In this paper, we propose and experimentally demonstrate an ultra-sensitive all-optical PAS gas sensor, incorporating with a near-infrared (NIR) diode laser, fiber-optic microphones (FOMs) and a double channel differential T-type photoacoustic cell. The FOM is realized by Fabry-Perot interferometry and novel gold-chromium (Au-Cr) composite nanomembranes. To meet the demand of high sensitivity and flat frequency response for the FOMs, the Au-Cr composite diaphragm is deliberately designed and fabricated by E-beam evaporation deposition with 330 nm in thickness and 6.35 mm in radius. Experimental results show that the FOM has a sensitivity of about 30 V/Pa and a flat frequency response from 300 to 900 Hz with fluctuation below 1 dB. Moreover, a double channel differential T-type photoacoustic cell is designed and employed in the all-optical PAS gas sensor, with the first-order resonant frequency of 610 Hz. The all-optical gas sensor is established and verified for CH₄ detection and the normalized noise equivalent absorption (NNEA) is 4.42 × 10⁻¹⁰ W∙cm⁻¹∙Hz^−1/2. The minimum detection limit (MDL) of 36.45 ppb is achieved with a 1 s integration time. The MDL could be further enhanced to 4.87 ppb with an integration time of 81 s, allowing ultra-sensitive trace gas detection.

In this paper, we propose and experimentally demonstrate a symmetric multi-resonant cavity photoacoustic cell (MR-PAC) with dual microphones detection, based on multi-resonator photoacoustic spectroscopy (MR-PAS). The designed photoacoustic cell contains three interconnected acoustic resonators to facilitate simultaneous control of three lasers for multi-gas sensing. Two microphones are symmetrically located at both sides of photoacoustic cell to implement two-point detection. The length of acoustic resonator is about 50 mm to minimize the photoacoustic cell, and the resonant frequency is around 3000 Hz. Feasibility and performance of the MR-PAC was demonstrated by simultaneous detection of C₂H₂, NO and CF₄ using a near infrared diode laser and two mid infrared quantum cascade lasers. The minimum detection limits (MDLs) of C₂H₂, NO and CF₄ are 480 ppb, 260 ppb and 0.57 ppb respectively with a 1 s integration time at normal atmospheric pressure. This minimized MR-PAS system is promising for the portable multi-gas sensing.

A small-volume highly-sensitive photoacoustic spectroscopy (PAS) methane detection system based on differential silicon cantilever optical microphones (SCOMs) is proposed and experimentally demonstrated. The system contains a compact non-resonant photoacoustic cell with a small volume of 1.2 mL and symmetrically-located dual SCOMs, as well as a distributed feedback laser at 1650.96 nm. The two identical SCOMs utilize the Fabry-Perot interferometric fiber-optic structure, with the differential Q-point demodulation algorithm to suppress the external vibration noise. Experimental results show that the SCOM has a high displacement sensitivity about 7.1 µm/Pa at 150 Hz and within 2.5 dB fluctuation between 5 Hz and 250 Hz. In the PAS gas sensing experiment, the normalized noise equivalent absorption coefficient of the PAS system is estimated to be 1.2 × 10⁻⁹ cm⁻¹·W·Hz^−1/2 and the minimum detection limit for methane is about 111.2 ppb with 1 s integration time. External disturbance is also applied to the dual SCOM system and results show excellent stability and noise resistance. The proposed PAS system exhibits superiorities of low gas consumption, high sensitivity and immunity to vibration and electromagnetic interference, which has an enormous potential in medicine, industry and environment.

Tunable Diode Laser Absorption Spectroscopy (TDLAS) has been widely applied in in situ and real-time monitoring of trace gas concentrations. In this paper, an advanced TDLAS-based optical gas sensing system with laser linewidth analysis and filtering/fitting algorithms is proposed and experimentally demonstrated. The linewidth of the laser pulse spectrum is innovatively considered and analyzed in the harmonic detection of the TDLAS model. The adaptive Variational Mode Decomposition-Savitzky Golay (VMD-SG) filtering algorithm is developed to process the raw data and could significantly eliminate the background noise variance by about 31% and signal jitters by about 12.5%. Furthermore, the Radial Basis Function (RBF) neural network is also incorporated and applied to improve the fitting accuracy of the gas sensor. Compared with traditional linear fitting or least squares method (LSM), the RBF neural network brings along the enhanced fitting accuracy within a large dynamic range, achieving an absolute error of below 50 ppmv (about 0.6%) for the maximum 8000 ppmv methane. The proposed technique in this paper is universal and compatible with TDLAS-based gas sensors without hardware modification, allowing direct improvement and optimization for current optical gas sensors.