Abstract:

Organic semiconductors (OSCs) have emerged as a compelling substitute for traditional inorganic counterparts, offering a pathway to cost-effective, scalable fabrication and relatively straightforward processing methodologies. An important element is the electronic architecture of organic semiconductors, which is critical for the optimal operation of thin-film constructs. A key objective involves the accurate ascertainment of frontier molecular orbital energies in organic semiconductor compounds.

This thesis focusses into the energetics underlying organic semiconductors and their consequential effects on the performance of organic-based devices. Through those projects, several aspects of the methods to measure energy level of OSCs and the consequences on the devices properties was studied. The study of different methods to measure the energy levels showed the discrepancies of the widely used cyclic voltammetry (CV) compared to photoelectron spectroscopy (PES) which showed stronger correlation with device properties. Solution to overcome the limited access of PES value was proposed using machine learning by the development of a chained model to predict PES values from the molecular structure of OSCs. More focused studies on the energy level of blend in organic photovoltaics, on solvents and interlayers were conducted to further understand the different aspect and mechanisms of organic devices thought the energetics.