(337am) Data-Enabled Experimental Development of Polymer-Based Organic Electronics

Data science approaches have resulted in significant advancements in the field of “big data analytics” for the accelerated development of many material systems. However, several challenges exist in applying widespread, data-driven approaches to facilitate the accelerated development of semiconducting devices formulated from polymeric materials. Conjugated polymer materials have demonstrated unprecedented performance for flexible, stretchable, and deformable device applications, though their discovery remains largely trial-and-error. A foremost challenge is the availability of experimental data that can yield the requisite knowledge necessary to inform robust performance and formulation precision at the manufacturing scale. The reliability of available experimental data to this end, such as in literature, is hindered by the need to interrogate several relevant process parameters and structural features in both solution and in thin film. This presentation details progress on the implementation of informatics methodologies for the development of polymer-based organic semiconductor technologies. The integration of high throughput experimentation laboratory techniques offers an avenue to traverse the small data gap afforded by the organic semiconductor parameter space. Robust data management systems provide a foundation for schema design and solutions for the challenges in small, sparse, materials data. Finally, the incorporation of “small data analytics” approaches on literature datasets provides a foundation for informing sequential experiments from which π-conjugated polymer domain knowledge can be extracted.