Recent advances in the efficiency of organic photovoltaics (OPVs) have been driven by judicious selection of processing conditions that result in a 'desired' morphology. An important theme of morphology research is the need to quantify the effect of processing conditions on nanoscale morphology and to relate this information to device efficiency in a closed loop. However, accurate and comprehensive morphology quantification still remains a pressing challenge. State-of-the-art quantification methods like XRD, GIWAXS, GISAXS and TEM provide film averaged or 2D projected features that only indirectly correlate with performance, thus making causal reasoning nontrivial. Accessing the 3D distribution of material however provides a natural means of directly mapping processing conditions to device performance. In this paper, we integrate two recently developed techniquesreconstruction of 3D spatial maps of morphology (HAADF-STEM and DART) and conversion of the resulting 3D maps into intuitive morphology descriptors (GraSPI)to comprehensively image and quantify 3D morphology under various processing conditions. We apply these techniques on films generated by two of the most common fabrication techniques, doctor blading and spin coating, additionally investigating the impact of thermal annealing on these samples. We find that the morphology of all samples exhibit very high connectivity to the electrodes. Not surprisingly, thermal annealing consistently increases the average domain size of polymer/fullerene rich phases in the samples, aiding improved exciton generation. Furthermore, annealing also improves the balance of interfaces, aiding enhanced exciton dissociation. The spinannealed sample was observed to have a very balanced distribution of charge transport paths to both electrodes, aiding enhanced charge transport and collection. A comparison of morphology descriptors impacting each stage of the photo physics (exciton generation, exciton dissociation, charge transport) reveals that the spin-annealed sample exhibits superior morphology-based performance indicators. This suggests that there is substantial room for improvement of blade based methods in terms of process optimization for morphology tuning to achieve enhanced performance of large area devices.

High efficiency polymer:fullerene photovoltaic device layers self-assemble with hierarchical features from ångströms to 100’s of nanometers. The feature size, shape, composition, orientation, and order all contribute to device efficiency and are simultaneously difficult to study due to poor contrast between carbon based materials. This study seeks to increase device efficiency and simplify morphology measurements by replacing the typical fullerene acceptor with endohedral fullerene Lu3N@PC80BEH. The metal atoms give excellent scattering contrast for electron beam and x-ray experiments. Additionally, Lu3N@PC80BEH has a lower electron affinity than standard fullerenes, which can raise the open circuit voltage of photovoltaic devices. Electron microscopy techniques are used to produce a detailed account of morphology evolution in mixtures of Lu3N@PC80BEH with the record breaking donor polymer, PTB7 and coated using solvent mixtures. We demonstrate that common solvent additives like 1,8-diiodooctane or chloronapthalene do not improve the morphology of endohedral fullerene devices as expected. The poor device performance is attributed to the lack of mutual miscibility between this particular polymer:fullerene combination and to co-crystallization of Lu3N@PC80BEH with 1,8-diiodooctane. This negative result explains why solvent additives mixtures are not necessarily a morphology cure-all.

Simulation of the microscopic processes in the active layers of organic photovoltaic devices directly from experimental film morphologies.