Achieving extraordinarily high sensitivity is a long-sought goal in the development of novel and more capable electromagnetic sensors. We present here how a coherent perfect absorber-laser (CPAL) enabled by parity-time (PT) symmetry breaking may be exploited to build ultrasensitive monochromatic electromagnetic sensors that use radio waves, microwaves, terahertz radiations, or light. We argue the possibility of using such CPAL sensors to detect extremely small-scale perturbations of admittance or refractive index caused by, for example, low-density gas molecules and microscopic properties, as they may drastically vary the system’s output intensity from very low (coherent absorption) to high (lasing). We derive the physical bounds on CPAL sensors, showing that their sensitivity and resolvability may go well beyond traditional electromagnetic sensors, such as sensors based on Fabry–Perot cavities.

We herein introduce a lightweight and zero-power smart face mask, capable of wirelessly monitoring coughs in real time and identifying proper mask wearing in public places during a pandemic. The smart face mask relies on the compact, battery-free radio frequency (RF) harmonic transponder, which is attached to the inner layer of the mask for detecting its separation from the face. Specifically, the RF transponder composed of miniature antennas and passive frequency multiplier is made of spray-printed silver nanowires (AgNWs) coated with a poly­(3,4-ethylenedioxythiophene):poly­(styrenesulfonate) (PEDOT:PSS) passivation layer and the recently discovered multiscale porous polystyrene-block-poly­(ethylene-ran-butylene)-block-polystyrene (SEBS) substrate. Unlike conventional on-chip or on-board wireless sensors, the SEBS-AgNWs/PEDOT:PSS-based RF transponder is lightweight, stretchable, breathable, and comfortable. In addition, this wireless device has excellent resilience and robustness in long-term and repeated usages (i.e., repeated placement and removal of the soft transponder on the mask). We foresee that this wireless smart face mask, providing simultaneous cough and mask-wearing monitoring, may mitigate virus-transmissive events by tracking the potential contagious person and identifying mask-wearing conditions. Moreover, the ability to wirelessly assess cough frequencies may improve diagnosis accuracy for dealing with several diseases, such as chronic obstructive pulmonary disease.

The detection of mycotoxins in food is urgently needed because they pose a significant threat to public health. In this study, we developed a quantitative detection platform for mycotoxins by integrating multicolor upconversion nanoparticle barcode technology with fluorescence image processing using a smartphone-based portable device. The multi-colored upconversion nanoparticle encoded microspheres (UCNMs) were used as encoded signals for detecting different mycotoxins simultaneously. After indirect competitive immunoassays using UCNMs, images could be captured by the portable device and the camera of a smartphone. Then, a self-written Android application, which is an HSV-based image recognition program installed on a smartphone, analyzed images and offered a reliable and accurate result in less than 1 min. The quantitative detection platform of mycotoxins proved to be feasible and reliable, and the limit of detection (LOD) was 1 ng, which was lower than that obtained from standard assays. This study demonstrates a method for detecting mycotoxins in food and other point of care analysis.

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