In this line of research we study molecular materials with potential for optoelectronic applications such as sensing, light-emitting diodes or photovoltaics. First-principles electronic structure analysis of the excited states of interest is performed with TDDFT or wave-function based methods depending on the problem. To gain insights into the dynamics of the process, real time non-adiabatic excited state dynamics are performed with either nuclear wave packed approaches using model Hamiltonians or by means of trajectory surface hopping dynamics. Knowledge about the states and dynamics involved in the process of interest allows to understand the mechanism and eventually find novel materials with improved properties. To this aim, traditional structure-property correlations and ultimately, Machine Learning algorithms, serve as major tools to guide the design of novel structures that fulfill target characteristics for a particular application.
