SWCNT Dataset
Published: 13 June 2023| Version 2 | DOI: 10.17632/vwd34rvphw.2
Contributor:
Marko CanadijaDescription
This is the dataset used for DNN training in the research paper: Čanađija, M.: Deep learning framework for carbon nanotubes: mechanical properties and modeling strategies, Carbon (2021). https://doi.org/10.1016/j.carbon.2021.08.091 It contains basic data about configurations and corresponding mechanical properties for all single-walled carbon nanotubes with diameter up to 4 nm. The dataset was obtained by MD simulations in LAMMPS using modified AIREBO potential. For all other details, please consult the above paper. The column names are self-explanatory. In the case you find this dataset useful, please cite the above paper. Full bibliographic data can be found at the listed DOI link.
Files
Institutions
Sveuciliste u Rijeci Tehnicki Fakultetu
Categories
Engineering, Physics, Machine Learning, Carbon Nanotube Properties, Computational Nanotechnology
Funding
Hrvatska Zaklada za Znanost
IP-2019-04-4703