Facilitating an Integrated Data-Centric Approach to Optimize Donor-Acceptor Copolymer Based Organic Field Effect Transistors

The ever-growing demands of consumers in a rapidly expanding global population underscore the need for innovative materials to develop efficient and affordable electronic devices. One such area grappling with this surge in demand is the realm of conjugated polymer (CP)--based electronic materials. These semiconducting polymers have emerged as promising substitutes for traditional silicon, paving the way for flexible, lightweight, and cost-effective electronic devices such as organic field-effect transistors (OFETs), light-emitting diodes, and solar cells. Unlike silicon, CPs can be processed as solutions, rendering them more suitable for developing electronic devices with room for optimization. Unfortunately, progress in organic electronics is hindered by the vast and intricate processing landscape of these polymers, which has been demonstrated to directly impact performance. Moreover, traditional research methodologies have relied heavily on trial-and-error approaches, which not only slow down progress but also hinder the acquisition of insights and impede advancements toward real-world applications. Recent advancements in high-throughput experimentation (HTE) and materials informatics present solutions to these challenges. Thus, this thesis aims to integrate existing knowledge of polymer design and processing with HTE and polymer informatics methods to accelerate the development of OFETs derived from donor-acceptor (D-A) copolymers. The chapters of this dissertation exemplify the benefits of integrating data-centric approaches into the established polymer electronics framework to streamline the advancement of these materials. Throughout this thesis, a consistent focus lies on carefully evaluating processing conditions to optimize the performance of CP-based OFETs. Initially, employing data science algorithms on meticulously curated process-property datasets unveils the key processing variables influencing device performance, with algorithm-derived insights guiding future experiments. Subsequently, these informatics insights are validated through relevant experiments investigating the manipulation of CP solution states. These experiments aim to elucidate how variations in solution state parameters, such as concentration, impact the morphology of the final film and the functionality of the device. Lastly, this study delves into the burgeoning domain of polymer semiconductor-insulator blends (PSIBs), highlighting the potential of HTE through the fabrication and characterization of gradient thin films. This approach complements traditional discrete experiments, facilitating rapid screening of processing spaces for these blend systems, especially concerning blend composition. Moreover, it also provides a pathway to more efficient and comprehensive insights, uncovering trends occurring within narrow windows that might otherwise go unnoticed. In essence, this thesis underscores the integration of HTE and materials informatics into the existing polymer electronics paradigm to expedite the discovery and development of D-A polymer-based-OFETs.

Level thesis:degree_level

Doctoral

Department dc:contributor.department

Chemical and Biomolecular Engineering

Grantor dc:publisher

Georgia Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Venkatesh, Rahul

Advisors dc:contributor.advisor

• Grover, Martha A.
• Meredith, J. Carson
• Reichmanis, Elsa

Committee members dc:contributor.committeemember

• Silva, Carlos
• Risko, Chad
• Medford, Andrew

• Conjugated Polymers
• Materials Informatics
• OFETs
• Data Science
• Processing
• High-throughput Experimentation

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/1853/75242

OAI identifier oai:identifier

oai:repository.gatech.edu:1853/75242