Gas identification in high-Q microbubble resonators

Machine learning-assisted high-accuracy and large dynamic range thermometer in high-Q microbubble resonators

Whispering gallery mode (WGM) resonators provide an important platform for fine measurement thanks to their small size, high sensitivity, and fast response time. Nevertheless, traditional methods focus on tracking single-mode changes for measurement, and a great deal of information from other resonances is ignored and wasted. Here, we demonstrate that the proposed multimode sensing contains more Fisher information than single mode tracking and has great potential to achieve better performance. Based on a microbubble resonator, a temperature detection system has been built to systematically investigate the proposed multimode sensing method. After the multimode spectral signals are collected by the automated experimental setup, a machine learning algorithm is used to predict the unknown temperature by taking full advantage of multiple resonances. The results show the average error of 3.8 × 10^-3°C within the range from 25.00°C to 40.00°C by employing a generalized regression neural network (GRNN). In addition, we have also discussed the influence of the consumed data resource on its predicted performance, such as the amount of training data and the case of different temperate ranges between the training and test data. With high accuracy and large dynamic range, this work paves the way for WGM resonator-based intelligent optical sensing.

AC field modulated DC magnetic field sensor based on optical whispering gallery mode microcapillary resonator

A sensitive DC magnetic field sensor is constructed by measuring the signal-to-noise ratio of an AC-modulated magnetic field at a particular frequency from an optical whispering gallery mode microcapillary resonator. The sensing element consists of an optical whispering gallery mode microcapillary resonator bonded to a magnetostrictive material that enables it to respond to external magnetic fields. A DC magnetic field sensitivity of 0.1703dB/Oe and a linear detection range from 4.8Oe to 65.7Oe are realized under an AC modulation field of 168.1kHz in the unshielded environment at room temperature. To our best knowledge, this sensitivity is about 2.3 times of the maximum sensitivity of other DC magnetic field sensors based on magnetic fluid or magnetostrictive material integrated fiber systems that use the dissipative sensing scheme. Furthermore, the sensor can operate at a stable temperature in the range of [-11∼45]°C, as long as the modulation frequency of the AC-modulation field is adjusted according to the ambient temperature. This sensor provides us with a novel DC magnetic field sensing scheme, which may play a role in industrial fields related to current and position detection in the future.

Optical Whispering-Gallery-Mode Microbubble Sensors

Whispering-gallery-mode (WGM) microbubble resonators are ideal optical sensors due to their high quality factor, small mode volume, high optical energy density, and geometry/design/structure (i.e., hollow microfluidic channels). When used in combination with microfluidic technologies, WGM microbubble resonators can be applied in chemical and biological sensing due to strong light–matter interactions. The detection of ultra-low concentrations over a large dynamic range is possible due to their high sensitivity, which has significance for environmental monitoring and applications in life-science. Furthermore, WGM microbubble resonators have also been widely used for physical sensing, such as to detect changes in temperature, stress, pressure, flow rate, magnetic field and ultrasound. In this article, we systematically review and summarize the sensing mechanisms, fabrication and packing methods, and various applications of optofluidic WGM microbubble resonators. The challenges of rapid production and practical applications of WGM microbubble resonators are also discussed.