GIST Develops LiDAR Sensor Coating That Maintains "Clear Vision" in Rain and Fog [Reading Science]

Inspired by Penguin Feather Structure: Removes Fog in 6 Seconds Using Only Sunlight and Adds Water-Repellent Function
Potential Applications for Optical Systems in Autonomous Vehicles, Robots, and Drones
Published in "Nature Communications"

An optical coating technology has been developed that maintains the performance of LiDAR sensors—the "eyes" of autonomous vehicles—even in rain and fog. By mimicking the microstructure of penguin feathers, this technology removes moisture and repels raindrops using only sunlight, without any additional power supply, making it possible to maintain stable LiDAR signals even under severe weather conditions.

On July 9, the Gwangju Institute of Science and Technology (GIST) announced that Professor Hyunho Jung and his research team from the Department of Electrical, Electronics and Computer Engineering have developed a "plasmonic helical structure" inspired by penguin feather morphology, thereby implementing an optical coating technology for LiDAR sensor covers.

A diagram showing the degradation of LIDAR signals occurring in severe weather. Provided by the research team

LiDAR is an optical sensor that uses lasers to precisely measure the distance and shape of surrounding objects, and is a core perception device for autonomous vehicles, robots, and smart mobility platforms. However, when rain or fog forms on the sensor surface, laser signals scatter, resulting in a significant drop in performance.

A Solution Inspired by Penguin Feathers

Conventional anti-fog and water-repellent coatings are each specialized for either moisture removal or droplet removal, making it difficult to achieve both functions simultaneously. While photothermal coatings are efficient at converting sunlight into heat, they have the drawback of absorbing the near-infrared spectrum used by LiDAR, which weakens sensor signals.

The research team found their solution in the structure of penguin feathers, which maintain body temperature and waterproofing even in extreme environments. Upon analyzing molted penguin feathers provided by the National Institute of Ecology, they confirmed that nanoscale melanosomes within the feathers absorb light to generate heat, and the microstructure of the surface prevents water droplets from sticking.

Based on this, the team developed a plasmonic structure with a three-dimensional silica helical architecture containing copper nanoparticles. This structure simultaneously absorbs light to generate heat and inhibits droplet adhesion, providing both anti-fog and water-repellent properties.

Moisture Removal with Sunlight Alone... Potential for Autonomous Applications

The new coating maintained a high transmittance of over 80% in the near-infrared region (905 nm) used by LiDAR, while increasing the surface temperature by about 9.3 degrees Celsius under ordinary sunlight. Moisture on the sensor surface was removed within six seconds, and in actual outdoor LiDAR tests, the coating demonstrated stable signal reception performance.

Research team photo. (From the back row, left to right, clockwise) Hyunho Jung, Professor of Electrical Engineering and Computer Science at GIST; Doeun Kim, Postdoctoral Researcher; Gyu Rin Kim, Integrated Master-PhD Student; Juhyung Lee, Integrated Master-PhD Student. Provided by GIST

The research team explained that they have also completed large-area fabrication and durability validation, securing performance levels suitable for application to actual automotive LiDAR sensor covers.

Professor Jung stated, "We have proposed a new concept for an optical platform that enables both anti-fogging and water-repellent functions using only sunlight, without any additional power supply, while not hindering LiDAR signals. In the future, we expect it to enhance the reliability of various outdoor optical systems, not only in autonomous vehicles but also in robots, drones, and smart windows."

This research was co-led by integrated master's and doctoral students Joohyeong Lee and Kyurin Kim as joint first authors, and the results were published online in the international journal Nature Communications on June 27.

This content was produced with the assistance of AI translation services.