ASE Manual Release 3.6.1.2825 CAMd - CampOS Wiki
ASE Manual Release 3.6.1.2825 CAMd - CampOS Wiki
ASE Manual Release 3.6.1.2825 CAMd - CampOS Wiki
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<strong>ASE</strong> <strong>Manual</strong>, <strong>Release</strong> 3.6.1.2828<br />
NEB.interpolate()<br />
Interpolate path linearly from initial to final state.<br />
Only the internal images (not the endpoints) need have calculators attached.<br />
See Also:<br />
optimize: Information about energy minimization (optimization).<br />
calculators: How to use calculators.<br />
Tutorials:<br />
• Diffusion of gold atom on Al(100) surface (NEB)<br />
• Dissociation<br />
• Dissociation<br />
Note: If there are M images and each image has N atoms, then the NEB object behaves like one big Atoms<br />
object with MN atoms, so its get_positions() method will return a MN × 3 array.<br />
7.16.2 Trajectories<br />
The code:<br />
from ase.optimize import QuasiNewton<br />
optimizer = QuasiNewton(neb, trajectory=’A2B.traj’)<br />
will write all images to one file. The Trajectory object knows about NEB calculations, so it will write M images<br />
with N atoms at every iteration and not one big configuration containing MN atoms.<br />
The result of the latest iteration can now be analysed with this command: ag A2B.traj@-5:.<br />
For the example above, you can write the images to individual trajectory files like this:<br />
for i in range(1, 4):<br />
qn.attach(io.PickleTrajectory(’A2B-%d.traj’ % i, ’w’, images[i]))<br />
The result of the latest iteration can be analysed like this:<br />
$ ag A.traj A2B-?.traj B.traj -n -1<br />
7.16.3 Restarting<br />
Restart the calculation like this:<br />
images = io.read(’A2B.traj@-5:’)<br />
7.16.4 Climbing image<br />
The “climbing image” variation involves designating a specific image to behave differently to the rest of the chain:<br />
it feels no spring forces, and the component of the potential force parallel to the chain is reversed, such that it<br />
moves towards the saddle point. This depends on the adjacent images providing a reasonably good approximation<br />
of the correct tangent at the location of the climbing image; thus in general the climbing image is not turned on<br />
until some iterations have been run without it (generally 20% to 50% of the total number of iterations).<br />
To use the climbing image NEB method, instantiate the NEB object like this:<br />
neb = NEB(images, climb=True)<br />
144 Chapter 7. Documentation for modules in <strong>ASE</strong>