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|=======================================================================| | | | Interatomic potentials library for MAISE code | | | | Alexey Kolmogorov's research group | | Binghamton University | | | | https://github.com/maise-guide/maise | |=======================================================================| a) nn_* models are neural network based potentials, trained with the MAISE code. They are named as: nn_(system name: series of elements)_(dimensionality of the dataset used for the training)(model version) e.g.: nn_CuPdAg_30 is a NN model for the Cu-Pd-Ag ternary constructed using the 3D (bulk) dataset. nn_CuAu_00 is a NN model for the Cu-Au system trained on the bulk and nanoparticle datasets. note: 1- Currently, models named as *0 are trained using 30-component input vector and with 6 Ang cut-off; while *1 models are trained using 51-component input vector and 7.5 Ang cut- off. b) gp_* models are Gupta potential parameters, collected from the literature, and named as: gp_(system name: series of elements)_(dimensionality of the system that model is prepared for)(model version) note: 1- GP models are collected from the literature (cited in the reference entry in the model file) and were originally for nanoparticles. 2- The cut-off range of the models are adjusted to be usable for the bulk systems, hence _3# models are created.