Graphene-Coated Nanowires Deliver Robust, Highly-Sensitive Skin-Friendly Wearable Sensors

A team of scientists from the Terasaki Institute for Biomedical Innovation (TIBI) has unveiled a next-generation fabrication method for wearable piezoresistive sensors — offering improved durability without sacrificing performance.

"The advancements made by our scientists address some of the challenges in costs, production, and effectiveness in wearable skin sensing," claims Ali Khademhosseini, PhD, TIBI's director and chief executive, of the team's work. "The impact of these improvements can be translated in a variety of ways to many biomedical and commercial applications."

The biggest problem with existing skin-based wearable pressure sensing is reliability: Traditionally, piezoresistive sensors are created using copper nanowires to balance performance and cost — but are known to corrode over time. Alternatives exist, but are considerably more expensive and complex to produce — making them unsuitable for mass production.

The solution, according to TIBI's team: Coating the copper nanowires with graphene oxide, which provides protection against corrosion without harming the wires' conductive properties. At the same time, the team developed a new microstructure — created by molding a substrate layer onto a sheet of sandpaper — that boosts the sensitivity range of the finished sensor.

"Our solutions-based method for protectively coating copper nanowires offer a simple, scalable and tunable way to guard against nanowire corrosion," claims lead author Yangzhi Zhu, Ph.D, of the result. "And our spray coating and molding techniques for sensor fabrication enable a more scalable, high throughput and modular approach."

The resulting sensors were tested for detection of bodily movements at the fingers, wrists, biceps, knees, and neck, plus monitoring of pulse at the carotid artery, swallowing, finger pressing, and testing: The team reports that all the measurements came through clear and comparable to commercial devices.

The team's work has been published under closed-access terms in the journal Small Methods.