Open Access
Add to BibSonomy
Abstract
An optimized remote material detection scheme based on the laser filament-induced plasma spectroscopy and light detection and ranging (FIPS-LIDAR) is proposed in this work. The elemental composition and concentration of aerosol are measured by FIPS-LIDAR. By focusing the femtosecond laser with a large aperture (Φ41 cm) concave mirror and coaxial fluorescence collection scheme, the remote detection of aerosol in air at μg/m3 level has been realized at a distance of 30 m. The limit of detection for Na+ in aerosol droplets is 8 ppm (3 μg/m3 in air), which is the lowest detection limit that has been reported using millijoule femtosecond laser pulse (4.4 mJ). Furthermore, using spectral preprocessing and optimization of the proposed significance of peak (SOP) algorithm, feature peak signals are extracted from weak signals and the limit of detection can be further decreased to 1.4 μg/m3.
© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Intense femtosecond laser propagation in atmosphere will be manifested as a unique phenomenon, namely, filamentation [1]. During the filamentation, the laser beam will be constrained inside a thin cylindrical volume with a diameter of ∼102 μm and the laser intensity inside the filament could be as high as 1014 W/cm2 [2]. The filament with high intensity could extend to a distance even further than a few tens kilometers [3]. Due to the high laser intensity, the molecule and atom will be ionized during the filamentation, producing a long plasma channel, which is normally intuitively referred to a filament [4].
Since the discovery of femtosecond laser filamentation in atmosphere, it has been expected as an attractive LIDAR technique of real-time remote sensing of atmospheric aerosol composition. The current general methods of atmospheric aerosol composition detection, such as ion chromatography (IC) [5], gas chromatography (GC) [6], X-ray fluorescence (XRF) [7], neutron activation analysis (NAA) [8], atomic absorption spectrometry (AAS) [9], mass spectrometry (MS) [10], etc., always separate aerosol particles from the atmosphere first and then analyze the chemical composition of the sample in laboratory. These methods can achieve accurate quantitative measurement. However, they cannot perform in-situ and real-time measurements and do not have remote sensing capability. In addition, although Fourier Transform infrared spectroscopy (FTIR) [11] may achieve remote sensing of the atmosphere, the technology mainly targets gaseous pollutants, and cannot remotely detect the chemical composition of the aerosol. Contrastingly, based on the femtosecond laser filamentation, different versions of aerosol remote sensing approaches have been studied, including absorption spectroscopy by using the supercontinuum generated during the filamentation [12,13], multiphoton fluorescence [14,15], terahertz spectroscopy [16,17], Raman spectroscopy [18,19] and filament-induced plasma spectroscopy (FIPS) [20,21]. Because of its ability of in-situ, real-time, remote sensing and simultaneous diagnostic of the chemical composition of air pollutants in different forms such as gas, aerosol, solid, etc., FIPS has aroused broad research interests [22–24].
In previous works [25,26], the Teramobile group has demonstrated that filaments can survive after long-distance interaction with aerosols. Then, Xu et al. reported that sharp distinctive fluorescence lines from biotargets could be revealed when the filament-induced time-resolved spectroscopy technique was used [27]. By focusing 130 mJ, 70 fs laser pulses at a focal length of 20 m, Fujii et al. [28] achieved the detection of sodium fluorescence in a cloud of 300 g/L (300000 ppm) salt concentration at a detection distance of 16 m. Using a similar method, Daigle et al. demonstrated that at a salt concentration of 300 mg/L (300 ppm), sodium fingerprint fluorescence could be efficiently distinguished for a laser-pulse energy of 5 mJ at a distance of 5 m [29]. The authors also found that at 50 m, the detection limit was ∼33 ppm with femtosecond laser pulses of 72 mJ. Moreover, Daigle et al. measured the limits of detection for different constituents in aerosol: 127 mg/L (127 ppm) for Fe, 27 mg/L (27 ppm) for Cu, 9 mg/L (9 ppm) for Pb, and 3 mg/L (3 ppm) for Na [30]. Recently, using a femtosecond laser with relatively low pulse energy (4.4 mJ), Golik et al. [31] measured the filament-induced fluorescence of aerosols containing Al, Ba, Na, etc. The detection limit of Na was 0.7 mg/L (0.7 ppm) at a distance of 0.5 m.
It should be noted that the above reported concentration is the mass proportion of the metal element in the aerosol droplet with the unit of ppm (see the black spheres in Fig. 1), which can be calculated by:
where m is the mass of the metal element and M is the mass of the solution. To compare the measurement results with those in the literatures, in this work the identical concentration calculation method is employed. Another concentration calculation method of aerosol is the proportion of pollutants per unit volume of air with the unit of μg/m3, such as the concentration marked next to the red pentagram in Fig. 1, which can be calculated by: where r is the average radius of the aerosol droplets, ρ is the density of the droplet and n represents the number density of aerosol droplets in air. In addition, the concentrations of gaseous pollutants can be expressed directly using their volume proportion or mole proportion in air with the unit of ppm (see the blue tetrahedrons in Fig. 1), which can be calculated by: where v is the volume of the gaseous pollutant and V is the volume of the Air. Figure 1 compares the detection limit of Na measured in this work and the detection limits of other elements in literatures [12,21–26].
Fig. 1. Reported detection limits with different laser energy at different distance [20,29–34]. The black spheres represent the mass proportion of the metal element in droplets, the blue tetrahedrons represent the volume proportion or mole proportion of gas molecules in air, and the red pentagram represents the measurement result in this work.
Although detailed characterization of laser filament has been performed at a distance as far as 1 km [35,36], the remote sensing of air pollutants by using FIPS was reported only up to 118 m [32]. The main obstacles lie in the deterioration of filament quality caused by significant phase distortions introduced during the long-distance propagation of laser pulse in air. Particularly, because the onset distance of the filament is proportional to the square of the initial laser diameters, beam expanding optics are very often implemented. Since it is easier to fabricate, large reflective beam expanding optics are more favorable than the transmission optics in practice. However, one has to face the challenge of severe aberration, such as astigmatism and coma of the reflective beam expanding setup. In order to overcome these difficulties, Daigle et al. have used an adaptive mirror in the beam expander and significantly enhanced the filament-induced backscattered signal [32]. Nevertheless, the application of an adaptive mirror in the scenario of FIPS has to overcome the attenuation and loss of returned fluorescence signal for backward collection.
In this paper, a large-aperture concave mirror with diameter of 41 cm is used as the secondary mirror in a Galileo telescope to expand the intense femtosecond laser beam. A carefully designed freeform surface phase plate is placed between the plano-concave lens and concave mirror to reshape the beam waveform, compensating the astigmatism of the setup. A filament is therefore generated at a distance of 30 m, which is practically limited by the lab size. The excited NaCl aerosol fluorescence signal is collected by the same Galileo telescope at the backward direction. The NaCl aerosol’s detection limit is 3 μg/m3 (PM2.5 = 3) in air, corresponding to 8 ppm (mass concentration) of Na+ in aerosol droplets. By combining the self-developed data processing algorithm, the detection limit could be further improved to 1.4 μg/m3.
2. Experimental setup
The experimental setup is shown in Fig. 2. A commercial Ti: sapphire femtosecond laser amplifier system (Legend elite, Coherent) is used to produce 800 nm, 4.4 mJ femtosecond laser pulses with an FWHM duration of 50 fs and a repetition rate of 500 Hz. A telescope consisting of a plano-concave lens (L1, f = -10 cm) and a large aperture (Φ41 cm) concave mirror (M2, f = 203 cm) is used to produce a filament. The distance between the concave mirror and the middle of the filament is 30 m. Since the laser beam is obliquely incident on the concave mirror, large astigmatism is introduced. A phase compensation plate with high transparency (93.6%) is designed specifically to compensate for astigmatism, which is placed between M2 and the dichroic mirror M1. The NaCl aerosol is produced by a liquid aerosol generator (HRH-WAG3, Huironghe Ltd.) and different concentrations of NaCl solutions are added in the aerosol generator. The generator is connected to a hollow transparent glass tube with a length of 50 cm. The diameter of the tube is 3 cm, and the middle of the filament is located at the opening of the tube. The aerosol is stably injected into the tube by controlling the air pump of the generator. The mean diameter of the particle size inside the tube is around 2 μm measured by an aerodynamic particle size spectrometer (TSI3321, TSI Inc). The transmittance of He–Ne laser through the aerosol-filled glass tube is measured to be 91%, from which a concentration of 0.376 g/m3 for aerosol droplets in air (3 μg/m3 for Na+ in air) is determined.
Fig. 2. Schematic of the experimental setup. Inset: Peak amplitude of the ultrasonic signal as a funciton of the laser propagation distance.
To evaluate the axial distribution of the laser filament, the ultrasonic signal emitted by the filament is measured using an ultrasonic probe (Model V306 OLYMPUS) point by point along the laser propagation direction. In this case, the glass tube is removed. The ultrasonic signal is amplified by an amplifier (Model 5072PR OLYMPUS) and recorded by an oscilloscope. The distribution of ultrasonic signal as a function of the propagation distance z is shown in the inset of Fig. 2, where the beginning and ending positions of the acoustic signal are determined by the intersection of the 3σ (3 times standard deviation of background noise) line and the acoustic intensity curve. The length of the filament characterized by the acoustic intensity curve is around 40 cm, and the left end of the aerosol tube is placed at the middle position of the filament.
The backward fluorescence signal emitted by the filament can be collected by the large concave mirror and the end of the tail fiber of the monochromator (Omni-λ300, Zolix) is placed at the conjugate plane of the glass tube entrance. It is worth mentioning that M1 is a dichroic mirror with a transmittance of 94.9% at 589 nm, ensuring that the aerosol fluorescence signal is transmitted and collected by the fiber. The fiber is mounted on a three-dimensional translation stage to make the end face of the fiber locate at the focal point of the concave mirror M2 (see Fig. 2) and achieve the maximal collection efficiency. Finally, the fluorescence spectrum emitted from the aerosol is measured by an intensified CMOS camera (iStar-sCMOS, Andor).
3. Results and discussion
According to the Beer-Lambert law and equivalent particle size method [37], the linear relation between extinction ratio -ln(I/I0) and mass volume concentration Cm for aerosol droplets in air can be expressed as:
where Km represents the mean extinction coefficient, D32 is the mean particle size, L is the thickness of the aerosol, and ρ is the mass density of the droplet. The mean diameter D32 of the multi-dispersed particle system is defined by: where the particle size distribution N(D) can be measured by the aerodynamic particle size spectrometer (TSI3321, TSI Inc), which is shown in Fig. 3(a).Fig. 3. (a) Size distribution N(D) measured by the aerodynamic particle size spectrometer (TSI3321, TSI Inc); (b) Relationship between -ln(I/I0) and aerosol droplet concentration Cm. The squares are experimental data which are fitted by the solid line. The dot line is theoretical relation between -ln(I/I0) and Cm calculated according to Eq. (4a).
The proportional coefficient $\frac{{3L{K_m}}}{{2\rho {D_{32}}}}$ in Eq. (4a) can be determined by measuring -ln(I/I0) and Cm. Cm is measured by weighing method. Then, the relation between Cm and -ln(I/I0) is obtained and shown in Fig. 3(b). The relative measurement error of the aerosol concentration is ∼4% which is determined by three repeated measurements. By linear fitting the data (see the solid line in Fig. 3(b)), the proportional coefficient $\frac{{3L{K_m}}}{{2\rho {D_{32}}}}$ is determined to be 0.25 which is close to the theoretical value predicted by Eq. (4)(a). Therefore, the mass volume concentration of aerosol in air can be obtained by measuring the extinction ratio -ln(I/I0).
To compensate the astigmatism introduced by the large aperture concave mirror M2 in Fig. 2, a phase compensating plate with freeform surface is designed by Zemax software based on the Fringe Zernike polynomial [38], which can be expressed as:
Fig. 4. Comparison between the actual and designed sag of the phase plate in horizontal (a) and vertical (b) directions, respectively.
Using the phase compensating plate, the quality of linear propagation laser beam is improved significantly. The cross-sectional intensity distributions recorded at the focus which is 30 m away from the concave mirror M2 with and without phase plate are shown in Fig. 5.
Fig. 5. Cross-sectional intensity distributions recorded by a CCD camera (M2S132M-H2, DO3THINK Inc.) at the focus without (a) and with (b) the phase compensating plate.
After compensating the astigmatism, the optimal pulse chirp that can generate the strongest NaCl aerosol fluorescence signal is investigated. The pulse chirp is adjusted by changing the effective grating spacing of the compressor inside the femtosecond laser amplifier system. The pulse duration is measured at the output of the compressor. The experimental results are shown in Fig. 6. The negative pulse duration (-Δt) means the laser pulse has a duration of Δt with negative chirp. From Fig. 6(a) it is seen that the fluorescence intensity varies significantly with the pulse chirp. The chirp parameter C is used to characterize the chirp parameter according to the relationship ${\tau _c} = {\tau _0}{(1 + {C^2})^{1/2}}$ between the laser compression limit pulse width (FWHM) ${\tau _\textrm{0}}$(50 fs) and the chirped pulse width (FWHM) ${\tau _c}$ [39]. C > 0 respects that the laser pulse is a positive chirp pulse, and C < 0 means that the laser pulse is a negative chirp pulse. The duration of the chirped pulse obtained by moving the grating spacing each time can be directly measured by the autocorrelator, and then converted into the corresponding chirp parameter C. From Fig. 6(b), it is found that the optimal pulse duration is 179 fs with a negative chirp.
Fig. 6. (a) Fluorescence spectra of NaCl aerosol excited by femtosecond laser filament after removing the background and supercontinuum envelope for laser pulses with different chirps (acquisition parameters: gate delay of 50 ns, gate width of 500 ns, exposure time of 30 s, gain of 4095); (b) Intensity of Na+ emission line at 589 nm as a function of the pulse chirp; (c) Beginning, middle and ending positions of the filament generated by femtosecond laser with different pulse chirps; (d) Length of the filament generated by femtosecond laser with different pulse chirps. The error bar is obtained by 10 repeating measurements.
Varying the chirp leads to the changes of the pulse duration and peak power of the femtosecond laser. Therefore, the position and length of the filament change accordingly. Figures 6(c) and 6(d) show the experimental results about the dependences of the filament position and length on the chirp parameter, i.e., the pulse duration. Both the filament position and length are obtained by measuring the acoustic profile of the filament. According to the chirp-induced changes in filament position and length shown in Figs. 6(c) and 6(d), the beginning and middle positions of the filament change so slightly as to be negligible. Therefore, the chirp-induced fluorescence signal enhancement is attributed to the enhancement and lengthening of the filament. Indeed, a certain degree of negative chirp can compensate for the positive group velocity dispersion (GVD) introduced in the laser propagation. When the negative chirp pulse exactly compensates the positive GVD, the pulse duration can be compressed to the minimum. Under this condition, the filament can obtain the highest peak intensity, which directly enhances the intensity of the excited fluorescence signal.
Using the optimal pulse width, the fluorescence spectra of NaCl aerosol excited by 4.4 mJ femtosecond laser filament are collected by the gated IsCMOS camera. The gate delay, gate width, exposure time and gain are 50 ns, 500 ns, 30 s and 4095, respectively, which means that the fluorescence of aerosol excited by 30000 laser pulses is accumulated in each spectral curve. Since most of the supercontinuum emission appears before the fluorescence peak of Na, these recording parameters can filter out most of the supercontinuum signals and obtain Na fluorescence emission peak with high signal-to-noise ratio. During the measurements, the filament-induced fluorescence spectra of NaCl aerosols with different concentrations are acquired. For each concentration, the data acquisition is repeated 5 times. The typical spectra are presented in Fig. 7(a). The fluorescence spectral intensity at 589 nm as a function of the concentration is summarized in Fig. 7(b). The limit of detection is 3 μg/m3 according to the 3σ criteria which is shown in Fig. 7(b). σ denotes the standard deviation of the background noise.
Fig. 7. (a) Fluorescence spectra of NaCl aerosol excited by femtosecond laser filament after removing the background and supercontinuum envelope at different NaCl aerosol concentrations; (b) Intensity of Sodium emission line at 589 nm as a function of NaCl aerosol concentrations. The black squares represent the peak intensities of the measured emission lines, and the red dots represent the peak intensity of the emission line processed by the spectral optimization algorithm. Inset: Fluorescence spectra of NaCl aerosol with concentration of 3 μg/m3.
To further improve the detection limit of aerosol by femtosecond laser filament, a spectral data processing algorithm is developed. The background spectra including the noises and the continuum spectrum induced by the inverse bremsstrahlung is firstly subtracted from the original fluorescence signal. Then the following 5 denoising steps (see Fig. 8) will be executed sequentially including: (1) median filtering, which is mainly used to remove impulse noises; (2) Savizkg-Golay (SG) smoothing for removing random noises; (3) fast Fourier transform (FFT) Filtering also for removing random noises; (4) discrete wavelet transform (DWT) filtering to remove baseline from the fluorescence spectrum; (5) significance of peak (SOP), which is used to recognize the emission peak by the frequency of the peak that should always be significant in many samples of FIPS data.
The final step of SOP is used to eliminate pseudo emission peaks. Since the emission peak’s intensity of the low concentration sample is close to the noise level, special care must be taken to eliminate the noise induced pseudo peaks. The significance of peak (SOP) algorithm is used to recognize the pseudo peak, and the calculation method can be expressed as:
where n is the number of occurrences of the certain emission peak, and N is the total number of samples which is 10 in this work. When the frequency of the peak occurrence is greater than a certain threshold, i.e., peak significance threshold (0.7 in this work), it is considered to be the true emission peak and retained in the data. Otherwise, the peak will be removed from the data.The processing results of three sets of spectra with different concentrations lower than the limit of detection obtained by experiments are shown in Fig. 9. It is seen from Fig. 9(a) that the emission peak at 589 nm cannot be recognized in the spectra before data processing. However, after data processing by the algorithm in Fig. 8, the emission peak for the sample with the concentration down to 1.4 μg/m3 can be identified which is shown Fig. 9(b). Therefore, the detection limit after data processing is only half of the limit of detection determined by experiments.
Fig. 9. (a) Fluorescence spectra of NaCl aerosol with concentrations lower than the limit of detection determined by experiments after removing the background and continuum spectrum; (b) Spectra after processed by the algorithm shown in Fig. 8, the peak significance threshold is 0.7.
4. Conclusions
In this work, by introducing a phase compensating plate and negative chirp, and utilizing large-aperture and coaxial collection scheme, the capability of FIPS-LIDAR with low pulse energy (4.4 mJ) for the remote trace detection in aqueous aerosol is demonstrated. The experimental limit of detection for Na in aerosol droplets is 8 ppm, corresponding to 3 μg/m3 (PM2.5 = 3) in air, which is the upper limit of the sensitivity of this method. Moreover, it is the lowest concentration that can currently be detected at a distance of 30 m with a low pulse energy of 4.4 mJ. Then, by performing spectral preprocessing and the optimization of the significance of peak (SOP) algorithm, the characteristic peak signal for the concentration of 1.4 μg/m3 (PM2.5 = 1.4) can be further identified, even it cannot be clearly distinguished in the original spectrum. This work provides effective guidance on experimental methods and data processing for remote trace detection in an atmospheric aerosol using low-energy femtosecond lasers.
Funding
National Key Research and Development Program of China (2018YFB0504400); Fundamental Research Funds for the Central Universities (63223052).
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. J. Kasparian and J. P. Wolf, “Physics and applications of atmospheric nonlinear optics and filamentation,” Opt. Express 16(1), 466–493 (2008). [CrossRef]
2. S. L. Chin, S. A. Hosseini, W. Liu, Q. Luo, F. Théberge, N. Aközbek, A. Becker, V. P. Kandidov, O. G. Kosareva, and H. Schroeder, “The propagation of powerful femtosecond laser pulses in opticalmedia: physics, applications, and new challenges,” Can. J. Phys. 83(9), 863–905 (2005). [CrossRef]
3. H. L. Xu and S. L. Chin, “Femtosecond Laser Filamentation for Atmospheric Sensing,” Sensors 11(1), 32–53 (2010). [CrossRef]
4. A. Couairon and A. Mysyrowicz, “Femtosecond filamentation in transparent media,” Phys. Rep. 441(2-4), 47–189 (2007). [CrossRef]
5. F. Pannier, X. Dauchy, M. Potin-Gautier, A. Astruc, and M. Astruc, “Speciation of butyltin compounds by ion chromatography coupled to electrothermal atomic absorption spectrometry,” Appl. Organomet. Chem. 7(3), 213–218 (1993). [CrossRef]
6. R. C. Blase, E. L. Patrick, J. N. Mitchell, and M. Libardoni, “Analysis of cave atmospheres by comprehensive two-dimensional gas chromatography (GC×GC) with flame ionization detection (FID),” Anal. Chem. Res. 3, 54–62 (2015). [CrossRef]
7. R. a. Tjallingii, “Influence of the water content on X-ray fluorescence core-scanning measurements in soft marine sediments,” Geochem., Geophys., Geosyst. 8(2), 1 (2007). [CrossRef]
8. G. A. English, R. B. Firestone, D. L. Perry, J. P. Reijonen, L. Ka-Ngo, G. F. Garabedian, G. L. Molnár, and Z. Révay, “Prompt gamma activation analysis (PGAA) and short-lived neutron activation analysis (NAA) applied to the characterization of legacy materials,” J. Radioanal. Nucl. Chem. 277(1), 25–29 (2008). [CrossRef]
9. V. Pallier, B. Serpaud, G. Feuillade-Cathalifaud, and J.-C. Bollinger, “Comparison of voltammetric and AAS methods for As(III) quantification in presence of iron species in model water samples with a low mineral content,” Int. J. Environ. Anal. Chem. 91(1), 1–16 (2011). [CrossRef]
10. M. E. Monge, G. A. Harris, P. Dwivedi, and F. M. Fernández, “Mass Spectrometry: Recent Advances in Direct Open Air Surface Sampling/Ionization,” Chem. Rev. 113(4), 2269–2308 (2013). [CrossRef]
11. C. Schütze, S. Lau, N. Reiche, U. Sauer, H. Borsdorf, and P. Dietrich, “Ground-based Remote Sensing with Open-path Fourier- transform Infrared (OP-FTIR) Spectroscopy for Large-scale Monitoring of Greenhouse Gases,” Energy Procedia 37, 4276–4282 (2013). [CrossRef]
12. J. Yu, D. Mondelain, G. Ange, R. Volk, S. Niedermeier, J. P. Wolf, J. Kasparian, and R. Sauerbrey, “Backward supercontinuum emission from a filament generated by ultrashort laser pulses in air,” Opt. Lett. 26(8), 533–535 (2001). [CrossRef]
13. J. Kasparian, M. Rodriguez, G. Méjean, J. Yu, E. Salmon, H. Wille, R. Bourayou, S. Frey, Y.-B. André, A. Mysyrowicz, R. Sauerbrey, J.-P. Wolf, and L. Wöste, “White-Light Filaments for Atmospheric Analysis,” Science 301(5629), 61–64 (2003). [CrossRef]
14. T. A. Labutin, V. N. Lednev, A. A. Ilyin, and A. M. Popov, “Femtosecond laser-induced breakdown spectroscopy,” J. Anal. At. Spectrom. 31(1), 90–118 (2016). [CrossRef]
15. S. L. Chin and H. Xu, “Tunnel ionization, population trapping, filamentation and applications,” J. Phys. B: At., Mol. Opt. Phys. 49(22), 222003 (2016). [CrossRef]
16. B. Clough, J. Liu, and X. C. Zhang, ““All air-plasma” terahertz spectroscopy,” Opt. Lett. 36(13), 2399–2401 (2011). [CrossRef]
17. V. Y. Fedorov and S. Tzortzakis, “Powerful terahertz waves from long-wavelength infrared laser filaments,” Light: Sci. Appl. 9(1), 186 (2020). [CrossRef]
18. J. H. Odhner, E. T. McCole, and R. J. Levis, “Filament-Driven Impulsive Raman Spectroscopy,” J. Phys. Chem. A 115(46), 13407–13412 (2011). [CrossRef]
19. A. V. Mitrofanov, M. V. Rozhko, D. A. Sidorov-Biryukov, A. A. Voronin, A. B. Fedotov, and A. M. Zheltikov, “Near-infrared-to-vacuum-ultraviolet high-harmonic Raman and plasma emission spectroscopy with ultrashort mid-infrared laser pulses,” J. Raman Spectrosc. 52(12), 2089–2099 (2021). [CrossRef]
20. Q. Luo, H. L. Xu, S. A. Hosseini, J. F. Daigle, F. Théberge, M. Sharifi, and S. L. Chin, “Remote sensing of pollutants using femtosecond laser pulse fluorescence spectroscopy,” Appl. Phys. B 82(1), 105–109 (2006). [CrossRef]
21. E. J. Kautz, M. C. Phillips, and S. S. Harilal, “Laser-induced fluorescence of filament-produced plasmas,” J. Appl. Phys. 130(20), 203302 (2021). [CrossRef]
22. H. L. Xu, Y. Kamali, C. Marceau, P. T. Simard, W. Liu, J. Bernhardt, G. Méjean, P. Mathieu, G. Roy, J.-R. Simard, and S. L. Chin, “Simultaneous detection and identification of multigas pollutants using filament-induced nonlinear spectroscopy,” Appl. Phys. Lett. 90(10), 101106 (2007). [CrossRef]
23. P. J. Skrodzki, M. Burger, L. A. Finney, F. Poineau, S. M. Balasekaran, J. Nees, K. R. Czerwinski, and I. Jovanovic, “Ultrafast Laser Filament-induced Fluorescence Spectroscopy of Uranyl Fluoride,” Sci. Rep. 8(1), 11629 (2018). [CrossRef]
24. J. Wu, Z. Wu, T. Chen, H. Zhang, Y. Zhang, Y. Zhang, S. Lin, X. Cai, A. Chen, Y. Jiang, S. Li, and M. Jin, “Spatial distribution of the fluorescence induced by femtosecond laser filamentation in ambient air,” Opt. Laser Technol. 131, 106417 (2020). [CrossRef]
25. G. Méjean, J. Kasparian, J. Yu, E. Salmon, S. Frey, J. P. Wolf, S. Skupin, A. Vinçotte, R. Nuter, S. Champeaux, and L. Bergé, “Multifilamentation transmission through fog,” Phys. Rev. E 72, 026611 (2005). [CrossRef]
26. R. Bourayou, G. Méjean, J. Kasparian, M. Rodriguez, E. Salmon, J. Yu, H. Lehmann, B. Stecklum, U. Laux, J. Eislöffel, A. Scholz, A. P. Hatzes, R. Sauerbrey, L. Wöste, and J.-P. Wolf, “White-light filaments for multiparameter analysis of cloud microphysics,” J. Opt. Soc. Am. B 22(2), 369–377 (2005). [CrossRef]
27. H. L. Xu, W. Liu, and S. L. Chin, “Remote time-resolved filament-induced breakdown spectroscopy of biological materials,” Opt. Lett. 31(10), 1540–1542 (2006). [CrossRef]
28. T. Fujii, N. Goto, M. Miki, T. Nayuki, and K. Nemoto, “Lidar measurement of constituents of microparticles in air by laser-induced breakdown spectroscopy using femtosecond terawatt laser pulses,” Opt. Lett. 31(23), 3456–3458 (2006). [CrossRef]
29. J. F. Daigle, G. Méjean, W. Liu, F. Théberge, H. L. Xu, Y. Kamali, J. Bernhardt, A. Azarm, Q. Sun, P. Mathieu, G. Roy, J. R. Simard, and S. L. Chin, “Long range trace detection in aqueous aerosol using remote filament-induced breakdown spectroscopy,” Appl. Phys. B 87(4), 749–754 (2007). [CrossRef]
30. J. F. Daigle, P. Mathieu, G. Roy, J. R. Simard, and S. L. Chin, “Multi-constituents detection in contaminated aerosol clouds using remote-filament-induced breakdown spectroscopy,” Opt. Commun. 278(1), 147–152 (2007). [CrossRef]
31. S. S. Golik, A. Y. Mayor, V. V. Lisitsa, Y. S. Tolstonogova, A. A. Ilyin, A. V. Borovskiy, and O. A. Bukin, “Limits of Detection of Chemical Elements in an Aqueous Aerosol in Filament-Induced Breakdown Spectroscopy,” J. Appl. Spectrosc. 88(2), 337–342 (2021). [CrossRef]
32. J. F. Daigle, Y. Kamali, M. Châteauneuf, G. Tremblay, F. Théberge, J. Dubois, G. Roy, and S. L. Chin, “Remote sensing with intense filaments enhanced by adaptive optics,” Appl. Phys. B 97(3), 701–713 (2009). [CrossRef]
33. J. F. Gravel, Q. Luo, D. Boudreau, X. P. Tang, and S. L. Chin, “Sensing of Halocarbons Using Femtosecond Laser-Induced Fluorescence,” Anal. Chem. 76(16), 4799–4805 (2004). [CrossRef]
34. W. Liu, H. L. Xu, G. Méjean, Y. Kamali, J. F. Daigle, A. Azarm, P. T. Simard, P. Mathieu, G. Roy, and S. L. Chin, “Efficient non-gated remote filament-induced breakdown spectroscopy of metallic sample,” Spectrochim. Acta, Part B 62(1), 76–81 (2007). [CrossRef]
35. M. Durand, A. Houard, B. Prade, A. Mysyrowicz, A. Durécu, B. Moreau, D. Fleury, O. Vasseur, H. Borchert, K. Diener, R. Schmitt, F. Théberge, M. Chateauneuf, J.-F. Daigle, and J. Dubois, “Kilometer range filamentation,” Opt. Express 21(22), 26836–26845 (2013). [CrossRef]
36. D. Thul, R. Bernath, N. Bodnar, H. Kerrigan, D. Reyes, J. Peña, P. Roumayah, L. Shah, D. Maukonen, J. Bradford, M. Baudelet, S. R. Fairchild, and M. Richardson, “The mobile ultrafast high energy laser facility - A new facility for high-intensity atmospheric laser propagation studies,” Opt. Lasers Eng. 140, 106519 (2021). [CrossRef]
37. P. B. Kowalczuk and J. Drzymala, “Physical meaning of the Sauter mean diameter of spherical particulate matter,” Part. Sci. Technol. 34(6), 645–647 (2016). [CrossRef]
38. T. Yang, J. Zhu, and G. Jin, “Nodal aberration properties of coaxial imaging systems using Zernike polynomial surfaces,” J. Opt. Soc. Am. A 32(5), 822–836 (2015). [CrossRef]
39. B. Shang, P. Qi, J. Guo, Z. Zhang, L. Guo, C. Chu, J. Liu, O. G. Kosareva, N. Zhang, L. Lin, and W. Liu, “Manipulation of Long-Distance femtosecond laser Filamentation: From physical model to acoustic diagnosis,” Opt. Laser Technol. 157, 108636 (2023). [CrossRef]
