71 Works

Autonomous TSAXS mapping of sDSA sample

Aaron Stein Gregory S. Doerk Marcus M. Noack, Masafumi Fukuto, Kevin G. Yager
Autonomous SAXS mapping of sDSA sample. Experimental transmission small-angle x-ray scattering (TSAXS) data collected as a function of position for 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. Measurement positions were selected machine-learning algorithm implementing a Gaussian Process (GP) method. Dataset contains raw SAXS detector images, as well as analysis results converting the image...

Data for Using 4D STEM to probe mesoscale order in molecular glass films prepared by physical vapor deposition

Debaditya Chatterjee, Shuoyuan Huang, Kaichen Gu, Jianzhu Ju, Junguang Yu, Harald Bock, Lian Yu, M. D. Ediger & Paul M. Voyles
4D STEM data for orientation mapping of phenanthroperylene ester anisotropic molecular glass thin films. Raw nanodiffraction data, intermediate analyses, and derived orientation maps for samples with varying domain size as a function of substrate temperature during deposition. Additional datasets from samples cooled for a higher temperature liquid crystal phase.

Scanning Electron Microscopy (SEM) images of Pathway-primed Layered Block Copolymer Thin Films

Kevin G. Yager & Sebastian T. Russell
Scanning electron microscopy (SEM) images (top-view and perspective view) of a variety of block copolymer (BCP) thin films. The films were formed by layering different BCP types and thermally annealing (at various temperatures and annealing times). The SEM images provide information about the nanostructure that forms as a result of the particular preparation/annealing history.

Electronic, redox, and optical property prediction of organic π-conjugated molecules through a hierarchy of machine learning approaches

Vinayak Bhat, Parker Sornberger, Balaji Sesha Sarath Pokuri, Rebekah Duke, Baskar Ganapathysubramanian & Chad Risko
Trained machine learning models on the [ocelot_chromophore_v1 dataset](https://acdc.alcf.anl.gov/mdf/detail/ocelot_chromophore_v1_v1.1/).

Neutron diffraction structure factors of silicate glasses

Ying Shi, Jörg Neuefeind & Mathieu Bauchy

Sputter deposited Mo thin films: multimodal characterization of residual stress, resistivity, crystallinity, and surface morphology.

David P. Adams, Sadhvikas J. Addamane, Joyce O. Custer, Frank W. Delrio, Luis J. Jauregui, Matias S. Kalaswad, Ryan M. Khan & Amelia A. Henriksen
Multimodal datasets of materials are rich sources of information which can be leveraged for expedited discovery of process-structure-property relationships and for designing materials with specific structures and/or properties. Here, we provide a multimodal dataset of magnetron sputter-deposited molybdenum (Mo) thin films, which are used in a variety of industries including high temperature applications, photovoltaics, and microelectronics. A process space consisting of 27 unique combinations of sputter power and Argon (Ar) deposition pressure was explored. The...

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...

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

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

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

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

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...

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.

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...

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

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)

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...

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

Dataset for SiO2 polymorphs using metaGGA functional

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

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.

Registration Year

  • 2022

Resource Types

  • Dataset