Hybrid 3D Printing of Artificial SA-II Afferents Using Engineered Composites with Negative Piezoresistance

The peripheral nervous system collects and efficiently transmits large amounts of sensory information through parallel signaling pathways. Afferent nerves play a key role by encoding tactile stimuli recognized by cutaneous mechanoreceptors and converting them into action potentials, which are then transmitted to the central nervous system. Replicating this function by creating an artificial peripheral nervous system holds significant potential for advancing medical and robotics applications. As a result, interest in neuromorphic systems has been increasing. Recently, there has been a proliferation of research into mimicking slowly adapting type 1 (SA-I) afferent nerve that measures pressure on the skin. Biological skin includes a multitude of receptors for different stimuli. Therefore, to mimic the capabilities of the biological somatosensory system, it is necessary to develop artificial afferent nerves that are sensitive to a range of stimuli such as stretching and vibration.
We developed a flexible artificial afferent nerve that emulates a slowly adapting type 2 (SA-II) mechanoreceptor that detects skin stretching. The artificial afferent nerve consists of a piezoresistive composite sensor mimicking Ruffini endings and a ring oscillator that converts the strain information into a frequency-domain signal that mimics action potentials. The coupling between the sensor and oscillator requires two unique sensor properties: (1) the sensor resistance must decrease while being stretched to achieve increasing frequency output, and (2) the resistance must change by several orders of magnitude to match bio-inspired frequency ranges. Therefore, we implemented a quantum tunneling composite material exhibiting negative piezoresistance over 6 orders of magnitude with a strain range of over 50%. The piezoresistor consists of nickel particles as the conductor and a continuous phase consisting of elastomers and oil. We showed that the oil inclusion increased the strain range and reduced the hysteresis compared to traditional quantum tunneling composite. Varying the ratios of these components allows for tuning the material's properties, including the overall conductivity, range of conductivity change, and dynamic range. The overall conductivity of the composite is primarily determined by the concentration of fillers. As the oil content increased, the range of conductivity variation increased. The cross-linking density of the polymer can change the composite’s dynamic range. These wide ranges of tunability suggest that our artificial neurons could potentially be adapted to different applications. Our artificial SA2 receptors are fabricated using a hybrid direct write 3D printing approach that uses pick-and-placing of an integrated circuit chip, prints a stretchable conductor as interconnects, and prints the negative piezoresistive material as a sensing component. Our printed artificial afferent nerves will aid in advances in neural prosthetics, soft robotics, and wearable electronics.