A recent partnership has opened up exciting possibilities in the field by developing a groundbreaking high-performance organic electrochemical neuron that operates within the frequency range of human neurons.
Creating artificial biological processes, like perception systems, has been a challenging goal for experts in organic electronics. This difficulty stems from the complexity of human senses, which depend on a flexible network of sensory neurons that activate in response to external stimuli.
A collaboration between Northwestern University and Georgia Tech has paved the way for advancements by designing a new high-performance organic electrochemical neuron that reacts in the same frequency range as human neurons. They have also built a comprehensive perception system by developing additional organic materials and integrating their engineered neurons with synthetic touch receptors and synapses, which allows for the real-time sensing and processing of tactile signals.
The findings, published this month in the journal Proceedings of the National Academy of Sciences (PNAS), could significantly enhance the capabilities of intelligent robots and other systems that currently face limitations due to less effective sensing technologies compared to humans.
“This study marks a notable advancement in organic electronics and their role in bridging the divide between biology and technology,” stated first author Yao Yao, an engineering professor at Northwestern. “We have developed an efficient artificial neuron that is compact yet boasts excellent neuronal capabilities. Using this innovation, we created a complete tactile neuromorphic perception system to replicate actual biological processes.”
According to corresponding author Tobin J. Marks, who holds the Charles E. and Emma H. Morrison Professorship of Chemistry at Northwestern’s Weinberg College of Arts and Sciences, existing synthetic neural circuits typically operate within a limited frequency range.
“The synthetic neuron in this research demonstrates exceptional performance in frequency modulation, offering a range that is 50 times broader than conventional organic electrochemical neural circuits,” Marks explained. “Our device’s remarkable neuronal traits position it as a major advancement in organic electrochemical neuron technology.”
Marks is recognized globally for his expertise in organometallic chemistry, chemical catalysis, materials science, organic electronics, photovoltaics, and nanotechnology. He also serves as a professor in Materials Science and Engineering, Chemical and Biological Engineering, and Applied Physics at Northwestern. Co-corresponding author Antonio Facchetti, a professor at Georgia Tech’s School of Materials Science and Engineering, is an adjunct professor of chemistry at Northwestern as well.
“This research unveils the first fully integrated neuromorphic tactile perception system using artificial neurons, which combines synthetic tactile receptors and artificial synapses,” said Facchetti. “It showcases the capability to convert tactile stimuli into spiking neuronal signals in real time and then transform these signals into post-synaptic responses.”
The research team included specialists from various departments and schools, with experts in organic synthesis designing advanced materials that were later integrated into electronic device circuit designs and manufacturing.
Replicating the human brain’s extensive network of 86 billion neurons poses significant challenges for sensing systems. Researchers face limitations in both the device’s size and the volume they can produce. In future iterations, the team aims to further miniaturize the device, bringing it closer to accurately resembling human sensory systems.
This research was funded by the Air Force Office of Scientific Research (FA9550-22-1-0423), the Northwestern University Materials Research Science and Engineering Center (MRSEC; funded by National Science Foundation DMR-230869), Flexterra Corporation, and through grants from the National Science Fund for Distinguished Young Scholars of China (No. 32425040) and the National Natural Science Foundation of China (Grant No. 32201648).
