We
present a multilayer implementation of the EOM-CCSD for the
computation of ionization potentials of atoms and molecules in the
presence of their environment. The method uses local orbitals to partition
the system into a number of hypothetical fragments and treat different
fragments of the system at different levels of theory. This approach
significantly reduces the computational cost with a systematically
controllable accuracy and is equally applicable to describe the environmental
effect of both bonded and nonbonded nature. An accurate description
of the interfragment interaction has been found to be crucial in determining
the accuracy of the calculated IP values.
We have presented a multi-layer implementation of the equation of motion coupled-cluster method for the electron affinity, based on local and pair natural orbitals. The method gives consistent accuracy for both localized and delocalized anionic states. It results in many fold speedup in computational timing as compared to the canonical and DLPNO based implementation of the EA-EOM-CCSD method. We have also developed an explicit fragment-based approach which can lead to even higher speed-up with little loss in accuracy. The multi-layer method can be used to treat the environmental effect of both bonded and non-bonded nature on the electron attachment process in large molecules.
We investigate the negatively charged
nitrogen-vacancy
center in
diamond using periodic density matrix embedding theory (pDMET). To
describe the strongly correlated excited states of this system, the
complete active space self-consistent field (CASSCF) followed by n-electron
valence state second-order perturbation theory (NEVPT2) was used as
the impurity solver. Since the NEVPT2-DMET energies show a linear
dependence on the inverse of the size of the embedding subspace, we
performed an extrapolation of the excitation energies to the nonembedding
limit using a linear regression. The extrapolated NEVPT2-DMET first
triplet–triplet excitation energy is 2.31 eV and that for the
optically inactive singlet–singlet transition is 1.02 eV, both
in agreement with the experimentally observed vertical excitation
energies of ∼2.18 eV and ∼1.26 eV, respectively. This
is the first application of pDMET to a charged periodic system and
the first investigation of the NV– defect using
NEVPT2 for periodic supercell models.
In the present work, we investigate the effect of aqueous environment on the vertical ionization potential (VIP) of adenine-thymine (AT) base pair using a multilayer equation of the motion-coupled cluster method. The microsolvation can cause both blue-shift and red-shit of the IP values. However, the bulk water environment always results in the red-shift of the vertical ionization potential. Our study shows that the correct treatment of the short-range interaction plays an essential role in determining the magnitude of the red-shift. We have developed a biased sampling scheme based on Koopmans' energy, which can significantly speed up the convergence with respect to the number of solvent-solute configurations.
We investigate the negatively charged nitrogen-vacancy center in diamond using periodic density matrix embedding theory (pDMET). To describe the strongly correlated excited states of this system, the complete active space self-consistent field (CASSCF) followed by n-electron valence state second-order perturbation theory (NEVPT2) was used as impurity solver. Since the NEVPT2-DMET energies show a linear dependence on the inverse of the size of the embedding subspace, we performed an extrapolation of the excitation energies to the non-embedding limit using linear regression. The extrapolated NEVPT2-DMET first triplet-triplet excitation energy is 2.31 eV and that for the optically inactive singlet-singlet transition is 1.02 eV, both in agreement with the experimentally observed vertical excitation energies of ~2.18 eV and ~1.26 eV, respectively. This is the first application of pDMET to a charged periodic system and the first investigation of the NV- defect using NEVPT2 for periodic supercell models.
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