Parts-per-billion detection of carbon monoxide: A comparison between quartz-enhanced photoacoustic and photothermal spectroscopy

Abstract

We report on a comparison between two optical detection techniques, one based on a Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) detection module, where a quartz tuning fork is acoustically coupled with a pair of millimeter-sized resonator tubes; and the other one based on a Photothermal Spectroscopy (PTS) module where a Fabry-Perot interferometer acts as transducer to probe refractive index variations. When resonant optical absorption of modulated light occurs in a gas sample, QEPAS directly detects acoustic waves while PTS probes refractive index variations caused by local heating. Compact QEPAS and PTS detection modules were realized and integrated in a gas sensor system for detection of carbon monoxide (CO), targeting the fundamental band at 4.6 μm by using a distributed-feedback quantum cascade laser. Performance was compared and ultimate detection limits up to ∼ 6 part-per-billion (ppb) and ∼15 ppb were reached for QEPAS and the PTS module, respectively, using 100 s integration time and 40 mW of laser power.

Keywords: Carbon monoxide; Fabry-Perot interferometer; Gas sensing; Laser spectroscopy; Quartz tuning fork.

Fig. 1

Gas density perturbation for one-dimensional hydrodynamic relaxation of a sample excited from a Gaussian intensity distribution single-pulse obtained by using Eq. 1. The density decrease at $z=0$ corresponds to the diffusive thermal mode, while the ‘wings’ represent the propagating acoustic mode. For the simulation, the following parameters have been used: beam waist, $w=10$ μm; acoustic attenuation constant, $\text{Γ}=1.2\cdot {10}^{-5}{\text{m}}^2{\text{s}}^{-1}$; thermal diffusivity, $D_T=2.2\cdot {10}^{-5}{\text{m}}^2{\text{s}}^{-1}$; speed of sound, $c=346{\text{m}\text{s}}^{-1}$. (b) Density perturbation at four different times (5, 20, 100 and 250 ns).

Fig. 2

Schematic of the gas sensor system for CO detection. DAQ: data acquisition card; MFC: mass flow controller; PCS: pressure control system; PM: power meter; TEC: thermoelectric cooler. The sensor system can easily accommodate QEPAS or PTS detection module.

Fig. 3

(a) Sketch of the QEPAS spectrophone inside of the gas cell. (b) Resonance profile of QTF-S15 at ambient pressure, as bare (circles) and with mR-tubes (squares). Lorentzian fit of bare S15 (red solid line) and spectrophone (blue solid line) have been performed to retrieve the resonance frequency and the Q-factor.

Fig. 4

(a) Sectioned view of the gas cell with the optical transducer. Top lid and windows not shown for clarity. (b) Enlarged view of the transducer head containing the interferometer: the probe beam (green) overlaps with the excitation beam (red) between the interferometer mirrors.

Fig. 5

(a) PTS signal demodulated at the 2nd harmonic as a function of the excitation source’s modulation frequency; (b) Noise level measured in 200 sccm gas flow (black) and in static conditions without excitation laser (red); (c) Signal-to-noise ratio calculated by ratio of the black curves in (a) and (b).

Fig. 6

(a) 2f-QEPAS signal for 100 ppm, 65 ppm, 40 ppm, 20 ppm and 5 ppm CO concentrations in N₂ when the sensor operates in spectral scan acquisition mode. (b) QEPAS peak signals plotted as a function of the CO concentration (datapoints) together with the best linear fit (solid line).

Fig. 7

(a) 2f-PTS signal as a function of time in the spectral scan acquisition mode for different CO concentrations in N₂. (b) PTS peak signals at different CO concentrations (datapoints) and the related best linear fit (solid line).

Fig. 8

Allan deviations (in ppb) for QEPAS and PTS sensors, both calculated starting from a 3 -h noise acquisition where the laser was turned ON and tuned to the absorption peak with pure N₂ within the gas cell. Dashed line represents the $1/\sqrt{t}$ trend. Dotted black line represents MDL at $t=$ 100 s.