Workflow: filtering molecules based on excitation energies¶
Identifying systems with certain physical properties out of a large database of molecules is a typical task that can be easily automatized. In this example we will show how this can be achieved with a simple PLAMS script.
Introducing the case study
In our toy study, we want to scan a database of structures, looking for all molecules that absorb light within a certain energy range. For example, between 2 and 4 eV.
A simple approach would be to calculate the excitation energies (and the corresponding oscillator strengths) using ADF’s time-dependent DFT (TD-DFT) for all the molecules in out database of structures. Since TD-DFT is an expensive method, this procedure can be computationally demanding for large numbers of molecules.
A faster approach would be to pre-screen the large database of molecules by first using a less accurate but more efficient method (e.g. time-dependent DFTB (TD-DFTB)) and then run the expensive TD-DFT calculations with ADF only for the systems exhibiting the most promising absorption energies in the faster-but-less-accurate calculations.
The basic workflow may look as follows:
Step 1
- Optimize the structure of all molecules in the database with DFTB and calculate excitation energies and oscillator strengths with TD-DFTB
- Select the molecules with electronic excitations of energies between 1 and 6 eV and non-zero oscillator strenght (since TD-DFTB is less accurate than TD-DFT, we opt for a larger energy range in this step). This should significantly reduce the number of molecules to be considered in the following steps.
Step 2
- Optimize the structures of the promising molecules with ADF.
- Compute the electronic excitations energies using ADF’s TD-DFT and select the molecules with excitations of energies between 2 and 4 eV (and non-zero oscillator strength).
Note: in this example we focus on the scripting aspects rather than studying physical phenomena. The computational methods used here might not be entirely appropriate to describe the physical properties of interest.
# Workflow with PLAMS
# A couple of useful function for extracting results:
@add_to_class(AMSResults)
def get_excitations(results):
"""Returns excitation energies (in eV) and oscillator strenghts (in Debye)."""
if results.job.ok():
exci_energies_au = results.readrkf('Excitations SS A','excenergies',file='engine')
oscillator_str_au = results.readrkf('Excitations SS A','oscillator strengths',file='engine')
# The results are stored in atomic units. Convert them to more convenient units:
exci_energies = Units.convert(exci_energies_au,'au','eV')
oscillator_str = Units.convert(oscillator_str_au,'au','Debye')
return exci_energies, oscillator_str
else:
return [],[]
@add_to_class(AMSResults)
def has_good_excitations(results, min_energy, max_energy, oscillator_str_threshold=1E-4):
"""Returns True if there is at least one excitation with non-vanishing oscillator strenght
in the energy range [min_energy, max_energy]. Unit for min_energy and max energy: eV. """
exci_energies, oscillator_str = results.get_excitations()
for e,o in zip(exci_energies, oscillator_str):
if min_energy < e < max_energy and o > oscillator_str_threshold:
return True
return False
# Calculation settings:
# =====================
# Settings for geometry optimization with the AMS driver:
go_sett = Settings()
go_sett.input.ams.Task = 'GeometryOptimization'
go_sett.input.ams.GeometryOptimization.Convergence.Gradients = 1.0e-4
# Settings for single point calculation with the AMS driver
sp_sett = Settings()
sp_sett.input.ams.Task = 'SinglePoint'
# Settings for the DFTB engine (including excitations)
dftb_sett = Settings()
dftb_sett.input.dftb.Model = 'SCC-DFTB'
dftb_sett.input.dftb.ResourcesDir = 'QUASINANO2015'
dftb_sett.input.dftb.Properties.Excitations.TDDFTB.calc = 'singlet'
dftb_sett.input.dftb.Properties.Excitations.TDDFTB.lowest = 10
dftb_sett.input.dftb.Occupation.Temperature = 5.0
# Settings for the geometry optimization with the ADF engine
adf_sett = Settings()
adf_sett.input.adf.Basis.Type = 'DZP'
adf_sett.input.adf.NumericalQuality = 'Basic'
# Settings for the excitation calculation using the ADF engine
adf_exci_sett = Settings()
adf_exci_sett.input.adf.Basis.Type = 'TZP'
adf_exci_sett.input.adf.XC.GGA = 'PBE'
adf_exci_sett.input.adf.NumericalQuality = 'Basic'
adf_exci_sett.input.adf.Symmetry = 'NoSym'
adf_exci_sett.input.adf.Excitations.lowest = 10
adf_exci_sett.input.adf.Excitations.OnlySing = ''
# Import all xyz files in the folder 'molecules'
molecules = read_molecules('molecules')
print("Step 1: prescreening with DFTB")
print("==============================")
promising_molecules = {}
for name, mol in molecules.items():
dftb_job = AMSJob(name='DFTB_'+name, molecule=mol, settings=go_sett+dftb_sett)
dftb_job.run()
if dftb_job.results.has_good_excitations(1,6):
promising_molecules[name] = dftb_job.results.get_main_molecule()
print(f"Found {len(promising_molecules)} promising molecules with DFTB")
print("Step 2: Optimization and excitations calculation with ADF")
print("=========================================================")
for name, mol in promising_molecules.items():
adf_go_job = AMSJob(name='ADF_GO_'+name, molecule=mol, settings=go_sett+adf_sett)
adf_go_job.run()
optimized_mol = adf_go_job.results.get_main_molecule()
adf_exci_job = AMSJob(name='ADF_exci_'+name, molecule=optimized_mol,
settings=sp_sett+adf_exci_sett)
adf_exci_job.run()
if adf_exci_job.results.has_good_excitations(2,4):
print(f"Molecule {name} has excitation(s) satysfying our criteria!")
print(optimized_mol)
exci_energies, oscillator_str = adf_exci_job.results.get_excitations()
print("Excitation energy [eV], oscillator strength:")
for e,o in zip(exci_energies, oscillator_str):
print(f"{e:8.4f}, {o:8.4f}")
Note
To execute this PLAMS script:
Download ExcitationsWorkflow.pyDownload molecules.tarand extract it$AMSBIN/plams ExcitationsWorkflow.py
Output
[14:41:27] PLAMS working folder: D:\adfsrc\trunk64\rundir.plams.ExcitationsWorkflow\plams_workdir
Step 1: prescreening with DFTB
==============================
[14:41:27] JOB DFTB_AlF3 STARTED
[14:41:27] JOB DFTB_AlF3 RUNNING
[14:41:28] JOB DFTB_AlF3 FINISHED
[14:41:28] JOB DFTB_AlF3 SUCCESSFUL
[14:41:28] JOB DFTB_CSCl2 STARTED
[14:41:28] JOB DFTB_CSCl2 RUNNING
[14:41:30] JOB DFTB_CSCl2 FINISHED
[14:41:30] JOB DFTB_CSCl2 SUCCESSFUL
[14:41:30] JOB DFTB_H2O STARTED
[14:41:30] JOB DFTB_H2O RUNNING
[14:41:31] JOB DFTB_H2O FINISHED
[14:41:31] JOB DFTB_H2O SUCCESSFUL
[14:41:31] JOB DFTB_NH3 STARTED
[14:41:31] JOB DFTB_NH3 RUNNING
[14:41:35] JOB DFTB_NH3 FINISHED
[14:41:35] Job DFTB_NH3 reported warnings. Please check the the output
[14:41:35] JOB DFTB_NH3 SUCCESSFUL
[14:41:35] JOB DFTB_S2Cl2 STARTED
[14:41:35] JOB DFTB_S2Cl2 RUNNING
[14:41:36] JOB DFTB_S2Cl2 FINISHED
[14:41:36] JOB DFTB_S2Cl2 SUCCESSFUL
Found 2 promising molecules with DFTB
Step 2: Optimization and excitations calculation with ADF
=========================================================
[14:41:36] JOB ADF_GO_CSCl2 STARTED
[14:41:36] JOB ADF_GO_CSCl2 RUNNING
[14:41:45] JOB ADF_GO_CSCl2 FINISHED
[14:41:45] JOB ADF_GO_CSCl2 SUCCESSFUL
[14:41:45] JOB ADF_exci_CSCl2 STARTED
[14:41:45] JOB ADF_exci_CSCl2 RUNNING
[14:41:52] JOB ADF_exci_CSCl2 FINISHED
[14:41:52] JOB ADF_exci_CSCl2 SUCCESSFUL
[14:41:52] JOB ADF_GO_S2Cl2 STARTED
[14:41:52] JOB ADF_GO_S2Cl2 RUNNING
[14:42:02] JOB ADF_GO_S2Cl2 FINISHED
[14:42:02] JOB ADF_GO_S2Cl2 SUCCESSFUL
[14:42:02] JOB ADF_exci_S2Cl2 STARTED
[14:42:02] JOB ADF_exci_S2Cl2 RUNNING
[14:42:09] JOB ADF_exci_S2Cl2 FINISHED
[14:42:09] JOB ADF_exci_S2Cl2 SUCCESSFUL
Molecule S2Cl2 has excitation(s) satysfying our criteria!
Atoms:
1 S -0.658306 -0.316643 0.909151
2 S -0.658306 0.316643 -0.909151
3 Cl 0.758306 0.752857 2.053018
4 Cl 0.758306 -0.752857 -2.053018
Excitation energy [eV], oscillator strength:
3.4107, 0.0114
3.5386, 0.0160
3.5400, 0.0011
3.9864, 0.1105
4.3225, 0.0049
4.3513, 0.2551
4.7544, 0.0011
4.9414, 0.0105
5.3188, 0.0036
5.3272, 0.0721
[14:42:09] PLAMS run finished. Goodbye
Test duration in seconds: 43