def calc_productAndTS(name):
smiles = 'C1' + name + 'C1'
mol = rdkitTools.smiles2plams(smiles)
mol.properties.smiles = smiles
product = dftb(templates.geometry.overlay(settings),
mol,
job_name=name + "_product")
constraint1 = "dist 1 2"
constraint2 = "dist 4 5"
sv1 = startvalue[name[0]]
sv2 = startvalue[name[2]]
# scan input
if name[0] == name[2]:
# symmetric molecule
scan = {
'constraint': [constraint1, constraint2],
'surface': {
'nsteps': 4,
'start': [sv1, sv2],
'stepsize': [0.1, 0.1]
}
}
else:
scan = {
'constraint': constraint1,
'surface': {
'nsteps': 4,
'start': sv1,
'stepsize': 0.1
},
'scan': {
'constraint': constraint2,
'surface': {
'nsteps': 4,
'start': sv2,
'stepsize': 0.1
}
}
}
# PES = gathered (promised) result objects for each point in the scan
PES = PES_scan(dftb,
settings,
product.molecule,
scan,
job_name=name + "_PESscan")
# get the object presenting the molecule with the maximum energy calculated from the scan
apprTS = select_max(PES, 'energy')
# perform the TS optimization using the default TS template
TS = dftb(templates.ts.overlay(settings),
apprTS.molecule,
job_name=name + "_TS")
return product, TS
def calc_productAndTS(name):
smiles = 'C1' + name[0] + "=" + name[1:] + 'C1'
mol = rdkitTools.smiles2plams(smiles)
mol.properties.smiles = smiles
product = adf(templates.geometry.overlay(settings),
dftb(templates.geometry.overlay(settings),
mol,
job_name=name + "_product_DFTB").molecule,
job_name=name + "_product")
constraint1 = Distance(1, 0)
constraint2 = Distance(4, 3)
# scan input
pes = PES(product.molecule,
constraints=[constraint1, constraint2],
offset=[2.0, 2.0],
get_current_values=False,
nsteps=5,
stepsize=[0.1, 0.1])
# PES = gathered (promised) result objects for each point in the scan
pesscan = pes.scan([dftb, adf], settings, job_name=name + "_PES")
# get the object presenting the molecule with the maximum energy
# calculated from the scan
apprTS = select_max(pesscan, 'energy')
DFTB_freq = dftb(templates.freq.overlay(settings),
apprTS.molecule,
job_name=name + "_DFTBfreq")
t = Settings()
t.specific.adf.geometry.inithess = DFTB_freq.kf.path
# Run the TS optimization, using the default TS template
TS = adf(templates.ts.overlay(settings).overlay(t),
DFTB_freq.molecule,
job_name=name + "_TS")
adf_freq = adf(templates.freq.overlay(settings),
TS.molecule,
job_name=name + "_freq")
return product, adf_freq
def test_linear_ts():
"""
compute a first approximation to the TS.
"""
# Read the Molecule from file
cnc = Molecule('test/test_files/C-N-C.mol', 'mol')
# User define Settings
settings = Settings()
settings.functional = "pbe"
settings.basis = "SZ"
settings.specific.dftb.dftb.scc
constraint1 = Distance(0, 4)
constraint2 = Distance(2, 3)
# scan input
pes = PES(cnc,
constraints=[constraint1, constraint2],
offset=[2.3, 2.3],
get_current_values=False,
nsteps=2,
stepsize=[0.1, 0.1])
# returns a set of results object containing the output of
# each point in the scan
lt = pes.scan([dftb, adf], settings)
# Gets the object presenting the molecule
# with the maximum energy calculated from the scan
apprTS = select_max(lt, "energy")
# Run the TS optimization, using the default TS template
ts = run(apprTS)
expected_energy = -3.219708290363864
assert abs(ts.energy - expected_energy) < 0.02
'constraint': constraint2,
'surface': {
'nsteps': 4,
'start': sv2,
'stepsize': 0.1
}
}
}
# returns a set of results object containing the output of
# each point in the scan
LT = PES_scan(dftb, settings, product, scan)
# Gets the object presenting the molecule
# with the maximum energy calculated from the scan
apprTS = select_max(LT, 'energy')
# Run the TS optimization, using the default TS template
TS = dftb(templates.ts.overlay(settings), apprTS.molecule)
# Actual execution of the jobs
reactives = [E_reactant, E_product, TS]
E_reactant, E_product, TS = run(gather(*reactives), n_processes=1)
# Retrieve the molecular coordinates
mol = TS.molecule
d1 = bond_distance(mol.atoms[0].coords, mol.atoms[1].coords)
d2 = bond_distance(mol.atoms[3].coords, mol.atoms[4].coords)
Eact = (TS.energy - E_ethene - E_reactant) * hartree2kcal
Ereact = (E_product - E_ethene - E_reactant) * hartree2kcal
scan = {
'constraint': [constraint1, constraint2],
'surface': {
'nsteps': 6,
'start': [2.3, 2.3],
'stepsize': [0.1, 0.1]
}
}
# returns a set of results object containing the output of
# each point in the scan
lt = PES_scan([dftb, adf], settings, cnc, scan)
# Gets the object presenting the molecule
# with the maximum energy calculated from the scan
apprTS = select_max(lt, "energy")
appr_hess = dftb(templates.freq.overlay(settings), apprTS.molecule)
t = Settings()
t.specific.adf.geometry.inithess = appr_hess.archive.path
# Run the TS optimization with ADF, using initial hessian from DFTB freq calculation
ts = run(adf(templates.ts.overlay(settings).overlay(t), appr_hess.molecule),
n_processes=1)
# Retrieve the molecular coordinates
mol = ts.molecule
r1 = mol.atoms[0].coords
r2 = mol.atoms[4].coords
pjob = adf(
templates.geometry.overlay(settings),
dftb(templates.geometry.overlay(settings),
pmol, job_name=name + "_p_DFTB").molecule,
job_name=name + "_p")
# Prepare TS jobs
# Define PES
pes = PES(pjob.molecule, constraints=[bond1, bond2],
offset=[2.0, 2.0], get_current_values=False, nsteps=5, stepsize=[0.1, 0.1])
# pesscan: gathered (promised) result objects for each point in the scan
pesscan = pes.scan([dftb, adf], settings, job_name=name + "_PES")
# Get the result with the maximum energy
apprTS = select_max(pesscan, 'energy')
# Calculate the DFTB hessian
DFTBfreq = dftb(templates.freq.overlay(settings), apprTS.molecule, job_name=name + "_DFTBfreq")
# Run the TS optimization, using the initial hession from DFTB
t = Settings()
t.specific.adf.geometry.inithess = DFTBfreq.kf.path
TS = adf(templates.ts.overlay(settings).overlay(t), DFTBfreq.molecule, job_name=name + "_TS")
# Perform a freq calculation
TSfreq = adf(templates.freq.overlay(settings), TS.molecule, job_name=name + "_freq")
# Add the jobs to the job list
job_list.append(gather(r1job, r2job, pjob, TSfreq, TS.optcycles))
