Remote Quantitative Analysis of Minerals Based on Multispectral Line-Calibrated Laser-Induced Breakdown Spectroscopy (LIBS) Xiong Wan,a,b,* Peng Wangb a Key Laboratory of Space Active Opto-Electronics Tehcnology, Shanghai Institute of Technical Physics of the Chinese Academy of Sciences, Shanghai 200083, China b Key Laboratory of Nondestructive Testing (Ministry of Education), Nanching Hangkong University, Nanchang 330063, China
Laser-induced breakdown spectroscopy (LIBS) is a feasible remote sensing technique used for mineral analysis in some unapproachable places where in situ probing is needed, such as analysis of radioactive elements in a nuclear leak or the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Here a compact custom 15 m focus optical component, combining a six times beam expander with a telescope, has been built, with which the laser beam of a 1064 nm Nd ; YAG laser is focused on remote minerals. The excited LIBS signals that reveal the elemental compositions of minerals are collected by another compact single lens-based signal acquisition system. In our remote LIBS investigations, the LIBS spectra of an unknown ore have been detected, from which the metal compositions are obtained. In addition, a multi-spectral line calibration (MSLC) method is proposed for the quantitative analysis of elements. The feasibility of the MSLC and its superiority over a single-wavelength determination have been confirmed by comparison with traditional chemical analysis of the copper content in the ore. Index Headings: Laser-induced breakdown spectroscopy; LIBS; Remote detection; Mineral detection; Quantitative analysis.
INTRODUCTION The exploitation of mineral resources always needs comprehensive scientific investigations and accurate analyses of mineral contents, but most mineral resources are located in remote areas with complex terrain. In those dangerous or difficult-to-access regions, such as caves and gorges, it is difficult to carry out in situ mineral analysis. Likewise, this difficulty of in situ analysis also exists on some special occasions, such as the analysis of radioactive elements in a nuclear leak and the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Remote material detection and analysis techniques have hence drawn much attention.1–5 Some passive remote sensing techniques, such as infrared imaging spectrometers, are utilized to map the approximate distributions of various minerals,6–8 with which the distribution of various materials can be approximately mapped but the elemental compositions cannot be obtained. Some remote Raman systems have utilized pulsed lasers and telescopes coupled to spectrographs to identify the components of minerals beyond tens of meters,9–11 which are Received 8 July 2013; accepted 19 March 2014. * Author to whom correspondence should be sent. E-mail: wanxiong@ mail.sitp.ac.cn. DOI: 10.1366/13-07203
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as yet only suitable to the analysis of some molecular structures of minerals. To investigate the composition and distribution of materials in remote areas simultaneously, some approaches have been proposed that merge active and passive techniques for remote monitoring of soils, water, clouds, etc.12,13 However, accurate element analysis is hardly achieved in these studies. As a powerful analytical tool for elemental composition, laser-induced breakdown spectroscopy (LIBS) has been developed and applied to a wide variety of fields for the elemental analysis of solids,14,15 liquids,16,17 suspensions,18 and even gaseous mixtures and aerosols.19,20 Furthermore, the feasibility of the remote elemental analysis of some fiber-based LIBS techniques has also been proven;21,22 these LIBS techniques need an optical fiber to be pre-laid to guide laser pulses as well as collect the induced spectral signals, which are not suitable for detecting objects existing in those places where it is impossible to pre-lay the fiber laser guider and signal collector. Remote filament-induced breakdown spectroscopy,23 based on filamentation induced by the nonlinear propagation of unfocused ultrashort laser pulses, has demonstrated its capability for remote elemental analysis. Nevertheless this technique employs a rather delicate femtosecond pulse-based system that needs precise adjustment and is susceptible to disturbance, which makes it difficult to adapt it to such hostile environments as outer space. Moreover, some remote detection techniques that combine LIBS with Raman spectroscopy that can be therefore used to simultaneously probe molecular and elemental compositions for remote materials have been proposed.3,4 These integrated LIBS techniques need a rather large mobile platform, which can hardly meet the need of space exploration. In the NASA Mars exploration mission, a ChemCam instrument was adopted in which a delicate LIBS unit24 was assembled and provided elemental analysis of rocks or soils on the Mars surface at distances of 1 to 7 m. In future space exploration, in situ LIBS with better accuracy in sensing at remoter distances and with better analysis is worthy of study. A remote LIBS system that mainly consists of a custom compact focusing optical device and a simple single lens–based signal collecting subsystem (SSCS) is proposed here. Laser pulses from a Q-switched Nd ; YAG laser hit the surface of a remote target via the compact focusing optical device, and the LIBS signal emitted from the focusing point on the surface of the target is then coupled into an optical fiber spectrometer via the SSCS. No delicate or cumbersome optical
0003-7028/14/6810-1132/0 Q 2014 Society for Applied Spectroscopy
APPLIED SPECTROSCOPY
FIG. 1. Layout of the remote LIBS system.
components are adopted in the remote LIBS system, which hence ensures a rather good portability. The time delay between the initiation of the laser pulses and the sampling of the spectrometer is adjusted with the laser controller. When the time delay is rather small (typically from 0 to 1.15 ls), the LIBS signals are large; however, the continuous background noise is also strong, resulting in a low signal-to-noise ratio (SNR). With the increment of the time delay, the LIBS signals decreases gradually, and the background noise descends sharply and is almost unobservable after a certain time delay. Then a maximal SNR can be obtained if this time delay is adopted. Finally the data of the spectrometer are sent to a computer for further processing. In the quantitative analysis of elements for a remote target, a multispectral line calibration (MSLC) method is proposed. Compared with traditional methods that often adopt a single spectral line of a certain element in the elemental analysis, not considering transition probabilities of different spectral lines of the element, MSLC employs a weighed superposition of intensities of several spectral lines, having relatively high transition probabilities, of an element for calibration. This method is based on the degeneracy of various ionic states of the same element, and its capability for remote elemental analysis is proven with a 15 m detection of an unknown ore.
EXPERIMENTAL LAYOUT OF REMOTE LIBS As shown in Fig. 1, the remote LIBS system consists of a 1064 nm Q-switched Nd : YAG laser (Beamtech Optronics Co., Nimma 400) that has a 10 ns pulse width with a 10 Hz repetition rate and a 400 mJ maximal pulse energy, a laser controller, a compact custom 15 m focus optical component that combines a 6X beam expander with a telescope, and a simple single lens–based signal collecting subsystem (SSCS). SSCS comprises a single lens and an optical fiber spectrometer (AvaSpec-2048USB2; Avantes Co.) whose sensing wavelength range is from 200 to 750 nm. The Q-switched Nd : YAG laser functions as the LIBS excitation source, whose emitted laser pulses are expanded via the six times beam expander and then focused on the remote object with the telescope when passing through the compact custom 15 m focus optical component.
FIG. 2. (a) The detected ore; (b) average LIBS spectrogram of the ore.
FULFILLMENT OF REMOTE LIBS Qualitative and Quantitative Analysis of a Remote Unknown Ore. An ore, with unknown elements placed 15 m away, was used to confirm the feasibility of the remote LIBS (Fig. 2a). The ore was cleaned with water and then was dried to eliminate superficial impurities. To obtain an approximate elemental composition of the ore and then analyze elements quantitatively, sufficient remote LIBS tests for the ore were carried out. In each test, 10 LIBS signals, which emitted from the focused point of the ore excited by 10 laser pluses, were sampled with the spectrometer and then were averaged to generate one group of LIBS spectral data. Here, 20 tests were conducted, which provided sufficient information not only for the qualitative analysis, but also for the following quantitative analysis. An average LIBS spectrogram, using 20 LIBS spectral data of the unknown ore, is depicted in Fig. 2b. Some metal elements, Ba, Fe, Ca, and Cu, accompanied with some nonmetal elements such as O and C were found in the ore after wavelengths of spectral lines were analyzed, which gave a qualitative elemental composition. A further quantitative analysis should be combined to further this method for practical applications. Here an MSLC has been proposed for the quantitative analysis of elements. In the MSLC experiment, Cu was chosen for a quantitative analysis. To conduct an accurate calibration, several chemical compounds were selected to configure
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TABLE I. Chemical ingredients of the specimens for the quantitative analysis of Cu. Specimen no.
Chemical ingredients
Mass (g)
1
CaCO3 BaCl2 CuSO45H2O CaCO3 CrO3 CdSO4 CuSO45H2O CaCO3 CdSO4 CuSO45H2O CaCO3 BaCl2 CuSO45H2O CaCO3 BaCl2 FeCl36H2O CuSO45H2O
9.5 0.3 0.35 9.23 0.19 0.18 0.44 9.67 0.28 0.65 9 0.5 0.8 8 1 0.85 0.85
2
3
4
5
Cu content (%) 0.8
1
1.5
1.7
2
five specimens whose elemental compositions are similar to that of the ore. When choosing the chemical compounds, their possible mutual chemical reactions must be considered and then be avoided. The contents of the target element (Cu) must be kept constant even after these reactions. Distilled water was adopted as the solvent during the configuration of the five specimens. The compounds were weighed according to their computed masses to get the five specimens with different Cu contents. CaCO3 was put into all the five specimens for easier solidification. All compounds for each specimen were poured into the distilled water successively and mixed evenly to get the solution of the
specimens, which then were placed into a drying oven and heated for 120 min at 60 8C. Finally, five blocks of specimens formed after the above procedures. Table I shows the chemical ingredients of the specimens for the quantitative analysis of Cu. The five blocks of specimens were placed in the same position and detected with the remote LIBS under the same conditions as the ore. LIBS spectrograms of the specimens are shown in Fig. 3. MSLC is proposed to improve the accuracy of calibrations, and multispectral lines (465.112, 510.554, and 521.820 nm) of Cu were chosen because these spectral lines have rather large transition probabilities (3.80eþ07, 2.0eþ06, and 7.5eþ07, respectively, referring to the NIST Database), which can reflect the content of the element more accurately. Figure 4 includes the fitting curves of the Cu content versus the intensity of spectral lines corresponding to wavelengths 465.112, 510.554, and 521.820 nm, respectively. From the initial 20 remotely probed LIBS spectral data, we obtained the mean values I1, I2, and I3 of the spectral intensity of the three LIBS spectral lines (465.112, 510.554, and 521.820 nm), which can be turned into three content values C1, C2, and C3 of Cu based on the fitting curves (Fig. 4). In MSLC, taking both the mean spectral intensity values I1, I2, and I3 and their corresponding calculated content values C1, C2, and C3 into consideration for the calibration, we employed a weighed superposition of C1, C2, and C3 as the final content C of Cu, which can be expressed as
FIG. 3. LIBS spectrograms of the five specimens.
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C¼
N X i¼1
Wi Ci
ð1Þ
FIG. 4.
Fitting curves of Cu at wavelengths 465.112, 510.554, and 521.820 nm.
where N is the number of the multi-spectral lines in MSLC (note: N = 3 in our experiment) and the weight factor Wi is denoted as X N Ii ; Wi ¼ Ii = i ¼ 1; 2; 3; :::; N ð2Þ i¼1
This means that the weight factor W i of Ci is proportional to the mean spectral intensity Ii. The data analysis of MSLS is shown in Table II. Finally, the Cu content determined with MSLC is 1.24%. Validation of the Remote LIBS Using a Chemical Experiment. A chemical experiment determining the Cu content of the same ore was designed and conducted to validate the accuracy and further feasibility of the proposed MSLC remote LIBS. The specific steps of the chemical experiment are as follows: (1) Take a 5 g ore specimen at the point where the laser was focused and put it into a hydrochloric acid (HCl) solution of 10% concentration to dissolve. (2) Pour in a NaOH solution of 50% concentration until no
more precipitate is generated; filter the precipitate, which contains the hydroxides of Cu, Fe, Ca, and other metal elements. (3) Pour an excess of aqueous ammonia into the precipitate, and copper hydroxide will create a complexation reaction and generate dissolvable copper ammonia complex ions: CuðOHÞ2 þ4NH3 H2 O ¼½CuðNH3 Þ4 ðOHÞ2 þ4H2 O ð3Þ while hydroxides of Fe, Ca, etc., keep the precipitate state. Then filter the precipitate again, reserving the solution of copper ammonia complex ions. (4) Add an appropriate amount of HCl to the solution of copper ammonia complex ions, and then add NaOH solution, until no more precipitate is generated. (5) Filter the precipitate, pour into 3000 ml of distilled water, and stir sufficiently; then filter the precipitate, which is pure Cu(OH)2; measure the Cu(OH)2. (6) Repeat steps 1 through 5 until five Cu(OH)2 precip-
TABLE II. Data analysis of MSLS for Cu in the ore.
Wavelength (nm) 465.112
510.554
521.820
Mean value, weigh factor, and corresponding content
Intensities of spectral line (counts) 287 179 201 470 761 1135 698 488 922 858 534 495
58 175 108 149 532 653 426 592 301 545 308 346
122 91 158 123 608 544 1473 413 415 581 912 268
35 94 72 457 516 103 338 507 319 104 240 541
48 461 88 467 1283 601 753 509 625 521 412 500
I1 = 192.15 W1 = 0.1449 C1 = 0.6545% I2 = 646.65 W2 = 0.4876 C2 = 1.731% I3 = 487.35 W3 = 0.3675 C3 = 0.8195%
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itates are obtained; put them into a specimen drying oven, baking them at 60 8C for 120 min, and then weigh the baked Cu(OH)2 powder and calculate the Cu mass. After weighing and calculation, the average Cu mass in the five ore specimens is 0.0622 g, the Cu content in the ore being approximately 1.244%, which is basically consistent with the result 1.24% obtained with the proposed MSLC remote LIBS. However, if the Cu content is determined only by a single wavelength method, it would be 0.6545, 1.731, and 0.8195% (Table II), which corresponds to the 465.112, 510.554, and 521.820 nm wavelengths, respectively, and obviously has a much larger deviation from the chemical experimental result 1.244% compared with the MSLC.
DISCUSSION A remote LIBS system consisting of a custom compact focusing optical device and a SSCS has been built, with which an unknown ore placed 15 m away has been detected. The Cu content of the ore has been determined with an MSLC method. LIBS ionic states at different wavelengths of the same element have a different distribution of energy and transition probability. MSLC introduces weighted values of spectral intensities into the calibration, which considers transition probabilities at different wavelengths and is based on the degeneracy of various ionic states of the same element. In addition, when fitting curves of the content versus the intensity, unlike the single wavelength method whose calculation is only at a specific wavelength considering neither transition probabilities nor degeneracy of ionic states, MSLC adopts several spectral lines that have rather large transition probabilities to calculate, which results in fewer errors. A chemical experiment has been conducted to validate the proposed MSLC remote LIBS, resulting in a definite consistency that hence confirms the feasibility of the proposed LIBS. Studies show that this remote LIBS can be applied to remote elemental analysis, such as analysis of radioactive elements in a nuclear leak and the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. ACKNOWLEDGMENTS This work was supported by the Chinese Natural Science Fund under Grant No. 81260225, the Jiangxi Natural Science Foundation under Grant No. 20122BAB202009, the Foundation of Jiangxi Education Bureau under Grant No. GJJ12408, and the ‘‘Hundred Talents Plan’’ project of CAS. 1. F.A. Kruse, A.B. Lefkoff, J.B. Dietz. ‘‘Expert System-Based Mineral Mapping in Northern Death Valley, California/Nevada, Using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)’’. Remote Sens. Environ. 1993. 44(2): 309-336. 2. R.N. Clark, G.A. Swayze, K.E. Livo, R.F. Kokaly, S.J. Sutley, J.B. Dalton, C.A. Gent. ‘‘Imaging Spectroscopy: Earth and Planetary Remote Sensing with the USGS Tetracorder and Expert Systems’’. J. Geophys. Res. 2003. 108(E12): 5131-5175. 3. J. Moros, J.A. Lorenzo, P. Lucena, L.M. Tobaria, J.J. Laserna. ‘‘Simultaneous Raman Spectroscopy—Laser-Induced Breakdown Spectroscopy for Instant Standoff Analysis of Explosives Using a Mobile Integrated Sensor Platform’’. Anal. Chem. 2010. 82(4): 13891400.
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4. J. Moros, J.J. Laserna. ‘‘New Raman–Laser-Induced Breakdown Spectroscopy Identity of Explosives Using Parametric Data Fusion on an Integrated Sensing Platform’’. Anal. Chem. 2011. 83(16): 6275-6285. 5. R.E. Russo, X. Mao, J.J. Gonzalez, V. Zorba, J. Yoo. ‘‘Laser Ablation in Analytical Chemistry’’. Anal. Chem. 2013. 85(13): 6162-6177. 6. T.B. McCord, G.B. Hansen, F.P. Fanale, R.W. Carlson, D.L. Matson, T.V. Johnson, W.D. Smythe, J.K. Crowley, P.D. Martin, A. Ocampo, C.A. Hibbitts, J.C. Granahan. ‘‘Salts on Europa’s Surface Detected by Galileo’s Near Infrared Mapping Spectrometer’’. Science. 1998. 280(5367): 1242-1245. 7. B.E. Hubbard, J.K. Crowley, D.R. Zimbelman. ‘‘Comparative Alteration Mineral Mapping Using Visible to Shortwave Infrared (0.4–2.4 lm) Hyperion, ALI, and ASTER Imagery’’. IEEE Trans. Geosci. Electron. 2003. 41(6): 1401-1410. 8. F.A. Kruse. ‘‘Mapping Surface Mineralogy Using Imaging Spectrometry’’. Geomorphology. 2012. 137(1): 41-56. 9. S.K. Sharma, S.M. Angel, M. Ghosh, H.W. Hubble, P.G. Lucey. ‘‘Remote Pulsed Laser Raman Spectroscopy System for Mineral Analysis on Planetary Surfaces to 66 Meters’’. Appl. Spectrosc. 2002. 56(6): 699-705. 10. A.K. Misra, S.K. Sharma, C.H. Chio, P.G. Lucey, B. Lienert. ‘‘Pulsed Remote Raman System for Daytime Measurements of Mineral Spectra’’. Spectrochim. Acta, Part A. 2005. 61(10): 2281-2287. 11. S.K. Sharma, P.G. Lucey, M. Ghosh, H.W. Hubble, K.A. Horton. ‘‘Stand-off Raman Spectroscopic Detection of Minerals on Planetary Surfaces’’. Spectrochim. Acta, Part A. 2003. 59(10): 2391-2407. 12. V.L. Mulder, S.D. Bruin, M.E. Schaepman, T.R. Mayr. ‘‘The Use of Remote Sensing in Soil and Terrain Mapping—A Review’’. Geoderma. 2011. 162(1-2): 1-19. 13. F.D. Meer, H. Werff, F.J. Ruitenbeek, C.A. Hecker, W.H. Bakker, M. Noomen, T. Woldai. ‘‘Multi- and Hyperspectral Geologic Remote Sensing: A Review’’. Int. J. Appl. Earth Obs. 2012. 14(1): 112-128. 14. J. Cunat, F.J. Fortes, J.J. Laserna. ‘‘Real Time and in situ Determination of Lead in Road Sediments Using a Man-Portable Laser-Induced Breakdown Spectroscopy Analyzer’’. Anal. Chim. Acta. 2009. 633(1): 38-42. 15. J.L. Gottfried, F.C. Lucia, C.A. Munson, A.W. Miziolek. ‘‘LaserInduced Breakdown Spectroscopy for Detection of Explosives Residues: A Review of Recent Advances, Challenges, and Future Prospects’’. Anal. Bioanal. Chem. 2009. 395(2): 283-300. 16. A. De Giacomo, M. Dell’Aglio, O. De Pascale. ‘‘Single Pulse-Laser Induced Breakdown Spectroscopy in Aqueous Solution’’. Appl. Phys. A.: Mater. Sci. Process. 2004. 79(4-6): 1035-1038. 17. A. De Giacomo, M. Dell’Aglio, O. De Pascale, M. Capitelli. ‘‘From Single Pulse to Double Pulse ns-Laser Induced Breakdown Spectroscopy under Water: Elemental Analysis of Aqueous Solutions and Submerged Solid Samples’’. Spectrochim. Acta, Part B. 2007. 62(8): 721-737. 18. R. Knopp, F.J. Scherbaum, J.I. Kim. ‘‘Laser Induced Breakdown Spectroscopy (LIBS) as an Analytical Tool for the Detection of Metal Ions in Aqueous Solutions’’. Fresenius’ J. Anal. Chem. 1996. 355(1): 16-20. 19. B.C. Windom, P.K. Diwakar, D.W. Hahn. ‘‘Dual-Pulse Laser Induced Breakdown Spectroscopy for Analysis of Gaseous and Aerosol Systems: Plasma-Analyte Interactions’’. Spectrochim. Acta, Part B. 2006. 61(7): 788-796. 20. M.E. Asgill, D.W. Hahn. ‘‘Particle Size Limits for Quantitative Aerosol Analysis Using Laser-Induced Breakdown Spectroscopy: Temporal Considerations’’. Spectrochim. Acta, Part B. 2009. 64(10): 1153-1158. 21. D.A. Cremers, J.E. Barefield, A.C. Koskelo. ‘‘Remote Elemental Analysis by Laser-Induced Breakdown Spectroscopy Using a FiberOptic Cable’’. Appl. Spectrosc. 1995. 49(6): 857-860. 22. A.I. Whitehouse, J. Young, I.M. Botheroyd, S. Lawson, C.P. Evans, J. Wright. ‘‘Remote Material Analysis of Nuclear Power Station Steam Generator Tubes by Laser-Induced Breakdown Spectroscopy’’. Spectrochim. Acta, Part B. 2001. 56(6): 821-830. 23. K. Stelmaszczyk, P. Rohwetter, G. Me´jean, J. Yu, E. Salmon, J. Kasparian, R. Ackerman, J.-P. Wolf, L. Woste. ‘‘Long-Distance Remote Laser-Induced Breakdown Spectroscopy Using Filamentation in Air’’. Appl. Phys. Lett. 2004. 85(18): 3977-3979. 24. R.C. Wiens, S. Maurice, B. Barraclough, M. Saccoccio, W.C. Barkley, J.F. Bell, C. McKay. ‘‘The ChemCam Instrument Suite on the Mars Science Laboratory (MSL) Rover: Body Unit and Combined System Tests’’. Space Sci. Rev. 2012. 170(1-4): 167-227.
Laser-induced breakdown spectroscopy (LIBS) is a feasible remote sensing technique used for mineral analysis in some unapproachable places where in situ probing is needed, such as analysis of radioactive elements in a nuclear leak or the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Here a compact custom 15 m focus optical component, combining a six times beam expander with a telescope, has been built, with which the laser beam of a 1064 nm Nd ; YAG laser is focused on remote minerals. The excited LIBS signals that reveal the elemental compositions of minerals are collected by another compact single lens-based signal acquisition system. In our remote LIBS investigations, the LIBS spectra of an unknown ore have been detected, from which the metal compositions are obtained. In addition, a multi-spectral line calibration (MSLC) method is proposed for the quantitative analysis of elements. The feasibility of the MSLC and its superiority over a single-wavelength determination have been confirmed by comparison with traditional chemical analysis of the copper content in the ore. Index Headings: Laser-induced breakdown spectroscopy; LIBS; Remote detection; Mineral detection; Quantitative analysis.
INTRODUCTION The exploitation of mineral resources always needs comprehensive scientific investigations and accurate analyses of mineral contents, but most mineral resources are located in remote areas with complex terrain. In those dangerous or difficult-to-access regions, such as caves and gorges, it is difficult to carry out in situ mineral analysis. Likewise, this difficulty of in situ analysis also exists on some special occasions, such as the analysis of radioactive elements in a nuclear leak and the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Remote material detection and analysis techniques have hence drawn much attention.1–5 Some passive remote sensing techniques, such as infrared imaging spectrometers, are utilized to map the approximate distributions of various minerals,6–8 with which the distribution of various materials can be approximately mapped but the elemental compositions cannot be obtained. Some remote Raman systems have utilized pulsed lasers and telescopes coupled to spectrographs to identify the components of minerals beyond tens of meters,9–11 which are Received 8 July 2013; accepted 19 March 2014. * Author to whom correspondence should be sent. E-mail: wanxiong@ mail.sitp.ac.cn. DOI: 10.1366/13-07203
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as yet only suitable to the analysis of some molecular structures of minerals. To investigate the composition and distribution of materials in remote areas simultaneously, some approaches have been proposed that merge active and passive techniques for remote monitoring of soils, water, clouds, etc.12,13 However, accurate element analysis is hardly achieved in these studies. As a powerful analytical tool for elemental composition, laser-induced breakdown spectroscopy (LIBS) has been developed and applied to a wide variety of fields for the elemental analysis of solids,14,15 liquids,16,17 suspensions,18 and even gaseous mixtures and aerosols.19,20 Furthermore, the feasibility of the remote elemental analysis of some fiber-based LIBS techniques has also been proven;21,22 these LIBS techniques need an optical fiber to be pre-laid to guide laser pulses as well as collect the induced spectral signals, which are not suitable for detecting objects existing in those places where it is impossible to pre-lay the fiber laser guider and signal collector. Remote filament-induced breakdown spectroscopy,23 based on filamentation induced by the nonlinear propagation of unfocused ultrashort laser pulses, has demonstrated its capability for remote elemental analysis. Nevertheless this technique employs a rather delicate femtosecond pulse-based system that needs precise adjustment and is susceptible to disturbance, which makes it difficult to adapt it to such hostile environments as outer space. Moreover, some remote detection techniques that combine LIBS with Raman spectroscopy that can be therefore used to simultaneously probe molecular and elemental compositions for remote materials have been proposed.3,4 These integrated LIBS techniques need a rather large mobile platform, which can hardly meet the need of space exploration. In the NASA Mars exploration mission, a ChemCam instrument was adopted in which a delicate LIBS unit24 was assembled and provided elemental analysis of rocks or soils on the Mars surface at distances of 1 to 7 m. In future space exploration, in situ LIBS with better accuracy in sensing at remoter distances and with better analysis is worthy of study. A remote LIBS system that mainly consists of a custom compact focusing optical device and a simple single lens–based signal collecting subsystem (SSCS) is proposed here. Laser pulses from a Q-switched Nd ; YAG laser hit the surface of a remote target via the compact focusing optical device, and the LIBS signal emitted from the focusing point on the surface of the target is then coupled into an optical fiber spectrometer via the SSCS. No delicate or cumbersome optical
0003-7028/14/6810-1132/0 Q 2014 Society for Applied Spectroscopy
APPLIED SPECTROSCOPY
FIG. 1. Layout of the remote LIBS system.
components are adopted in the remote LIBS system, which hence ensures a rather good portability. The time delay between the initiation of the laser pulses and the sampling of the spectrometer is adjusted with the laser controller. When the time delay is rather small (typically from 0 to 1.15 ls), the LIBS signals are large; however, the continuous background noise is also strong, resulting in a low signal-to-noise ratio (SNR). With the increment of the time delay, the LIBS signals decreases gradually, and the background noise descends sharply and is almost unobservable after a certain time delay. Then a maximal SNR can be obtained if this time delay is adopted. Finally the data of the spectrometer are sent to a computer for further processing. In the quantitative analysis of elements for a remote target, a multispectral line calibration (MSLC) method is proposed. Compared with traditional methods that often adopt a single spectral line of a certain element in the elemental analysis, not considering transition probabilities of different spectral lines of the element, MSLC employs a weighed superposition of intensities of several spectral lines, having relatively high transition probabilities, of an element for calibration. This method is based on the degeneracy of various ionic states of the same element, and its capability for remote elemental analysis is proven with a 15 m detection of an unknown ore.
EXPERIMENTAL LAYOUT OF REMOTE LIBS As shown in Fig. 1, the remote LIBS system consists of a 1064 nm Q-switched Nd : YAG laser (Beamtech Optronics Co., Nimma 400) that has a 10 ns pulse width with a 10 Hz repetition rate and a 400 mJ maximal pulse energy, a laser controller, a compact custom 15 m focus optical component that combines a 6X beam expander with a telescope, and a simple single lens–based signal collecting subsystem (SSCS). SSCS comprises a single lens and an optical fiber spectrometer (AvaSpec-2048USB2; Avantes Co.) whose sensing wavelength range is from 200 to 750 nm. The Q-switched Nd : YAG laser functions as the LIBS excitation source, whose emitted laser pulses are expanded via the six times beam expander and then focused on the remote object with the telescope when passing through the compact custom 15 m focus optical component.
FIG. 2. (a) The detected ore; (b) average LIBS spectrogram of the ore.
FULFILLMENT OF REMOTE LIBS Qualitative and Quantitative Analysis of a Remote Unknown Ore. An ore, with unknown elements placed 15 m away, was used to confirm the feasibility of the remote LIBS (Fig. 2a). The ore was cleaned with water and then was dried to eliminate superficial impurities. To obtain an approximate elemental composition of the ore and then analyze elements quantitatively, sufficient remote LIBS tests for the ore were carried out. In each test, 10 LIBS signals, which emitted from the focused point of the ore excited by 10 laser pluses, were sampled with the spectrometer and then were averaged to generate one group of LIBS spectral data. Here, 20 tests were conducted, which provided sufficient information not only for the qualitative analysis, but also for the following quantitative analysis. An average LIBS spectrogram, using 20 LIBS spectral data of the unknown ore, is depicted in Fig. 2b. Some metal elements, Ba, Fe, Ca, and Cu, accompanied with some nonmetal elements such as O and C were found in the ore after wavelengths of spectral lines were analyzed, which gave a qualitative elemental composition. A further quantitative analysis should be combined to further this method for practical applications. Here an MSLC has been proposed for the quantitative analysis of elements. In the MSLC experiment, Cu was chosen for a quantitative analysis. To conduct an accurate calibration, several chemical compounds were selected to configure
APPLIED SPECTROSCOPY
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TABLE I. Chemical ingredients of the specimens for the quantitative analysis of Cu. Specimen no.
Chemical ingredients
Mass (g)
1
CaCO3 BaCl2 CuSO45H2O CaCO3 CrO3 CdSO4 CuSO45H2O CaCO3 CdSO4 CuSO45H2O CaCO3 BaCl2 CuSO45H2O CaCO3 BaCl2 FeCl36H2O CuSO45H2O
9.5 0.3 0.35 9.23 0.19 0.18 0.44 9.67 0.28 0.65 9 0.5 0.8 8 1 0.85 0.85
2
3
4
5
Cu content (%) 0.8
1
1.5
1.7
2
five specimens whose elemental compositions are similar to that of the ore. When choosing the chemical compounds, their possible mutual chemical reactions must be considered and then be avoided. The contents of the target element (Cu) must be kept constant even after these reactions. Distilled water was adopted as the solvent during the configuration of the five specimens. The compounds were weighed according to their computed masses to get the five specimens with different Cu contents. CaCO3 was put into all the five specimens for easier solidification. All compounds for each specimen were poured into the distilled water successively and mixed evenly to get the solution of the
specimens, which then were placed into a drying oven and heated for 120 min at 60 8C. Finally, five blocks of specimens formed after the above procedures. Table I shows the chemical ingredients of the specimens for the quantitative analysis of Cu. The five blocks of specimens were placed in the same position and detected with the remote LIBS under the same conditions as the ore. LIBS spectrograms of the specimens are shown in Fig. 3. MSLC is proposed to improve the accuracy of calibrations, and multispectral lines (465.112, 510.554, and 521.820 nm) of Cu were chosen because these spectral lines have rather large transition probabilities (3.80eþ07, 2.0eþ06, and 7.5eþ07, respectively, referring to the NIST Database), which can reflect the content of the element more accurately. Figure 4 includes the fitting curves of the Cu content versus the intensity of spectral lines corresponding to wavelengths 465.112, 510.554, and 521.820 nm, respectively. From the initial 20 remotely probed LIBS spectral data, we obtained the mean values I1, I2, and I3 of the spectral intensity of the three LIBS spectral lines (465.112, 510.554, and 521.820 nm), which can be turned into three content values C1, C2, and C3 of Cu based on the fitting curves (Fig. 4). In MSLC, taking both the mean spectral intensity values I1, I2, and I3 and their corresponding calculated content values C1, C2, and C3 into consideration for the calibration, we employed a weighed superposition of C1, C2, and C3 as the final content C of Cu, which can be expressed as
FIG. 3. LIBS spectrograms of the five specimens.
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C¼
N X i¼1
Wi Ci
ð1Þ
FIG. 4.
Fitting curves of Cu at wavelengths 465.112, 510.554, and 521.820 nm.
where N is the number of the multi-spectral lines in MSLC (note: N = 3 in our experiment) and the weight factor Wi is denoted as X N Ii ; Wi ¼ Ii = i ¼ 1; 2; 3; :::; N ð2Þ i¼1
This means that the weight factor W i of Ci is proportional to the mean spectral intensity Ii. The data analysis of MSLS is shown in Table II. Finally, the Cu content determined with MSLC is 1.24%. Validation of the Remote LIBS Using a Chemical Experiment. A chemical experiment determining the Cu content of the same ore was designed and conducted to validate the accuracy and further feasibility of the proposed MSLC remote LIBS. The specific steps of the chemical experiment are as follows: (1) Take a 5 g ore specimen at the point where the laser was focused and put it into a hydrochloric acid (HCl) solution of 10% concentration to dissolve. (2) Pour in a NaOH solution of 50% concentration until no
more precipitate is generated; filter the precipitate, which contains the hydroxides of Cu, Fe, Ca, and other metal elements. (3) Pour an excess of aqueous ammonia into the precipitate, and copper hydroxide will create a complexation reaction and generate dissolvable copper ammonia complex ions: CuðOHÞ2 þ4NH3 H2 O ¼½CuðNH3 Þ4 ðOHÞ2 þ4H2 O ð3Þ while hydroxides of Fe, Ca, etc., keep the precipitate state. Then filter the precipitate again, reserving the solution of copper ammonia complex ions. (4) Add an appropriate amount of HCl to the solution of copper ammonia complex ions, and then add NaOH solution, until no more precipitate is generated. (5) Filter the precipitate, pour into 3000 ml of distilled water, and stir sufficiently; then filter the precipitate, which is pure Cu(OH)2; measure the Cu(OH)2. (6) Repeat steps 1 through 5 until five Cu(OH)2 precip-
TABLE II. Data analysis of MSLS for Cu in the ore.
Wavelength (nm) 465.112
510.554
521.820
Mean value, weigh factor, and corresponding content
Intensities of spectral line (counts) 287 179 201 470 761 1135 698 488 922 858 534 495
58 175 108 149 532 653 426 592 301 545 308 346
122 91 158 123 608 544 1473 413 415 581 912 268
35 94 72 457 516 103 338 507 319 104 240 541
48 461 88 467 1283 601 753 509 625 521 412 500
I1 = 192.15 W1 = 0.1449 C1 = 0.6545% I2 = 646.65 W2 = 0.4876 C2 = 1.731% I3 = 487.35 W3 = 0.3675 C3 = 0.8195%
APPLIED SPECTROSCOPY
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itates are obtained; put them into a specimen drying oven, baking them at 60 8C for 120 min, and then weigh the baked Cu(OH)2 powder and calculate the Cu mass. After weighing and calculation, the average Cu mass in the five ore specimens is 0.0622 g, the Cu content in the ore being approximately 1.244%, which is basically consistent with the result 1.24% obtained with the proposed MSLC remote LIBS. However, if the Cu content is determined only by a single wavelength method, it would be 0.6545, 1.731, and 0.8195% (Table II), which corresponds to the 465.112, 510.554, and 521.820 nm wavelengths, respectively, and obviously has a much larger deviation from the chemical experimental result 1.244% compared with the MSLC.
DISCUSSION A remote LIBS system consisting of a custom compact focusing optical device and a SSCS has been built, with which an unknown ore placed 15 m away has been detected. The Cu content of the ore has been determined with an MSLC method. LIBS ionic states at different wavelengths of the same element have a different distribution of energy and transition probability. MSLC introduces weighted values of spectral intensities into the calibration, which considers transition probabilities at different wavelengths and is based on the degeneracy of various ionic states of the same element. In addition, when fitting curves of the content versus the intensity, unlike the single wavelength method whose calculation is only at a specific wavelength considering neither transition probabilities nor degeneracy of ionic states, MSLC adopts several spectral lines that have rather large transition probabilities to calculate, which results in fewer errors. A chemical experiment has been conducted to validate the proposed MSLC remote LIBS, resulting in a definite consistency that hence confirms the feasibility of the proposed LIBS. Studies show that this remote LIBS can be applied to remote elemental analysis, such as analysis of radioactive elements in a nuclear leak and the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. ACKNOWLEDGMENTS This work was supported by the Chinese Natural Science Fund under Grant No. 81260225, the Jiangxi Natural Science Foundation under Grant No. 20122BAB202009, the Foundation of Jiangxi Education Bureau under Grant No. GJJ12408, and the ‘‘Hundred Talents Plan’’ project of CAS. 1. F.A. Kruse, A.B. Lefkoff, J.B. Dietz. ‘‘Expert System-Based Mineral Mapping in Northern Death Valley, California/Nevada, Using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)’’. Remote Sens. Environ. 1993. 44(2): 309-336. 2. R.N. Clark, G.A. Swayze, K.E. Livo, R.F. Kokaly, S.J. Sutley, J.B. Dalton, C.A. Gent. ‘‘Imaging Spectroscopy: Earth and Planetary Remote Sensing with the USGS Tetracorder and Expert Systems’’. J. Geophys. Res. 2003. 108(E12): 5131-5175. 3. J. Moros, J.A. Lorenzo, P. Lucena, L.M. Tobaria, J.J. Laserna. ‘‘Simultaneous Raman Spectroscopy—Laser-Induced Breakdown Spectroscopy for Instant Standoff Analysis of Explosives Using a Mobile Integrated Sensor Platform’’. Anal. Chem. 2010. 82(4): 13891400.
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