Influence of non-adiabatic effects on linear absorption spectra in the condensed phase: Methylene blue

TL;DR

This paper presents a first-principles approach combining vibronic coupling and non-adiabatic effects to accurately model the linear absorption spectra of solvated chromophores, demonstrated on methylene blue in water.

Contribution

The authors develop a robust method that parameterizes a vibronic Hamiltonian from molecular dynamics data, incorporating environmental and non-adiabatic effects for spectral modeling.

Findings

The model accurately reproduces the experimental spectrum of methylene blue.

Vibrationally driven population transfer explains the spectral shoulder.

Explicit quantum solvation is crucial for precise spectral lineshape prediction.

Abstract

Modeling linear absorption spectra of solvated chromophores is highly challenging as contributions are present both from coupling of the electronic states to nuclear vibrations and solute-solvent interactions. In systems where excited states intersect in the Condon region, significant non-adiabatic contributions to absorption lineshapes can also be observed. Here, we introduce a robust approach to model linear absorption spectra accounting for both environmental and non-adiabatic effects from first principles. This model parameterizes a linear vibronic coupling (LVC) Hamiltonian directly from energy gap fluctuations calculated along molecular dynamics (MD) trajectories of the chromophore in solution, accounting for both anharmonicity in the potential and direct solute-solvent interactions. The resulting system dynamics described by the LVC Hamiltonian are solved exactly using the thermalized time-evolving density operator with orthogonal polynomials algorithm (T-TEDOPA). The approach is applied to the linear absorption spectrum of methylene blue (MB) in water. We show that the strong shoulder in the experimental spectrum is caused by vibrationally driven population transfer between the bright S1 and the dark S2 state. The treatment of the solvent environment is one of many factors which strongly influences the population transfer and lineshape; accurate modeling can only be achieved through the use of explicit quantum mechanical solvation. The efficiency of T-TEDOPA, combined with LVC Hamiltonian parameterizations from MD, leads to an attractive method for describing a large variety of systems in complex environments from first principles.