ADF: Task COSMO-RS Compound¶
The ADFCOSMORSCompoundJob
class generates results identical to the “Task COSMO-RS Compound” in the AMS ADF graphical user interface. This python interface allows users to easily generate the .coskf files for one or many structures. A possible usage is given in ADF and COSMO-RS workflow.
To follow along
Download and unzip
compounds_xyz.zip
then, either
Download
cosmors_compound.py
(run as$AMSBIN/amspython cosmors_compound.py
).Download
cosmors_compound.ipynb
(see also: how to install Jupyterlab in AMS)
Worked Example¶
Generating coskf files from xyz¶
The example will first load all the molecules in the folder compounds_xyz
and then optimize the gas geometry using ADF, and perform the ADF COSMO calculation for each compound. When the calculations are finished, we will find all the .coskf files in the test_coskfs_xyz
directory.
from scm.plams import from_smiles, read_molecules, init, JobRunner, config
from scm.plams.recipes.adfcosmorscompound import ADFCOSMORSCompoundJob
import os
# this line is not required in AMS2025+
init();
PLAMS working folder: /path/plams/examples/COSMORSCompound/plams_workdir
Enable the parallel calculation through JobRunner
. Here, we’ll assign one core to each job, and we can have up to eight jobs running all at once.
config.default_jobrunner = JobRunner(parallel=True, maxjobs=8) # Set the default jobrunner to be parallel
config.default_jobmanager.settings.hashing = None # Disable rerun prevention
config.job.runscript.nproc = 1 # Number of cores for each job
config.log.stdout = 1 # Suppress plams output
molecules = read_molecules("./compounds_xyz")
results = []
for name, mol in molecules.items():
job = ADFCOSMORSCompoundJob(molecule=mol, coskf_name=name, coskf_dir="test_coskfs_xyz")
results.append(job.run())
[19.03|15:14:40] JOB plamsjob STARTED
[19.03|15:14:40] JOB plamsjob STARTED
[19.03|15:14:40] JOB plamsjob/gas STARTED
[19.03|15:14:40] JOB plamsjob/solv STARTED
[19.03|15:14:40] JOB plamsjob/sigma STARTED
for result in results:
result.wait()
[19.03|15:14:40] Waiting for job plamsjob to finish
[19.03|15:14:40] JOB plamsjob.002/gas STARTED
[19.03|15:14:40] JOB plamsjob.002/solv STARTED
[19.03|15:14:40] Waiting for job gas to finish
[19.03|15:14:40] JOB plamsjob.002/sigma STARTED
[19.03|15:14:40] Waiting for job solv to finish
[19.03|15:14:40] Waiting for job gas to finish
[19.03|15:14:40] Waiting for job solv to finish
[19.03|15:14:45] JOB plamsjob.002/gas SUCCESSFUL
[19.03|15:14:49] JOB plamsjob.002/solv SUCCESSFUL
[19.03|15:14:49] JOB plamsjob.002/sigma SUCCESSFUL
[19.03|15:14:50] JOB plamsjob.002 SUCCESSFUL
[19.03|15:14:57] JOB plamsjob/gas SUCCESSFUL
[19.03|15:15:10] JOB plamsjob/solv SUCCESSFUL
[19.03|15:15:10] JOB plamsjob/sigma SUCCESSFUL
... (PLAMS log lines truncated) ...
print(f"coskf files generated: {', '.join([f for f in os.listdir('./test_coskfs_xyz')])}")
coskf files generated: CO.coskf, H2O.coskf
Generating .coskf files from smiles¶
Now, we will specify the smiles and name of a set of compounds and generate the initial geometry of each compound using from_smiles
function. With the setting, nconfs=100
and forcefield='uff'
, we will generate 100 conformers and find the one with the lowest energy using ‘uff’ forcefield. When the calculations are finished, we will find all the .coskf file in the test_coskfs_smiles
directory.
rd_smiles = ["O", "CO"]
rd_names = ["H2O", "CO"]
molecules = {}
for name, smiles in zip(rd_names, rd_smiles):
molecules[name] = from_smiles(smiles, nconfs=100, forcefield="uff")[0] # lowest energy one in 100 conformers
Lastly, we give this information to the ADFCOSMORSCompoundJob
class, including the name of the coskf files as well as the directory in which we’ll find them after the calculations complete. Using the setting, preoptimization='GFN1-xTB'
and singlepoint=False
, it will utilize the DFTB for a quick pre-optimization. Subsequently, it will execute a gas phase optimization using ADF, followed by the solvation calculation.
results = []
for name, mol in molecules.items():
job = ADFCOSMORSCompoundJob(
molecule=mol, # The initial structure
coskf_name=name, # a name to be used for coskf file
coskf_dir="test_coskfs_smiles", # a directory to put the .coskf files generated
preoptimization="GFN1-xTB", # perform preoptimize or not
singlepoint=False, # run a singlepoint in gasphase and solvation calculation without geometry optimization. Cannot be combined with `preoptimization`
name=name,
) # an optional name for the calculation directory
results.append(job.run())
[19.03|15:15:16] JOB H2O STARTED
[19.03|15:15:16] JOB CO STARTED
[19.03|15:15:16] JOB H2O/preoptimization STARTED
[19.03|15:15:16] JOB CO/preoptimization STARTED
for result in results:
result.wait()
[19.03|15:15:16] Waiting for job H2O to finish
[19.03|15:15:16] JOB CO/gas STARTED
[19.03|15:15:16] JOB H2O/gas STARTED
[19.03|15:15:16] JOB H2O/solv STARTED
[19.03|15:15:16] JOB CO/solv STARTED
[19.03|15:15:16] JOB H2O/sigma STARTED
[19.03|15:15:16] JOB CO/sigma STARTED
[19.03|15:15:16] Waiting for job gas to finish
[19.03|15:15:16] Waiting for job preoptimization to finish
[19.03|15:15:16] Waiting for job preoptimization to finish
[19.03|15:15:16] Waiting for job gas to finish
[19.03|15:15:16] Waiting for job solv to finish
[19.03|15:15:16] Waiting for job solv to finish
[19.03|15:15:16] JOB H2O/preoptimization SUCCESSFUL
[19.03|15:15:16] JOB CO/preoptimization SUCCESSFUL
[19.03|15:15:23] JOB H2O/gas SUCCESSFUL
[19.03|15:15:27] JOB H2O/solv SUCCESSFUL
... (PLAMS log lines truncated) ...
[19.03|15:15:31] Waiting for job CO to finish
print(f"coskf files generated: {', '.join([f for f in os.listdir('./test_coskfs_smiles')])}")
coskf files generated: CO.coskf, H2O.coskf
Complete Python code¶
#!/usr/bin/env amspython
# coding: utf-8
# ## Generating coskf files from xyz
# The example will first load all the molecules in the folder ``compounds_xyz`` and then optimize the gas geometry using ADF, and perform the ADF COSMO calculation for each compound. When the calculations are finished, we will find all the .coskf files in the ``test_coskfs_xyz`` directory.
from scm.plams import from_smiles, read_molecules, init, JobRunner, config
from scm.plams.recipes.adfcosmorscompound import ADFCOSMORSCompoundJob
import os
# this line is not required in AMS2025+
init()
# Enable the parallel calculation through `JobRunner`. Here, we'll assign one core to each job, and we can have up to eight jobs running all at once.
config.default_jobrunner = JobRunner(parallel=True, maxjobs=8) # Set the default jobrunner to be parallel
config.default_jobmanager.settings.hashing = None # Disable rerun prevention
config.job.runscript.nproc = 1 # Number of cores for each job
config.log.stdout = 1 # Suppress plams output
molecules = read_molecules("./compounds_xyz")
results = []
for name, mol in molecules.items():
job = ADFCOSMORSCompoundJob(molecule=mol, coskf_name=name, coskf_dir="test_coskfs_xyz")
results.append(job.run())
for result in results:
result.wait()
print(f"coskf files generated: {', '.join([f for f in os.listdir('./test_coskfs_xyz')])}")
# ## Generating .coskf files from smiles
# Now, we will specify the smiles and name of a set of compounds and generate the initial geometry of each compound using `from_smiles` function. With the setting, `nconfs=100` and `forcefield='uff'`, we will generate 100 conformers and find the one with the lowest energy using 'uff' forcefield. When the calculations are finished, we will find all the .coskf file in the ``test_coskfs_smiles`` directory.
rd_smiles = ["O", "CO"]
rd_names = ["H2O", "CO"]
molecules = {}
for name, smiles in zip(rd_names, rd_smiles):
molecules[name] = from_smiles(smiles, nconfs=100, forcefield="uff")[0] # lowest energy one in 100 conformers
# Lastly, we give this information to the `ADFCOSMORSCompoundJob` class, including the name of the coskf files as well as the directory in which we'll find them after the calculations complete. Using the setting, `preoptimization='GFN1-xTB'` and `singlepoint=False`, it will utilize the DFTB for a quick pre-optimization. Subsequently, it will execute a gas phase optimization using ADF, followed by the solvation calculation.
results = []
for name, mol in molecules.items():
job = ADFCOSMORSCompoundJob(
molecule=mol, # The initial structure
coskf_name=name, # a name to be used for coskf file
coskf_dir="test_coskfs_smiles", # a directory to put the .coskf files generated
preoptimization="GFN1-xTB", # perform preoptimize or not
singlepoint=False, # run a singlepoint in gasphase and solvation calculation without geometry optimization. Cannot be combined with `preoptimization`
name=name,
) # an optional name for the calculation directory
results.append(job.run())
for result in results:
result.wait()
print(f"coskf files generated: {', '.join([f for f in os.listdir('./test_coskfs_smiles')])}")
Source code for ADFCOSMORSCompound
¶
import os, shutil
from collections import OrderedDict
from typing import List, Optional, Union, Dict, Literal, Tuple
from scm.plams.interfaces.adfsuite.ams import AMSJob
from scm.plams.interfaces.adfsuite.crs import CRSJob
from scm.plams.interfaces.adfsuite.densf import DensfJob
from scm.plams.tools.periodic_table import PeriodicTable
from scm.plams.mol.molecule import Molecule
from scm.plams.core.basejob import MultiJob
from scm.plams.core.results import Results
from scm.plams.core.settings import Settings
from scm.plams.core.functions import add_to_instance, requires_optional_package
from scm.plams.interfaces.adfsuite.quickjobs import model_to_settings
from scm.plams.tools.hbc_utilities import parse_mesp, write_HBC_to_COSKF, view_HBC
import numpy as np
__all__ = ["ADFCOSMORSCompoundJob", "ADFCOSMORSCompoundResults"]
class ADFCOSMORSCompoundResults(Results):
"""Results class for ADFCOSMORSCompoundJob"""
def coskfpath(self):
"""
Returns the path to the resulting .coskf
"""
return os.path.join(self.job.path, self.job.coskf_name)
def get_main_molecule(self):
"""
Returns the optimized molecule
"""
return self.job.children["solv"].results.get_main_molecule()
def get_input_molecule(self):
"""
Returns the input molecule
"""
for job in self.job.children.values():
return job.results.get_input_molecule()
def get_sigma_profile(self, subsection: str = "profil"):
"""
Returns the sigma profile of the molecule. For more details see `CRSResults.get_sigma_profile`.
"""
return self.job.children["crs"].results.get_sigma_profile(subsection=subsection)
class ADFCOSMORSCompoundJob(MultiJob):
"""
A class for performing the equivalent of Task: COSMO-RS Compound in the AMS GUI
Args:
molecule : a PLAMS |Molecule|
Keyword Args:
coskf_name : A name for the generated .coskf file. If nothing is specified, the name of the job will be used.
coskf_dir : The directory in which to place the generated .coskf file. If nothing is specified, the file will be put in the plams directory corresponding to the job.
preoptimization : If None, do not preoptimize with a fast engine priori to the optimization with ADF. Otherwise, it can be one of 'UFF', 'GAFF', 'GFNFF', 'GFN1-xTB', 'ANI-2x', 'M3GNet-UP-2022'. Note that you need valid licenses for ForceField or DFTB or MLPotential to use these preoptimizers.
singlepoint (bool) : Run a singlepoint in gasphase and with solvation to generate the .coskf file on the given Molecule. (no geometry optimization). Cannot be combined with ``preoptimization``.
settings (Settings) : A |Settings| object. settings.runscript.nproc, settings.input.adf.custom_options. If 'adf' is in settings.input it should be provided without the solvation block.
mol_info (dict) : an optional dictionary containing information will be written to the Compound Data section within the COSKF file.
hbc_from_MESP (bool) : Defaults to False. Performs DENSF analysis to determine the hydrogen bond center (HBC) used in COSMOSAC-DHB-MESP.
name : an optional name for the calculation directory
Example:
.. code-block:: python
mol = from_smiles('O')
job = ADFCOSMORSCompoundJob(
molecule = mol,
preoptimization = 'UFF',
coskf_dir = 'coskfs',
coskf_name = 'Water',
name = 'H2O',
mol_info = {'CAS':'7732-18-5'}
)
job.run()
print(job.results.coskfpath())
"""
_result_type = ADFCOSMORSCompoundResults
def __init__(
self,
molecule: Union[Molecule, None],
coskf_name: Optional[str] = None,
coskf_dir: Optional[str] = None,
preoptimization: Optional[str] = None,
singlepoint: bool = False,
settings: Optional[Settings] = None,
mol_info: Optional[Dict[str, Union[float, int, str]]] = None,
hbc_from_MESP: bool = False,
**kwargs,
):
"""
Class for running the equivalent of "COSMO-RS Compound" in the AMS
GUI. Note that these are ADF calculations, not COSMO-RS
calculations!
Initialize two or three jobs:
1. (Optional): Preoptimization with force field or semi-empirical method ('UFF', 'GAFF', 'GFNFF', 'GFN1-xTB', 'ANI-2x' or 'M3GNet-UP-2022')
Note: A valid license for ForceField or DFTB or MLPotential is required.
2. Gasphase optimization or single-point calculation (BP86, TZP, BeckeGrid Quality Good)
3. Take optimized structure and run singlepoint with implicit solvation
Access the result .coskf file with ``job.results.coskfpath()``.
Note: this file will be called jobname.coskf, where jobname is the
name of the ADFCOSMORSCompoundJob.
"""
if preoptimization and singlepoint:
raise ValueError("Cannot combine preoptimization with singlepoint")
MultiJob.__init__(self, children=OrderedDict(), **kwargs)
self.input_molecule = molecule
self.mol_info = dict()
if mol_info is not None:
self.mol_info.update(mol_info)
self.settings = settings or Settings()
self.coskf_name = coskf_name
self.coskf_dir = coskf_dir
self.hbc_from_MESP = hbc_from_MESP
if self.coskf_dir is not None and not os.path.exists(self.coskf_dir):
os.mkdir(self.coskf_dir)
if self.coskf_name is None:
self.coskf_name = f"{self.name}.coskf"
elif isinstance(self.coskf_name, str) and not self.coskf_name.endswith(".coskf"):
self.coskf_name += ".coskf"
gas_s = Settings()
gas_s += ADFCOSMORSCompoundJob.adf_settings(solvation=False, settings=self.settings)
gas_job = AMSJob(settings=gas_s, name="gas")
if not singlepoint:
gas_job.settings.input.ams.Task = "GeometryOptimization"
if preoptimization:
preoptimization_s = Settings()
preoptimization_s.runscript.nproc = 1
preoptimization_s.input.ams.Task = "GeometryOptimization"
preoptimization_s += model_to_settings(preoptimization)
preoptimization_job = AMSJob(
settings=preoptimization_s, name="preoptimization", molecule=self.input_molecule
)
self.children["preoptimization"] = preoptimization_job
elif singlepoint:
gas_job.settings.input.ams.Task = "SinglePoint"
@add_to_instance(gas_job)
def prerun(self): # noqa: F811
if not singlepoint and preoptimization:
self.molecule = self.parent.children["preoptimization"].results.get_main_molecule()
else:
self.molecule = self.parent.input_molecule
self.parent.mol_info, self.parent.atomic_ion = ADFCOSMORSCompoundJob.get_compound_properties(
self.molecule, self.parent.mol_info
)
self.children["gas"] = gas_job
if self.hbc_from_MESP:
densf_job = DensfJob(settings=ADFCOSMORSCompoundJob.densf_settings(), name="densf")
self.children["densf"] = densf_job
@add_to_instance(densf_job)
def prerun(self): # noqa: F811
gas_job.results.wait()
self.inputjob = f"../gas/adf.rkf #{self.parent.name}"
solv_s = Settings()
solv_s.input.ams.Task = "SinglePoint"
solv_job = AMSJob(settings=solv_s, name="solv")
@add_to_instance(solv_job)
def prerun(self): # noqa: F811
gas_job.results.wait()
self.settings.input.ams.EngineRestart = "../gas/adf.rkf"
self.settings.input.ams.LoadSystem.File = "../gas/ams.rkf"
molecule_charge = gas_job.results.get_main_molecule().properties.get("charge", 0)
self.settings.input.ams.LoadSystem._1 = f"# {self.parent.name}"
self.settings.input.ams.LoadSystem._2 = f"# charge {molecule_charge}"
self.settings += ADFCOSMORSCompoundJob.adf_settings(
solvation=True,
settings=self.parent.settings,
elements=list(set(at.symbol for at in self.parent.input_molecule)),
atomic_ion=self.parent.atomic_ion,
)
@add_to_instance(solv_job)
def postrun(self):
if self.parent.hbc_from_MESP:
densf_job.results.wait()
densf_path = densf_job.results.kfpath()
else:
densf_path = None
ADFCOSMORSCompoundJob.convert_to_coskf(
rkf_path=self.results.rkfpath(file="adf"),
coskf_name=self.parent.coskf_name,
plams_dir=self.parent.path,
coskf_dir=self.parent.coskf_dir,
mol_info=self.parent.mol_info,
densf_path=densf_path,
)
self.children["solv"] = solv_job
sigma_s = Settings()
sigma_s.input.property._h = "PURESIGMAPROFILE"
compounds = [Settings()]
sigma_s.input.compound = compounds
crsjob = CRSJob(settings=sigma_s, name="sigma")
@add_to_instance(crsjob)
def prerun(self): # noqa F811
self.parent.children["solv"].results.wait()
self.settings.input.compound[0]._h = os.path.join(self.parent.path, self.parent.coskf_name)
self.children["crs"] = crsjob
@staticmethod
def get_compound_properties(
mol: Molecule, mol_info: Optional[Dict[str, Union[float, int, str]]] = None
) -> Tuple[Dict[str, Union[float, int, str]], bool]:
if mol_info is None:
mol_info = dict()
mol_info["Molar Mass"] = mol.get_mass()
mol_info["Formula"] = mol.get_formula()
try:
rings = mol.locate_rings()
flatten_atoms = [atom for subring in rings for atom in subring]
nring = len(set(flatten_atoms))
mol_info["Nring"] = int(nring)
except:
pass
atomic_ion = len(mol.atoms) == 1
return mol_info, atomic_ion
@staticmethod
def _get_radii() -> Dict[str, float]:
"""Method to get the atomic radii from solvent.txt (for some elements the radii are instead the Klamt radii)"""
with open(os.path.expandvars("$AMSHOME/data/gui/solvent.txt"), "r") as f:
mod_allinger_radii = [float(x) for i, x in enumerate(f) if i > 0]
radii = {PeriodicTable.get_symbol(i): r for i, r in enumerate(mod_allinger_radii, 1) if i <= 118}
klamt_radii = {
"H": 1.30,
"C": 2.00,
"N": 1.83,
"O": 1.72,
"F": 1.72,
"Si": 2.48,
"P": 2.13,
"S": 2.16,
"Cl": 2.05,
"Br": 2.16,
"I": 2.32,
}
radii.update(klamt_radii)
return radii
@staticmethod
def solvation_settings(elements: Optional[List[str]] = None, atomic_ion: bool = False) -> Settings:
sett = Settings()
radii = {
"H": 1.3,
"He": 1.275,
"Li": 2.125,
"Be": 1.858,
"B": 1.792,
"C": 2.0,
"N": 1.83,
"O": 1.72,
"F": 1.72,
"Ne": 1.333,
"Na": 2.25,
"Mg": 2.025,
"Al": 1.967,
"Si": 2.48,
"P": 2.13,
"S": 2.16,
"Cl": 2.05,
"Ar": 1.658,
"K": 2.575,
"Ca": 2.342,
"Sc": 2.175,
"Ti": 1.992,
"V": 1.908,
"Cr": 1.875,
"Mn": 1.867,
"Fe": 1.858,
"Co": 1.858,
"Ni": 1.85,
"Cu": 1.883,
"Zn": 1.908,
"Ga": 2.05,
"Ge": 2.033,
"As": 1.967,
"Se": 1.908,
"Br": 2.16,
"Kr": 1.792,
"Rb": 2.708,
"Sr": 2.5,
"Y": 2.258,
"Zr": 2.117,
"Nb": 2.025,
"Mo": 1.992,
"Tc": 1.967,
"Ru": 1.95,
"Rh": 1.95,
"Pd": 1.975,
"Ag": 2.025,
"Cd": 2.083,
"In": 2.2,
"Sn": 2.158,
"Sb": 2.1,
"Te": 2.033,
"I": 2.32,
"Xe": 1.9,
"Cs": 2.867,
"Ba": 2.558,
"La": 2.317,
"Ce": 2.283,
"Pr": 2.275,
"Nd": 2.275,
"Pm": 2.267,
"Sm": 2.258,
"Eu": 2.45,
"Gd": 2.258,
"Tb": 2.25,
"Dy": 2.242,
"Ho": 2.225,
"Er": 2.225,
"Tm": 2.225,
"Yb": 2.325,
"Lu": 2.208,
"Hf": 2.108,
"Ta": 2.025,
"W": 1.992,
"Re": 1.975,
"Os": 1.958,
"Ir": 1.967,
"Pt": 1.992,
"Au": 2.025,
"Hg": 2.108,
"Tl": 2.158,
"Pb": 2.283,
"Bi": 2.217,
"Po": 2.158,
"At": 2.092,
"Rn": 2.025,
"Fr": 3.033,
"Ra": 2.725,
"Ac": 2.567,
"Th": 2.283,
"Pa": 2.2,
"U": 2.1,
"Np": 2.1,
"Pu": 2.1,
"Am": 2.1,
"Cm": 2.1,
"Bk": 2.1,
"Cf": 2.1,
"Es": 2.1,
"Fm": 2.1,
"Md": 2.1,
"No": 2.1,
"Lr": 2.1,
"Rf": 2.1,
"Db": 2.1,
"Sg": 2.1,
"Bh": 2.1,
"Hs": 2.1,
"Mt": 2.1,
"Ds": 2.1,
"Rg": 2.1,
"Cn": 2.1,
"Nh": 2.1,
"Fl": 2.1,
"Mc": 2.1,
"Lv": 2.1,
"Ts": 2.1,
"Og": 2.1,
} # from _get_radii()
if elements:
radii = {k: radii[k] for k in sorted(elements)}
if atomic_ion:
charge_method = "method=atom corr"
else:
charge_method = "method=Conj corr"
sett.input.adf.solvation = {
"surf": "Delley",
"solv": "name=CRS cav0=0.0 cav1=0.0",
"charged": charge_method,
"c-mat": "Exact",
"scf": "Var All",
"radii": radii,
}
return sett
@staticmethod
def adf_settings(
solvation: bool, settings=None, elements: Optional[List[str]] = None, atomic_ion: bool = False
) -> Settings:
"""
Returns ADF settings with or without solvation
If solvation == True, then also include the solvation block.
"""
s = Settings()
if settings:
s = settings.copy()
if "basis" not in s.input.adf and "xc" not in s.input.adf:
s.input.adf.Basis.Type = "TZP"
s.input.adf.Basis.Core = "Small"
s.input.adf.XC.GGA = "BP86"
s.input.adf.Symmetry = "NOSYM"
s.input.adf.BeckeGrid.Quality = "Good"
if solvation:
s += ADFCOSMORSCompoundJob.solvation_settings(elements=elements, atomic_ion=atomic_ion)
return s
@staticmethod
def densf_settings(grid: Literal["Medium", "Fine"] = "Medium") -> Settings:
s = Settings()
s.input.GRID = f"{grid}\nEnd"
s.input.Density = "SCF"
s.input.Potential = "COUL SCF"
return s
@staticmethod
@requires_optional_package("scm.libbase")
def convert_to_coskf(
rkf_path: str,
coskf_name: str,
plams_dir: str,
coskf_dir: Optional[str] = None,
mol_info: Optional[Dict[str, Union[float, int, str]]] = None,
densf_path: Optional[str] = None,
) -> None:
"""
Convert an adf.rkf file into a .coskf file
Args:
rkf_path (str) : absolute path to adf.rkf
coskf_name (str) : the name of the .coskf file
plams_dir (str) : plamsjob path to write out the .coskf file
coskf_dir (Optional[str]) :additional path to store the .coskf file
mol_info (Optional[Dict[str, Union[float, int, str]]]) : Optional information to write out in the "Compound Data" section of the .coskf file
densf_path (Optional[str]) : path to the densf output .t41 file
"""
from scm.libbase import KFFile
with KFFile(rkf_path) as rkf:
cosmo = rkf.read_section("COSMO")
coskf_path = os.path.join(plams_dir, coskf_name)
with KFFile(coskf_path, autosave=False) as rkf:
for key, value in cosmo.items():
rkf.write("COSMO", key, float(value) if isinstance(value, np.float64) else value)
for key, value in mol_info.items():
rkf.write("Compound Data", key, float(value) if isinstance(value, np.float64) else value)
if densf_path is not None:
HBC_xyz, HBC_atom, HBC_angle, HBC_info = parse_mesp(densf_path, coskf_path)
write_HBC_to_COSKF(coskf_path, HBC_xyz, HBC_atom, HBC_angle, HBC_info)
if coskf_dir is not None:
shutil.copy2(coskf_path, os.path.join(coskf_dir, coskf_name))
@staticmethod
def update_hbc_to_coskf(coskf: str, visulization: bool = False) -> None:
"""
Determine the hydrogen bond center for existing COSKF file
Args:
coskf (str) : Existing COSKF file
visulization (bool) : Visulization of hydrogen bond center
"""
molecule = Molecule(coskf)
coskf_name = os.path.basename(coskf).replace(".coskf", "")
atomic_ion = len(molecule.atoms) == 1
gas_settings = ADFCOSMORSCompoundJob.adf_settings(solvation=False, atomic_ion=atomic_ion)
gas_settings.input.ams.Task = "SinglePoint"
gas_job = AMSJob(molecule=molecule, settings=gas_settings, name=f"gas_{coskf_name}")
gas_job.run()
gas_rkf = gas_job.results.rkfpath(file="adf")
densf_settings = ADFCOSMORSCompoundJob.densf_settings()
densf_job = DensfJob(gas_rkf, settings=densf_settings, name=f"densf_{coskf_name}")
densf_job.run()
t41 = densf_job.results.kfpath()
HBC_xyz, HBC_atom, HBC_angle, HBC_info = parse_mesp(t41, coskf)
write_HBC_to_COSKF(coskf, HBC_xyz, HBC_atom, HBC_angle, HBC_info)
if visulization:
view_HBC(coskf)
Brief API Documentation¶
- class ADFCOSMORSCompoundJob(molecule, coskf_name=None, coskf_dir=None, preoptimization=None, singlepoint=False, settings=None, mol_info=None, hbc_from_MESP=False, **kwargs)[source]¶
A class for performing the equivalent of Task: COSMO-RS Compound in the AMS GUI
- Parameters:
molecule – a PLAMS
Molecule
- Keyword Arguments:
coskf_name – A name for the generated .coskf file. If nothing is specified, the name of the job will be used.
coskf_dir – The directory in which to place the generated .coskf file. If nothing is specified, the file will be put in the plams directory corresponding to the job.
preoptimization – If None, do not preoptimize with a fast engine priori to the optimization with ADF. Otherwise, it can be one of ‘UFF’, ‘GAFF’, ‘GFNFF’, ‘GFN1-xTB’, ‘ANI-2x’, ‘M3GNet-UP-2022’. Note that you need valid licenses for ForceField or DFTB or MLPotential to use these preoptimizers.
singlepoint (bool) – Run a singlepoint in gasphase and with solvation to generate the .coskf file on the given Molecule. (no geometry optimization). Cannot be combined with
preoptimization
.settings (Settings) – A
Settings
object. settings.runscript.nproc, settings.input.adf.custom_options. If ‘adf’ is in settings.input it should be provided without the solvation block.mol_info (dict) – an optional dictionary containing information will be written to the Compound Data section within the COSKF file.
hbc_from_MESP (bool) – Defaults to False. Performs DENSF analysis to determine the hydrogen bond center (HBC) used in COSMOSAC-DHB-MESP.
name – an optional name for the calculation directory
Example
mol = from_smiles('O') job = ADFCOSMORSCompoundJob( molecule = mol, preoptimization = 'UFF', coskf_dir = 'coskfs', coskf_name = 'Water', name = 'H2O', mol_info = {'CAS':'7732-18-5'} ) job.run() print(job.results.coskfpath())
- static convert_to_coskf(rkf_path, coskf_name, plams_dir, coskf_dir=None, mol_info=None, densf_path=None)[source]¶
Convert an adf.rkf file into a .coskf file
- Parameters:
rkf_path (str) – absolute path to adf.rkf
coskf_name (str) – the name of the .coskf file
plams_dir (str) – plamsjob path to write out the .coskf file
coskf_dir (Optional[str]) – additional path to store the .coskf file
mol_info (Optional[Dict[str, Union[float, int, str]]]) – Optional information to write out in the “Compound Data” section of the .coskf file
densf_path (Optional[str]) – path to the densf output .t41 file