Technical Description: Solution-processed oligomer-based organic photovoltaic materials are promising candidates for next-generation solar cells due to their low-cost potential, ease of fabrication, and tunable characteristics. The relationship between molecular structure and materials morphology critically affects performance characteristics such as charge mobility. This collaborative project, sponsored by the Designing Materials to Revolutionize and Engineer Our Future (DMREF) program, explores the structure-morphology relationship, and then uses knowledge gained to employ a screening and iterative design approach. The project unites computational, synthetic, and device construction and characterization research labs at UCLA to accelerate development of these materials. A tiered computational approach for multiscale morphology modeling of oligomeric donor material is being developed, using a combination of rapid sampling and accurate ranking techniques using integrated electronic structure calculations, crystal structure prediction, molecular dynamics (MD) simulations, and charge transport calculations. Crystal structure prediction methods sample possible packing arrangements and provide initial geometries for MD simulations of each arrangement, upon which high-accuracy accelerated MD with a polarizable force field can be employed to simulate local chemical properties and disorder. As part of this approach, known first-principles and charge transport analysis methods predict donor morphology-influenced properties such as hole mobility and bulk electronic structure. From combinations of large libraries of donor and acceptor subunits, screened oligomers with promising electronic structures and morphologies are synthesized via site-selective cross-coupling reactions. Microscopy and x-ray diffraction methods are used to analyze morphologies, including morphology changes due to annealing, and to compare to theoretical predictions. Photoluminescence quenching, transient absorption spectroscopy, and charge extraction by linearly increasing voltage are used to assess device performance. This tightly knit collaborative effort enables feedback from experimental results to be used for iterative systematic tuning of candidate molecules and improvements of computational methods.
Non-technical Description: The need for clean and affordable energy demands the development and improvement of alternative energy sources. The sun supplies the Earth with 9000 times the world's current energy consumption, making solar power an attractive option. Oligomer (small molecule)-based organic solar cells are low cost relative to the current solar technology and have experienced significant increases in power efficiency in recent years. But major improvements are needed to enhance its commercialization potential. In a collaborative project, computational, synthetic, and device characterization research labs at UCLA are developing new methods and models to improve prediction of materials morphology - the way in which many molecules fit together - in these devices. The goal is to predict the performance of oligomer-based organic solar cell performance and to accelerate the discovery of new materials. From vast libraries of candidate molecules, the performance of new high-performance devices is screened computationally to predict promising molecules to be used to create and test devices and then improve performance of these devices. This project involves graduate students in diverse research teams to learn and develop interdisciplinary skills. Students involved gain experience in each aspect of the project. Encouragement of the next generation of scientists to engage in STEM careers is being fostered through mentorship of undergraduate students and through K-12 outreach.
