Theory and experiments are both valuable sources of knowledge for materials design, and in the proposed research, new statistical methods will be created to optimally integrate all sources of information, including experimental data, simulations, and expert opinion. This project will develop procedures to integrate knowledge learned from engineering principles (including chemical kinetics, mass transfer, etc.), relevant experiments in publications, and expert experience to develop an “initial model” of the salient features of π-conjugated polymer material microstructures. Then, this model will guide the design of a “first-pass” experimental dataset. Although the model will not be perfect at this stage, it can still play a valuable role in directing the experiments into promising regions. The collected data will not only validate the initial model, but also stimulate further review of engineering knowledge in resolving mismatches seen between data and initial model outcomes. The initial model will then be updated and the nextpass experiment with a more narrowly focused design space will be planned. The project will design a sequence of physical experiments, mismatch resolutions and model updating to improve the material informatics that will accelerate the design of new π-conjugated polymer materials.
Although the statistical methods to be developed are generally applicable, context will be provided by π-conjugated polymer materials applicable to flexible electronics, photovoltaics and sensors. To exploit the unique capabilities of organic electronics in flexible devices and economical roll-to-roll high throughput printing, high charge carrier mobility is a prerequisite. However, mobility is highly dependent on the final morphology of the thin semiconducting film that serves as the device active layer. Organic semiconductors exhibit domains of crystallinelike order interspersed with amorphous regions, and the size and extent of order within each type of domain influences the molecular packing and subsequent electronic behavior. The morphology in all regions evolves as the film is deposited and processed. Understanding of the impact of chemistry and processing on the active layer morphology is very limited and is dominated by tedious, observational approaches. A coherent understanding of how π-conjugated semiconductor chains interact, associate and align to form the interconnected nanocrystallite structures that are essential for charge carrier transport is lacking, and there are far too many design variables to effectively explore this vast design space using a purely empirical approach. Thus, the results of this research will enable the design and optimization of robust materials chemistries and the required, associated large-area, large-scale device fabrication process recipes.
Students should have a strong calculus background, as well as basic skills in statistics or data mining.