maise-net                               
                                                             
                  Python interface to maise                     
     for automated neural network potential construction
                                                                
                          ====                              
                                                                
        With any use of this script, please cite:              
     
         'MAISE: Construction of neural network interatomic     
             models and evolutionary structure optimization'    
                                                                
         arXiv:2005.12131                                       

                          ====                              
                                                                
               Questions and bug reports:                   
                                                                
        Samad  Hajinazar         hajinazar@binghamton.edu       
        Alexey Kolmogorov        kolmogorov@binghamton.edu      
                                                                
                          ====                              
                                                                
                    HOW-TO and NOTES                          
                                                                
 1) The maise-net wrapper, version 2.0, is developed for 
    automated dataset generation with MAISE and VASP codes 
    for automated construction of neural network potentials.    
    It generates: single atom reference data (REFS), 2-4 atoms      
    clusters (CLST), equation of state for high-symmetry  
    structures (EOSZ), and evolutionary datasets of bulk or      
    nanoparticle structures with a set of arbitrary sizes as    
    defined in "setup" (EVOS). Optionally, EOSN (EOS data for
    the unique minima in EVOS data) and TEST (DFT relaxation
    for NN-based minima found in the test evolutionary search)
    data can be generated, as well.                                  
                                                                
 2) maise-net works with any out-of-the-box version of the Python  
    (2.X/3.X) and does not need any non-standard module.        
                                                                
 3) Local optimizations and energy calculations are performed   
    with VASP package. VASP should be already installed on      
    user's system with "vasp" executable in the system path.    
                                                                
 4) "maise" executive (version 2.7 or newer) and proper 
    "POTCAR" for the system should be provided in the 
     local INI/ directory by the user.             
                                                                
 5) Following files are job related and cluster specific;       
    their header should be manually adjusted in the indicated   
    part of the scripts, while the type of the cluster is       
    defined in the "setup" file with QUET flag:                 
                                                                
     INI/jesz     for EVO run in cycle 0                            
     INI/jesn     for EVO run in cycles 1+                           
     INI/jdft     for DFT runs                                  
     INI/jtrn     for training jobs                             
     INI/jeos     for DFT runs in EOS and TST runs