Nonlinear-response properties in a simplified time-dependent density functional theory (sTD-DFT) framework: Evaluation of excited-state absorption spectra.
Marc de WergifosseStefan GrimmePublished in: The Journal of chemical physics (2019)
The energy conversion efficiency of organic solar cells seems crucial for a clean future. The design of new light-harvesting devices needs an in-depth understanding of their optical properties, including the excited-state absorption (ESA). In biology, the optical characterization of photochemical/physical processes happening in photosynthetic pigments and proteins can be difficult to interpret due to their structural complexities. Experimentally, an ultrafast transient absorption experiment can probe the excited state interaction with light. Quantum chemistry could play an important role to model the transient absorption spectrum of excited states. However, systems that need to be investigated can be way too large for existent software implementations. In this contribution, we present the first sTDA/sTD-DFT (simplified time-dependent density functional theory with and without Tamm Dancoff approximation) implementation to evaluate the ESA of molecules. The ultrafast ESA evaluation presents a negligible extra cost with respect to sTDA/sTD-DFT original schemes for standard ground state absorption. The sTD-DFT method shows ability to assign ESA spectra to the correct excited state. We showed that in the literature, wrong assignments were proposed as for the L34/L44 mixture and N-methylfulleropyrrolidine. In addition, sTDA/sTD-DFT-xTB tight-binding variants are also available, allowing the evaluation of ESA for systems of a few thousands of atoms, e.g., the spectrum of the photoactive yellow protein composed of 1931 atoms.
Keyphrases
- density functional theory
- molecular dynamics
- energy transfer
- solar cells
- healthcare
- physical activity
- blood brain barrier
- primary care
- mental health
- gene expression
- cerebral ischemia
- binding protein
- transcription factor
- quality improvement
- dna methylation
- high speed
- data analysis
- genome wide
- atomic force microscopy
- clinical evaluation