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High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region
Accepted Manuscript Title: High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region Authors: Zhenhui Du, Jinyi Li, Xiuhan Cao, Hong Gao, Yiwen Ma PII: DOI: Reference:
S0925-4005(17)30457-4 http://dx.doi.org/doi:10.1016/j.snb.2017.03.040 SNB 21952
To appear in:
Sensors and Actuators B
Received date: Revised date: Accepted date:
26-7-2016 7-3-2017 10-3-2017
Please cite this article as: Zhenhui Du, Jinyi Li, Xiuhan Cao, Hong Gao, Yiwen Ma, High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region, Sensors and Actuators B: Chemical http://dx.doi.org/10.1016/j.snb.2017.03.040 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region Zhenhui Dua, b*, Jinyi Lic, Xiuhan Caoa, Hong Gaoa, Yiwen Maa a. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, China b.Department of chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America c. Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin, China
Highlights 1. A CS2 sensor with high-sensitive of detection limit 19.5ppb, corresponding absorbance as 3×10-5 for band spectrum was provided. 2. The optimized modulation index reasonably balanced the spectral discrimination and the SNR in WMS with band spectrum. 3. The optical fringes buried in the detected signal was distinguished and removed by EMD algorithm. 4. The robust and versatile method enabling WMS to band spectrum is instructive for VOCs detection.
Abstract A sensitive carbon disulfide (CS2) sensor based on wavelength modulation spectroscopy (WMS) in the mid-infrared fingerprint region was reported. The strong band spectrum of carbon disulfide's combination band (ν1+ν3), near 2177.6 cm-1, was used in the sensor. To enable WMS for wideband spectrum, a parameter of Spectral Discrimination (SD) was defined and used as a criterion for optimizing the modulation index, which was finally determined to be around 0.8 instead of 2.2 commonly used for a isolated line spectrum. And the second harmonic signal was processed with empirical mode decomposition (EMD) algorithm to distinguish and remove the optical fringes buried in the detected signal. The sensor performances were tested by implementing a set of CS2 concentration experiments. The results showed that the sensor response linearity was 0.999 and the relative measuring error was less than 1 %. The sensitivity, i. e. 3σ detection limit, was as low as 60 ppb with integration time of 240 s with optical path length of 5 m, corresponding to absorbance of 3×10-5. Overall, benefiting from strong fingerprint absorption and methods of applying WMS to wideband spectrum, the sensor is promising for both environmental and industrial CS2 detection. *
Corresponding author. Tel.: +86 22 2740 3290; Fax: +86 22 2740 3290 E-mail address: [email protected] (Zhenhui Du) Current address: Department of chemistry, MIT, Cambridge, United States of America 1
Keywords: CS2 sensor, Tunable laser absorption spectroscopy (TLAS), wavelength modulation spectroscopy (WMS), mid-infrared fingerprints, wideband spectrum, distributed feedback quantum cascade laser (DFB-QCL), optical fringes, empirical mode decomposition (EMD)
1. Introduction Carbon disulfide (CS2) is a toxic volatile sulfur compound (VSC) with stinky smell and is extensively produced by both natural and anthropogenic sources [1]. Natural sources include soils and oceans [2], food wastes [3], marshland and volcano eruptions [4]. Anthropogenic emissions derive from biomass burning and chemical uses [2], rayon fiber and cellophane productions[5]. CS2 is not only a harmful air pollutant which participates in atmospheric photochemical reactions, but also combustible and dangerous for industrial safety. What’s more, exposure to even low level of CS2 may increase health risks in especial nervous diseases [6]. Atmospheric CS2 concentration threshold limits of 6.7 ppm and 10 ppm in workplace are recommended by the U. S. Environmental Protection Agency (EPA) [7] and the National Institute for Occupational Safety and Health (NIOSH) [8], respectively. Hence, it is essential to detect environmental and industrial CS2 with real time, in situ at sub-ppm or even lower level. Common methods for detecting CS2 include combined gas chromatography and mass spectroscopy (GC-MS) [9-11], gas sensors [12, 13] and optical spectroscopy [14-16]. GC-MS provides specific and sensitive analysis with high accuracy and precision, however, it is time-consuming and costly. A magnesium metal-organic framework compounds based fluorescence sensor may be limited by the low response time for its adsorption [12]. A nanosized-CeO2 chemiluminescence based carbon disulfide sensor has high sensitivity [13], however the strict conditions for catalytic oxidation reaction may be very difficult to meet in field. Optical spectroscopy is useful tool for molecular transition researching and high-sensitivity sensing with selectivity. Blanque et al. [14] investigate the absorption spectra of CS2 in the 2800-3000 cm-1 region with high-resolution FTS, and provide new spectra data for global analysis of this molecule. Yu et al. [15] observe atmospheric CS2 with ultraviolet differential optical absorption spectroscopy, and a open path of 1.4 km is used to achieve a detection limit around 2 ppb. Waclawek et al. [16] demonstrate a CS2 sensor based on quartz-enhanced photoacoustic spectroscopy with 1σ detection limit of 28 ppb depending on concentration of water vapor. Wavelength modulation spectroscopy (WMS) has been demonstrated to have high sensitivity for in situ, real time sensing of trace gas with isolated line spectrum [17-24]. Mid-infrared region is especially attractive for strong fingerprint absorption of many compounds [20-22]. However, the band spectra features usually consist of a series of overlapping lines, which might undermine the profile features of the harmonic and complicate the signal model in WMS. Moreover, the similarity between overlapping spectrum and intrinsically existed optical fringes might lead to complex signal processing and even disable the measurement [23, 24]. In this paper, a sensitive WMS-based CS2 sensor was reported. Both of CS2 fingerprint spectra and atmospheric interference spectra were examined for the sensor’s spectral region determination. The modulation index of the laser used in the sensor was re-investigated and optimized to minimize overlapping of the harmonic signals and to improve the elimination of the potential spectral interferences when WMS applying for band spectrum. Then the 2nd harmonic signal of the wideband spectrum was processed with empirical mode decomposition (EMD) algorithm to distinguish and remove the optical fringes buried in the detected signal. The sophisticated sensor was 2
set up with a distributed feedback quantum cascade laser (DFB-QCL) and a multipass gas cell, and the sensor performances were verified under laboratory conditionings.
2. Methods 2.1 Wavelength modulation spectroscopy WMS is commonly used in tunable laser absorption spectroscopy (TLAS) to improve the sensitivity for trace gas sensing. The WMS theory has been detailed previously [25, 26] and is therefore only briefly reviewed here, the signal mathematic model is described as well. A periodic sawtooth ramp ridden by a high-frequency sinusoidal is applied to the laser injection current, and the laser wavelength ν(t) is scanned across the transition of gas to be detected: (t ) c a cos t -1
(1) -1
Where νc (cm ) is the center wavenumber of the modulated laser, νa (cm ) is the modulation depth, ω is the radian frequency. In case of ideal conditions, all kinds of interferences are ignored, the modulated absorption signal is detected by a photodetector and then processed using a lock-in amplifier to demodulate the signal at the harmonics nf (1f, 2f, 3f, etc.). The second harmonic component (2f) is commonly used for calculating the concentration of the target gas. In case of optically thin (α(ν)CL＜ 0.05), the ideal 2f signal is modeled as: Aideal 2 f
2I 0 CL a( c a cos )cos 2 d I 0CL 0
(2)
Where I0 is the incident laser intensity, C is the gas concentration, L is the optical path. When I0 and L are constant, the amplitude of 2f signal is proportional to the gas concentration. Practically, apart from the 2f signal descript in Eq. (2), the detected signal consists of random noises and derivation of the optical fringes as well. The optical fringes appear as unpleasant spectral features which usually mixed with the target absorption, and constitute one of the major obstacles in the gas detection based on WMS. Usually, in an carefully designed and fabricated system, the optical fringes are well reduced, and only small residual fringes remains with sine or cosine profiles [27-29]. The random noises en can be seen as little time-varying wiggles superimposed on the true underlying signal, with a pretty small standard deviation [30]. Therefore, the detected signal could be described as: Adetected 2 f e n a j (t ) cos j (t )t Aideal 2 f
(3)
Where aj(t) is the instantaneous amplitude and ωj(t) the instantaneous frequency of jth fringe component, Aideal 2f is the ideal 2f-WMS signal modeled by Eq. (2). The different characters between those different type of components are the keys to recognize them correctly. 2.2 Carbon disulfide spectra region Selection The strong absorption spectra of CS2 and that of potentially atmospheric and industrial interferences were screened to determine the optimized operating wavelength for the sensor. According to the Pacific Northwest National Laboratory (PNNL) database [31], three fundamental infrared absorption bands of CS2 are located at ν1 (656.5 cm-1), ν2 (396.7 cm-1), and ν3 (1523 cm-1), respectively. The available CS2 absorption coefficient spectra with obvious absorption from 600 cm-1 to 3400 cm-1 were plotted in Fig. 1. The second strongest absorption region at combination band ν1+ν3, around 2180 cm-1, was considered and shown in the insert panel of the Fig. 1. It might not be the only proper choice, but is based on the operating wavenumber range of the quantum cascade laser that was available in our laboratory. 3
Fig. 1. Absorption coefficient spectra of CS2 (from the PNNL database) over the wavenumber region 600-3400 cm-1 with 0.06 cm−1 resolution, 1atm, 296K.
To avoid strong interference from ambient atmosphere, the atmospheric spectral line (from the HITRAN database) and the calculated absorbance based on the V.E. Zuev Institute of Atmospheric Optics (IAO) standard atmosphere (mean latitude, summer, H = 0) [32] were examined along with the CS2 absorption features of ν1+ν3 band. Fig. 2 shows the absorbance of CS2 with 1 ppm×m versus that of IAO atmosphere with 1 m optical path length. Around the CS2 absorption peak at 2177.6 cm-1, there is no interference spectra from atmospheric abundant gases of CO2 and H2O, and very little interference from trace gas of N2O with the small absorbance and the space as far as 0.4 cm-1. Fig. 2. Absorption spectra of the CS2 at concentrations of 1 ppm×m (from the PNNL database) versus IAO atmospheric model (from the HITRAN database) at 1 m optical path, 1atm, 296K.
Furthermore, the absorption spectra of the mostly co-existing compounds, such as SO2, H2S, CS and NH3 were examined as well. No obvious absorption was found around the spectral region 2177.6 cm-1. Hence, it was demonstrated that the CS2 absorption at 2177.6 cm-1 suffers bare disturbance and thus it must be a preferred selection for a CS2 spectral sensor. 2.3 Sensor setup The proposed CS2 sensor was comprised of a DFB-QCL (QD4580CM1, Thorlabs Inc.) with wavelength of 4.59 μm and power of 40 mW, a multipass gas cell with path length variable from 2 m to 100 m, a mid-infrared pre-amplified photodetector (PDA20H, Thorlabs Inc.) with bandwidth of 10 kHz, a laser controller (QCL1500+, Wavelength Electronics Inc.) with super-low current noise of 3nA/√Hz, and a home-made digital lock-in amplifier (DLIA). The DLIA consists of a direct digital synthesis, a phase sensitive detector, an digital low-pass filter with selectable order and time constant, and an embedded processor. The schematic and photograph of the CS2 sensor were shown in Fig. 3. Fig. 3. (a) Schematic of CS2 sensor employing a 4590nm QCL as a spectroscopic source and multipass gas cell; (b) Photograph of primary components of the sensor, where LCD is the laser controller, PD is the photodetector, MPC is the multipass cell, DLIA is the home-made digital lock-in amplifier.
The optical system was elaborately designed and fabricated to reduce the optical fringes. The optical path length of the gas cell was set as 5 m to guarantee optically thin. The injection current and operating temperature of the DFB-QCL were guaranteed by the laser controller. The laser temperature was set and controlled at 30 ℃ ± 0.005 ℃ by a two-stage thermo-electric cooler (TEC). The laser injection current was swept from 525 mA to 565 mA to cover the band spectrum at 2177.6 cm-1 and modulated by sinusoidal frequency of 2.56 KHz, which was limited by the bandwidth of the PD and optimized to reduce the quantization error in the DLIA. And the modulation index was further investigated in the section 2.3 to meet the WMS for the band spectrum of CS2. The 2f-WMS signal was demodulated and processed with the DLIA to calculate the concentration of CS2. 2.4 Optimizing the modulation index The modulation index always plays a pivotal role in WMS measurement. Modulation index of 2.2 is recognized as the optimum to achieve the maximum SNR for WMS with isolated spectrum line. However, the 2f-WMS signal profile with a somewhat bigger modulation index would be broaden and overlapped by the adjacent spectrum, interference and optical fringes as well. The overlapping may deteriorate and even disable the WMS measurement, especially for band spectra. So the modulation index determination should balance the spectral discrimination and the SNR in WMS for a band spectrum. 4
The 2f-WMS signal profile of band spectrum with modulation index was re-investigated. The CS2 band spectrum around 2177.6 cm-1 was used (shown in Fig. 4(a)), the 2f-WMS signal under modulation index 0.2-2.2 was simulated (shown in Fig. 4(b)). Fig. 3 showed that the overlapping was obviously and heavier with the modulation index bigger than 1.5. In order to evaluate the spectral discrimination of the 2f-WMS signal, a parameter to describe spectral discrimination (SD) was defined, as shown in the insert panel of Fig. 4(b), A and B were the adjacent valleys of 2f neighboring signals, C was the middle point of the line connecting A and B, D point at the signal curve was vertical to C point. The model of SD could be described as: SD
hCD 0.5 hA hB
(4)
Where, hA and hB are the amplitude of absorption valleys A and B, respectively. hCD is the height difference between point C and D. If the neighboring 2f valleys were separated completely, then hCD=( hA + hB)/2, thus SD=1; Else if the neighboring 2f valleys were overlapped completely, the four points A, B, C, D were all coincided, then hCD=0, thus SD=0. So the range of spectral discrimination is obviously from 0 to 1. Fig. 4. (a) 30.5 ppm×5 m CS2 spectra from 2178.5 to 2176.6 cm-1; (b) simulated 2f signals from a series of modulation index over the range 0.2 to 2.2, with an insert describing the definition of spectral discrimination; (c) the spectral discrimination and normalized amplitude of 2f signals under different modulation index
The SD under different modulation index in Fig. 4(b) was calculated and shown in Fig. 4(c). And the normalized amplitude of 2f signals under different modulation index was plotted in Fig. 4(c) as well. The SD and normalized amplitude of 2f signals exhibit reverse with the modulation index. To balance the SD and normalized amplitude of 2f signals, the cross of the two curve, around the modulation index 0.8, should be a good compromise for optimizing WMS for the band spectrum of CS2 detection. 2.5 Removing the optical fringes With the above mentioned optimized modulation index, the profile characteristics of the components descript in Eq. (3) exhibit a distinctive trait. For example, the optical fringes are small and sine or cosine in a well designed and fabricated system [29], which are easy to distinguish with the 2f-WMS signals. So, the EMD algorithm was used to distinguish and remove the optical fringes from the detected signal. EMD is an adaptive signal processing method, which makes the instantaneous frequency of the decomposed signal have physical meaning. Indeed, the EMD has been successfully used in WMS to remove noises from polluted signals[33, 34]. Generally, the anterior IMF components are corresponding to the high frequency noise signal and optical fringes [35], and the sum of the rest IMF components represents for gas absorption signal. The procedure employing EMD to decompose and reconstruct the 2f signal is described in Fig. 5(a), the detected 2f signal was decomposed into IMFs with different characteristics. A reference 2f signal around 2177.6 cm-1 was simulated under the same conditions (temperature and pressure) as the experiments below, while the correlation coefficient (R) between each IMF and the reference 2f signal was calculated. As shown in Fig. 5(b), the reference 2f signal was decomposed into three components by EMD, which could help us to judge the IMFs of detected 2f signal. Fig. 5. Arithmetic flow chart (a) and the detail of simulated reference 2f signal with its IMFs (b).Simulation conditions (T=296K, P=1atm, C=30.5ppm, L=5m, m=0.8)
According to the features such as correlation coefficient and frequency and signal profile, we 5
can distinguish the physical meaning of IMFs. The noise IMF is generally high-frequency and low-amplitude and is easy to remove. The optical fringes IMF could be used to locate interference sources and lead to a purposeful adjustment, which could reduce even remove fringes in ray path. The absorption information is commonly not conform to the criterions of IMF, so it should be described with not just one but several IMFs, which have big correlation coefficient with reference 2f signal and stay symmetric relating to the absorption peak around 2177.6 cm-1. In Fig. 5(b), even the residue component RES is not satisfied with the conditions of IMF, it is definitely a part of the absorption information. The absorption components were added together to reconstruct the unpolluted 2f signal. According to the calibration curve obtained from concentration level experiment, the amplitude of reconstructed 2f signals could be transformed into concentration values, so that we can realize the monitoring of carbon disulfide.
3. Experimental results A series of experiments were carried out based on the above-mentioned sensor configuration. CS2 reference gas with concentration of 30.5 ppm was used to test the sensor. The gas flow was controlled by a mass flow controller (Type 8715, Burkert Inc.) and the flow rate was set to be 500ml/min during the experiments. The modulation index of 0.8 and the integral time of 1 s were adopted to acquire the 2f signal. Firstly, the effectiveness of EMD in removing the optical fringes was tested. Thanks to the well-aligned optical system especially the application of wedge optical windows in the gas cell, most major fringes were already restrained. However, small fringes remains in the 2f signal, as shown in Fig. 6(a). The acquired signal was decomposed into IMFs, as shown in Fig. 6(b). It is worth to note that the correlation coefficient listed in Fig. 6(b) was that between each IMF and the simulated reference 2f signal (shown in Fig. 5b), by which the IMF with sine-like profile and low correlation coefficient was distinguished to be the optical fringes. Benefiting from the outstanding filter in the DLIA, the noises were perfectly restrained and thus they will not appear among IMFs. Fig. 6. The detected 2f signal (a), the collection of IMFs that EMD decomposed from the detected 2f signal (b), and the reconstructed 2f signal versus simulated 2f signal (c), with correlation coefficient of 0.9532
As we can see from fig. 6(b), the IMF1 was very similar to sine wave and correlation coefficient with the reference 2f signal as low as 0.042, in the right of the signal model in Eq. (3), the IMF1 was judged as optical fringes. The IMF2, IMF3, IMF4 are symmetric relating to the absorption peak and all have a correlation coefficient bigger than 0.3, so they stand a good chance of containing absorption information. Compared with Fig. 5(b), although the RES of detected 2f signal had a 0.057 correlation coefficient, it was similar to the RES of reference 2f signal, and due to the small tuning range of the QCL, the RES put up few periodical character. So in our conjecture, RES should be judged as a part of absorption information instead of fringes and thus it was kept back in the reconstruct processing. The component IMF1 was subtracted from the detected 2f signal to reconstruct the 2f signal. As indicated in Fig. 6(c), due to the eliminating of optical fringe illustrated by IMF1, the reconstructed 2f signal became very smooth and similar to the simulated 2f signal. The correlation coefficient between the simulated and reconstructed 2f signals was as high as 0.95, which indicated that few absorption information was lost in the procedures of decomposition and reconstruction. Thanks to the completeness of EMD, the absorption line shape suffered little distortion. Secondly, to verify the sensor performances, a set of concentration experiments were conducted. Nine dilute mixtures of CS2 in N2 was configured at levels of 0.61, 1.525, 2.44, 6.1, 9.15, 12.2, 15.25, 6
18.3, 30.5 ppm. EMD was employed to decompose and reconstruct each group of 2f signal, as can be seen in Fig. 7, the measured 2f signals at different CS2 levels were plotted, while a linear fitting was executed between the 2f amplitudes and the expected concentration values; in addition, the measurement error after calibration was calculated. Fig. 7. The reconstructed 2f signals (a) of CS2 at various concentrations from 0.61ppm to 30.5ppm, and the linear relation(b) with fitting error(c) between the measured and expected concentration values
From fig. 7(a), we conclude that the 2f-WMS amplitude was increased with the expected concentration of CS2, the fitting result in Fig. 7(b) showed there was a very good linearity (0.9996) between the amplitude of 2f signal and the CS2 concentration, and from the residual between the measured and expected concentration, the maximum measurement error was -0.3 ppm, which means that the relative error is less than 1 %. Finally, the detection limit of the sensor was evaluated with a continuous measurement of the CS2 reference gas for 40 minutes. The measurement values and the calculated Allan variance are shown in Fig. 8. The Allan variance indicates that the sensor achieved a sensitivity of 200 ppb with a measurement rate of 1 Hz, as shown in Figure 8(b). which can meet the requirement of atmospheric environment monitoring for CS2. The 1σ detection limit is 19.5 ppb with an integration time of 240 s, which corresponded to an absorbance of 3×10-5. Fig. 8. Measurement results (a) of 30.5 ppm CS2 concentration during 40 min at 1-s response time, with the corresponding “Allan Plot” (b) as a function of integration time. The minimum indicates that it achieved 19.5 ppb with a 240 s integration time.
4. Discussion It is demonstrated that the sensor achieves high-sensitivity. The detection limit of absorbance 3×10-5 is almost 2-order lower than that in direct absorption spectroscopy, and is near that in WMS with an isolated line spectrum. The sensor benefits the strong fingerprint absorption and the methods of applying WMS for band spectrum. Though the adopted modulation index 0.8 might sacrifice the 2f signal amplitude about 40 % than that of 2.2 according to the literature [26, 36], however the gain from removing optical fringes by the proposed methods has completely compensated and even exceeded the loss of the signal-background-ratio (SBR) [29]. Indeed, the optical fringes removing in WMS for band spectrum depends on the spectral discrimination, i.e. the modulation index. The sensitivity of the sensor, i.e. commonly used 3σ detection limit, is 60 ppb corresponding to the Allan variance of 19.5 ppb with optical path length of 5 m, which can meet the requirement of atmospheric environment monitoring for CS2. A lower detection limit of sub-ppb level can be accomplished by the maximum optical path length 100 m of the gas cell in the sensor. Moreover, increasing modulation frequency as well as applying a detector with higher bandwidth is also promising to realize further improvements. By this way, the improved CS2 sensor will achieve more outstanding performance in applications. The methods reported in this paper are to enable the WMS for band spectrum by comprising the Spectral Discrimination (SD) and the amplitude of the 2nd harmonic signal, and then effectively eliminate the significant interference of optical fringes in the system. The parameter SD is used to descript and evaluate the level of the overlapping for the 2f signal. The optimized modulation index may changed with the profile of the target band spectrum, however, the SD should be larger than 0.5 in all circumstances to assure the WMS measurement. 7
Additionally, the procedure of analyzing the IMFs, shown in Fig. 6, is aiming to judge whether a IMF is the optical fringes, and to demonstrate the method. Therefore it is not necessary to repeat the analyzing procedure in a practical sensor. We only need to decompose the detected signal with EMD and subtract the optical fringe components from the results, and then to calculate the gas concentration. Moreover, the performance of EMD is not sensitive to the shift of the optical fringes and barely relies on high SNR of the signal [34]. Nevertheless, EMD also has limitations, and thus it could not always separate components perfectly [37]. If there is few difference between the optical fringes and the absorption signal, it will be difficult for us to discern them. Fortunately, in most cases the spectra line profiles are always distinct from the optical fringes.
5. Conclusion A high-sensitive carbon disulfide sensor based on WMS in the mid-infrared fingerprint region is reported in this paper. The sensor works at the strong band absorption near 2177.6 cm-1, which can avoid both the atmospheric and industrial spectral interference. The optimized modulation index reasonably balance the spectral discrimination and the SNR in WMS for a band spectrum. So the optical fringes buried in the detected signal can be easily distinguished and removed by EMD algorithm. The sensor achieved a excellent response linearity of 0.999, and a pretty good detection limit of 19.5 ppb corresponding to absorbance of 3×10-5. The sensor benefits from the strong fingerprint absorption and the methods of applying WMS for band spectrum, and it is promising for environmental CS2 detection and industrial applications. The methods report in this paper, optimizing the modulation index and removing optical fringes by EMD, are robust and versatile, which can also be applied to detect other volatile organic compounds for band absorption by the modified WMS in the mid-infrared strong fingerprint region.
Acknowledgements This work is supported by the Special-funded Program on National Key Scientific Instruments Equipment Development (2012YQ06016501) of China, the National Natural Science Foundation of China (61505142) and the Tianjin Natural Science Foundation (16JCQNJC02100).
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Biographies Zhenhui Du received his Ph.D. in 2004 from Tianjin University, China. Now he is an associate professor in Tianjin University. His research interests cover the following sectors: optical measurement technology, environment monitoring, weak signal detection and processing. Jinyi Li received his Ph.D. in 2013 from Tianjin University, China. Now he is a lecturer in Tianjin Polytechnic University, China. His research interests are focused mainly on spectroscopic detection and laser gas sensors. Xiuhan Cao received his B.S. degree in 2010 from Hebei University Of Technology, China. Now he is a MS student of instrument and meter engineering at Tianjin University, China. He works on tunable laser spectroscopy and WMS-based sensors. Hong Gao received her B.S. degree in 2010 from Hebei University Of Technology, China. Now she is a MS student of instrument and meter engineering at Tianjin University, China. She works on tunable laser spectroscopy and absolute spectrum measurement. Yiwen Ma received her Ph.D. in 2009 from Tianjin University, China. Now she is an associate professor in Tianjin University. Her research interests are focused mainly on spectroscopic detection and environmental applications.
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S0925-4005(17)30457-4 http://dx.doi.org/doi:10.1016/j.snb.2017.03.040 SNB 21952
To appear in:
Sensors and Actuators B
Received date: Revised date: Accepted date:
26-7-2016 7-3-2017 10-3-2017
Please cite this article as: Zhenhui Du, Jinyi Li, Xiuhan Cao, Hong Gao, Yiwen Ma, High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region, Sensors and Actuators B: Chemical http://dx.doi.org/10.1016/j.snb.2017.03.040 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
High-sensitive carbon disulfide sensor using wavelength modulation spectroscopy in the mid-infrared fingerprint region Zhenhui Dua, b*, Jinyi Lic, Xiuhan Caoa, Hong Gaoa, Yiwen Maa a. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, China b.Department of chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America c. Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin, China
Highlights 1. A CS2 sensor with high-sensitive of detection limit 19.5ppb, corresponding absorbance as 3×10-5 for band spectrum was provided. 2. The optimized modulation index reasonably balanced the spectral discrimination and the SNR in WMS with band spectrum. 3. The optical fringes buried in the detected signal was distinguished and removed by EMD algorithm. 4. The robust and versatile method enabling WMS to band spectrum is instructive for VOCs detection.
Abstract A sensitive carbon disulfide (CS2) sensor based on wavelength modulation spectroscopy (WMS) in the mid-infrared fingerprint region was reported. The strong band spectrum of carbon disulfide's combination band (ν1+ν3), near 2177.6 cm-1, was used in the sensor. To enable WMS for wideband spectrum, a parameter of Spectral Discrimination (SD) was defined and used as a criterion for optimizing the modulation index, which was finally determined to be around 0.8 instead of 2.2 commonly used for a isolated line spectrum. And the second harmonic signal was processed with empirical mode decomposition (EMD) algorithm to distinguish and remove the optical fringes buried in the detected signal. The sensor performances were tested by implementing a set of CS2 concentration experiments. The results showed that the sensor response linearity was 0.999 and the relative measuring error was less than 1 %. The sensitivity, i. e. 3σ detection limit, was as low as 60 ppb with integration time of 240 s with optical path length of 5 m, corresponding to absorbance of 3×10-5. Overall, benefiting from strong fingerprint absorption and methods of applying WMS to wideband spectrum, the sensor is promising for both environmental and industrial CS2 detection. *
Corresponding author. Tel.: +86 22 2740 3290; Fax: +86 22 2740 3290 E-mail address: [email protected] (Zhenhui Du) Current address: Department of chemistry, MIT, Cambridge, United States of America 1
Keywords: CS2 sensor, Tunable laser absorption spectroscopy (TLAS), wavelength modulation spectroscopy (WMS), mid-infrared fingerprints, wideband spectrum, distributed feedback quantum cascade laser (DFB-QCL), optical fringes, empirical mode decomposition (EMD)
1. Introduction Carbon disulfide (CS2) is a toxic volatile sulfur compound (VSC) with stinky smell and is extensively produced by both natural and anthropogenic sources [1]. Natural sources include soils and oceans [2], food wastes [3], marshland and volcano eruptions [4]. Anthropogenic emissions derive from biomass burning and chemical uses [2], rayon fiber and cellophane productions[5]. CS2 is not only a harmful air pollutant which participates in atmospheric photochemical reactions, but also combustible and dangerous for industrial safety. What’s more, exposure to even low level of CS2 may increase health risks in especial nervous diseases [6]. Atmospheric CS2 concentration threshold limits of 6.7 ppm and 10 ppm in workplace are recommended by the U. S. Environmental Protection Agency (EPA) [7] and the National Institute for Occupational Safety and Health (NIOSH) [8], respectively. Hence, it is essential to detect environmental and industrial CS2 with real time, in situ at sub-ppm or even lower level. Common methods for detecting CS2 include combined gas chromatography and mass spectroscopy (GC-MS) [9-11], gas sensors [12, 13] and optical spectroscopy [14-16]. GC-MS provides specific and sensitive analysis with high accuracy and precision, however, it is time-consuming and costly. A magnesium metal-organic framework compounds based fluorescence sensor may be limited by the low response time for its adsorption [12]. A nanosized-CeO2 chemiluminescence based carbon disulfide sensor has high sensitivity [13], however the strict conditions for catalytic oxidation reaction may be very difficult to meet in field. Optical spectroscopy is useful tool for molecular transition researching and high-sensitivity sensing with selectivity. Blanque et al. [14] investigate the absorption spectra of CS2 in the 2800-3000 cm-1 region with high-resolution FTS, and provide new spectra data for global analysis of this molecule. Yu et al. [15] observe atmospheric CS2 with ultraviolet differential optical absorption spectroscopy, and a open path of 1.4 km is used to achieve a detection limit around 2 ppb. Waclawek et al. [16] demonstrate a CS2 sensor based on quartz-enhanced photoacoustic spectroscopy with 1σ detection limit of 28 ppb depending on concentration of water vapor. Wavelength modulation spectroscopy (WMS) has been demonstrated to have high sensitivity for in situ, real time sensing of trace gas with isolated line spectrum [17-24]. Mid-infrared region is especially attractive for strong fingerprint absorption of many compounds [20-22]. However, the band spectra features usually consist of a series of overlapping lines, which might undermine the profile features of the harmonic and complicate the signal model in WMS. Moreover, the similarity between overlapping spectrum and intrinsically existed optical fringes might lead to complex signal processing and even disable the measurement [23, 24]. In this paper, a sensitive WMS-based CS2 sensor was reported. Both of CS2 fingerprint spectra and atmospheric interference spectra were examined for the sensor’s spectral region determination. The modulation index of the laser used in the sensor was re-investigated and optimized to minimize overlapping of the harmonic signals and to improve the elimination of the potential spectral interferences when WMS applying for band spectrum. Then the 2nd harmonic signal of the wideband spectrum was processed with empirical mode decomposition (EMD) algorithm to distinguish and remove the optical fringes buried in the detected signal. The sophisticated sensor was 2
set up with a distributed feedback quantum cascade laser (DFB-QCL) and a multipass gas cell, and the sensor performances were verified under laboratory conditionings.
2. Methods 2.1 Wavelength modulation spectroscopy WMS is commonly used in tunable laser absorption spectroscopy (TLAS) to improve the sensitivity for trace gas sensing. The WMS theory has been detailed previously [25, 26] and is therefore only briefly reviewed here, the signal mathematic model is described as well. A periodic sawtooth ramp ridden by a high-frequency sinusoidal is applied to the laser injection current, and the laser wavelength ν(t) is scanned across the transition of gas to be detected: (t ) c a cos t -1
(1) -1
Where νc (cm ) is the center wavenumber of the modulated laser, νa (cm ) is the modulation depth, ω is the radian frequency. In case of ideal conditions, all kinds of interferences are ignored, the modulated absorption signal is detected by a photodetector and then processed using a lock-in amplifier to demodulate the signal at the harmonics nf (1f, 2f, 3f, etc.). The second harmonic component (2f) is commonly used for calculating the concentration of the target gas. In case of optically thin (α(ν)CL＜ 0.05), the ideal 2f signal is modeled as: Aideal 2 f
2I 0 CL a( c a cos )cos 2 d I 0CL 0
(2)
Where I0 is the incident laser intensity, C is the gas concentration, L is the optical path. When I0 and L are constant, the amplitude of 2f signal is proportional to the gas concentration. Practically, apart from the 2f signal descript in Eq. (2), the detected signal consists of random noises and derivation of the optical fringes as well. The optical fringes appear as unpleasant spectral features which usually mixed with the target absorption, and constitute one of the major obstacles in the gas detection based on WMS. Usually, in an carefully designed and fabricated system, the optical fringes are well reduced, and only small residual fringes remains with sine or cosine profiles [27-29]. The random noises en can be seen as little time-varying wiggles superimposed on the true underlying signal, with a pretty small standard deviation [30]. Therefore, the detected signal could be described as: Adetected 2 f e n a j (t ) cos j (t )t Aideal 2 f
(3)
Where aj(t) is the instantaneous amplitude and ωj(t) the instantaneous frequency of jth fringe component, Aideal 2f is the ideal 2f-WMS signal modeled by Eq. (2). The different characters between those different type of components are the keys to recognize them correctly. 2.2 Carbon disulfide spectra region Selection The strong absorption spectra of CS2 and that of potentially atmospheric and industrial interferences were screened to determine the optimized operating wavelength for the sensor. According to the Pacific Northwest National Laboratory (PNNL) database [31], three fundamental infrared absorption bands of CS2 are located at ν1 (656.5 cm-1), ν2 (396.7 cm-1), and ν3 (1523 cm-1), respectively. The available CS2 absorption coefficient spectra with obvious absorption from 600 cm-1 to 3400 cm-1 were plotted in Fig. 1. The second strongest absorption region at combination band ν1+ν3, around 2180 cm-1, was considered and shown in the insert panel of the Fig. 1. It might not be the only proper choice, but is based on the operating wavenumber range of the quantum cascade laser that was available in our laboratory. 3
Fig. 1. Absorption coefficient spectra of CS2 (from the PNNL database) over the wavenumber region 600-3400 cm-1 with 0.06 cm−1 resolution, 1atm, 296K.
To avoid strong interference from ambient atmosphere, the atmospheric spectral line (from the HITRAN database) and the calculated absorbance based on the V.E. Zuev Institute of Atmospheric Optics (IAO) standard atmosphere (mean latitude, summer, H = 0) [32] were examined along with the CS2 absorption features of ν1+ν3 band. Fig. 2 shows the absorbance of CS2 with 1 ppm×m versus that of IAO atmosphere with 1 m optical path length. Around the CS2 absorption peak at 2177.6 cm-1, there is no interference spectra from atmospheric abundant gases of CO2 and H2O, and very little interference from trace gas of N2O with the small absorbance and the space as far as 0.4 cm-1. Fig. 2. Absorption spectra of the CS2 at concentrations of 1 ppm×m (from the PNNL database) versus IAO atmospheric model (from the HITRAN database) at 1 m optical path, 1atm, 296K.
Furthermore, the absorption spectra of the mostly co-existing compounds, such as SO2, H2S, CS and NH3 were examined as well. No obvious absorption was found around the spectral region 2177.6 cm-1. Hence, it was demonstrated that the CS2 absorption at 2177.6 cm-1 suffers bare disturbance and thus it must be a preferred selection for a CS2 spectral sensor. 2.3 Sensor setup The proposed CS2 sensor was comprised of a DFB-QCL (QD4580CM1, Thorlabs Inc.) with wavelength of 4.59 μm and power of 40 mW, a multipass gas cell with path length variable from 2 m to 100 m, a mid-infrared pre-amplified photodetector (PDA20H, Thorlabs Inc.) with bandwidth of 10 kHz, a laser controller (QCL1500+, Wavelength Electronics Inc.) with super-low current noise of 3nA/√Hz, and a home-made digital lock-in amplifier (DLIA). The DLIA consists of a direct digital synthesis, a phase sensitive detector, an digital low-pass filter with selectable order and time constant, and an embedded processor. The schematic and photograph of the CS2 sensor were shown in Fig. 3. Fig. 3. (a) Schematic of CS2 sensor employing a 4590nm QCL as a spectroscopic source and multipass gas cell; (b) Photograph of primary components of the sensor, where LCD is the laser controller, PD is the photodetector, MPC is the multipass cell, DLIA is the home-made digital lock-in amplifier.
The optical system was elaborately designed and fabricated to reduce the optical fringes. The optical path length of the gas cell was set as 5 m to guarantee optically thin. The injection current and operating temperature of the DFB-QCL were guaranteed by the laser controller. The laser temperature was set and controlled at 30 ℃ ± 0.005 ℃ by a two-stage thermo-electric cooler (TEC). The laser injection current was swept from 525 mA to 565 mA to cover the band spectrum at 2177.6 cm-1 and modulated by sinusoidal frequency of 2.56 KHz, which was limited by the bandwidth of the PD and optimized to reduce the quantization error in the DLIA. And the modulation index was further investigated in the section 2.3 to meet the WMS for the band spectrum of CS2. The 2f-WMS signal was demodulated and processed with the DLIA to calculate the concentration of CS2. 2.4 Optimizing the modulation index The modulation index always plays a pivotal role in WMS measurement. Modulation index of 2.2 is recognized as the optimum to achieve the maximum SNR for WMS with isolated spectrum line. However, the 2f-WMS signal profile with a somewhat bigger modulation index would be broaden and overlapped by the adjacent spectrum, interference and optical fringes as well. The overlapping may deteriorate and even disable the WMS measurement, especially for band spectra. So the modulation index determination should balance the spectral discrimination and the SNR in WMS for a band spectrum. 4
The 2f-WMS signal profile of band spectrum with modulation index was re-investigated. The CS2 band spectrum around 2177.6 cm-1 was used (shown in Fig. 4(a)), the 2f-WMS signal under modulation index 0.2-2.2 was simulated (shown in Fig. 4(b)). Fig. 3 showed that the overlapping was obviously and heavier with the modulation index bigger than 1.5. In order to evaluate the spectral discrimination of the 2f-WMS signal, a parameter to describe spectral discrimination (SD) was defined, as shown in the insert panel of Fig. 4(b), A and B were the adjacent valleys of 2f neighboring signals, C was the middle point of the line connecting A and B, D point at the signal curve was vertical to C point. The model of SD could be described as: SD
hCD 0.5 hA hB
(4)
Where, hA and hB are the amplitude of absorption valleys A and B, respectively. hCD is the height difference between point C and D. If the neighboring 2f valleys were separated completely, then hCD=( hA + hB)/2, thus SD=1; Else if the neighboring 2f valleys were overlapped completely, the four points A, B, C, D were all coincided, then hCD=0, thus SD=0. So the range of spectral discrimination is obviously from 0 to 1. Fig. 4. (a) 30.5 ppm×5 m CS2 spectra from 2178.5 to 2176.6 cm-1; (b) simulated 2f signals from a series of modulation index over the range 0.2 to 2.2, with an insert describing the definition of spectral discrimination; (c) the spectral discrimination and normalized amplitude of 2f signals under different modulation index
The SD under different modulation index in Fig. 4(b) was calculated and shown in Fig. 4(c). And the normalized amplitude of 2f signals under different modulation index was plotted in Fig. 4(c) as well. The SD and normalized amplitude of 2f signals exhibit reverse with the modulation index. To balance the SD and normalized amplitude of 2f signals, the cross of the two curve, around the modulation index 0.8, should be a good compromise for optimizing WMS for the band spectrum of CS2 detection. 2.5 Removing the optical fringes With the above mentioned optimized modulation index, the profile characteristics of the components descript in Eq. (3) exhibit a distinctive trait. For example, the optical fringes are small and sine or cosine in a well designed and fabricated system [29], which are easy to distinguish with the 2f-WMS signals. So, the EMD algorithm was used to distinguish and remove the optical fringes from the detected signal. EMD is an adaptive signal processing method, which makes the instantaneous frequency of the decomposed signal have physical meaning. Indeed, the EMD has been successfully used in WMS to remove noises from polluted signals[33, 34]. Generally, the anterior IMF components are corresponding to the high frequency noise signal and optical fringes [35], and the sum of the rest IMF components represents for gas absorption signal. The procedure employing EMD to decompose and reconstruct the 2f signal is described in Fig. 5(a), the detected 2f signal was decomposed into IMFs with different characteristics. A reference 2f signal around 2177.6 cm-1 was simulated under the same conditions (temperature and pressure) as the experiments below, while the correlation coefficient (R) between each IMF and the reference 2f signal was calculated. As shown in Fig. 5(b), the reference 2f signal was decomposed into three components by EMD, which could help us to judge the IMFs of detected 2f signal. Fig. 5. Arithmetic flow chart (a) and the detail of simulated reference 2f signal with its IMFs (b).Simulation conditions (T=296K, P=1atm, C=30.5ppm, L=5m, m=0.8)
According to the features such as correlation coefficient and frequency and signal profile, we 5
can distinguish the physical meaning of IMFs. The noise IMF is generally high-frequency and low-amplitude and is easy to remove. The optical fringes IMF could be used to locate interference sources and lead to a purposeful adjustment, which could reduce even remove fringes in ray path. The absorption information is commonly not conform to the criterions of IMF, so it should be described with not just one but several IMFs, which have big correlation coefficient with reference 2f signal and stay symmetric relating to the absorption peak around 2177.6 cm-1. In Fig. 5(b), even the residue component RES is not satisfied with the conditions of IMF, it is definitely a part of the absorption information. The absorption components were added together to reconstruct the unpolluted 2f signal. According to the calibration curve obtained from concentration level experiment, the amplitude of reconstructed 2f signals could be transformed into concentration values, so that we can realize the monitoring of carbon disulfide.
3. Experimental results A series of experiments were carried out based on the above-mentioned sensor configuration. CS2 reference gas with concentration of 30.5 ppm was used to test the sensor. The gas flow was controlled by a mass flow controller (Type 8715, Burkert Inc.) and the flow rate was set to be 500ml/min during the experiments. The modulation index of 0.8 and the integral time of 1 s were adopted to acquire the 2f signal. Firstly, the effectiveness of EMD in removing the optical fringes was tested. Thanks to the well-aligned optical system especially the application of wedge optical windows in the gas cell, most major fringes were already restrained. However, small fringes remains in the 2f signal, as shown in Fig. 6(a). The acquired signal was decomposed into IMFs, as shown in Fig. 6(b). It is worth to note that the correlation coefficient listed in Fig. 6(b) was that between each IMF and the simulated reference 2f signal (shown in Fig. 5b), by which the IMF with sine-like profile and low correlation coefficient was distinguished to be the optical fringes. Benefiting from the outstanding filter in the DLIA, the noises were perfectly restrained and thus they will not appear among IMFs. Fig. 6. The detected 2f signal (a), the collection of IMFs that EMD decomposed from the detected 2f signal (b), and the reconstructed 2f signal versus simulated 2f signal (c), with correlation coefficient of 0.9532
As we can see from fig. 6(b), the IMF1 was very similar to sine wave and correlation coefficient with the reference 2f signal as low as 0.042, in the right of the signal model in Eq. (3), the IMF1 was judged as optical fringes. The IMF2, IMF3, IMF4 are symmetric relating to the absorption peak and all have a correlation coefficient bigger than 0.3, so they stand a good chance of containing absorption information. Compared with Fig. 5(b), although the RES of detected 2f signal had a 0.057 correlation coefficient, it was similar to the RES of reference 2f signal, and due to the small tuning range of the QCL, the RES put up few periodical character. So in our conjecture, RES should be judged as a part of absorption information instead of fringes and thus it was kept back in the reconstruct processing. The component IMF1 was subtracted from the detected 2f signal to reconstruct the 2f signal. As indicated in Fig. 6(c), due to the eliminating of optical fringe illustrated by IMF1, the reconstructed 2f signal became very smooth and similar to the simulated 2f signal. The correlation coefficient between the simulated and reconstructed 2f signals was as high as 0.95, which indicated that few absorption information was lost in the procedures of decomposition and reconstruction. Thanks to the completeness of EMD, the absorption line shape suffered little distortion. Secondly, to verify the sensor performances, a set of concentration experiments were conducted. Nine dilute mixtures of CS2 in N2 was configured at levels of 0.61, 1.525, 2.44, 6.1, 9.15, 12.2, 15.25, 6
18.3, 30.5 ppm. EMD was employed to decompose and reconstruct each group of 2f signal, as can be seen in Fig. 7, the measured 2f signals at different CS2 levels were plotted, while a linear fitting was executed between the 2f amplitudes and the expected concentration values; in addition, the measurement error after calibration was calculated. Fig. 7. The reconstructed 2f signals (a) of CS2 at various concentrations from 0.61ppm to 30.5ppm, and the linear relation(b) with fitting error(c) between the measured and expected concentration values
From fig. 7(a), we conclude that the 2f-WMS amplitude was increased with the expected concentration of CS2, the fitting result in Fig. 7(b) showed there was a very good linearity (0.9996) between the amplitude of 2f signal and the CS2 concentration, and from the residual between the measured and expected concentration, the maximum measurement error was -0.3 ppm, which means that the relative error is less than 1 %. Finally, the detection limit of the sensor was evaluated with a continuous measurement of the CS2 reference gas for 40 minutes. The measurement values and the calculated Allan variance are shown in Fig. 8. The Allan variance indicates that the sensor achieved a sensitivity of 200 ppb with a measurement rate of 1 Hz, as shown in Figure 8(b). which can meet the requirement of atmospheric environment monitoring for CS2. The 1σ detection limit is 19.5 ppb with an integration time of 240 s, which corresponded to an absorbance of 3×10-5. Fig. 8. Measurement results (a) of 30.5 ppm CS2 concentration during 40 min at 1-s response time, with the corresponding “Allan Plot” (b) as a function of integration time. The minimum indicates that it achieved 19.5 ppb with a 240 s integration time.
4. Discussion It is demonstrated that the sensor achieves high-sensitivity. The detection limit of absorbance 3×10-5 is almost 2-order lower than that in direct absorption spectroscopy, and is near that in WMS with an isolated line spectrum. The sensor benefits the strong fingerprint absorption and the methods of applying WMS for band spectrum. Though the adopted modulation index 0.8 might sacrifice the 2f signal amplitude about 40 % than that of 2.2 according to the literature [26, 36], however the gain from removing optical fringes by the proposed methods has completely compensated and even exceeded the loss of the signal-background-ratio (SBR) [29]. Indeed, the optical fringes removing in WMS for band spectrum depends on the spectral discrimination, i.e. the modulation index. The sensitivity of the sensor, i.e. commonly used 3σ detection limit, is 60 ppb corresponding to the Allan variance of 19.5 ppb with optical path length of 5 m, which can meet the requirement of atmospheric environment monitoring for CS2. A lower detection limit of sub-ppb level can be accomplished by the maximum optical path length 100 m of the gas cell in the sensor. Moreover, increasing modulation frequency as well as applying a detector with higher bandwidth is also promising to realize further improvements. By this way, the improved CS2 sensor will achieve more outstanding performance in applications. The methods reported in this paper are to enable the WMS for band spectrum by comprising the Spectral Discrimination (SD) and the amplitude of the 2nd harmonic signal, and then effectively eliminate the significant interference of optical fringes in the system. The parameter SD is used to descript and evaluate the level of the overlapping for the 2f signal. The optimized modulation index may changed with the profile of the target band spectrum, however, the SD should be larger than 0.5 in all circumstances to assure the WMS measurement. 7
Additionally, the procedure of analyzing the IMFs, shown in Fig. 6, is aiming to judge whether a IMF is the optical fringes, and to demonstrate the method. Therefore it is not necessary to repeat the analyzing procedure in a practical sensor. We only need to decompose the detected signal with EMD and subtract the optical fringe components from the results, and then to calculate the gas concentration. Moreover, the performance of EMD is not sensitive to the shift of the optical fringes and barely relies on high SNR of the signal [34]. Nevertheless, EMD also has limitations, and thus it could not always separate components perfectly [37]. If there is few difference between the optical fringes and the absorption signal, it will be difficult for us to discern them. Fortunately, in most cases the spectra line profiles are always distinct from the optical fringes.
5. Conclusion A high-sensitive carbon disulfide sensor based on WMS in the mid-infrared fingerprint region is reported in this paper. The sensor works at the strong band absorption near 2177.6 cm-1, which can avoid both the atmospheric and industrial spectral interference. The optimized modulation index reasonably balance the spectral discrimination and the SNR in WMS for a band spectrum. So the optical fringes buried in the detected signal can be easily distinguished and removed by EMD algorithm. The sensor achieved a excellent response linearity of 0.999, and a pretty good detection limit of 19.5 ppb corresponding to absorbance of 3×10-5. The sensor benefits from the strong fingerprint absorption and the methods of applying WMS for band spectrum, and it is promising for environmental CS2 detection and industrial applications. The methods report in this paper, optimizing the modulation index and removing optical fringes by EMD, are robust and versatile, which can also be applied to detect other volatile organic compounds for band absorption by the modified WMS in the mid-infrared strong fingerprint region.
Acknowledgements This work is supported by the Special-funded Program on National Key Scientific Instruments Equipment Development (2012YQ06016501) of China, the National Natural Science Foundation of China (61505142) and the Tianjin Natural Science Foundation (16JCQNJC02100).
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Biographies Zhenhui Du received his Ph.D. in 2004 from Tianjin University, China. Now he is an associate professor in Tianjin University. His research interests cover the following sectors: optical measurement technology, environment monitoring, weak signal detection and processing. Jinyi Li received his Ph.D. in 2013 from Tianjin University, China. Now he is a lecturer in Tianjin Polytechnic University, China. His research interests are focused mainly on spectroscopic detection and laser gas sensors. Xiuhan Cao received his B.S. degree in 2010 from Hebei University Of Technology, China. Now he is a MS student of instrument and meter engineering at Tianjin University, China. He works on tunable laser spectroscopy and WMS-based sensors. Hong Gao received her B.S. degree in 2010 from Hebei University Of Technology, China. Now she is a MS student of instrument and meter engineering at Tianjin University, China. She works on tunable laser spectroscopy and absolute spectrum measurement. Yiwen Ma received her Ph.D. in 2009 from Tianjin University, China. Now she is an associate professor in Tianjin University. Her research interests are focused mainly on spectroscopic detection and environmental applications.
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