Sensing structure without touching

This innovation, detailed in the journal Science and Technology of Advanced Materials by the team from Qingdao University along with collaborators from other parts of China and South Korea, leverages the disruption in electric fields to sense objects up to 100 millimetres away.

Electronic skins are increasingly vital in enabling bionic robots to sense and respond to their surroundings swiftly, facilitating the analysis and manipulation of objects. Traditional sensors depend on physical contact and consequent deformation, which alters electrical capacitance. However, this approach often suffers from limited sensitivity due to the uniform response across different areas.

Xinlin Li from Qingdao University explained the breakthrough: “To bring greater sensitivity and versatility we have developed new composite films with surprising and very useful electrical properties.” The innovation stems from combining two materials known for their high dielectric constants into a composite that, unexpectedly, exhibits a low dielectric constant. This paradoxical outcome makes the sensor exceedingly responsive to electric fields.

The sensor's design involves a blend of graphitic carbon nitride and polydimethylsiloxane, processed through dispensing printing. This 3D printing technique allows precise control over the sensor's structure, enabling it to detect objects from a distance of 5 to 100 millimetres without direct contact. Li highlighted the sensor's superior performance: “The performance was outstanding, in terms of sensitivity, speed of response and robust stability through many cycles of use,” underscoring its potential for wearable technologies and electronic skins. It promises applications in medical monitoring and the burgeoning Internet of Things (IoT), facilitating remote control over various devices.

Integrating the sensing grid with a printed circuit board, the researchers enabled data transmission over 4G networks, paving the way for widespread mobile connectivity.

The team is now focused on refining this technology for mass production and exploring new applications beyond shape and motion detection. They envisage possibilities in human-computer interaction, such as gesture recognition, and human motion detection for obstacle avoidance and gait monitoring, which could significantly benefit intelligent medical care.