Automatic Characterization of High-Performance MEMS-Based IR Sensors.

Area of Science:

• Optoelectronics and Sensor Technology
• Materials Science
• Micro-electromechanical Systems (MEMS)

Background:

• Infrared (IR) sensors are crucial for applications in spectroscopy, health monitoring, and communications.
• Metasurface-enhanced micro-electromechanical system (MEMS)-based IR sensors show high performance, but experimental characterization is time-consuming and costly.
• Determining the performance limits of novel IR sensing technologies is essential for their advancement.

Purpose of the Study:

• To develop an automated, low-cost, and rapid solution for characterizing miniaturized IR sensing devices.
• To experimentally determine the performance limits of MEMS-based IR sensors.
• To identify trade-offs and statistical relationships in sensor performance based on device geometry.

Main Methods:

• An automated platform was designed for rapid characterization of on-chip IR sensors.
• The system utilizes optical and radiofrequency interrogation techniques for efficient testing.
• The platform can test over 1500 sensors on a single wafer, with approximately 20 seconds per device.

Main Results:

• The automated system successfully characterized over 1500 MEMS-based IR sensors.
• Data revealed significant trade-offs between responsivity and noise related to device thickness.
• Statistical analysis provided insights into sensing response variations with device geometrical dimensions.
• The best devices achieved a quality factor of 2391 and a responsivity of 164 Hz/nW.

Conclusions:

• The proposed automated platform offers an efficient and cost-effective method for characterizing next-generation IR sensing devices.
• This system accelerates the understanding and optimization of MEMS-based IR sensors.
• The findings facilitate the development of advanced IR sensing technologies for diverse applications.