Dear ænet community,
The tutorial is designed to run on Deepnote (
https://deepnote.com), and the Deepnote project will later be made available at:
There are three notebooks in the Deepnote project:
- 01-aenet-installation.ipynb: ænet and ASE installation
- 02-aenet-lammps-setup.ipynb: LAMMPS and aenet-LAMMPS installation
- 03-aenet-tutorial-ipynb: The actual tutorial
Note that running the second notebook takes quite long because it compiles LAMMPS.
Best regards,
Nong
P.S. If you make use of ænet, please cite the following references as appropriate:
A more in-depth tutorial for the construction of ANN potentials can be found in:
A.M. Miksch, T. Morawietz, J. Kästner, A. Urban, N. Artrith, “Strategies for the Construction of Machine-Learning Potentials for Accurate and Efficient Atomic-Scale Simulations”, Mach. Learn.: Sci. Technol. 2 (2021) 031001.
N. Artrith and A. Urban, Comput. Mater. Sci. 114 (2016) 135-150.
N. Artrith, A. Urban, and G. Ceder, Phys. Rev. B 96 (2017) 014112.
The ænet-LAMMPS interface:
M. S. Chen, T. Morawietz, H. Mori, T. E. Markland, and N. Artrith, J. Chem. Phys. 155 (2021) 074801.
A. H. Larsen et al., J. Phys.: Condens. Matter 29 (2017) 273002.
A. P. Thompson et al., Comp. Phys. Commun. 271 (2022) 10817.
Contact: N. Artrith (
n.ar...@uu.nl), M. S. Chen (
mi...@stanford.edu), A. M. Miksch (
mik...@theochem.uni-stuttgart.de),
A. Urban (
a.u...@columbia.edu)