74 Works

Datasets with uncertainty quantification from DFT, MD, and experiments and their rescaled uncertainties after Bayesian automated weighting

Joshua J. Gabriel, Noah H. Paulson, Thien C. Duong, Chandler A. Becker, Francesca Tavazza, Ursula R. Kattner & Marius Stan
Excel spreadsheet contains sub-sheets of 1. the raw DFT, MD, and Experimental datasets named according to the convention adopted in https://doi.org/10.1016/j.mtla.2021.101216 2. the mean rescaled uncertainty of each heat capacity dataset of the solid and liquid phase of aluminum (Cp_Solid and Cp_Liquid) 3. the mean rescaled uncertainty of each heat capacity dataset of the solid and liquid phase of aluminum (H_Solid and H_Liquid)

DFT Dataset of Ternary and Quaternary II–VI Zincblende Semiconductor Alloys

Arun Mannodi-Kanakkithodi
This dataset contains high-throughput density functional theory (DFT) computations on ternary and quaternary alloys of II-VI zincblende semiconductors with Cd or Zn at the cation site and S, Se or Te at the anion site. Computed properties include formation and mixing energies, electronic band gaps, and optical absorption spectra, from different levels of theory (GGA-PBE, HSE06, with and without spin-orbit coupling).

Dataset for publication \"Spin-polarized imaging of strongly interacting fermions in the ferrimagnetic state of Weyl candidate CeBi\"

Christian E. Matt, Yu Liu, Harris Pirie, Nathan C. Drucker, Na Hyun Jo, Brinda Kuthanazhi, Zhao Huang, Christopher Lane, Jian-Xin Zhu, Paul C. Canfield & Jennifer E. Hoffman
Dataset for article to appear in Phys Rev B

Dataset for \"A new generation of effective core potentials from correlated and spin-orbit calculations: selected heavy elements\"

Guangming Wang, Benjamin Kincaid, Haihan Zhou, Abdulgani Annaberdiyev, M. Chandler Bennett, Jaron T. Krogel & Lubos Mitas
Dataset for "A new generation of effective core potentials from correlated and spin-orbit calculations: selected heavy elements". Data is categorized by each element.

Datasets for Accelerating Catalysts Screening via Machine-learned Local Coordination Graph Representations

Hieu A. Doan, Chenyang Li, Logan Ward, Mingxia Zhou, Larry A. Curtiss & Rajeev S. Assary
A priori catalyst designs from reliable first principles simulations and emerging artificial intelligence tools are desired to accelerate materials development. In the context of upgrading biomass materials via deoxygenation reaction to value-added chemicals, molybdenum carbides (Mo2C) have been considered among the best and economically viable catalysts. One of the bottlenecks related to longer term stability of Mo2C catalysts is the susceptibility to surface oxidation, which requires the use of excess hydrogen for active site regeneration....

Supporting data for \"Orbital Mixer: Using Atomic Orbital Features for Basis Dependent Prediction of Molecular Wavefunctions\"

Kirill Shmilovich, Devin Willmott, Ivan Batalov, Mordechai Kornbluth, Jonathan Mailoa & J. Zico Kolter
This repository contains supporting data and code for the paper titled "Orbital Mixer: Using Atomic Orbital Features for Basis Dependent Prediction of Molecular Wavefunctions" by Kirill Shmilovich, Devin Willmott, Ivan Batalov, Mordechai Kornbluth, Jonathan Mailoa, and J. Zico Kolter

High-throughput DFT calculations of formation energy, stability and oxygen vacancy formation energy of ABO3 perovskites

Antoine Emery & Chris Wolverton
Dataset containing DFT-calculated formation energy and convex hull energies of 4914 perovskite oxides

Mask RCNN defect detection dataset

Ryan Jacobs & Dane Morgan

University of Alabama Heusler database

Chris Borg
Dataset containing saturation magnetization values of 1153 Heusler compounds

Training Dataset for Locating Atoms in STEM images

Jingrui Wei, Ben Blaiszik, Dane Morgan & Paul M Voyles

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

Bing Huang, O. Anatole von Lilienfeld, Jaron T. Krogel & Anouar Benali

BraggNN: Training Dataset

Nikil Ravi, Zhengchun Liu, Hemant Sharma, Pranshu Chaturvedi, E.A. Huerta, Aristana Scourtas, Schmidt KJ, Ryan Chard & Ben Blaiszik
# BraggNN Training Dataset ## Data There are two HDF5 files in the dataset * The `frames-exp4train.hdf5` contains diffraction frames, stored as a 3D array (dataset name must be "frames"). The first dimension is the frame ID starting with 0, i.e., the series of frames at different scanning angle. The second and third dimensions are the height and width of the area detector. * The file `peaks-exp4train-psz11.hdf5` contains the peak position information, generated using conventional...

Predicting the thermodynamic stability of perovskite oxides using machine learning models

Wei Li, Ryan Jacobs & Dane Morgan
Dataset containing DFT-calculated stabilities (as convex hull energies) of 1929 perovskite oxides

A database to enable discovery and design of piezoelectric materials

Maarten de Jong, Wei Chen, Henry Geerlings, Mark Asta & Kristin A. Persson
Dataset containing DFT-calculated piezoelectric properties for 941 materials

MPNN_transformer for molecular dynamics applications in leadership class supercomputers

Hyun Park, Ruijie Zhu & EA Huerta

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
The dataset of organic pi-conjugated molecules chromophore descriptors for electronic, optical, and redox properties computed with DFT. The dataset is a part of the [OCELOT database](https://oscar.as.uky.edu).

The Effect of Polymer Grafting on the Mechanical Properties of PEG-grafted Cellulose Nanocrystals in Poly(Lactic Acid)

Nicholas Macke, Christina M. Hemminsen & Stuart J. Rowan
Contains data for the publication "The Effect of Polymer Grafting on the Mechanical Properties of PEG-grafted Cellulose Nanocrystals in Poly(Lactic Acid)". Includes AFM, conductivity, DMA, DSC, Kaiser testing, tensile testing, TGA, and WAXS data along with source files for the manuscript figures.

High-Throughput Density Functional Theory Dataset of Pb-site Impurities in Hybrid Perovskites

Arun Mannodi-Kanakkithodi & Maria K.Y. Chan

Dataset for \"The binding of atomic hydrogen on graphene from density functional theory and diffusion Monte Carlo calculations\"

Amanda Dumi, Shiv Upadhyay, Leonardo Bernasconi, Hyeondeok Shin, Anouar Benali & Kenneth D. Jordan
The files and data used for "The binding of atomic hydrogen on graphene from density functional theory and diffusion Monte Carlo calculations". A.B. and H.S were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. An award of computer time was provided by the Innovative and Novel Computational Impact on...

Ultrasensitive Molecular Sensors Based on Real‐Time Impedance Spectroscopy in Solution‐Processed 2D Materials

David C. Moore, Ali Jawaid, Robert Busch, Michael Brothers, Paige Miesle, Adam Miesle, Rahul Rao, Jonghoon Lee, Lucas K. Beagle, Michael Motala, Shay Goff Wallace, Julia R. Downing, Ajit Roy, Christopher Muratore, Mark C. Hersam, Richard Vaia, Steve Kim & Nicholas R. Glavin
Chemical sensors based on solution-processed 2D nanomaterials represent an extremely attractive approach toward scalable and low-cost devices. Through the implementation of real-time impedance spectroscopy and development of a three-element circuit model, redox exfoliated MoS2 nanoflakes demonstrate an ultrasensitive empirical detection limit of NO2 gas at 1 ppb, with an extrapolated ultimate detection limit approaching 63 ppt. This sensor construct reveals a more than three orders of magnitude improvement from conventional direct current sensing approaches as...

BraggNN: Validation Dataset

Nikil Ravi, Zhengchun Liu, Hemant Sharma, Pranshu Chaturvedi, E.A. Huerta, Aristana Scourtas, Schmidt KJ, Ryan Chard & Ben Blaiszik
# BraggNN Validation Dataset This dataset contains `13799` samples from the training dataset, and is used to evaluate, and provide metrics for, the models that were trained on the larger training dataset. ## Data The data are located in the `/data` folder, and store the collected peaks and frames. There are two datasets in the hdf5 file: - `Patch`: input to the BraggNN model. It is a 3D array where its first dimension is the...

Supporting data for \"Temporally coherent backmapping of molecular trajectories from coarse-grain to atomistic resolution\"

Kirill Shmilovich, Marc Stieffenhofer, Nicholas E. Charron & Moritz Hoffmann
This repository contains supporting data and code for the paper titled "Temporally coherent backmapping of molecular trajectories from coarse-grain to atomistic resolution" by Kirill Shmilovich, Marc Stieffenhofer, Nicholas E. Charron, and Moritz Hoffmann

GEOM with Hessians

Simon Axelrod & Rafael Gómez-Bombarelli
Here you can find 1.3 million Hessians from 1,511 species in the BACE dataset. The conformers were computed with CREST using xTB, and released as part of the GEOM dataset. If you use this data, please cite our paper: https://www.nature.com/articles/s41597-022-01288-4.

Exploring effective charge in electromigration using machine learning

Yu-chen Liu, Ben Afflerbach, Ryan Jacobs, Shih-kang Lin & Dane Morgan
Dataset containing effective charge values for 49 metal host-impurity pairs

Mechanical properties of some steels

Gareth Conduit
Dataset containing compositions and mechanical properties (yield strength, tensile strength, elongation) of 312 steel alloys

Registration Year

  • 2022
    74

Resource Types

  • Dataset
    71
  • Model
    3