10.17632/2T5C59RRRF.1
Amsler, Maximilian
Maximilian
Amsler
FLAME: A library of atomistic modeling environments
Mendeley
2020
Dataset
Computational Physics
Structure Prediction
Potential Energy Surface
Neural Network
Rostami, Samare
Samare
Rostami
Tahmasbi, Hossein
Hossein
Tahmasbi
Khajehpasha, Ehsan Rahmatizad
Ehsan Rahmatizad
Khajehpasha
Faraji, Somayeh
Somayeh
Faraji
Rasoulkhani, Robabe
Robabe
Rasoulkhani
Ghasemi, S. Alireza
S. Alireza
Ghasemi
2020-07-10
10.1016/j.cpc.2020.107415
10.17632/2t5c59rrrf
GNU Public License Version 3
FLAME is a software package to perform a wide range of atomistic simulations for exploring the potential energy surfaces (PES) of complex condensed matter systems. The available methods include molecular dynamics simulations to sample free energy landscapes, saddle point searches to identify transition states, and gradient relaxations to find dynamically stable geometries. In addition to such common tasks, FLAME implements a structure prediction algorithm based on the minima hopping method (MHM) to identify the ground state structure of any system given solely the chemical composition, and a framework to train a neural network potential to reproduce the PES from ab initio calculations. The combination of neural network potentials with the MHM in FLAME allows a highly efficient and reliable identification of the ground state as well as metastable structures of molecules and crystals, as well as of nano structures, including surfaces, interfaces, and two-dimensional materials. In this manuscript, we provide detailed descriptions of the methods implemented in the FLAME code and its capabilities, together with several illustrative examples.