Computational Materials Science
ISSN: 0927-0256
Datasets associated with articles published in Computational Materials Science
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- Data for: Crystal structure classification in ABO3 perovskites via machine learning1. List of all 5329 ABO3 perovskite-type oxides (Microsoft Excel Worksheet (.xlsx)) 2. List of all 675 ABO3 perovskite-type oxides used in this study (Microsoft Excel Worksheet (.xlsx))
- Data for: Molecular Dynamics of Aluminum Nano Particles adsorbed by Ethanol Molecules Using the ReaxFF Reactive Force FieldIn files for LAMMPS MD simulations.
- Data for: Affect of the graphene layers on the melting temperature of silicon by molecular dynamics simulationsThe data have been used to present the figures in the paper.
- Data for: Bulk and Surface Properties of Gypsum: A Comparison between Classical Force Fields and Dispersion-Corrected DFT CalculationsLAMMPS input files to run molecular dynamics simulations for gypsum with different force fields.
- Data for: Candidate Replacements for Lead in CH3NH3PbI3 from First Principles CalculationsDensity functional theory calculations of the electronic structure and optical absorption for the orthorhombic phase of the hybrid organic-inorganic perovskites with various cation substitutions and for three different exchange-correlation functionals with and without including spin-orbit coupling interactions.
- Data for: Predicting the thermodynamic stability of perovskite oxides using machine learning modelsSupplemental information for the paper: Predicting the thermodynamic stability of perovskite oxides using machine learning models. This contains the dataset of the stability data of over 1900 perovskite oxides and the source code for predicting the stability of new compositions.
- Data for: How to Apply the Phase Field Method to Model Radiation DamageThese are the input files and .csv files used to calculate these data. The simulations were run using the MOOSE framework, (mooseframework.org).
- Data for: Determination of Strain Fields on Two-Dimensional Images using the STC methodThis is data for "Determination of Strain Fields on Two-Dimensional Images using the STC method".
- Data for: Accurate representation of the distributions of the 3D Poisson-Voronoi typical cell geometrical featuresgvolume.txt contains the grid of points (xgrid.v) and the kernel density estimate (Epanechnikov kernel, cross validation bandwidth h=0.05) of volume of 1,000,000 Poisson-Voronoi typical cells ( intensity parameter lambda=1) evaluated in the grid points (y.v). gsurfacearea.txt contains the grid of points (xgrid.a) and the kernel density estimate (Epanechnikov kernel, cross validation bandwidth h=0.25) of surface area of 1,000,000 Poisson-Voronoi typical cells ( intensity parameter lambda=1) evaluated in the grid points (y.a). gnfaces.txt contains the absolute (nf) and relative frequencies (pf) of number of faces 1,000,000 Poisson-Voronoi typical cells ( intensity parameter lambda=1)
- Data for: Identifying key parameters for predicting radiation-tolerant materials by machine learningThis dataset is a collection of radiation-tolerant materials for training machine-learning models.
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