Recent advances in efficiency of organic photovoltaics are driven by judicious selection of processing conditions that result in a “desired” morphology. An important theme of morphology research is quantifying the effect of processing conditions on morphology and relating it to device efficiency. State-of-the-art morphology quantification methods provide film-averaged or 2D-projected features that only indirectly correlate with performance, making causal reasoning nontrivial. Accessing the 3D distribution of material, however, provides a means of directly mapping processing to performance. In this paper, two recently developed techniques are integrated—reconstruction of 3D morphology and subsequent conversion into intuitive morphology descriptors —to comprehensively image and quantify morphology. These techniques are applied on films generated by doctor blading and spin coating, additionally investigating the effect of thermal annealing. It is found that morphology of all samples exhibits very high connectivity to electrodes. Not surprisingly, thermal annealing consistently increases the average domain size in the samples, aiding exciton generation. Furthermore, annealing also improves the balance of interfaces, enhancing exciton dissociation. A comparison of morphology descriptors impacting each stage of photophysics (exciton generation, dissociation, and charge transport) reveals that spin-annealed sample exhibits superior morphology-based performance indicators. This suggests substantial room for improvement of blade-based methods (process optimization) for morphology tuning to enhance performance of large area devices.
- blade spin as-cast anneal
- internal morphology analysis
- organic photovoltaic cells
- tortuosity connectivity fraction
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Materials Science(all)