Executive Summary : | Organic semiconductors are carbon-based optoelectronic materials that are utilized in a broad spectrum of optoelectronic and photovoltaic applications, stretching from organic light-emitting diodes to perovskite solar cells. However, the discovery of novel organic electronic materials with targeted properties is often hindered by the complex relationship between the structure and the relevant properties. Until the present time, the mainstream of organic electronic research usually involves experimental techniques for the design and discovery of novel materials, with theoretical calculations contributing only post-facto rationalization of the observed device performance. Such a traditional route of synthesizing and characterizing a vast set of organic compounds in the hope of unveiling promising molecules is both cumbersome and challenging. On the contrary, predictive and reliable computational chemistry techniques combined with rational design approaches have the capability of guiding materials discovery as a means of distinguishing the promising synthetic targets and thus, minimizing experimental effort consumed on organic systems with poor performance. Our main goal in this project is to utilize high-throughput computing to accelerate the materials discovery process by selecting promising structural moieties based on a minimum threshold for important parameters before investing time in the laboratory to synthesize and characterize them. The initial targets in our approach will be to explore the chemical space of non-fullerene acceptors (NFAs) for organic solar cells and TADF-based emitters and host materials for organic light-emitting diodes. |