Direct MaxFlux method

A Python implementation of the direct MaxFlux method for transition state search

sample.py

from ase.io import write, read
from ase.calculators.emt import EMT
from dmf import DirectMaxFlux

# read idpp-interpolated images created from react.xyz and prod.xyz
# see ASE's document for how to generate it
ref_images = read('idpp_images.traj',index=':')

# set up a variational problem of the direct MaxFlux method
mxflx = DirectMaxFlux(ref_images,nmove=3,update_teval=True)

# set up calculators
for image in mxflx.images:
    image.calc = EMT()

# solve the variational problem
mxflx.add_ipopt_options({'output_file':'sample_ipopt.out'})
mxflx.solve(tol='middle')

# write final path and history of x(tmax)
write('sample_fin.traj',mxflx.images)
write('sample_tmax.traj',mxflx.history.images_tmax)

Requirements

• NumPy
• SciPy
• ASE
• cyipopt

Documentation

See this GitHub Pages.

Limitations

Currently, only non-periodic systems are supported.