CAREER: Molecular Design Rules Governing Chirality Transfer in Conjugated Polymers

About This Grant

Non-Technical Summary: This project will develop a new class of flexible, lightweight materials that can actively change how they interact with light and electronic signals. Many modern devices, from medical sensors to communication systems, use materials whose properties are fixed once they are manufactured. This research aims to overcome that limitation by creating materials that can be electrically “reprogrammed” in real time. The approach combines well-established plastics that conduct electricity with small, “handed” molecules that twist light in unique ways. When mixed together, these components can produce materials that respond to electrical signals by altering how they absorb and emit light or how they control the flow of electronic information. The new materials developed in this work have the potential to support future quantum technologies by enabling low-power devices that control light and electron spin, key ingredients for quantum communication and information processing. To accelerate discovery, the project will employ robotic laboratory systems guided by machine learning and artificial intelligence (AI), allowing the research team to rapidly test and analyze thousands of material combinations. This “self-driving lab” approach dramatically speeds up scientific progress while training students in automation, programming, and artificial intelligence. Educational activities will include hands-on spectrometer-building kits distributed to schools and universities, broadening access to scientific tools. By advancing scientific knowledge, developing future researchers, and enabling new technological opportunities in AI and quantum science, this project promotes the progress of science and contributes to national prosperity and welfare. Technical Summary: This research will establish molecular-level design rules for chirality transfer in conjugated polymer systems by integrating automated thin-film fabrication, Bayesian optimization, and multiscale structural and chiroptical characterization. The project investigates how noncovalent interactions between achiral conjugated polymers and chiral small molecules generate circular dichroism, circularly polarized luminescence, and spin-selective transport. Aim 1 employs high-throughput robotic platforms coupled with AI and machine learning to map processing–structure–chirality relationships across polymer–additive libraries, identifying key chemical and processing parameters that maximize chiroptical responses for quantum science applications. Aim 2 combines X-ray scattering, nanoscale imaging, and chiroptical spectroscopy to elucidate the supramolecular mechanisms that govern chirality transfer and determine the roles of molecular packing, phase behavior, and local interactions. Aim 3 explores chemical and electrochemical doping as a reversible external stimulus to modulate chiroptical properties and induce chiral polaron formation, including in situ circular dichroism spectroelectrochemistry to track doping-dependent optical signatures. Together, these efforts will produce a mechanistic framework linking additive chemistry, polymer structure, and external stimuli to dynamically tunable chiroptical functionality in conjugated polymers, informing the design of reconfigurable materials for photonic, spintronic and quantum applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.