Development of a bio-inspired stretchable network for intelligent composites

The human skin hosts an array of sensors capable of detecting numerous traits that are important to how we function and survive. This is combined with local and global processing in a hierarchical nervous system in order to manage the vast amount of data generated, in the form of our peripheral and central nervous systems, illustrated in Fig 1. With the goal of transferring similar functionality to composite structures the Structures and Composites Laboratory at Stanford University, in collaboration with researchers at UCLA, has developed a bio-inspired, micro-fabricated, embeddable stretchable network capable of hosting multiple sensors and computational suites, illustrated in Fig 2. Utilizing non-standard micro-fabrication techniques, an entire networked array of elements is fabricated simultaneously, composed of sensor nodes and interconnects that can include wires, temperature sensors, strain sensors, ultrasonic actuators, ultrasonic sensors, and signal processing. The substrate is then etched into a form that can be stretched and expanded to cover an area orders of magnitude larger than the original processing area and interfaced into local and global processors for data analysis [1]. Fig 3 contains before and after photos of an interconnect undergoing 1 dimensional extension. When embedded in a composite, this form of sensor network has the potential to provide localized sensor information about multiple aspects of the composite's condition, including temperature, deformation and damage, much like skin [2]. Due to the small physical size and dispersed nature of the network components, this network can be embedded into a composite laminate with minimal effect on the overall structural strength. However, due to the nature of the processing and use of a non-standard polyimide substrate, unique fabrication methods had to be developed to create this bio-inspired network. This paper presents an overview of the ongoing research and systems that have been integrated into this network in pursuit of a bio-inspired material capable of detecting temperature, damage, deformation and other traits. To date Resistive Temperature Detectors (RTDs), resistive strain gauges, piezoelectric elements, diodes, and microprocessors have been integrated into the network to serve these purposes. An un-stretched and expanded network consisting of piezoelectric elements and electrical interconnects can be seen in Fig 4 and Fig 5 respectively. Software interfaces, running on laptops, have served to process gathered information into a useful form mimicking the central nervous system. Additionally, synaptic transistors based on carbon nanotube (CNT) based composite that can process the signals from the network have been developed at UCLA, shown in Fig 6. These synaptic transistors can be tuned and are capable of providing signal processing, memory, and learning functions through modification of ionic fluxes in neurons and synapses. This enables the circuit to collectively process the signals through 103-104 synapses to establish spatial and temporal correlated functions.