Electronic Excitations in Complex Molecular Environments: Many-Body Green's Functions Theory in VOTCA-XTP
arXiv:1811.03645 · doi:10.1021/acs.jctc.8b00617
Abstract
Many-body Green's functions theory within the GW approximation and the Bethe-Salpeter Equation (BSE) is implemented in the open-source VOTCA-XTP software, aiming at the calculation of electronically excited states in complex molecular environments. Based on Gaussian-type atomic orbitals and making use of resolution of identify techniques, the code is designed specifically for non-periodic systems. Application to the small molecule reference set successfully validates the methodology and its implementation for a variety of excitation types covering an energy range from 2-8 eV in single molecules. Further, embedding each GW-BSE calculation into an atomistically resolved surrounding, typically obtained from Molecular Dynamics, accounts for effects originating from local fields and polarization. Using aqueous DNA as a prototypical system, different levels of electrostatic coupling between the regions in this GW-BSE/MM setup are demonstrated. Particular attention is paid to charge-transfer (CT) excitations in adenine base pairs. It is found that their energy is extremely sensitive to the specific environment and to polarization effects. The calculated redshift of the CT excitation energy compared to a nucelobase dimer treated in vacuum is of the order of 1 eV, which matches expectations from experimental data. Predicted lowest CT energies are below that of a single nucleobase excitation, indicating the possibility of an initial (fast) decay of such an UV excited state into a bi-nucleobase CT exciton. The results show that VOTCA-XTP's GW-BSE/MM is a powerful tool to study a wide range of types of electronic excitations in complex molecular environments.
References in corpus (11)
- Canonical sampling through velocity-rescaling
- Libxc: a library of exchange and correlation functionals for density functional theory
- First-principles GW calculations for fullerenes, porphyrins, phtalocyanine, and other molecules of interest for organic photovoltaic applications
- A Benchmark of GW Methods for Azabenzenes: Is the GW Approximation Good Enough?
- Quasi-Particle Self-Consistent for Molecules
- An assessment of the low-lying excitation energies and triplet instabilities of organic molecules with an ab initio Bethe-Salpeter equation approach
- Structural relaxations in electronically excited poly(para-phenylene)
- Correlated electron-hole mechanism for molecular doping in organic semiconductors
- Numerical integration for ab initio many-electron self energy calculations within the GW approximation
- A systematic benchmark of the ab initio Bethe-Salpeter equation approach for low-lying optical excitations of small organic molecules
- Solvent effects on optical excitations of poly para phenylene ethynylene studied by QM/MM simulations based on Many-Body Green's Functions Theory
Cited by in corpus (12)
- NWChem: Past, Present, and Future
- Cubic-scaling all-electron GW calculations with a separable density-fitting space-time approach
- Improved general-purpose five-point model for water: TIP5P/2018
- Quantitative Predictions of Photoelectron Spectra in Amorphous Molecular Solids from Multiscale Quasiparticle Embedding
- Assessment of the Ab Initio Bethe-Salpeter Equation Approach for the Low-Lying Excitation Energies of Bacteriochlorophylls and Chlorophylls
- LayerPCM: An implicit scheme for dielectric screening from layered substrates
- Universal polarization energies for defects in monolayer, surface and bulk hexagonal boron nitride : A finite-size fragments GW approach
- Many-body calculations with very large scale polarizable environments made affordable: a fully ab initio QM/QM approach
- Code modernization strategies for short-range non-bonded molecular dynamics simulations
- Polarizable Continuum Models and Green's Function Formalism: On the Dynamics of the Solvent Electrons
- Memory efficient Fock-space recursion scheme for computing many-fermion resolvents
- A Kernel-based Machine Learning Approach to Computing Quasiparticle Energies within Many-Body Green's Functions Theory