Towards Sustainable Sensor Technologies through Hybrid Approaches

The growth of flexible and wearable electronics commensurate with the proliferation of microelectronic devices is enabling high impact applications in healthcare and robotics. However, as such electronic devices increase in number, an increasingly urgent need to create materials and devices that can be part of a circular or self-repairable economy becomes critical. In this talk, I will discuss using organic materials science and engineering approaches as a way to scale skin-like sensors for more sustainable technological and societal impact through self-healing or degradability.

To scale to human-like performance, neuromorphic engineering provides an exciting avenue to mimic the high performance of the human nervous systems and sensors. Critically, the energy efficiency of the human neural networks for learning relies on event-driven, temporally encoded action potential streams. In this talk, I will discuss how we can digitize tactile information through inspiration from somatosensory neural science.

We have developed an asynchronous protocol for parallel transmission of tactile information in an artificial peripheral nervous system we call ACES: Asynchronously Coded Electronic Skins. The parallel transmission encodes spatial temporal information with very high temporal precision (sub-100ns) even when large numbers > 10,000 sensor nodes are transmitting simultaneously. Such systems can be interfaced with soft sensors or flexible/stretchable electronics to enable more intuitive robotics and healthcare applications.