Gapped Phase in Semimetallic T d ‐WTe 2 Induced by Lithium Intercalation

Mengjing Wang, Aakash Kumar, Hao Dong, John M. Woods, Joshua V. Pondick, Shiyu Xu, David J. Hynek, Peijun Guo, Diana Y. Qiu & Judy J. Cha
1. Files for the DFT calculations of i) Td phase (WTe2) - scf input, scf output, bands input , ii) Td' phase (WLi0.5Te2) - scf input, scf output, bands input, using Quantum Espresso software package 2. Pseudopotential files for PAW-PBE, fully relativistic calculations

Real-time Porosity Mapping and Visualization for Synchrotron Tomography

Aniket Tekawade, Viktor Nikitin, Yashas Satapathy, Zhengchun Liu, Xuan Zhang, Peter Kenesei, Francesco De Carlo, Rajkumar Kettimuthu & Ian Foster
This data is of a 3d-printed steel cylindrical specimen (nominal diameter 6-millimeter) scanned under monochromatic hard X-ray. The mosaic comprised of 3 horizontal and 6 vertical positions (total 18 scans). The field-of-view for each scan was approximately 2.2 mm wide and 1.4 mm tall with 1.17 micrometer voxel size. With an exposure time of 0.13 milliseconds for 3000 projections, scanning this mosaic took ~2 hours not counting instrument-specific overheads in moving motors to reposition the...

First-principles simulation of light-ion microscopy of graphene

Alina Kononov, Alexandra Olmstead, Andrew D. Baczewski & André Schleife
TDDFT simulations of light-ion irradiated graphene performed with Qbox/Qb@ll (https://github.com/LLNL/qball)

Project Elwood: MD Simulated Monomer Properties

L Schneider, M Schwarting, J Mysona, H Liang, M Han, P Rauscher, J Ting, S Venkatram, R Ross, K Schmidt, B Blaiszik, I Foster & J de Pablo

Data: Sucrose-mediated formation and adhesion strength of Streptococcus mutans biofilms on titanium

Tony Butera, Laura J. Waldman & Martha E. Grady
Bacterial biofilms associated with implants remain a significant source of infections in dental, implant, and other healthcare industries due to challenges in biofilm removal. Biofilms consist of bacterial cells surrounded by a matrix of extracellular polymeric substance (EPS), which protects the colony from many countermeasures, including antibiotic treatments. Biofilm EPS composition is also affected by environmental factors. In the oral cavity, the presence of sucrose affects the growth of Streptococcus mutans that produce acids, eroding...

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov, Artur Kadurin, Simon Johansson, Hongming Chen, Sergey Nikolenko, Alan Aspuru-Guzik & Alex Zhavoronkov

Discovery and engineering of low work function perovskite materials

Tianyu Ma, Ryan Jacobs, John Booske & Dane Morgan
Dataset containing DFT-calculated O p-band center energies for 2912 perovskite oxides

Data-driven analysis of the electronic-structure factors controlling the work functions of perovskite oxides

Yihuang Xiong, Weinan Chen, Wenbo Guo, Hua Wei & Ismaila Dabo
Dataset containing DFT-calculated work functions of (001) oriented, AO- and BO2-terminated perovskite surfaces

Machine learning modeling of superconducting critical temperature

Valentin Stanev, Corey Oses, A. Gilad Kusne, Efrain Rodriguez, Johnpierre Paglione, Stefano Curtarolo & Ichiro Takeuchi
Dataset containing experimentally measured superconducting critical temperatures for 16414 materials

Dataset for \"Assessing the accuracy of compound formation energies with quantum Monte Carlo\"

Eric B. Issacs, Hyeondeok Shin, Abdulgani Annaberdiyev, Chris Wolverton, Lubos Mitas, Anouar Benali & Olle Heinonen
Dataset for formation energies of VPt2 and CuI using DFT (PBE, SCAN, PBE0, and PBE0-SO) and QMC(DMC). All files are input and output files are in the Quantum espresso and DIRAC code format and QMCPACK format.

Dataset for SiO2 polymorphs using metaGGA functional

Sukriti Manna, Subramanian KRS Sankaranarayanan & Pierre Darancet
VASP run directory for SiO2 polymorphs

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