Bulk-heterojunction organic photovoltaic (OPV) devices consist of active layers made of electron donor/acceptor blends. Understanding the impact of the blend morphologies on the optoelectronic processes occurring in OPVs is of crucial importance for a complete description of the device physics and the achievement of higher device efficiencies. However, high-resolution morphology data are scarce and theoretical methodologies with the appropriate level of details and affordable computational costs are underdeveloped. As a result, previous device modeling often had to rely on artificially generated blend morphologies, which do not represent those in actual devices. Here, by considering three-dimensional donor/acceptor blend morphologies recently determined via electron tomography, we have established an original approach that allows us to perform device-scale simulations of charge transport in actual blend morphologies. The current characteristics, carrier distributions, and internal current pathways and densities are determined and compared to those based on the artificial morphologies often used in OPV-related studies.

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.

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.