NEB

[NW]

Hello,

I run a NEB simulation and I provided the script file in the attachment. The simulation created a lot of NEB hdf5 files as Nudged Elastic Band_0, Nudged Elastic Band_1, Nudged Elastic Band_2, ... . Why I got a lot of files? and which one is the results? because each of them is different from the others.

[Daniele Stradi]

Hello,

as shown in this tutorial, there should be only two NEB files, one with the non-optimized and one with the optimized reaction path:
https://docs.quantumwise.com/tutorials/neb_pt/neb_pt.html

Could you please attach also the log file of the calculation?

Best
Daniele 

[NW]

Thanks Daniele,
Here is the log file.

[Daniele Stradi]

Hi, What you are experiencing is due to the fact that you have set the same output file for (i) the trajectory_filename and (ii) the output file of the OptimizeNudgedElasticBand class. In the case of (i) the output will be a new NEB configuration at each NEB iteration. These will be called "Nudged Elastic Band_X" with X being the number of the NEB iteration. The configuration with the highest X value will correspond to the most converged NEB iteration. In the case of (ii) the only NEB configurations that will be written to the output will be those of iteration 0 and of the final NEB iteration, which should correspond to the fully converged NEB path.  I would suggest that you set two separate files for (i) and (ii), as shown below. This will allow you to have a clearer overview of the files that are created during the NEB run. Best, Daniele

Code

# -------------------------------------------------------------
# Optimize Geometry
# -------------------------------------------------------------
neb_configuration = OptimizeNudgedElasticBand(
    neb_configuration,
    max_forces=0.02*eV/Ang,
    max_steps=200,
    max_step_length=0.2*Ang,
    trajectory_filename='trajectory_NEB.hdf5',
    optimizer_method=LBFGS(),
    preoptimization=True,
    climbing_image=True,
)
nlsave('NEB.hdf5', neb_configuration)
nlprint(neb_configuration)

[NW]

Perfect. Thank you so much.