Summary: A new room-temperature infrared sensor developed by UC Davis combines MEMS vibration technology with radio-frequency tuning, enabling highly sensitive detection for cancer diagnostics, environmental monitoring, and next-generation smart devices.
Researchers at the University of California, Davis have developed an advanced room-temperature infrared (IR) sensor that could eliminate the need for costly cryogenic cooling while delivering high sensitivity for a wide range of applications. The breakthrough, published in Nature Communications, introduces a new sensing architecture that combines micro-electromechanical systems (MEMS) with radio-frequency (RF) reflectometry.
A tiny infrared sensor is seen under a powerful microscope. The new UC Davis sensor is designed to pick up weak signals without the need for freezing temperatures.
Unlike conventional infrared detectors that rely on photodetectors and often require sub-zero operating temperatures to reduce noise, the new sensor uses a microscopic vibrating membrane. When exposed to infrared light, the membrane changes its vibration frequency according to the intensity of the incoming signal. These changes are then measured using radio waves and an RF interrogation technique known as critical coupling, dramatically amplifying weak infrared signals.
The infrared sensor is seen under a microscope and illuminated by a laser. The repeating shapes, which look like perforations, are nanometric resonators that compose the sensor’s metasurface.
The technology enables detection of infrared signals as low as 740 picowatts, while also supporting measurements up to 100 microwatts, providing an exceptionally wide dynamic range. Because the sensor’s operating point can be tuned electronically, it can adapt to different sensing environments and target signals in real time.
A key advantage of the platform is its ability to maintain high responsivity at room temperature, reducing system complexity, power consumption, and deployment costs. This makes the technology attractive for emerging applications in AI-powered medical diagnostics, cancer biomarker detection, environmental monitoring, air-quality sensing, wildfire detection, and future smart consumer electronics.
Responsivity of reflectometric RF MEMS-based IR detectors.
The sensor was originally developed to support research into non-invasive cancer detection by identifying molecular signatures in blood and saliva samples. However, its adaptable architecture suggests much broader potential across healthcare, industrial sensing, and advanced infrared imaging systems.
As demand grows for compact, energy-efficient sensing technologies, the UC Davis infrared sensor demonstrates how MEMS engineering and RF signal processing can create a new generation of high-performance infrared detection platforms without the limitations of traditional cooled detectors.
