High Performance and Spectrally Selective IR Sensing Based on Integrating MEMS and Metasurfaces

Infrared (IR) sensing is an ever-growing field due to their versatility and wide-ranging applications, including sensing, spectroscopy, and imaging, in areas such as defense, safety, health, space, and automotive. The current trends are toward miniaturized, silicon-compatible, and high-performance devices operating at room temperature (Photonics 2022,9(5),331). Micro-Electro-Mechanical Systems (MEMS) have emerged as a state-of-the-art technology capable of providing highly sensitive, compact, low-cost, and low power devices for IR sensing (28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS) 2015, 73–76). Novel detector designs incorporating tailored metasurface designs for spectrally selective mid-IR detection have been demonstrated, achieving low noise equivalent power (NEP) and high sensitivity (Nat Commun 2016, 7, 11249; J Microelectromech Syst 2021, 30, 165-172; Nanophotonics 2021, 10, 4). However, the development of these sensors is limited by several important shortcomings. First, the characterization process of this technology is cumbersome and time-consuming requiring dicing and PCB bonding of individual devices together with homemade IR and RF setups. Additionally, IR absorbing metasurfaces are usually printed using e-beam lithography, which is a relatively slow technique that limit the number of devices that can be fabricated. As a result, it is unclear the correlation between the geometrical dimensions and performance of this type of devices. Second, these sensors have been excited mostly with blackbody radiators that generate a broadband IR beam in which shorter wavelengths are much more powerful than longer ones. In that scenario, it is not possible to elucidate which contributions from the IR beam dominate the sensor response, and thus the performance reported to date may be misleading. And third, the sensors responsivity is currently obtained by monitoring the shift of the RF MEMS resonance frequency upon IR exposure. However, this approach is challenging to implement in real-time applications and may lead to sub-optimal sensing performance.