Sella transition state search with AMSΒΆ

Note: This example requires AMS2023 or later.

This example shows how to couple the Sella code to AMS using the AMS ASE calculator.

Sella implements special algorithms and coordinate systems for performing transition state searches.

AMS also internally implements several methods. The example compares

  • Sella with AMS/ADF providing the energies and forces

  • AMS-only, where the initial hessian is calculated with DFTB and the TS search is done with ADF

For more information about Sella, refer to the Sella documentation and examples.


Sella is not included with AMS and not supported by SCM. To install it into the AMS python environment, run

$AMSBIN/amspython -m pip install sella

Example usage: (Download

#!/usr/bin/env amspython
import os
import time

from import read
from scm.plams import *
from scm.plams.interfaces.adfsuite.ase_calculator import AMSCalculator
from sella import Sella


This examples runs a transition state search with the Sella python package and
compares results and timings to the builtin transition state search in AMS (using a DFTB hessian to initialize the DFT transition state search).

This example requires an ADF license.


def adf_settings():
    s = Settings()
    s.input.adf.basis.type = 'DZP'
    s.input.adf.basis.core = 'None'
    s.input.adf.xc.gga = 'pbe'
    s.input.adf.symmetry = 'nosym'
    return s

def run_sella(molecule):
    """ Run a TS search with Sella """
    s = adf_settings()
    s.input.ams.task = 'SinglePoint' = 'Yes'

    atoms = toASE(molecule)

    if os.path.exists("sella.log"):
    if os.path.exists("sella.traj"):

    with AMSCalculator(settings=s, amsworker=True) as calc:
        atoms.calc = calc
        opt = Sella(atoms, internal=True, logfile="sella.log", trajectory="sella.traj"), steps=50)  # 0.027 eV/ang roughly matches AMS default criterion 0.001 Ha/ang

    traj = read("sella.traj", ":")
    print(f"Sella converged after {len(traj)} single-point calculations")
    print(f"Final energy: {atoms.get_potential_energy()} eV")

    optimized_mol = fromASE(atoms)
    return optimized_mol

def run_ams(molecule):
    """ Run DFT transition state search but use initial hessian calculated with DFTB """
    s = adf_settings()
    s.input.ams.task = 'TransitionStateSearch'
    s.input.ams.geometryoptimization.initialhessian.type = 'CalculateWithFastEngine'
    job = AMSJob(settings=s, molecule=molecule, name='ams_ts')
    print(f"AMS finished after {len(job.results.get_history_property('Energy'))} iterations")
    print(f"AMS optimized energy: {job.results.get_energy(unit='eV')} eV")

def get_molecule():
    return AMSJob.from_input("""
             C         0.049484    0.042994    0.000000
             H        -0.068980    0.638928   -0.915972
             H        -0.068980    0.638928    0.915972
             H        -0.841513   -0.626342    0.000000
             H         0.555494   -1.148227    0.000000
             Hg        2.303289   -0.007233    0.000000
             Cl        4.429752    0.776056    0.000000
             Cl        1.342057   -2.676083    0.000000


def main():
    os.environ['OMP_NUM_THREADS'] = '1'
    mol = get_molecule()

    start = time.time()
    print(f"Sella finished in {time.time()-start} seconds")

    start = time.time()
    print(f"AMS finished in {time.time()-start} seconds")


if __name__ == '__main__':