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Abstract
A trace gas sensing technique of light-induced off-axis cavity-enhanced thermoelastic spectroscopy (OA-CETES) in the near-infrared was demonstrated by combing a high-finesse off-axis integrated cavity and a high Q-factor resonant quartz tuning fork (QTF). Sensor parameters of the cavity and QTF were optimized numerically and experimentally. As a proof-of-principle, we employed the OA-CETES for water vapor (H2O) detection using a QTF (Q-factor ∼12000 in atmospheric pressure) and a 10cm-long Fabry-Perot cavity (finesse ∼ 482). By probing a H2O line at 7306.75 cm-1, the developed OA-CETES sensor achieved a minimum detection limit (MDL) of 8.7 parts per million (ppm) for a 300 ms integration time and a normalized noise equivalent absorption (NNEA) coefficient of 4.12 × 10−9cm-1 WHz-1/2. Continuous monitoring of indoor and outdoor atmospheric H2O concentration levels was performed for verifying the sensing applicability. The realization of the proposed OA-CETES technique with compact QTF and long effective path cavity allows a class of optical sensors with low cost, high sensitivity and potential for long-distance and multi-point sensing.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Corrections
13 July 2021: A typographical correction was made to Fig. 10.
1. Introduction
Optical gas sensors have drawn a wide range of applications in recent years due to its high detection sensitivity and “finger-print” identifying characteristics [1–3]. A quartz tuning fork (QTF) is a type of crystal oscillator, which has been used in optical gas sensors for various fields, such as Femto-Newtonian force sensing [4], humidity detection [5], and high-resolution magnetic force microscopy [6,7]. In 2002, a standard ∼32-kHz QTF was first demonstrated by Kosterev et al. [8] as an acoustic wave transducer, named quartz enhanced photoacoustic spectroscopy (QEPAS). However, QEPAS is a contact detection technique, where the QTF should be embedded in the gas analyte, which limits its application in some fields, such as long-distance gas sensing, combustion diagnostics and corrosive gas analysis [9,10].
Recently, QTF has been employed as a thermoelastic transducer to monitor the electromagnetic radiation, which converts the photothermal energy generated by optical absorption into a mechanical motion and then transforms it into an electrical signal based on quartz’s piezoelectric effect [11]. This new QTF-based technique was first reported by Ma et al. in 2018, called quartz-enhanced photothermal spectroscopy (QEPTS) or light-induced thermoelastic spectroscopy (LITES) [12], which is an alternative method to QEPAS and can overcome the above-mentioned shortcomings in QEPAS. Also, QEPTS is a non-contact detection technique and thereby suitable for long-distance and multi-point sensing with much simpler sensor structure without using complicated acoustic micro-resonator [13,14]. Furthermore, compared with an optical detector-based system, such as tunable diode laser absorption spectroscopy (TDLAS), the QTF-based QEPTS system also shows superiority since a QTF is cheap, tiny and independent to the laser wavelength. Also, QEPTS can operate in a wide spectral range from visible to far-infrared region, since a quartz crystal has an inherent light absorption in a broad spectral region. Hence, a QTF is especially attractive for QEPTS gas sensing in the mid- and far-infrared region, where traditional optical detectors are generally expensive and difficult to acquire [15,16]. In addition, a comparison of the performance of QEPTS and TDLAS was experimentally investigated in Ref. [17]. As a result, a carbon monoxide (CO) detection limit for TDLAS and QEPTS system of 2.16 parts per million (ppm) and 470 parts per trillion (ppt) was achieved respectively at the same conditions, which illustrated that the QTF-based QEPTS technique is capable of a superior performance with lower detection limit compared with the photodetector-based TDLAS.
In order to enhance the sensitivity of the QEPTS technique, Ma et al. used several single-/multi-pass absorption cells to substantially increase the interaction path between the laser and the sampled gas species [17,18]. Different from the single-/multi-pass cell (S/MPC) with an optical path length of few centimeters to tens of meters, a cavity with two highly-reflective mirrors (>99%) can provide much longer effective path length of tens of meters to several kilometers. Therefore, a stronger gas absorption and a higher detection sensitivity can be achieved since the minimum absorption coefficient is inversely proportional to the effective optical path according to the Lambert-Beer law [19]. Furthermore, compared to a Fabry-Perot cavity, more high-order modes are excited in an off-axis cavity, the free spectral range (FSR) decreases, and the optical noise becomes relatively smaller, leading to a better cavity mode structure and mechanical stability.
In this paper, a light-induced off-axis cavity-enhanced thermoelastic spectroscopy (OA-CETES) sensor was demonstrated by combing a high-finesse optical cavity (i.e., gas cell) and a high Q-factor thermoelastic QTF (i.e. detector), which verified that the cavity mode modulated at half of the QTF’s resonance frequency (f0) can generate a response through the piezoelectric effect of the QTF. Optimization on the sensor parameters were performed including the cavity output spot pattern, thermoelastic QTF excitation position, wavelength modulation depth, off-axis laser-to-cavity coupling distance, and normalized noise equivalent absorption (NNEA) coefficient. Water vapor (H2O) was selected as the proof of principle to estimate the proposed OA-CETES sensor performance.
2. Experimental set-up
2.1 Absorption line selection
As depicted in Fig. 1(a), the absorption spectra of 8.7 ppm H2O (i.e., the detection limit of this sensor), 2 ppm CH4 (i.e., normal environmental concentration) and 400 ppm CO2 (i.e., normal environmental concentration) under an effective path length of 15 m are simulated using the high transmission (HITRAN) molecular spectroscopy database. An H2O line centered at 7306.75 cm-1 was selected as the optimal absorption line almost with no absorption of ambient CH4 and CO2. Thus the interference of atmospheric CH4 and CO2 can be neglected. The emitting wavenumber of the distributed feedback (DFB) laser versus the driving current was measured by a Fourier Transform Spectrometer (model iS50, Thermo Scientific), as shown in Fig. 1(b). According to the calibration result, the laser central current was set to 65 mA at 30°C for H2O detection.
Fig. 1. (a) HITRAN simulated absorbance of H2O near 7306.75 cm-1 (8.7 ppm, red line), CH4 (2 ppm, black line) and CO2 (400 ppm, blue line). (b) Laser wavenumber versus driving current with temperatures of 28, 29 and 30 ℃.
2.2 Sensor structure and design
A schematic of the demonstrated OA-CETES sensor system is shown in Fig. 2. To probe the interference free H2O absorption line at 7306.75 cm-1, a temperature controller (TC, TED 200C, Thorlabs) and a current driver (CD, LDC202C, Thorlabs) were employed with a central current of 65 mA and a temperature of 30°C for laser operation. An optical isolator (OI) was placed after the laser to avoid the feedback of the cavity. A single-mode optical collimator (OC) was utilized to couple the laser into the cavity with an off-axis configuration. The cavity was formed by two dielectric mirrors with a length of ∼10 cm and a reflectivity of 99.35%, leading to an effective optical length of 15 m, which was equivalent to ∼150 times of the laser propagation distance inside the cavity. Photograph of the designed cage-based cavity (i.e., absorption cell) is shown in Fig. 2(a). The cavity output was divided into two parts using a flip mirror (FM). One part was focused by a lens (f = 2 cm) and then coupled to a photodetector (PD) for direct absorption spectroscopic (DAS) H2O detection (dotted red lines in Fig. 2). Data processing was carried out through a data acquisition card (DAQ) and a LabVIEW platform. In DAS, the laser wavelength was scanned by a triangular wave signal with a frequency of 0.1 Hz and an amplitude of 1.2 V, leading to a wavenumber tuning range of 7306.4−7307.1 cm-1.
Fig. 2. Experimental configuration of the demonstrated OA-CETES sensor system. DFB laser, distributed feedback laser; SMF, single-mode fiber; OI, optical isolator; OC, optical collimator; FM, flip mirror; TA, trans-impedance amplifier; PD, photodetector; DAQ, data acquisition card. (a) Photograph of the fabricated cage-based cavity (i.e., gas cell) with a dimension size of 12 × 8 × 6 cm3. (b) Photograph of the thermoelastic QTF with an optimal focus point (red point).
The other part was focused by a lens (f = 2 cm) into a specific position on the surface of the QTF for light-induced thermoelastic detection (solid red lines in Fig. 2). The focus position of the QTF is shown in Fig. 2(b). A resonant frequency f0 of 32.760 kHz and a Q-factor of ∼12,000 of the QTF were determined using an electric excitation method [20]. The product model of the QTF was KDS DT-38 with QTF prong’s dimensions of length (3.325 mm), width (0.465 mm) and thickness (0.222 mm). The room temperature during the experiment was 20 ℃, and the temperature had little effect on the QTF’s response according to Ref. [21]. In future work, the QTF can be placed in a temperature-controlled cell to completely eliminate the influence of ambient temperature on the QTF’s response. Wavelength modulation spectroscopy was carried out by adding a sine wave modulation signal to the triangular wave scan signal. The modulation signal has a frequency of 16.380 kHz (i.e., half of the f0) and an optimal modulation amplitude of 0.6 V. In this manner, the QTF’s piezoelectric current was transformed to voltage via a trans-impedance amplifier (TA, feedback resistance: 10 MΩ), which was then demodulated by a lock-in amplifier (LIA, SR830) at a frequency of f0. With respect to the LIA parameters, the time constant was set to 300 ms and the slope filter was set to 24 dB/oct, resulting in a detection bandwidth of 0.26 Hz. In this experiment, ambient H2O and dry N2 entered the cavity through a three-way valve. The H2O concentration level inside the cavity could be changed by controlling the flow of N2. The gas inlet and outlet were closed to ensure that the H2O concentration inside the cavity remained stable during the measurement. In this way, the corresponding H2O concentration level was determined in real-time by comparing the DAS experimental absorbance value with the simulated one according to the HITRAN database. Furthermore, we used the DAS method to statically detect the H2O concentration in the cavity. It was found that the H2O concentration did not change, which proved that H2O adsorption and desorption had no effect on the experimental result.
3. Experimental optimization
3.1 Cavity output spot pattern optimization
In OA-CETES, the parameters of the cavity (e.g., output power and spot diameter with different spot distribution after the second cavity mirror) have an effect on the QTF response and the sensor’s sensitivity. A high cavity output power will linearly increase the QTF’s output intensity, resulting in a high thermal power disturbance on the surface of the QTF prong. However, the cavity output power can be affected by many factors including the incident light intensity, gas absorption, and the mirror reflectivity. With a specific cavity output power, the QTF response is also related to the spot pattern (leading to different light intensity density) of the cavity output. As depicted in Fig. 3(b), the influence of different spot pattern on the thermoelastic QTF response was analyzed using a finite element method (FEM) and a simulation tool COMSOL Multiphysics 5.5. In off-axis cavity-enhanced spectroscopy, if the “re-entrant condition” is satisfied by the cavity geometry, the optimal spot pattern on the second cavity mirror is similar to the “Herriott” spot distribution with a ring-shaped light spot pattern [22,23]. As shown in Fig. 3(a), by changing the propagation path of the intra-cavity beam with the same optical path length, different spot distribution after the second cavity mirror was realized, which was then focused on the QTF with different spot diameters through the convergence of the lens. With a point heat source placed at the bottom of the two prongs, the relationship between the QTF response and the spot diameter from 40 to 158 μm was numerically simulated, as demonstrated in Fig. 3(b). The results indicate that a small heat disturbance diameter was beneficial to the increase of the QTF signal. Related experimental investigation was performed with a cavity output power of 50 μW. Light beam with different focused spot diameter from 60 to 240 μm was measured by a commercial beam quality analyzer (Pyrocam IIIHR, Ophir Photonics). As depicted in Fig. 3(b), the experimental result is consistent with the theoretical one, which reveals that a cavity output distribution pattern with a small spot diameter is required to increase the QTF’s response and thereby improve the sensitivity of the OA-CETES sensor.
Fig. 3. (a) Schematic diagram of the light propagation path with different focused spot pattern. (b) The simulated QTF response and measured 2f amplitude versus different spot diameter of the heat source. Inset photographs are the simulated and measured light spots focused on the QTF.
3.2 Thermoelastic QTF position optimization
In addition to the spot characteristics of the cavity output, another factor that influences the QTF response is the light excitation position on the QTF. To achieve the largest response induced by the mechanical motion of the QTF in OA-CETES, the optimization on the position of the focus point on the QTF’s surface was numerically performed. As depicted in Fig. 4(a), 9 different points were analyzed by changing the location of the thermal source in the FEM simulation. Points 1-3 and 9-7 represent the excitation positions on the QTF’s left and right prongs, respectively. It can be seen that the QTF response all increase when it approaches to the bottom of the QTF, which is strictly consistent with the previous studies [24,25]. Furthermore, the QTF response at the bottom of the QTF from point 4 to 6 was also simulated, and the signal increases with the focus point approaching to the middle of the QTF’s bottom, which reveals that the optimal focus position is located at the middle bottom between the two prongs. Experimental investigation was then carried out with similar excitation points from 1 to 9 used in the simulation, as shown in Fig. 4(b). Generally, most areas on the QTF surface are coated with silver film as electrodes, and the reflectivity of the coating is higher than that of quartz material, which is not conducive to the photo-thermal transform. This is why the QTF response amplitudes of points 3 and 7 (without silver film, which means that more photons are absorbed by the QTF and leading to a high signal response) are higher than those of points 4 and 6 (with silver film) at the bottom of the QTF, resulting in a difference between experimental and theoretical (without silver film consideration) results. However, comparing Figs. 4(a) and 4(b), the most sensitive areas are located at the middle of the QTF’s bottom, which are therefore employed in the proposed OA-CETES sensor to achieve the optimal detection performance.
Fig. 4. (a) Simulated QTF response at 9 different excitation positions. Inset is a model of the QTF with the simulated 9 excitation positions marked for optimization. (b) The experimentally measured QTF response at 9 different excitation positions. Inset is the photograph of a 32.760 kHz QTF with 9 excitation positions marked for optimization.
3.3 Modulation depth optimization
To experimentally maximize the 2f signal of the OA-CETES, modulation depth optimization was then performed. A concentration level of 495 ppm H2O (determined by DAS method) was filled into the cavity to achieve the relationships among the 2f signal amplitude, modulation depth and modulation amplitude, as shown in Fig. 5. The optimum modulation amplitude for H2O detection was found to be 0.6 V, leading to a modulation depth (denoted by Δυ) of 0.34 cm-1. In this experiment, the full width at half maximum (FWHM) of the H2O line width (γ) was 0.18 cm-1 based on the HITRAN database and an optimized modulation coefficient of Δυ/γ=1.8 was achieved.
3.4 Off-axis coupling distance optimization
In off-axis cavity-enhanced spectroscopy, the off-axis incident distance is a key to obtain the optimal laser-to-cavity coupling efficiency. In this case, the relationship between the off-axis distance and the output signal was analyzed. As shown in Fig. 6, when the focus point of the laser beam deviates from the central axis by 1 mm (the cavity mirror radius was 6.35 mm), the output signal amplitude reaches the maximum value with a H2O concentration level of 495 ppm, which confirms that the sensor is in an optimal state for maximizing the cavity mode excitation. A pair of 0.5-inch diameter dielectric mirrors (Layertec GmbH) with a radius of curvature (RoC) of 20 cm was used to form an optical cavity. The on-axis FSR was calculated to be 1.5 GHz with a cavity length of 10 cm. By using the off-axis configuration, the FSR of the cavity was effectively decreased and an extremely dense spectrum was generated with an off-axis FSR of ∼342 MHz (i.e., 0.01 cm-1) based on the cavity mode spectra using the DAS method.
Fig. 6. 2f amplitude versus off-axis distance. Inset is the coupling scheme from on-axis to off-axis configuration.
3.5 NNEA optimization using Matlab simulation
To figure out the optimal state between the optical path length and the thermoelastic QTF signal-to-noise ratio (SNR), the relationships of the minimum H2O absorption coefficient (αmin), cavity output power on the QTF (PQTF), required laser power (Plaser) and NNEA coefficient as a function of the cavity mirror reflectivity (R) were analyzed, as demonstrated in Fig. 7. In the off-axis cavity, once the laser power is injected into the cavity, the instantaneous optical intensity can be expressed as [26]:
When the light propagating inside the cavity reaches a steady state, the PQTF is given by:
where P0 is the incident laser power (15 mW), c is the light speed and L represents the cavity length. T (assuming R + T=1) is the cavity transmittance coefficient. C is the laser-to-cavity coupling factor. Probing a minimum detectable H2O absorption coefficient (αmin), the related NNEA can be described as: where ENBW is defined as equivalent noise detection bandwidth. The time constant and filter slope of the LIA were set to 300 ms and 24 dB/octave, respectively, leading to an ENBW of 0.26 Hz. As depicted in Fig. 7, with the increase of R, the effective path gets longer, and the minimum detectable absorption decreases. Furthermore, due to the decrease of the cavity output power with increasing R, the PQTF onto the QTF’s surface also decreases correspondingly. As a result, the calculated NNEA decreases with the increase of R and becomes stable under a high reflectivity.Fig. 7. Relationship of the minimum H2O absorption coefficient (αmin), cavity output power on the QTF (PQTF), required laser power (Plaser) and NNEA coefficient as a function of cavity mirror reflectivity (R).
Also, we experimentally found that the minimum cavity output power that the QTF can generate a response was ∼15 μW. As shown in Fig. 7, the NNEA decreases as R increases, but the required initial laser power P0 increases accordingly. However, laser sources with much high power may arise additional issues including high price, high shot-to-shot noise, and increasing the possibility of damage to the cavity mirror, etc. Therefore, the incident laser power in absorption spectroscopy is generally in a range of 1−20 mW. According to the simulation results in Fig. 7, a mirror reflectivity around 0.9985 may be an appropriate choice for meeting sufficient laser power requirement and achieving a sufficiently low NNEA and noise level. In this work, considering the given laser power, the QTF response and the demanded SNR, a mirror reflectivity of 0.9935 will be used in the subsequent experiments to evaluate the OA-CETES sensor performance.
4. Experimental results and discussion
4.1 SNR and detection limit evaluation
Different from the on-axis cavity-enhanced spectroscopy with only TEM00 mode and one light spot on the second mirror, in off-axis cavity-enhanced spectroscopy, the off-axis laser-to-cavity configuration suppresses the transmission of the fundamental mode and enhances the output of high-order modes, thereby realizing the optimal coupling between the laser and the integrated cavity [27,28]. In this way, the scanned and modulated laser beam can be almost continuously transmitted into the cavity. Therefore, a QTF can be used to detect the cavity output with specific modulated wavelength to achieve a 2f signal. As shown in Fig. 8(a), the SNR evaluation of the OA-CETES sensor based on thermoelastic detection was investigated with a H2O concentration level of 305 ppm. A maximum 2f amplitude of 0.0663 mV was obtained with a 760 Torr pressure and a 300 K temperature. The background noise of the OA-CETES sensor was detected by tuning the laser wavelength to be far away from the H2O absorption line around 7306.75 cm-1 [29], as depicted in Fig. 8(b). The standard deviation (SD, 1σ) of the noise was determined to be 1.9 µV, leading to a SNR level of 0.0663/0.0019 = 35 and a detection limit (1σ) of 8.7 ppm for H2O detection, corresponding to a NNEA coefficient of 4.12 × 10−9 cm-1 WHz-1/2.
Fig. 8. (a) 2f signal with a 305 ppm H2O gas sample. (b) The background noise of the OA-CETES sensor.
4.2 Linear response evaluation
As shown in Fig. 9, the linear response of the sensor was further evaluated by investigating the 2f amplitudes versus H2O concentration level employing the above optimal parameters. For each concentration, 20 recordings of the 2f signal were averaged to improve the precision of the result. The data was depicted as a function of H2O mixing ratio, and an R-square value of ∼0.997 was achieved, which confirmed a good linear response of the demonstrated OA-CETES sensor system.
4.3 Field sensing application
For verifying the sensing applicability of the demonstrated OA-CETES technique, continuous, day and night monitoring of indoor and outdoor atmospheric H2O mixing ratios was performed with a 5 s acquisition time. The sensor system, as shown in Fig. 2, was placed inside the Tang Aoqing building on the Jilin University campus in Changchun, China, with GPS coordinates: 125.291448° E, 43.831747° N. Monitoring of indoor H2O concentration levels was first carried out in an ultra-clean laboratory environment (in the Infrared Opto-Electron Application Laboratory at Jilin University) for 3 h on December 29, 2020, as shown in Fig. 10(a). It can be found that the measured H2O concentration level shows an average value of ∼1800ppm. This concentration level was lower than the normal indoor humidity even in the winter, which was mainly due to the lack of indoor and outdoor air exchange caused by the closed environment in the ultra-clean laboratory. In order to evaluate the accuracy of the OA-CETES, a comparison with a commercial instrument (AIRMAR, model 150WX, sampling time: 5 s, detection limit: 100 ppm) was performed. As depicted in Fig. 10(a), the variation trend of the atmospheric H2O concentration measured by the OA-CETES sensor is in a good agreement with that of the AIRMAR.
Fig. 10. Continuous monitoring of H2O concentration levels (a) in an ultra-clean laboratory environment by this sensor and a commercial AIRMAR instrument, and (b) in the atmosphere by this sensor and the commercial AIRMAR instrument from December 30, 2020 to December 31, 2020 on the Jilin University Campus.
The sensor system was also evaluated for monitoring the H2O concentration levels in the outdoor atmosphere, which was conducted from 6:00 am on December 30, 2020 to 18:00 pm on December 31, 2020 (∼36 hours sampling). The outside ambient air was pumped into the cavity (i.e., gas cell) via a 3 m-long ϕ 1-inch PTFE tube using an oil-free pump (Model N816.3, KNF). As demonstrated in Fig. 10(b), the measured H2O concentration level varied from 1500 to 4500 ppm with a mean value of ∼2500 ppm. Also the OA-CETES results are in good agreement with the AIRMAR with a similar concentration varied trend. Since the developed OA-CETES sensor possess a much higher detection sensitivity than AIRMAR, it is therefore possible to measure the H2O concentration evolution in time with a higher accuracy. For example, several oscillations were observed at ∼9:00 am on December 31, 2020, but no similar trend was observed using the AIRMAR instrument. In the future, longer-term analysis will be carried out for the study of seasonal and annual variations of atmospheric H2O concentration.
4.4 Comparison and discussion
The performances of the previously reported QTF-based QEPTS sensor systems and the proposed OA-CETES one are summarized in Table 1. NNEA is used here to impartially compare the sensing performance, which is independent of gas absorption line strength, laser power and detection bandwidth. As shown in Table 1, the NNEA of the proposed OA-CETES is lower than the reported QEPTS sensors in Refs. [12,25], which is mainly due to the fabricated high-finesse cavity with a stable cage-based configuration and a long light-gas interaction path. In addition, the NNEAs in Refs. [17,11] are ∼5 times as low as this OA-CETES, benefiting from the high Q-factor of the QTF in a low pressure gas cell [17] (Q-factor: 50177, gas pressure: 20 Torr) and from a custom QTF (Q-factor: 9080, f0: 9.35 kHz), where the energy accumulation time is more than 3 times higher than that of a standard 32.760 kHz QTF [11].
Table 1. Performance Comparison Between the Previous Reported QEPTS Sensor Systems and the Proposed OA-CETES Sensor System
5. Conclusion
In this paper, a trace gas detection method of OA-CETES was demonstrated in the near-infrared. A compact cavity with a 15m-long effective path was fabricated as the gas cell to enhance optical absorption. A resonant QTF with a high Q-factor of 12000 was employed as the cavity-enhanced thermoelastic detector. Taking H2O detection as a proof of principle, a NNEA value of 4.12×10−9 cm-1 WHz-1/2 was achieved for the sensor system. Further improvement of the detection sensitivity can be realized either by using a cavity mirror with higher reflectivity to increase the effective optical path length or by placing the QTF in a low-pressure absorption cell for improving the Q-factor.
Funding
National Natural Science Foundation of China (61627823, 61775079, 61960206004); Jilin Scientific and Technological Development Program (20180201046GX, 20190101016JH, 20200401059GX); Program for Jilin University Science and Technology Innovative Research Team (JLUSTIRT, 2021TD-39).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
References
1. S. D. Qiao, Y. He, and Y. F. Ma, “Trace gas sensing based on single-quartz-enhanced photoacoustic-photothermal dual spectroscopy,” Opt. Lett. 46, 2449–2452 (2021). [CrossRef]
2. Z. T. Lang, S. D. Qiao, Y. He, and Y. F. Ma, “Quartz tuning fork-based demodulation of an acoustic signal induced by photo-thermo-elastic energy conversion,” Photoacoustics 22, 100272 (2021). [CrossRef]
3. Y. F. Ma, R. Lewicki, M. Razeghi, and F. K. Tittel, “QEPAS based ppb-level detection of CO and N2O using a high power CW DFB-QCL,” Opt. Express 21, 1008–1019 (2013). [CrossRef]
4. M. Barbic, L. Eliason, and J. Ranshaw, “Femto-Newton force sensitivity quartz tuning fork sensor,” Sensor. Actut. A-Phys. 136564–566 (2007). [CrossRef]
5. J. Zhang, C. Dai, X. Su, and S. J. O’Shea, “Determination of liquid density with a low frequency mechanical sensor based on quartz tuning fork,” Sensor. Actut. B-Chem. 84, 123–128 (2002). [CrossRef]
6. D. Hussain, J. Song, H. Zhang, X. Meng, Y. Wen, and H. Xie, “Optimizing the quality factor of quartz tuning fork force sensor for atomic force microscopy: impact of additional mass and mass rebalance,” IEEE Sens. J. 17, 2797–2806 (2017). [CrossRef]
7. J. A. Hedberg, A. Lal, Y. Miyahara, P. Grütter, G. Gervais, M. Hilke, L. Pfeiffer, and K. W. West, “Low temperature electrostatic force microscopy of a deep two-dimensional electron gas using a quartz tuning fork,” Appl. Phys. Lett. 97, 143107 (2010). [CrossRef]
8. A. A. Kosterev, Y. A. Bakhirkin, R. F. Curl, and F. K. Tittel, “Quartz-enhanced photoacoustic spectroscopy,” Opt. Lett. 27, 1902–1904 (2002). [CrossRef]
9. H. D. Zheng, Y. H. Liu, H. Y. Lin, B. Liu, X. H. Gu, D. Q. Li, B. C. Huang, Y. C. Wu, L. P. Dong, W. G. Zhu, J. Y. Tang, H. Y. Guan, H. H. Lu, Y. C. Zhong, J. B. Fang, Y. H. Luo, J. Zhang, J. H. Yu, Z. Chen, and F. K. Tittel, “Quartz-enhanced photoacoustic spectroscopy employing pilot line manufactured custom tuning forks,” Photoacoustics 17, 100158 (2020). [CrossRef]
10. Y. F. Ma, Y. He, L. G. Zhang, X. Yu, J. B. Zhang, R. Sun, and F. K. Tittel, “Ultra-high sensitive acetylene detection using quartz-enhanced photoacoustic spectroscopy with a fiber amplified diode laser and a 30.72 kHz quartz tuning fork,” Appl. Phys. Lett. 110, 031107 (2017). [CrossRef]
11. Y. F. Ma, Y. He, P. Patimisco, A. Sampaolo, S. D. Qiao, X. Yu, F. K. Tittel, and V. Spagnolo, “Ultra-high sensitive trace gas detection based on light-induced thermoelastic spectroscopy and a custom quartz tuning fork,” Appl. Phys. Lett. 116, 011103 (2020). [CrossRef]
12. Y. F. Ma, Y. He, Y. Tong, X. Yu, and F. K. Tittel, “Quartz-tuning-fork enhanced photothermal spectroscopy for ultra-high sensitive trace gas detection,” Opt. Express 26, 32103–32110 (2018). [CrossRef]
13. Y. Q. Hu, S. D. Qiao, Y. He, Z. T. Lang, and Y. F. Ma, “Quartz-enhanced photoacoustic-photothermal spectroscopy for trace gas sensing,” Opt. Express 29, 5121–5127 (2021). [CrossRef]
14. S. D. Qiao, Y. F. Ma, P. Patimisco, A. Sampaolo, Y. He, Z. T. Lang, F. K. Tittel, and V. Spagnolo, “Multi-pass quartz-enhanced photoacoustic spectroscopy-based trace gas sensing,” Opt. Lett. 46, 977–980 (2021). [CrossRef]
15. Y. Li, R. Z. Wang, F. K. Tittel, and Y. F. Ma, “Sensitive methane detection based on quartz-enhanced photoacoustic spectroscopy with a high-power diode laser and wavelet filtering,” Opt. Laser Eng. 132, 106155 (2020). [CrossRef]
16. S. D. Russo, A. Zifarelli, P. Patimisco, A. Sampaolo, T. T. Wei, H. P. Wu, L. Dong, and V. Spagnolo, “Light-induced thermo-elastic effect in quartz tuning forks exploited as a photodetector in gas absorption spectroscopy,” Opt. Express 28, 19074–19084 (2020). [CrossRef]
17. Y. He, Y. F. Ma, Y. Tong, X. Yu, and F. K. Tittel, “Ultra-high sensitive light-induced thermoelastic spectroscopy sensor with a high Q-factor quartz tuning fork and a multipass cell,” Opt. Lett. 44, 1904–1907 (2019). [CrossRef]
18. Y. F. Ma, Y. Q. Hu, S. D. Qiao, Y. He, and F. K. Tittel, “Trace gas sensing based on multi-quartz-enhanced photothermal spectroscopy,” Photoacoustics 20, 100206 (2020). [CrossRef]
19. K. Y. Zheng, C. T. Zheng, N. N. Ma, Z. D. Liu, Y. Yang, Y. Zhang, Y. D. Wang, and F. K. Tittel, “Near-Infrared broadband cavity-enhanced spectroscopic multigas sensor using a 1650 nm light emitting diode,” ACS Sens. 4, 1899–1908 (2019). [CrossRef]
20. A. A. Kosterev, P. R. Buerki, L. Dong, M. Reed, T. Day, and F. K. Tittel, “QEPAS detector for rapid spectral measurements,” Appl. Phys. B 100, 173–180 (2010). [CrossRef]
21. M. Köhring, S. Böttger, U. Willer, and W. Schade, “Temperature effects in tuning fork enhanced interferometric photoacoustic spectroscopy,” Opt. Express 21, 20911–20922 (2013). [CrossRef]
22. G. F. Shen, X. Chao, and K. Sun, “Modeling the optical field in off-axis integrated-cavity-output spectroscopy using the decentered Gaussian beam model,” Appl. Opt. 57, 2947–2954 (2018). [CrossRef]
23. G. S. Engel, W. S. Drisdell, F. N. Keutsch, E. J. Moyer, and J. G. Anderson, “Ultrasensitive near-infrared integrated cavity output spectroscopy technique for detection of CO at 1.57 μm: new sensitivity limits for absorption measurements in passive optical cavities,” Appl. Opt. 45, 9221–9229 (2006). [CrossRef]
24. L. E. Hu, C. T. Zheng, M. H. Zhang, K. Y. Zheng, J. Zheng, Z. W. Song, X. Y. Li, Y Zhang, Y. D. Wang, and F. K. Tittel, “Long-distance in-situ methane detection using near-infrared light-induced thermo-elastic spectroscopy,” Photoacoustics 21, 100230 (2021). [CrossRef]
25. L. E. Hu, C. T. Zheng, Y. Zhang, J. Zheng, Y. D. Wang, and F. K. Tittel, “Compact all-fiber light-induced thermoelastic spectroscopy for gas sensing,” Opt. Lett. 45, 1894–1897 (2020). [CrossRef]
26. K. Y. Zheng, C. T. Zheng, J. H. Li, N. N. Ma, Z. D. Liu, Y. Zhang, Y. D. Wang, and F. K. Tittel, “Near-infrared methane sensor system using off-axis integrated cavity output spectroscopy with novel dual-input dual-output coupling scheme for mode noise suppression,” Sensor. Actut. B-Chem. 308, 127674 (2020). [CrossRef]
27. J. B. Paul, L. Lapson, and J. G. Anderson, “Ultrasensitive absorption spectroscopy with a high-finesse optical cavity and off-axis alignment,” Appl. Opt. 40, 4904–4910 (2001). [CrossRef]
28. J. J. Wang, X. Tian, Y. Dong, J. J. Chen, T. Tan, G. D. Zhu, W. D. Chen, and X. M. Gao, “High-sensitivity off-axis integrated cavity output spectroscopy implementing wavelength modulation and white noise perturbation,” Opt. Lett. 44, 3298–3301 (2019). [CrossRef]
29. L. E. Hu, C. T. Zheng, J. Zheng, Y. D. Wang, and F. K. Tittel, “Quartz tuning fork embedded off-beam quartz-enhanced photoacoustic spectroscopy,” Opt. Lett. 44, 2562–2565 (2019). [CrossRef]
