Designing polymers for use in next-generation bioelectronics

(Press-News.org) Engineered polymers hold promise for use in next generation technologies such as light-harvesting devices and implantable electronics that interact with the nervous system – but creating polymers with the right combination of chemical, physical and electronic properties poses a significant challenge. New research offers insights into how polymers can be engineered to fine-tune their electronic properties in order to meet the demands of such specific applications.

“Silicon-based electronics have been around for decades, and we have a thorough understanding of the electronic properties of materials used in those technologies,” says Aram Amassian, co-corresponding author of a journal article on the work and a professor of materials science and engineering at North Carolina State University. “But we are now trying to develop a new generation of electronics that makes use of polymers in things like bioelectronics – and we do not yet have a detailed understanding of how the way we process and engineer polymers influences their electronic properties. That limits our ability to fine-tune the electronic properties of polymers to meet the demands of specific applications.”

To make electronically useful polymer materials, you can create conjugated polymers that are able to carry a charge. But to control the amount of charge that can be carried by the polymer, you need to “dope” it – incorporating a second molecule into the polymer in order to modify the material’s electronic properties.

“However, it’s not as simple as adding more doping agents if you want to increase the amount of charge the polymer can handle,” Amassian says. “Electronic properties are affected by a range of variables and suffer when too much dopant is added. In fact, going into this study, we weren’t even entirely sure which variables were relevant and which weren’t. Using conventional experimental techniques, it would basically take forever to figure it all out.”

To that end, the researchers created a system that made use of artificial intelligence (AI)-based algorithms and high-throughput processing to maximize experimental efficiency in order to understand how a doped polymer’s processing, structure and electronic properties related to each other. The algorithms were developed by co-corresponding author Baskar Ganapathysupramanian, the Joseph C. and Elizabeth A. Anderlik Professor in Engineering at Iowa State University.

The “DopeBot” system was tasked with producing the widest possible range of conductivities using a polymer called pBTTT and a doping agent called F4TCNQ. DopeBot then ran 32 experiments in which the pBTTT was doped with the F4TCNQ. Parameters that could be varied included the solvent used in the doping process and the temperature of the doping process.

The results of those reactions were characterized manually, and that characterization data fed back into DopeBot – which used those findings to inform what the next 32 experiments should be. This was done four times and repeated three more times with different parameters, meaning DopeBot conducted 224 experiments.

These experiments provided a tremendous amount of information: data on the parameters of all 224 experiments; data on the molecular and physical structure of the doped polymer that resulted from each experiment; and data on the electronic, optical and structural properties of the doped polymers.

The researchers then used advanced analytic techniques to determine how the processing parameters, structure and electronic properties related to each other.

“But that analysis only gave us correlations,” Amassian says. “To move from correlation to causation, we took a deep dive into the science underlying what happened in these experiments.”

Amassian worked with co-author Raja Ghosh, assistant professor of chemistry at NC State, who used advanced quantum chemical calculations to reveal the link between where dopants are located in the polymer and the electronic properties.

“This work sheds light on the chemical and physical characteristics that play a key role in giving engineered polymers the electronic properties we’re looking for, which is crucial for informing the way we engineer polymers for these applications,” Amassian says.

“We are already building on this work to develop new materials for use in bioelectronic applications,” says Amassian. “That work is being done with collaborators from NC State, the University of Buffalo and the Karlsruhe Institute of Technology in Germany, with support from the National Science Foundation’s Designing Materials to Revolutionize and Engineer our Future program. Our goal there is to create organic bioelectronic materials that are ready for market adoption in healthcare and beyond, not solely to advance our understanding of the basic science involved.”

The paper, “AI-Guided High Throughput Investigation of Conjugated Polymer Doping Reveals Importance of Local Polymer Order and Dopant-Polymer Separation,” will be published Oct. 8 in the journal Matter. First author of the paper is Jacob Mauthe, a postdoctoral researcher at NC State. Second and third authors of the paper are Ankush Kumar Mishra and Abhradeep Sarkar, Ph.D. students at Iowa State University and NC State, respectively. Additional co-authors on the paper come from NC State, the University of North Carolina at Chapel Hill and the University of Washington.

This research was done with support from the Office of Naval Research under grant N00014-23-1-2001 and the National Science Foundation under grant 2323716.

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