Review: Applications of single-shot laser-induced breakdown spectroscopy

Review: Applications of single-shot laser-induced breakdown spectroscopy

Spectrochimica Acta Part B 65 (2010) 185–191 Contents lists available at ScienceDirect Spectrochimica Acta Part B j o u r n a l h o m e p a g e : w ...

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Spectrochimica Acta Part B 65 (2010) 185–191

Contents lists available at ScienceDirect

Spectrochimica Acta Part B j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s a b

Review

Review: Applications of single-shot laser-induced breakdown spectroscopy Anna P.M. Michel Princeton Institute for the Science and Technology of Materials, Princeton University, 70 Prospect Ave, Princeton, NJ 08540, United States

a r t i c l e

i n f o

a b s t r a c t

Article history: Received 22 June 2009 Accepted 21 January 2010 Available online 29 January 2010

As applications for laser-induced breakdown spectroscopy (LIBS) become more varied with a greater number of field and industrial LIBS systems developed and as the technique evolves to be more quantitative that qualitative, there is a more significant need for LIBS systems capable of analysis with the use of a single laser shot. In single-shot LIBS, a single laser pulse is used to form a single plasma for spectral analysis. In typical LIBS measurements, multiple laser pulses are formed and collected and an ensemble-averaged method is applied to the spectra. For some applications there is a need for rapid chemical analysis and/or non-destructive measurements; therefore, LIBS is performed using a single laser shot. This article reviews in brief several applications that demonstrate the applicability and need for single-shot LIBS. © 2010 Elsevier B.V. All rights reserved.

Keywords: Laser-induced breakdown spectroscopy LIBS Single-shot

Contents 1. Introduction . . . . . . . . . . . . 2. Key issues with single-shot LIBS . . 3. Data processing . . . . . . . . . . 4. Cultural heritage . . . . . . . . . . 5. Explosives and military applications . 6. Materials Science. . . . . . . . . . 7. Metals and metal alloys . . . . . . 8. Biological . . . . . . . . . . . . . 9. Environmental applications . . . . . 10. Combustion and catalytic converters 11. Forensics . . . . . . . . . . . . . 12. Conclusions . . . . . . . . . . . . References . . . . . . . . . . . . . . . .

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1. Introduction Laser-induced breakdown spectroscopy (LIBS) has numerous applications including industrial processes, environmental chemistry, biology, and cultural heritage. As LIBS systems become more highly integrated into research laboratories, field-going systems, and industrial processes there is a greater need for systems that are capable of rapid chemical analysis using a single laser shot. The use of a single laser shot allows for spectral analysis of a single plasma. In typical LIBS systems, measurements are made in an ensembleaveraged method with numerous laser-induced plasmas created and their spectral data averaged. Although this method may be

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suitable for many applications, there are many applications where the ability to use a single laser shot (single plasma formation) is highly preferable. The applications of single-shot LIBS are often unique and may have special requirements, for example, avoiding sample destruction. However, the use of single-shot LIBS brings about significant challenges especially in relation to reproducibility, data processing requirements, and the ability to obtain quantitative measurements. An investigation into current research draws attention to a range of applications for single-shot LIBS; yet, exposes the infancy of quantitative single-shot LIBS.

2. Key issues with single-shot LIBS

E-mail address: [email protected]. 0584-8547/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.sab.2010.01.006

One of the issues that has plagued all LIBS work is shot-to-shot reproducibility which significantly limits the ability to make highly

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accurate quantitative measurements. LIBS performance has been identified as improving with the square root of the number of laser shots applied to the sample [1]; thus, ensemble-averaged LIBS data collection has been viewed more favorably and used more frequently than single-shot analysis. Shot-to-shot reproducibility of a LIBS signal is affected by a variety of factors including the coupling of the laser energy to the sample surface and the temperature of the plasma [2]. These factors are affected by the laser (e.g. laser stability, laser fluence, and optical angle of incoming beam). Each laser pulse produces a plasma and the plasmas can vary in temperature and electron density [3]. The sample itself also affects the shot-to-shot variability due to such factors as surface texture, roughness, and sample heterogeneity [2]. Michel and Chave [4] demonstrated that single-shot LIBS data are drawn from an extreme value distribution for both bulk aqueous solutions and solid samples. The extreme nature is attributed to the shot-to-shot variability of plasma formation. Research that aims to improve the sensitivity and precision of LIBS has primarily focused on using ensemble-averaged LIBS data to reduce the effect of spectral fluctuations observed on a shot-to-shot level. However, for many applications, ensemble-averaged LIBS is not ideal, for example, ensemble averaging reaches a natural limit when low concentrations (e.g., aerosols) aerosols, are studied [5]. 3. Data processing Several groups have applied data analysis techniques to try to circumvent some of the reproducibility issues that are inherent to single-shot LIBS and a few of them are reviewed here. Carranza and Hahn [5] looked at ways to use sampling statistics for improved single-shot analysis. They aimed to understand the effects of singleshot laser pulse energy on the analysis of both gaseous and aerosol systems and to gain an understanding of the precision of single-shot LIBS. To reduce the variability of single-shot data, they suggest data normalization using a peak-to-base ratio. Improved quantitative single-shot LIBS measurements are thought to occur when the plasma achieves a saturation condition for absorption of pulse energy by the plasma. This work implements a filtering algorithm to deal with the significant signal noise associated with single-shot spectra and to eliminate irregular spectra. These irregular spectra are attributed to a variety of factors including weak ionization of the plasma, only a small amount of analyte being present in the plasma volume, and imperfect collection of the plasma emission. Carranza and Hahn conclude that single-shot LIBS measurements should be made with enough laser pulse energy to reach saturation with respect to absorbed pulse energy and that it is critical to use an optical collection geometry that minimizes spatial variability. In a separate study, Carranza et al. [6] compared single-shot spectral conditional analysis methods in order to detect single particles using an aerosol stream of silica microspheres. The two methods compared used 1) the peak-to-base ratio and 2) the signal-to-noise ratio (S:N). S:N was defined as the ratio of the integrated atomic emission line intensity (peak area) to the average noise of the adjacent continuum intensity (rms). The rms was calculated using a least-squares fit over a narrow featureless spectral region of about 40 pixels. The S:N method showed improved spectral discrimination. Quantitative single-shot LIBS analysis was examined by Xu et al. [7]. Xu et al. used single-shot LIBS as the basis for a new data acquisition and analysis method to compensate for the fluctuations in LIBS single-shot signals. This method uses the fact that the spectral baseline fluctuates in a similar manner to spectral peak fluctuations. Their method was tested successfully on soils and aerosols and calibration curves were obtained using a series of single shots. A modified version of this method enables concentration prediction using single-shot LIBS. A material identification approach was developed by Munson et al. who used three chemometric techniques [linear correlation, principal

component analysis (PCA), and soft independent modeling of class analogy (SIMCA)] for classifying biomaterials and chemical warfare stimulants [8]. However, Munson et al. found that when single-shot spectra were analyzed, they could only partially differentiate the samples. Improved differentiation was shown when they used spectral averages. Thus, this work again points to an issue with single-shot LIBS. Another method of processing single-shot data, was demonstrated by Ramil et al. who used artificial neural networks for the rapid classification of archaeological ceramics [9]. Using two proposed artificial neural network (ANN) algorithms, single-shot spectra were analyzed. Using these algorithms to identifying ceramics, they achieved a 91% mean success rate using their ANN1 algorithm and an 85% mean success rate with their ANN2 algorithm. Using a linear correlation method, their percent success in single-shot identification was 86%. These high success rates suggest that such methods are viable options for material identification applications. A different approach was shown by Hahn et al., who proposed the use of conditional analysis. Hahn et al. examined the statistical sampling problem presented by the need to analyze effluent metal emissions [10]. Similar to other work using single-shot analysis, Hahn et al. found significant variability in shot-to-shot data. One such example of variability was seen in the analysis of an incinerator waste stream where two single-shot spectra were compared. In one spectrum a trace amount of Be was detected and no Cd or Fe was detected, whereas in the second spectrum, the Cd signal saturated the detector. A conditional analysis approach was proposed that separates single-shot particle hits from misses. Using this conditional analysis, improvement in sensitivity was achieved. Single-shot spectra were then identified that had metal signals that were twenty times greater than the multi-shot averaged metal signals, thus showing significant signal-to-noise ratios [10]. Gibb-Snyder et al. [11] used correlation analysis for differentiating Bacillus anthracis surrogate spores from common aerosol mixtures using single-shot LIBS. However, false negatives and false positives sometimes resulted. De Lucia et al. [14] used partial least-squares discriminant analysis (PLS-DA) to discriminate explosives from non-explosives and Gottfried et al. [15] used PLS-DA for biological warfare agents. De Lucia et al. aimed to use PLS-DA samples that included non-explosives such as house dust and fingerprints and explosives such as cyclotrimethylenetrinitramine (RDX) and trinitrotoluene (TNT). LIBS spectra were taken on samples at 20 m and 30 m standoff distances and using PLSDA were able to identify samples as being an explosive versus a nonexplosive with a 77% success rate and a 5% false positive rate. A similar experiment was conducted at a distance of 50 m with much poorer identification found (15% correct identification and a 7.8% false positive rate), although it should be noted that the standoff system was designed for ∼ 30 m distance. Reproducibility is the most significant issue with single-shot LIBS. Without improvements to reproducibility, single-shot LIBS will never reach the level of accurate measurements needed to consider it a truly quantitative technique. Numerous factors contribute to reproducibility. Linear correlation can be used to compare a spectrum to a reference spectrum. When a set of experimental spectra are compared to reference spectra using correlation methods, a set of correlation coefficients are calculated. The coefficients show a statistical distribution which is dependent on the experimental conditions used to create the spectra. Lentjes et al. [12] used single-shot LIBS on Si and Al samples to examine the effect of experimental parameters (e.g. pulse energy) on the variance and mean of these correlation coefficients. This study showed a decrease in the variance and the mean with decreasing signal strength, a decrease in the variation of correlation coefficients and an increase in the mean with increasing pulse energy, a decrease in plasma emission intensity and the signal-to-noise ratio (S:N) with an increase in delay time, an increase in variance and a decrease in mean for shorter integration times, and a decrease in

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variance and an increase in mean with a decrease in optical resolution. Using linear correlation analysis, using single-shot LIBS, they could correctly identify samples (aluminum alloys) with a 75% success rate. However, using ensemble-average spectra and correlation analysis, they could achieve a 99.9% identification success rate [13], again pointing to the shortcomings of current use of single-shot analysis. The variety of methods proposed may be significantly different in approach, yet all focus on trying to overcome or account for shot-toshot variability. Robust data processing methods that can account for the variability are essential if single-shot LIBS is to become a truly quantitative technique. 4. Cultural heritage One important application that has emerged for single-shot LIBS is cultural heritage. Cultural heritage includes the historical study of art and artifacts and analytical chemistry provides an important means for its study. As a result of the high value of items such as artwork, there is a need for non-destructive analytical techniques. Using the LIBS technique in a single-shot mode for in situ analysis of art results in little damage and can be considered practically non-destructive. LIBS has the added advantage that it requires less than a µg of sample and no sample preparation, whereas many other analytical techniques require significant sample sizes and sample preparation. In addition, since it is an optical technique that is capable of field-going applications, LIBS systems can be taken directly to the art instead of the art needing to be taken into a laboratory setting. Single-shot LIBS has significant potential applications for cultural heritage. LIBS can be used for pigment or material identification which can answer questions about dating, origin, and possible forgery. In addition, effects of the environment on a piece can be studied, for example, to look at pollutant deposition on a piece. This in term can lead to a better understanding of the condition of a piece. One example of a cultural heritage application was shown by Acquaviva et al. [16] who used single-shot LIBS for the analysis of ordnance, more specifically a gun found in the Adriatic seabed. This work demonstrated that LIBS is a useful diagnostic tool to test the restoration level of artwork. In applications of cultural heritage such as this one, there is a need for rapid elemental analysis with little sample damage and no sample preparation needed. The use of singleshot LIBS is important for cultural heritage applications as significant spatial resolution studies can be made effectively with little damage to the sample. Similarly, depth studies with little damage are possible. Homogeneity studies are also made possible with the use of singleshot LIBS. Acquaviva et al. [16] investigated the effectiveness of restorative cleaning of ordnance by analyzing it before and after its restoration. Prior to using cleaning methods, LIBS can detect the presence of non-native elements. Thus, the type of cleaning needed can be determined. After cleaning, LIBS can determine if the nonnative elements have been completely removed. In the ordnance work, prior to cleaning, elements identified as being present were Cu I and Cu II and Sn I. The presence of these elements suggested that the gun was made primarily of bronze since copper is the main component of bronze alloys. After the restorative cleaning, Fe I and Fe II, Pb I, and Al I were identified as being present. Ca spectral lines were identified to be present on the sample before cleaning but not after, suggesting that the cleaning processes for item conservation was successful. In another application of cultural heritage, Acquaviva et al. [17] used single-shot LIBS for the restoration process of the bust of St. Gregory the Armenian. LIBS was used to perform a qualitative examination to determine the metal alloys present in the bust and to determine the status of the restoration carried out on the artwork. Using LIBS, they showed that part of the bust believed to be made of brass was actually made of gold. Furthermore, it was found that the bust was covered with polluted layers high in elements such as calcium.

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Another cultural heritage application was demonstrated by Anglos et al. who used single-shot LIBS for the analysis of paint used in artworks [18]. Spectral characteristics and elemental peaks of pigments were first determined using modern and old pigments on powder and model oil painting samples. LIBS analysis was then used to show chemical differences of both retouched and un-retouched areas. Similarly, Bruder et al. used single-shot LIBS for wall painting pigment analysis [19]. This work used single-shot LIBS for elemental analysis which allowed for pigment recognition. The craters formed from the LIBS plasma were then used for Raman spectroscopy for molecular determination and to confirm the LIBS analysis findings. Other examples of single-shot cultural heritage applications include the classification of archaeological ceramics [9], the analysis of paint pigments [20], characterization of parchment (a writing material produced from animal skin) [1], the analysis of historical paper documents [21], and polychromes from the Spanish Baroque period and from the XV century [22]. 5. Explosives and military applications Two important areas that benefit from single-shot LIBS are explosives detection and military applications. Such applications require rapid detection with minimal laser shots. For these applications, it is often preferable to use single-shot standoff detection for the safety of the LIBS system operator. Lopez-Moreno et al. [23] demonstrated the use of single-shot standoff LIBS for the detection of energetic materials at distances up to 45 m. The field portable system developed was used to characterize organic compounds and was capable of detecting a solid residue of 2,4-dinitrotoluene (DNT) acetone solution evaporated on an aluminum plate using a single-shot spectrum. De Lucia et al. [14] used single-shot, although using a double pulse, LIBS for explosives detection at standoff distances. This work required single-shot analysis as the residue being analyzed was present only in trace amounts. Gottfried et al. used a similar set up for single-shot (double pulse) standoff detection of biological warfare agent surrogates [15]. Other applications include the detection of the explosive TNT [24] and the detection of halons, which are used by the military for fire suppression in some weapons systems [25]. In a different application, Harmon et al. utilized single-shot LIBS for the identification of plastic landmine casings [26,27]. This work used a single cleaning shot followed by a single laser data collection shot. Single-shot LIBS was utilized as it is considered the most likely to be used under field operation of a LIBS landmine sensor system. The absolute peak intensities in the spectra were shown to vary which they attributed to the surface roughness of the plastic mines. This roughness can lead to differences in incidence angle of the incoming laser beam, light absorption, and surface reflectance. Variations of intensity may also be due to laser-sample coupling and light reflection during both breakdown and plasma formation. Using single-shot analysis, distinct differences between anti-personnel and anti-tank mines using broadband spectral differences were shown. This work was aided by the development of a library of single-shot LIBS spectra for landmine casings and plastic objects which was used to then compare unknown samples with using linear correlation methods. Additional work on single-shot LIBS for mine detection was carried out by Bohling et al. [28]. 6. Materials Science Several applications in the field of materials science have utilized single-shot LIBS. For example, single-shot LIBS has been used for the analysis of thin films produced by pulsed laser ablation of multielemental targets [29]. The advantage of single-shot LIBS for such an application is it avoids the ablation of materials at depths greater than the thickness of the films. Aragon et al. also used single-shot LIBS for the analysis of thin films and found significantly higher line intensities

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for the thin film analysis than for bulk sample analysis [30]. Another materials science application is the surface analysis of solar cells [31]. Depth analysis studies using single shots revealed a loss of spectral peak intensity with each subsequent shot due to the small loss of optical focus with each consecutive shot.

[34] quantitatively investigated the effect of surface topography on the characterization of stainless steel and showed that an increase of laser irradiance decreased the effects of surface irregularities (reported as an improved relative standard deviation). Polished surfaces also improved signal reproducibility.

7. Metals and metal alloys

8. Biological

Although the analysis of metals and metal alloys often does not require extreme care to prevent sample destruction; there are several applications that benefit from single-shot LIBS, to avoid significant destruction. To understand the amount of sample that is ablated, several groups have estimated ablation values for metals. Such estimates are calculated after a series of plasmas have been formed. Caneve et al. [32] compared single and double pulse LIBS on copperbased alloys. Using a contact profilometer, the mass of ablated material was determined. It should be noted that changes to experimental conditions, such as laser pulse energy, pulse width, or sample type/characteristics, greatly affect the ablation rate (defined as crater depth per laser shot). Caneve et al. suggest that for the copperbased alloys, on the order of 200 shots are needed to produce a measurable crater for ablation rate estimation. The ablation rate was found to be 0.8–0.11 µm/shot. This ablation rate was shown by Caneve et al. to be easily changed by sample elemental composition with an increased ablation rate with increased Zn content. This was attributed to the lowering of the melting point with increased Zn content. An ablation rate was also calculated by Cabalin et al. [33] for stainless steel samples in air and ranged from about 0.14 – 3.4 μm/shot, dependent on conditions used. The ablation rate was found to be nonuniform through a sample and to be dependent on both the focusing of the laser pulse and the energy of the pulse. For example, if a sample is placed below the focal point, a plasma will result from the breakdown of the gas surrounding the sample which will in turn shield the actual sample from the laser. As a result, the amount of the sample ablated will be less. If the focus is on the sample, a deep and narrow crater will form which will confine a plasma within the crater; thus, shielding laser energy and resulting in material deposition. In contrast, a larger diameter crater allows a plasma to expand freely with ablated material able to exit the crater. Cabalin et al. report a range of average mass amount ablated and demonstrated that it increases with increasing laser pulse energy. All ablated mass amounts measured are in the range of 10–52 ng/pulse for energies of 4.5–14.6 mJ/pulse and for samples of thickness 250–1000 µm. Cravetchi et al. used single-shot femtosecond LIBS for the microanalysis using μJ pulses of aluminum alloys [35]. Using single shots consecutively in the same location revealed that a second shot showed a reduction in signal compared to the first shot. Subsequent pulses led to an increase of the signal back to approximately the level of the first shot possibly due to a change in physical–chemical properties of the sample surface. Single-shot spectra of an aluminum alloy matrix using µJ pulse energies could be used to detect such elements as Mg, Al, and Mn. Cravetchi et al. suggest that sample characteristics, like surface roughness and variations of local reflectivity, can affect plasma plume formation and thus can affect single-shot LIBS microanalysis using low pulse energies. Further work by Cravetchi et al. [36,37] used single-shot LIBS for the analysis of Al alloys using microanalysis. This work showed the ability to distinguish different precipitates (e.g. Mn– Fe–Cu versus Mg–Cu and Al–Cu–Fe–Mn versus Al–Cu–Mg) in Al alloys. Furthermore, single shots were used for 2D mapping of precipitates. Work by Bauer et al. used an Echelle spectrometer coupled with a time-gated ICCD camera for the simultaneous measurements of all detectable analyte lines by single laser shots for aluminum. This work showed it was possible to obtain information on inhomogeneities of solid samples with single shots [38]. Single-shot analysis has also been applied to the qualitative analysis of a silver ornament and an aluminum sheet [39] and for stainless steel [33,34]. Cabalin et al.

Single-shot LIBS is important for the study of biological samples especially when samples are fragile, such as leaves, or small in size, such as aerosols or spores. Single-shot LIBS was used by Galiova et al. to investigate the heavy metal accumulation in plants by the analysis of leaves [40,41]. In plant science, leaf analysis is important for identifying where in a plant ions are stored and pollutants are accumulated. Furthermore, single-shot LIBS for leaf analysis can address spatial resolution questions. Medical applications can also benefit from single-shot LIBS. For example, single-shot LIBS has been used for the identification of the major and minor constituents of cholesterol gallstones [42]. LIBS can be used to determine the constituents both on the stone surface and inside the stones. The LIBS technique is advantageous for this type of work since it is a rapid technique, is not time intensive, and does not require sample preparation. In this work, LIBS spectra were analyzed for elemental identification and comparison of relative concentrations. Both mineral elements (e.g. calcium, copper, magnesium, sodium, and potassium) and organic elements (e.g. carbon, nitrogen, oxygen, and hydrogen) were studied. The intensity of the atomic lines of C, Ca, H, Mg, N, Na, O, and K were shown to be different for pigmented and non-pigmented regions of stones, thus suggesting concentration differences. Application of LIBS to the analysis of biological samples is useful for samples that are small in size, though it is not without its challenges. Aerosol analysis is a unique application that requires significant work in order to actually form a plasma on an aerosol particle. Hybl et al. [43] used single-shot LIBS for the analysis of biological aerosols by using fluorescence cuing (using a 266 nm laser to stimulate fluorescence from individual particles and conditional upon the fluorescence signal, fires a laser for LIBS). This allowed a 75% probability of a particle being inside a plasma on each shot. However, there was still significant variation in the signal strength most likely due to the variation in the position of the particle inside the plasma. Spores have also been the focus of LIBS for the analysis of biological samples, for example, B. anthracis surrogate spores, were analyzed by Gibb-Snyder et al. [11]. Areas of spectra where strong emission lines are expected from the NIST handbook of basic atomic spectroscopic data were selected. The elemental composition of the spores was known from previous analytical work. Correlation analysis and principal component analysis were used for the analysis; yet, this work suggests shortcomings in using a library for identification since differences in spore spectra and outdoor air were found to be small. It was suggested that more spectra are needed for improved libraries to make such analyses more robust and therefore improve spore identification. In work by Dixon and Hahn [44], single-shot single particle analysis for the detection of bioaerosols (Bacillus spores) was explored. A real-time algorithm was used to calculate a peak-tobase ratio. Ca peaks at 393.4 nm and 396.9 nm were used and a baseline was defined as the average intensity of an adjacent region to the Ca peaks that did not contain interfering atomic emission peaks. A peak-to-base threshold value was set to obtain a false hit rate of 1–2 false hits per 2000 laser shots. Each spectrum identified as a hit was manually inspected for the presence of distinct emission peaks corresponding to both emission lines. 20,000 single laser shots resulted in 45 particle hits based on the presence of the two Ca peaks. Five of the particle hits were discounted as it was believed that multiple spores were hit. The measured equivalent calcium

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concentration was calculated using both Ca lines and corresponding calibration curves. By looking at the degree of variation between the measured equivalent calcium concentrations from each of the lines, the precision of the technique could be determined. The relative percent deviation between the analyte responses of these two lines was calculated as the difference in the equivalent calcium concentrations based on the two lines normalized by the average value of the two equivalent concentrations. Perfect agreement between the two lines would yield a relative percent deviation of zero which is what was found. When looking at an individual single-shot spectrum, the agreement between the two calcium emission lines showed that there was an average deviation of 34.8% with a relative standard deviation of 78%. Spores can be detected based on the calcium emission with a mass of 1 fg; however, the uncertainty of measurement is on the order of 35%. Na and Mg spectral peaks were also compared and it was concluded that the mass of Mg and Na was too small to be detected by single-shot LIBS under the conditions used. Overall it was found that detection and identification of single Bacillus spores was not feasible using the current LIBS set up. 9. Environmental applications Applications in the environmental arena that can benefit from single-shot LIBS range from rock analysis to soil analysis. Harmon et al. [2] illustrate the use of single-shot LIBS for various minerals and thus suggest its use for geochemical, mineralogical, and environmental surveying. One example of such work is the use of single-shot broadband spectra to create libraries of shales which were then used to compare with unknown samples [2]. These unknowns were all identified as being in the right group and were mostly specimen identifiable. Aerosols are again an important application that can benefit from single-shot LIBS [45,46]. Hahn and Lunden [45] showed that emission lines were detectable in single-shot spectra yet these spectra had a lower S:N than when ensemble averaging was used. This was attributed to the random shot noise from the intensifier of the ICCD detector system. Moskal and Hahn showed that single-shot LIBS [47] is capable of distinguishing wood treated with copper chromated arsenate versus untreated wood. Treated wood is an environmental hazard for disposal, yet, acts as a preservative by protecting it from insect and fungal deterioration. Numerous other applications have used single-shot LIBS for environmental analysis. For example, the analysis of heavy metals in soil was carried out by Pandhija and Rai [39]. Soil samples were made into pellets and analyzed to show qualitatively to contain such elements as Al, Ba, Mg, Si, Ti, C, Mn, N, O, Fe, Ca, Na, K, Li, and Pb. Heavy metals (Mg, Al, Fe, Cu, and Hg) were further investigated to determine how soil depth affects their concentration. Their concentration was greater at the soil surface and less at greater soil depths. This was shown by comparison of atomic line intensity. Further quantitative studies were carried out by the creation of calibration curves and reference samples with known constituents and the same matrix as unknown samples. Soil samples were spiked with varying concentrations of Pb by adding pure Pb(NO3)2 to create calibration curves (Pb concentration versus intensity ratio of spectral line of Pb at 220.3 nm and Fe at 234.3 nm). Wainner et al. examined environmental lead contamination [48]. Shot-to-shot background-subtracted variability for the two systems was examined for Pb powder dopant (Pb 405.8 nm). The relative standard deviation of the single shots was found to be 35% for the laboratory system and 45% for the portable system. Furthermore, single-shot LIBS was capable of detecting Pb in soil samples at concentrations of 100 ppm and 400 ppm. Significant shot-to-shot variation was seen in the work by Wainner et al. and was partially contributed to the inhomogeneity of the samples.

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McMillan et al. attempted to use LIBS to discriminate between different types (origin location) of beryl (Be3Al2Si6O18), a gem forming mineral [49]. A library of single-shot broadband LIBS spectra was created for 21 beryl samples which varied in color and country of origin. “Unknown” samples were then randomly selected from the beryl samples and a single-shot broadband LIBS spectrum acquired for each sample. Using linear correlation analysis, the “unknown” was then compared to the library. Peak intensities for greater than 13,600 spectrometer pixels in the 200–980 nm spectral range were compared to the 21 library spectra with a match considered the one with the highest correlation coefficient. 35 of 37 specimens were identified correctly. In this study, variability was attributed to surface texture, roughness, and small-scale mineralogical and chemical heterogeneity of the sample. 10. Combustion and catalytic converters Several groups have shown the use of single-shot LIBS for studying aspects of combustion [50,51] and for the analysis of catalytic converters [53,54]. Lucena et al. [53] used single-shot LIBS for studying Pt, Rh, and Zr in catalytic converters (non-conducting ceramics). Lucena et al. [54], used LIBS to study three-way catalysts which are aluminum-coated ceramics that include platinum-group metals. LIBS was used for the detection of P, Zn, Pb, Pt, Pd, Ce, and Si. Single-shot LIBS has been used for the analysis of engine/ combustion system equivalence ratios and measurements of hydrocarbons, for example, the measurement of C, O, N, and CN in engine exhaust gas [50,51]. Using single-shot LIBS, Ferioli et al. found that spectral peaks were less distinctive than those identified using ensemble-averaged data. Additional noise was seen when using single-shot LIBS which was attributed to both the intensifier readout and the plasma emission. In an attempt to overcome the signal-tonoise issue, it was suggested to average over more pixels through the integration of a signal across a broader spectral range. Joshi et al. [52] demonstrated the simultaneous use of laser sparks for LIBS to measure equivalence ratio in natural gas engines and for engine ignition. This work obtained single-shot spectra containing the resolved peaks of Hα, O715, and O777 and the partially overlapping, non-resolved peaks of N742, N744, and N746 in a gaseous medium in a combustion chamber. When 300 spectra were averaged, a strong linear correlation between line intensity ratios from LIBS and equivalence ratios was found which showed that in-cylinder LIBS for engine equivalence ratio measurements is feasible. The use of single-shot spectra would be a significant benefit to this application if it can be used to quantify equivalence ratios for individual cycles. The potential for single-shot LIBS to be used was analyzed by examining the variation of individual measurements. Variability of line intensity ratios for Hα/O777 and Hα/Ntot (Ntot is the total integrated area of three atomic nitrogen lines 742, 744, and 746 nm) was found to be about 7% of the mean. The variability is attributed to fluctuation in the actual overall equivalence ratio, the signal-to-noise ratio of spectra, variation of the laser spark, the effect of vibration on alignment of optical components, and fluctuation of the local equivalence ratio at the spark location. The actual equivalence ratio fluctuation was determined to be minimal, thus not greatly affecting the variability. The S:N was found to be high; thus, again minimally contributing to the variability. Shot-to-shot fluctuations exist for laser-induced breakdown events and Joshi et al. suggest that in high pressure air environments, these fluctuations are on the order of 1–6%. Such fluctuations typically affect similar spectral lines the same; therefore, ratios result in only a ∼0.01% fluctuation, thus this is a minimal effect. Variability in a combustion environment can be significantly increased by the presence of soot and other particulates. The presence of these contaminants lowers the breakdown threshold intensity and affects the plasma. Another factor that was considered to contribute to the

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variability is vibration which can affect both laser delivery and spark collection. However, the majority of fluctuations were attributed to actual variation in equivalence ratio at the spark location with additional variability contributed by vibration effects and contamination (soot and particulates).

11. Forensics The field of forensics can greatly benefit from the analytical nature of LIBS and furthermore from single-shot LIBS due to the often small sample size to be analyzed. For example, one unique application is the detection of gunshot residues on the hands of a shooter [55]. This application required tape to be used to collect residue from a hand which was then analyzed using a single-shot due to the fragility and thinness of the tape. MicroLIBS, using pulse energies less than 100 µJ, can be used for single-shot analysis and has been demonstrated to be effective for the detection and two-dimensional mapping of fingerprints [56]. In work by Taschuk et al., [56], latent fingerprints (those resulting from the transfer of skin oil) on a Si wafer were examined by the observation of Na emission lines using femtosecond pulses. Due to the destructive nature of LIBS, single-shot LIBS is essential. Na, although ubiquitous, was used for the analysis. S:N was defined here as the background corrected strength of the line of interest divided by the standard deviation of a region away from the peak that did not contain spectral peaks. To map fingerprints, a one-dimensional scan over the fingerprint was completed which found that in fingerprint ridges, the Na signal was much lower. One significant drawback of using single-shot LIBS for fingerprint mapping, is the amount of time needed to measure even a small part of a fingerprint (e.g. 20 min to analyze 1% of a thumbprint with single-shot mapping).

12. Conclusions Single-shot LIBS shows tremendous possibility for the chemical analysis of a range of sample types and also for the identification of samples. The potential for using single-shot LIBS is shown here to be applicable to cultural heritage samples, explosives, military applications, metals and metal alloys, biological samples, environmental samples, combustion analysis and catalytic converters, and forensics samples. The advantages of using single-shot LIBS include rapid chemical analysis, the ability to not destroy a sample, and the ability to map a sample. The most significant drawback of this technique is the reproducibility of the spectral line intensity which numerous factors can affect. Shot-to-shot variations may result from the laser source (e.g. pulse instability), interactions (e.g. laser pulse–plasma, plasma– sample, and laser pulse–sample), amount of sample ablated, characteristics of the sample (e.g. roughness, chemical composition, and homogeneity), matrix effects, moving breakdown, environmental factors (e.g. presence of particulates or moisture), scattering of light, and breakdown threshold. The shot-to-shot variations thus lead to difficulties with using single-shot LIBS for quantitative work. However, in many application qualitative analysis is all that is required or needed, thus making single-shot LIBS a viable option.

References [1] B. Dolgin, Y. Chen, V. Bulatov, I. Schechter, Use of LIBS for rapid characterization of parchment, Anal. Bioanal.Chem. V386 (2006) 1535–1541. [2] R.S. Harmon, F.C. De Lucia, C.E. McManus, N.J. McMillan, T.F. Jenkins, M.E. Walsh, A. Miziolek, Laser-induced breakdown spectroscopy — an emerging chemical sensor technology for real-time field-portable, geochemical, mineralogical, and environmental applications, Appl. Geochem. 21 (2006) 730–747. [3] I.B. Gornushkin, B.W. Smith, G.E. Potts, N. Omenetto, J.D. Winefordner, Some considerations on the correlation between signal and background in laserinduced breakdown spectroscopy using single-shot analysis, Anal. Chem. 71 (1999) 5447–5449.

[4] A.P.M. Michel, A.D. Chave, Analysis of laser-induced breakdown spectroscopy (LIBS) spectra: the case for extreme value statistics, Spectrochim. Acta Part B 62 (2007) 1370–1378. [5] J.E. Carranza, D.W. Hahn, Sampling statistics and considerations for single-shot analysis using laser-induced breakdown spectroscopy, Spectrochim. Acta Part B 57 (2002) 779–790. [6] J.E. Carranza, K. Lida, D.W. Hahn, Conditional data processing for single-shot spectral analysis by use of laser-induced breakdown spectroscopy, Appl. Opt. 42 (2003) 6022–6028. [7] L. Xu, V. Bulatov, V.V. Gridin, I. Schechter, Absolute analysis of particulate materials by laser-induced breakdown spectroscopy, Anal. Chem. 69 (1997) 2103–2108. [8] C.A. Munson, F.C. De Lucia Jr., T. Piehler, K.L. McNesby, A.W. Miziolek, Investigation of statistics strategies for improving the discriminating power of laser-induced breakdown spectroscopy for chemical and biological warfare agent simulants, Spectrochim. Acta Part B 60 (2005) 1217–1224. [9] A. Ramil, A.J. Lopez, A. Yanez, Application of artificial neural networks for the rapid classification of archaeological ceramics by means of laser induced breakdown spectroscopy (LIBS), Appl. Phys. A 92 (2008) 197–202. [10] D.W. Hahn, W.L. Flower, K. Henken, Discrete particle detection and metal emissions monitoring using laser-induced breakdown spectroscopy, Appl. Spectrosc. 51 (1997) 1836–1844. [11] E. Gibb-Snyder, B. Gullett, S. Ryan, L. Oudejans, A. Touati, Development of sizeselective sampling of Bacillus anthracis surrogate spores from simulated building air intake mixtures for analysis via laser-induced breakdown spectroscopy, Appl. Spectrosc. 60 (2006) 860–870. [12] M. Lentjes, K. Dickman, J. Meijer, Influence of process parameters on the distribution of single shot correlation coefficients obtained by correlating LIBspectra, Appl. Phys. A 88 (2007) 661–666. [13] M. Lentjes, K. Dickmann, J. Meijer, Calculation and optimization of sample identification by laser induced breakdown spectroscopy via correlation analysis, Spectrochim. Acta Part B 62 (2007) 56–62. [14] F.C. De Lucia Jr, J.L. Gottfried, C.A. Munson, A.W. Miziolek, Multivariate analysis of standoff laser-induced breakdown spectroscopy spectra for classification of explosive-containing residues, Appl. Opt. 47 (2008) G112–G121. [15] J.L. Gottfried, F.C. De Lucia Jr., C.A. Munson, A.W. Miziolek, Standoff detection of chemical and biological threats using laser-induced breakdown spectroscopy, Appl. Spectrosc. 62 (2008) 353–363. [16] S. Acquaviva, M. DeGiorgi, C. Marini, R. Poso, Elemental analyses by laser induced breakdown spectroscopy as a restoration test on a piece of ordnance, J. Cult. Herit. 5 (2004) 365–369. [17] S. Acquaviva, M. De Giorgi, C. Marini, R. Poso, A support of restoration intervention of the bust of St. Gregory the Armenian: compositional investigations by laser induced breakdown spectroscopy, Appl. Surf. Sci. 248 (2005) 218–223. [18] D. Anglos, C. Balas, C. Fotakis, Laser spectroscopic and optical imaging techniques in chemical and structural diagnostics of painted artwork, Am. Lab. (1999) 60–67. [19] R. Bruder, V. Detalle, C. Coupry, An example of the complementarity of laserinduced breakdown spectroscopy and Raman microscopy for wall painting pigment analysis, J. Raman Spectrosc. 38 (2007) 909–915. [20] I. Osticioli, M. Wolf, D. Anglos, An optimization of parameters for application of a laser-induced breakdown spectroscopy microprobe for the analysis of works of art, Appl. Spectrosc. 62 (2008) 1242–1249. [21] A. Kaminska, M. Sawczak, K. Komar, G. Sliwinski, Application of the laser ablation for conservation of historical paper documents, Appl. Surf. Sci. 253 (2007) 7860–7864. [22] M. Martin, M. Castillejo, R. Torres, D. Silva, F. Guerra-Librero, LIBS spectra of polychromes with a low cost ccd camera based detector, J. Cult. Herit. 1 (Supplement 1) (2000) S293–S296. [23] C. Lopez-Moreno, S. Palanco, J. Javier Laserna, F. De Lucia Jr, A.W. Miziolek, J. Rose, R.A. Walters, A.J. Whitehouse, Test of a stand-off laser-induced breakdown spectroscopy sensor for the detection of explosive residues on solid surfaces, J. Anal. At. Spectrom. 21 (2006) 55–60. [24] Y. Dikmelik, C. McEnnis, J.B. Spicer, Femtosecond and nanosecond laser-induced breakdown spectroscopy of trinitrotoluene, Optics Express 16 (2008) 5332–5337. [25] C.K. Williamson, R.G. Daniel, K.L. McNesby, A.W. Miziolek, Laser-induced breakdown spectroscopy for real-time detection of halon alternative agents, Anal. Chem. 70 (1998) 1186–1191. [26] R.S. Harmon, F.C. De Lucia Jr., A. Lapointe, R.J. Winkel Jr., A.W. Miziolek, Discrimination and identification of plastic landmine casings by single-shot broadband LIBS, Proc. SPIE 5794 (2005) 92. [27] R.S. Harmon, F.C. De Lucia Jr., A. Lapointe, R.J. Winkel Jr., A.W. Miziolek, LIBS for landmine detection and discrimination, Anal. Bioanal.Chem. 385 (2006) 1140–1148. [28] C. Bohling, D. Scheel, K. Hohmann, W. Schade, M. Reuter, G. Holl, Fiber-optic laser sensor for mine detection and verification, Appl. Opt. 45 (16) (2006) 3817–3825. [29] S. Acquaviva, E. D'Anna, M. De Giorgi, F. Moro, Laser-induced breakdown spectroscopy for compositional analysis of multielemental thin films, Spectrochim. Acta Part B 61 (2006) 810–816. [30] C. Aragon, V. Madurga, J.A. Aguilera, Application of laser-induced breakdown spectroscopy to the analysis of the composition of thin films produced by pulsed laser deposition, Appl. Surf. Sci. 197-198 (2002) 217–223. [31] J.M. Vadillo, S. Palanco, M.D. Romero, J.J. Laserna, Applications of laser-induced breakdown spectroscopy (LIBS) in surface analysis, Fresenius J. Anal. Chem. 355 (1996) 909–912. [32] L. Caneve, F. Colao, R. Fantoni, V. Spizzichino, Laser ablation of copper based alloys by single and double pulse laser induced breakdown spectroscopy, Appl. Phys. A 85 (2006) 151–157.

A.P.M. Michel / Spectrochimica Acta Part B 65 (2010) 185–191 [33] L.M. Cabalin, D. Romero, J.M. Baena, J.J. Laserna, Saturation effects in the laser ablation of stainless steel in air at atmospheric pressure, Fresenius J. Anal. Chem. 365 (1999) 404–408. [34] L.M. Cabalin, D. Romero, J.M. Baena, J.J. Laserna, Effect of surface topography in the characterization of stainless steel using laser-induced breakdown spectrometry, Surf. Interface Anal. 27 (1999) 805–810. [35] I.V. Cravetchi, M.T. Taschuk, Y.Y. Tsui, R. Fedosejevs, Evaluation of femtosecond LIBS for spectrochemical microanalysis of aluminium alloys, Anal. Bioanal.Chem. V385 (2006) 287–294. [36] I.V. Cravetchi, M. Taschuk, G.W. Rieger, Y.Y. Tsui, R. Fedosejevs, Spectrochemical microanalysis of aluminum alloys by laser-induced breakdown spectroscopy: identification of precipitates, Appl. Opt. 42 (2003) 6138–6147. [37] I. Cravetchi, M. Taschuk, Y. Tsui, R. Fedosejevs, Scanning microanalysis of Al alloys by laser-induced breakdown spectroscopy, Spectrochim. Acta Part B 59 (2004) 1439–1450. [38] H.E. Bauer, F. Leis, K. Niemax, Laser induced breakdown spectrometry with an Echelle spectrometer and intensified charge coupled device detection, Spectrochim. Acta Part B 53 (1998) 1815–1825. [39] S. Pandhija, A.K. Rai, Laser-induced breakdown spectroscopy: a versatile tool for monitoring traces in materials, Pramana-Journal of Physics 70 (2008) 553–563. [40] M. Galiova, J. Kaiser, K. Novotney, J. Novotny, T. Vaculovic, M. Liska, R. Malina, K. Stejskal, V. Adam, R. Kizek, Investigation of heavy-metal accumulation in selected plant samples using laser induced breakdown spectroscopy and laser ablation inductively coupled plasma mass spectrometry, Appl. Phys. A 93 (2008) 917–922. [41] M. Galiova, J. Kaiser, K. Novotny, O. Samek, L. Reale, R. Malina, K. Palenikova, M. Liska, V. Cudek, V. Kanicky, V. Otruba, A. Poma, A. Tucci, Utilization of laser induced breakdown spectroscopy for investigation of the metal accumulation in vegetal tissues, Spectrochim. Acta Part B 62 (2007) 1597–1605. [42] V.K. Singh, V. Rai, A.K. Rai, Variational study of the constituents of cholesterol stones by laser-induced breakdown spectroscopy, Lasers Med. Sci. 24 (2009) 27–33. [43] J.D. Hybl, S.M. Tysk, S.R. Berry, M.P. Jordan, Laser-induced fluorescence-cued, laser-induced breakdown spectroscopy biological-agent detection, Appl. Opt. 45 (2006) 8806–8814. [44] P.B. Dixon, D.W. Hahn, Feasibility of detection and identification of individual bioaerosols using laser-induced breakdown spectroscopy, Anal. Chem. 77 (2005) 631–638.

191

[45] D.W. Hahn, M.M. Lunden, Detection and analysis of aerosol particles by laserinduced breakdown spectroscopy, Aerosol Sci. Technol. 33 (2000) 30–48. [46] J.E. Carranza, B.T. Fisher, G.D. Yoder, D.W. Hahn, On-line analysis of ambient air aerosols using laser-induced breakdown spectroscopy, Spectrochim. Acta Part B: At. Spectrosc. 56 (2001) 851–864. [47] T. Moskal, D. Hahn, On-line sorting of wood treated with chromated copper arsenate using laser-induced breakdown spectroscopy, Appl. Spectrosc. 56 (2002) 1337–1344. [48] R.T. Wainner, R.S. Harmon, A.W. Miziolek, K.L. McNesby, P.D. French, Analysis of environmental lead contamination: comparison of LIBS field and laboratory instruments, Spectrochim. Acta Part B 56 (2001) 777–793. [49] N.J. McMillan, C.E. McManus, R.S. Harmon, F.C.D. Lucia, A.W. Miziolek, Laserinduced breakdown spectroscopy analysis of complex silicate minerals — beryl, Anal. Bioanal.Chem. V385 (2006) 263–271. [50] F. Ferioli, P.V. Puzinauskas, S.G. Buckley, Laser-induced breakdown spectroscopy for on-line engine equivalence ratio measurements, Appl. Spectrosc. 57 (2003) 1183–1189. [51] F. Ferioli, S.G. Buckley, Measurements of hydrocarbons using laser-induced breakdown spectroscopy, Combust. Flame 144 (2006) 435–447. [52] S. Joshi, D.B. Olsen, C. Dumitrescu, P.V. Puzinauskas, Laser-induced breakdown spectroscopy for in-cylinder equivalence ratio measurements in laser-ignited natural gas engines, Appl. Spectrosc. 63 (2009) 549–554. [53] P. Lucena, J.J. Laserna, Three-dimensional distribution analysis of platinum, palladium and rhodium in auto catalytic converters using imaging-mode laserinduced breakdown spectrometry, Spectrochim. Acta Part B: At. Spectrosc. 56 (2001) 177–185. [54] P. Lucena, J.M. Vadillo, J.J. Laserna, Compositional mapping of poisoning elements in automobile three-way catalytic converters by using laser-induced breakdown spectrometry, Appl. Spectrosc. 55 (2001) 267–272. [55] C.R. Dockery, S.R. Goode, Laser-induced breakdown spectroscopy for the detection of gunshot residues on the hands of a shooter, Appl. Opt. 42 (2003) 6153–6158. [56] M. Taschuk, Y. Tsui, R. Fedosejevs, Detection and mapping of latent fingerprints by laser-induced breakdown spectroscopy, Appl. Spectrosc. 60 (2006) 1322–1327.