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zmfhtm2045

Member

Registered: 2023-04-17

Posts: 5

UV/Vis absorption simulation of diradicals

Hello, I am studying for the organometallic cobalt complex having diradical characteristics (experimentally observed).

The thing I want to do is simulation of UV-Vis absorption spectra simulation about singlet diradical organometallic compound.

Could I simulate that by using Orca and Multiwfn?

If possible, how can I set the keyword for the Orca? I tried spin-flip TDDFT calculation for the compounds but, it fails with a error message (Error: CSI/TDDFT) ... aborted.)

Here, my last trial of input files.

!B3LYP DEF2-SVP CPCM(acetonitrile) PAL8
%maxcore 8000
%TDDFT
SF TRUE
NROOTS 30
END
* xyz 3 1 Co.xyz *

sobereva

Tian Lu (Multiwfn developer)

From: Beijing

Registered: 2017-09-11

Posts: 1,830

Website

Re: UV/Vis absorption simulation of diradicals

The provided information is not enough to figure out the reason. BTW, using NEVPT2 would be more reliable. There is a CASSCF tutorial of ORCA on its website, you can consult it, which described in detail how to perform CASSCF and multireference calculations on transition metal complexes.

jxzou

Member

Registered: 2023-09-11

Posts: 7

Re: UV/Vis absorption simulation of diradicals

Hi, my suggestion is to use the MRSF-TDDFT method in the free software package GAMESS. The SF-TDDFT method in ORCA/GAMESS suffers from the spin-contamination problem during practical calculations, while MRSF-TDDFT is almost exact spin-pure (whose spin-contamination can hardly be seen). It is very easy to perform an MRSF-TDDFT calculation. Here is an example:

Step 1. perform an ROKS (i.e. RODFT) calculation
Open-shell ROKS calculations are usually not easy. It is recommended to use PySCF/Gaussian to perform this calculation. The PySCF input file is show below

from pyscf import gto, dft, lib
from mokit.lib.py2fch_direct import fchk

lib.num_threads(64)
mol = gto.M()
mol.atom = '''
C   -0.12264859        0.00599759       -0.75931820
C   -0.13393227        0.05086047        0.75572332
O    1.29017598        0.03740604       -0.91156021
O    1.12879647       -0.57344495        0.94545004
H   -0.54539878       -0.92543383       -1.16182063
H   -0.91791476       -0.55372886        1.23567184
H   -0.13429527        1.07605238        1.15229831
H   -0.56478278        0.88229116       -1.25644448
'''

mol.basis = 'aug-cc-pVDZ'
mol.charge = 0
mol.spin = 2
mol.verbose = 4
mol.build(parse_arg=False)

mf = dft.ROKS(mol)
mf.xc = 'bhandhlyp'
mf.grids.atom_grid = (99,590)
mf.max_cycle = 128
mf.max_memory = 128000 #MB
old_e = mf.kernel()

mo = mf.stability()[0]
dm = mf.make_rdm1(mo, mf.mo_occ)
mf.kernel(dm0=dm)

mf.stability()
fchk(mf, 'high_spin.fch', density=True)

Submit the PySCF job

python test.py >test.out 2>&1

Here fchk() is a module in the open-source package MOKIT. To run this example, you need to install PySCF and MOKIT (which can both be installed via `conda install`).

Step 2. transfer molecular orbitals (MO) and generate input files
After the PySCF job is accomplished, one obtains the wave function file high_spin.fch. Now run the following command

fch2inp high_spin.fch -mrsf

One obtains the file high_spin.inp, which contains MRSF-TDDFT keywords, Cartesian coordinates, basis set data and converged ROKS MOs.

Step 3. perform the MRSF-TDDFT calculation
Run the following command

/path_to_gamsss/rungms high_spin.inp 00 48 >high_spin.gms 2>&1

Here 48 CPU cores are used for parallel computations.