Plastic that conducts electricity may seem unlikely, but a special class of materials known as "electronic polymers" merges the flexibility of plastic with the functionality of metal. These materials hold potential for breakthroughs in wearable devices, printable electronics, and advanced energy storage systems.
The creation of thin films from electronic polymers has been challenging due to the need for precise balance in physical and electronic properties. Researchers at Argonne National Laboratory and the University of Chicago have addressed this issue using artificial intelligence. They employed an AI-driven automated materials laboratory called Polybot to explore processing methods and produce high-quality films. This laboratory is located at Argonne's Center for Nanoscale Materials.
Polybot represents a method in autonomous discovery that combines robotics with AI to speed up innovation. According to Jie Xu, a scientist at Argonne, "Polybot operates on its own, with a robot running the experiments based on AI-driven decisions." Xu added, "We are creating a method that highlights how AI and automation can transform chemical engineering and materials science."
Henry Chan, a computational materials scientist at Argonne, noted that "using AI-guided exploration and statistical methods, Polybot efficiently gathered reliable data," which helped identify thin film processing conditions meeting multiple material goals. The platform optimizes two key properties: conductivity and coating defects, enhancing device reliability and electrical performance.
The project also developed "recipes" for large-scale production of these films. Aikaterini Vriza from Argonne highlighted the use of advanced computer programs that process images to evaluate film quality. "These programs not only helped us perform experiments and create films, but they also allowed us to capture images," she said.
Researchers collected valuable data intended for sharing within the scientific community through a database. Vriza emphasized, "Data is critical...by sharing this data, we hope to motivate the community to contribute to, test and improve our methodology."
This research impacts beyond laboratory settings by providing guidelines for large-scale production of electronic polymers. It offers practical advice for scientists and manufacturers exploring electronic polymer applications.
The project utilized resources like the Materials Engineering Research Facility at Argonne for electronic printing support and DOE’s Brookhaven National Laboratory’s National Synchrotron Light Source II for characterization.
Contributors include Chengshi Wang, Yeon-Ju Kim, Rohit Batra among others from Argonne; Naisong Shan and Nan Li from The University of Chicago; Subramanian K.R.S. Sankaranarayanan from both Argonne and the University of Illinois Chicago.
Jie Xu remarked on future directions: “This project is just the beginning...Next we want to dive deeper into using AI and automated processes.”
Funding was provided by U.S Department of Energy Office of Basic Energy Sciences among others.
Citation: “Autonomous platform for solution processing of electronic polymers,” Nature Communications.
—Adapted from an article first published by Argonne National Laboratory