Organic semiconducting polymers have demonstrated potential in the production of large-area, low-cost, flexible electronic devices. Recently discovered push−pull copolymers (donor−acceptor (D−A) polymers), with a polymer backbone consisting of alternating electron-deficient (acceptor) and electron-rich (donor) units, have exhibited significant improvement in electronic performance compared to semicrystalline homopolymers. The high mobility observed in D−A polymers has been attributed to the rigid, planar backbone conformation with minimal steric hindrance between the donor and acceptor units. However, the vast and complex device processing space combined with a lack of standardized reporting makes reproducibility within the field difficult and impedes the development of these materials. Curating and analyzing centralized datasets is a promising approach to resolve the issue of reproducibility, gain new insights, and guide future experiments. Here, a data set was constructed containing processing and performance information of 115 published organic field effect transistor devices, fabricated using the commercially available D-A polymer, DPP-DTT. A customized classification algorithm was applied to the data set, which identified polymer solution concentration as a key factor in device performance and recommended a reduced design range for this variable that would lead to improved hole mobility. Experiments performed to confirm the insights from the data curation exercise revealed a strong influence of solution concentration on the polymer chain excitonic interactions and electronic performance. As recommended by the classification algorithm, devices were fabricated at the critical polymer chain overlap concentration of 5 g/L in chlorobenzene, which resulted in improved hole mobility. It is hypothesized that the polymer chain overlap in the solution state contributes to improved charge transport in the solid state. The results highlight the advantage of integrating materials informatics approaches into the existing polymer electronics methodologies.

Data science guided experiments identify conjugated polymer solution concentration as a key parameter in device performance

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.