Anal. Chem. 2001, 73, 2959-2967
Standardless Semiquantitative Analysis of Metals Using Single-Shot Laser Ablation Inductively Coupled Plasma Time-of-Flight Mass Spectrometry Andrew M. Leach and Gary M. Hieftje*
Department of Chemistry, Indiana University, Bloomington, Indiana 47405
A method has been developed that allows the accurate, standardless measurement of the elemental composition of metal samples from single laser ablation (LA) pulses. This technique provides a fast, low-sample-consumption means for the characterization of samples having a range of matrixes. The method directly compares adjusted elemental signals with the total mass spectrometric signal to produce relative percent composition information. Three mathematical techniques were used to determine the accuracy and precision of single-shot LA measurement. Comparison of the techniques showed that a linear regression calculation, which plots individual elemental signals as a function of the summed signal for all elements in the sample on a point-by-point basis during a laser ablation transient proved superior. The simultaneous extraction capability of time-of-flight mass spectrometry permits the sampling of all analytes from any temporal position within the transient laser ablation pulse, thereby reducing quantitation error. A typical concentration dynamic range of 3 orders of magnitude, from 0.1 to 100%, was achieved. However, by measuring low-abundance isotopes for matrix elements, the dynamic range of the technique was extended to 4 orders of magnitude. The new technique is largely immune to sample matrix effects commonly experienced in laser ablation. By performing a complete elemental analysis from a single ablation pulse, high spatial resolution should be achieved. Laser ablation (LA) is a powerful technique for the direct elemental analysis of solid samples with high spatial resolution.1,2 When combined with an appropriate detector such as an inductively coupled plasma mass spectrometer (ICPMS), LA has been able to produce sensitive elemental determinations, and with minimal sample preparation. However, several fundamental aspects of the laser ablation process have limited the technique’s application to quantitative analysis. The mass of analyte ablated per laser pulse has been shown to be strongly dependent upon the matrix composition of the sample. Additionally, shot-to-shot variations in laser power and the interaction between the laser and the sample surface can result in large fluctuations in analyte signal.3 (1) Durrant, S. F. J. Anal. At. Spectrom. 1999, 14, 1385-1403. (2) Russo, R. E.; Mao, X.; Borisov, O. V. Trends Anal. Chem. 1998, 17, 461469. 10.1021/ac001272n CCC: $20.00 Published on Web 06/02/2001
© 2001 American Chemical Society
External and internal standards are often used to partially correct for these variations. However, the production of matrixmatched external standards is costly and the selection of a universal internal standard nearly impossible. Alternatively, external measurement of the ablation event and of the mass ablated can be used to reduce matrix-related problems. For example, the acoustic signature of the ablation-generated plasma has been used to correct for variations in the mass ablated from metal samples.4-6 Additionally, light scattered by the ablated analyte plume has been used to reduce matrix effects experienced in the analysis of a wide variety of samples.7-9 All of these methods for reducing matrix effects in LA add complexity, cost, and time to what should be a simple technique. The most common method for improving LA precision is to use high repetition rate lasers (typically 10 or 20 Hz) and largevolume ablation cells.3 The rapid generation of multiple LA analyte plumes within the ablation cell produces an averaged signal that significantly reduces measurement fluctuations. Regrettably, this approach greatly compromises the inherent spatial resolution of LA, since it precludes the use of single pulses. Since early experimentation with laser microprobe analysis, a number of methods have been developed to provide semiquantitative information for solid samples. Morton et al.10 demonstrated a technique that correlated vaporized sample mass with analyte signals in laser microprobe analysis. This method determined the vaporized sample mass through the measurement of laser crater dimensions following the elemental analysis. Although the method provided good accuracy for elemental concentrations, off-line measurement of ablation craters significantly complicated the experiment. Webb and Webb11 described a powerful method that mathematically adjusted atomic emission signals with experimentally determined weighting factors to produce relative elemental (3) Russo, R. E. Appl. Spectrosc. 1995, 49, 14A-28A. (4) Chen, G.; Yeung, E. S. Anal. Chem. 1988, 60, 2258-2263. (5) Pang, H.-m.; Wiederin, D. R.; Houk, R. S.; Yeung, E. S. Anal. Chem. 1991, 63, 390-394. (6) Chaleard, C.; Mauchien, P.; Uebbing, N. A. J.; Lacour, J. L.; Geertsen, C. J. Anal. At. Spectrom. 1997, 12, 183-188. (7) Richner, P.; Borer, M. W.; Brushwyler, K. R.; Hieftje, G. M. Appl. Spectrosc. 1990, 44, 1290-1296. (8) Baker, S. A.; Smith, B. W.; Winefordner, J. D. Appl. Spectrosc. 1998, 52, 154-160. (9) Watling, R. J. J. Anal. At. Spectrom. 1998, 13, 927-934. (10) Morton, K. L.; Nohe, J. D.; Madsen, B. S. Appl. Spectrosc. 1973, 27, 109117. (11) Webb, M. S. W.; Webb, R. J. Anal. Chim. Acta 1971, 55, 67-75.
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concentrations. This technique provided accurate elemental composition of samples with dissimilar matrix compositions. Semiquantitative analysis with mass spectrometry has been addressed by several research groups.12-16 By performing a ratioed measurement of individual analyte signal to the total ion signal, Svec and co-workers12 demonstrated that laser mass spectrometry could produce carbon, oxygen, and nitrogen concentrations without the use of standards. Cromwell and Arrowsmith13 described experiments that measured relative sensitivity factors for analytes as a function of ICP conditions and laser powers. Under certain operating conditions, accurate measurement of elemental concentrations from metal and glass standards was possible. In the present study, a technique has been developed that allows the accurate measurement of elemental concentrations from a single laser ablation pulse and for samples having a range of matrix compositions. This method requires the simultaneous measurement of all elements from the transient signal and assumes that the sum of those elements should equal the mass ablated. Time-of-flight mass spectrometry (TOFMS), which extracts a packet of ions containing all mass-to-charge ratios (m/z) for mass analysis, allows this reconstruction to take place. After mathematical adjustment of the measured analyte signals to account for instrument biases, the ratio of the individual elemental signals to the summed signal from all detected elements produces percent composition values directly. The high spectral generation rate of TOFMS, typically 20 000 complete mass spectra per second (1-238 m/z), makes possible the use of this semiquantitative method for the analysis of fast transient signals.17,18 The semiquantitative technique proposed in this paper has been used to provide accurate composition information for elements present at concentrations ranging from 0.02 to 100% by mass from a wide variety of metal samples. The relative nature of these measurements has proved to make the technique largely immune to matrix-related signal variations. This method was used in conjunction with single laser ablation pulses to minimize sample consumption (∼9 ng from most samples) and to maximize spatial resolution. EXPERIMENTAL SECTION Metal Standards. Materials were obtained from Alcoa Spectrochemical Standards (ALCOA, Alcoa Center, PA), Analytical Reference Materials International, Inc. (ARMI, Evergreen, CO), the Brammer Standard Co., Inc. (BNRM, Houston, TX), National Institute of Standards and Technology (NIST, Gaithersburg, MD) and Research Institute CKD PRAHA (CKD, Praha, Czechoslovakia). The semiquantitative method was trained with 15 standards chosen to encompass a wide range of sample matrixes including aluminum (ALCOA SS 2025), cobalt (BNRM 171, BNRM 172), copper (BNRM 715W, CKD 304A, ARMI 89A), copper/zinc (ARMI 83A, ARMI 88A, NIST 1107), iron (BNRM 81F, BNRM 85C, (12) Shankai, Z.; Conzemius, R. J.; Svec, H. J. Anal. Chem. 1984, 56, 382-385. (13) Cromwell, E. F.; Arrowsmith, P. Anal. Chem. 1995, 67, 131-8. (14) Denoyer, E. R. J. Anal. At. Spectrom. 1992, 7, 1187-1193. (15) van de Weijer, P.; Baeten, W. L. M.; Bekkers, M. H. J.; Vullings, P. J. M. G. J. Anal. At. Spectrom. 1992, 7, 599-603. (16) Pearce, N. J. G.; Perkins, W. T.; Fuge, R. J. Anal. At. Spectrom. 1992, 7, 595-598. (17) Guilhaus, M. Spectrochim. Acta, Part B 2000, 55, 1511-1525. (18) Myers, D. P.; Ray, S. J.; Hieftje, G. M. In Inorganic Mass Spectrometry; Barshick, C. M., Duckworth, D. C., Smith, D. H., Eds.; Marcel Dekker: New York, 2000; Vol. 23, pp 447-505.
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BNRM 87E, BNRM 89E, BNRM 91E), and nickel (BNRM H-3A). A stainless steel sample (BNRM 84E) that was not part of the training set was used to validate the technique. All samples were ablated with ∼60 single laser pulses prior to the collection of data to ensure the removal of surface contamination and oxidation. Laser Ablation System. An LSX-200 laser ablation system (CETAC, Omaha, NE) was employed in all experiments. This system employs a frequency-quadrupled Nd:YAG laser (266 nm), which generates pulses that are less than 6 ns in duration and up to 5 mJ in energy. Ablation spot size is controlled by an adjustable ceramic aperture positioned between the laser and the focusing optics. Spot size can be varied from 10 to 260 µm in diameter. The ability to alter the beam spot size without adjustment of the laser focus, combined with a flat laser beam intensity profile, makes the power density at the sample surface largely independent of spot size. Power density as a function of ablation spot size was confirmed by replacement of the ablation cell with a power meter (models 361 and 380101, Scientech, Boulder, CO). A power density of 0.60 ( 0.02 GW/cm2 was measured for spot diameters ranging from 50 to 260 µm. The ablation system has been modified to reduce transient sample pulse widths. In particular, the LSX-200 system was fitted with a low internal volume ablation cell (0.70 cm3), which was connected to the ICP by 1 m of 0.16-cm-diameter Tygon tubing. Additionally, valves ordinarily used to bypass the ablation cell during sample changes were eliminated. Helium (0.8 L/min) was used to sweep analyte particles from the ablation cell. Supplementary argon (0.8 L/min) was added to the helium flow after the ablation cell by means of a plastic T connection. Inductively Coupled Plasma Time-of-Flight Mass Spectrometer. A Renaissance ICP-TOFMS instrument (LECO, St. Joseph, MI) was used for elemental detection. The ICP was operated at 40.68 MHz with a forward rf power of 1.6 kW. A plasma sampling depth of 14 mm above the load coil was used. Sampling and skimming aperture diameters of 0.5 mm were employed. The TOFMS system was operated at a spectral generation rate of 20 kHz. The tremendous volume of data the TOFMS system produces is compressed by combining multiple individual complete mass spectra into a single integrated spectrum. In these experiments, the shortest integration time, 12.75 ms (255 integrated mass spectra), provided high temporal fidelity for the transient analyte signals. The ICP-TOFMS is equipped with a wire comb electrode similar to one described by Enke and co-workers,19 positioned within the flight tube for the selective removal of unwanted ions from the ion beam. To this electrode a transverse rejection ion pulse (TRIP) was applied to deflect ICP matrix ions, including 16O+ and 40Ar+. Data were exported from the Renaissance system and analyzed with simple spreadsheet software. Ablation Crater Measurements. A JSM-5800LV scanning electron microscope (JEOL, Ltd., Akishima, Japan) was used to image the laser ablation craters. An electron acceleration potential of 15 kV was used in all experiments, with the working distance ranging from 14 to 17 mm. Crater depths were imaged by positioning the sample surfaces at a 10° angle relative to the electron beam. Replicate measurements were made for a series of craters with varied depths corresponding to an increased (19) Vlasak, P. R.; Beussman, D. J.; Davenport, M. R.; Enke, C. G. Rev. Sci. Instrum. 1996, 67, 68-72.
Table 1. r Weighting Factor Used in Eq 2 element
R weighting factor
element
R weighting factor
Al Ti V Cr Mn Fe Co Ni
11 6.27 4.8 5.2 4.8 4.2 5.2 4.25
Cu Zn Nb Mo Sn W Pb
6.7 15 2 1.6 1.4 1.25 1.3
number of coincident ablation events. A calibration curve was used to determine the ablation depth per laser pulse. RESULTS AND DISCUSSION Data Manipulation and Weighting Factors. Each analyte of interest (15 in this experiment) was measured at a unique m/z, usually corresponding to the most abundant isotope. The simultaneous extraction of ions for mass analysis by time-of-flight systems reduces multiplicative noise produced by ICP fluctuations and detection electronics drift.20 Equation 1 minimizes electronic
Figure 1. Temporal profile produced from a single laser ablation pulse of BNRM H-3A. Eleven elements present at concentrations greater than 0.08% by mass are displayed.
weighting factor that accounts for several experimental characteristics including instrumental mass bias and ICP ionization efficiency and ψ and φ are the isotopic abundances of the analyte of interest and any isobaric interferences for the m/z at which the measurement was made, respectively. In situations where no isobaric interference exists, φ becomes zero and the interference (second) term is disregarded. A unique R term was determined for each element (Table 1) by ablating 15 standards having a wide range of sample matrix compositions. Since not every element was present at a certified value in each standard, the R terms were calculated in some instances with as few as four standards. The R terms were varied in an iterative fashion to produce the most accurate elemental compositions for all of the samples in the training set. With a few notable exceptions, the R term was found to decline with increased mass. This mass bias is mainly a result of the combined effects of the TOFMS sampling bias and Coulombic repulsion. The
sampling bias is a consequence of the ICP offset potential (typically 1-5 eV), which supplies all ions with an equal energy and thus mass-dependent velocities within the ion optic system. This massdependent velocity results in a mass-dependent density of ions within the TOFMS extraction region, where light ions are present at lower density and thus diminished concentration. Coulombic repulsion resulting from the high density of positive ions within the TOFMS ion optics produces an additional bias against light masses. Since argon (m/z ) 40) is the most abundant species in the ion optic train, ions lighter than argon will be most severely affected. In addition to mass bias, the R terms provide a correction for differences in elemental atomization and ionization efficiency. As predicted by the Saha equation, most of the elements determined in this study should exhibit ionization efficiencies greater than 95%, assuming an ionization temperature of 7500 K and an electron number density of 1 × 1015 cm-3.21 Elements that should experience a lower degree of ionization include cobalt (93%), copper (90%), zinc (75%), and tungsten (94%). Additionally, the high ICP central channel gas flow used in this study required the use of a relatively large ICP sampling depth (14 mm above the load coil), elevating the probability of entrainment of ambient gas species including N2 and O2. Production and ionization of polyatomics such as NO (first ionization potential of 9.27 eV) within the plasma could further restrict the ionization of elements with high first-ionization potentials; an example is zinc (9.39 eV). Reduced ionization efficiency is compensated by an elevated R term. Data Analysis. Figure 1 shows a transient of the weighted elemental signals from a nickel-based alloy (BNRM H-3A) interrogated with a single laser pulse. On the basis of electron microscope images, a 100-µm-diameter crater with a sampling depth of ∼170 nm per laser pulse resulted in roughly 9 ng of sample being ablated in this single-shot experiment. Three methods were compared for the determination of elemental composition from single-shot transients. All three of the methods
(20) Leach, A. M.; Heisterkamp, M.; Adams, F. C.; Hieftje, G. M. J. Anal. At. Spectrom. 2000, 15, 151-155.
(21) Jarvis, K. E.; Gray, A. L.; Houk, R. S. Handbook of Inductively Coupled Plasma Mass Spectrometry; Blackie & Son Ltd.: Glasgow, 1992.
Sc,Analyte 1 )
(
) (
)
Sa,Analyte 1 Sa,Analyte 1 Sb Sb
(1)
Blank
multiplicative noise by using the ratio of the raw signal (Sa) of each analyte to the background signal (Sb) measured at a m/z for which no mass spectral peak is expected. A signal blank was calculated by averaging for 0.5 s (∼40 integration periods) prior to each laser pulse sequence. The electronic-noise-corrected analyte signal (Sc) was then modified to produce the true signal for each analyte (Sd) by accounting for instrumental mass bias, ICP ionization efficiency, isotopic abundance, and isobaric interferences by using eq 2. In eq 2, R is a
Sd,Analyte 1 ) R
1 1 S - R φSc,Interference ψ c,Analyte 1 ψ
(2)
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Figure 2. The transient signal from Figure 1 plotted as the analyte signal (Sd) for each element as a function of the summed signal produced by all ablated elements (∑Sd). In this format, the slope for each analyte determined from a linear regression directly gives that element’s fractional composition in the sample. See eq 2 for definition of Sd.
produced relative percent composition values by measuring the ratio of individual elemental signals (Sd) with the summed signal from all elements present in the sample (∑Sd). The first method, hereafter known as “peak area”, used the ratio of the integrated peak areas of individual elements to the summed signal. The second technique, called “discrete average”, produced elemental composition values by performing the ratioing process for each discrete integration window within the LA transient. The elemental composition for the transient was determined from the average of discrete measurements. As seen in Figure 1, 13-20 individual data points were used for each element, depending upon concentration and signal-to-noise ratio (S/N). Data points for individual elements that were below the detection limit (S/N ) 3) were disregarded. Similar to the second method, the third employed the discrete measurements within the transient signal to determine percent compositions. However, the third method plotted the individual analyte signals as a function of the total signal recorded for all of the analytes in the sample at the same point in time (Figure 2). Linear regression analysis was then used to determine the percent composition of each element, directly measured as the slope of lines produced by the elements. Because of the mathematical process used to determine elemental compositions, the third quantitation technique is called “linear regression”. The relative nature of the quantitation techniques used in this study dictates that all ratioed elemental signals correspond to the same temporal position within the laser ablation transient. If elemental signals were measured in a sequential fashion, the changing concentration profile of the transient would result in the incorrect elevation or depression of ion signals relative to m/z measured earlier or later in the same mass scan. The ratioing processes used in this study would then compound the previous measurement error to result in incorrect elemental compositions. This type of quantitation error associated with the measurement of transient signals with sequentially scanned detectors is known as spectral skew.22 Although TOFMS does not detect all m/z simultaneously, the ions that form a given TOF mass spectrum 2962 Analytical Chemistry, Vol. 73, No. 13, July 1, 2001
Figure 3. Normalized analyte signals from the single-shot ablation of the brass standard ARMI 83A. Each element was normalized to its own maximum signal to allow the comparison of relative analyte signals as a function of position within the transient. All analytes display similar temporal profiles, suggesting that particles contain roughly the same relative elemental concentrations.
are extracted from the ionization source at the same time. This simultaneous extraction of all m/z makes TOFMS immune to spectral skew and thus suitable for the present study. Significance of Transient Peak Shape. Laser ablation produces a cloud of particles ranging in size from single nanometers to tens of micrometers.23,24 Depending upon the gas flow within the ablation cell, the population of particles smaller than 1-3 µm is efficiently transported from the ablation cell to the ionization source as a continuous stream of analyte. However, as has been previously demonstrated,3 individual large particles or small groups of particles can be seen with a fast detector. In the current study, a low-volume ablation cell and minimal transfer tubing were used to condense the cloud of particles produced by a single laser pulse into a concentrated sample plug. Figure 3 shows the normalized elemental signals from a transient produced by the single-shot ablation of the brass standard ARMI 83A. The similar temporal profiles displayed by all of the elements monitored in Figure 3 suggests a uniform distribution of elements in the particle cloud that accurately reflects the composition of the sample. Although the vast majority of LA transients monitored in this study demonstrated behavior similar to the peaks seen in Figure 3, several transients included large, narrow peaks (less than or equal to one integration period in width), suggesting the arrival at the ICP of one or more large particles. Figure 4 shows the normalized elemental signals from a single-shot LA of the brass standard ARMI 88A. Although the individual particle or particles seen most clearly in the lead trace are visible in all of the elemental profiles, the nonstoichiometric lead and tin concentrations in this spike imply either spatial inhomogeneity in the sample or the ejection of one or more particles with selectively enriched elemental concentration.25 (22) Holland, J. F.; Enke, C. G.; Allison, J.; Stults, J. T.; Pickston, J. D.; Newcome, B.; Watson, J. T. Anal. Chem. 1983, 55, 997A-1012A. (23) Arrowsmith, P.; Hughes, S. K. Appl. Spectrosc. 1988, 42, 1231-1239. (24) Jeong, S. H.; Borisov, O. V.; Yoo, J. H.; Mao, X. L.; Russo, R. E. Anal. Chem. 1999, 71, 5123-5130.
Table 2. Accuracy and Precision for the Single-Shot Analysis of 15 Standards accuracy (% error)
a
precision (% RSD)
% composition
peak area
discrete average
linear regression
peak area
discrete average
linear regression
10.0-100.0 1.0-9.9 0.1-0.9
3 15 20
4 16 34
3 16 19
naa na na
1.3 5.0 11.1
0.1 0.4 1.0
na, not available.
Figure 4. Normalized analyte signals from the single-shot ablation of the brass standard ARMI 88A. Each element was normalized to its own maximum signal to allow the comparison of relative analyte signals as a function of position within the transient. The spike, equal to or less than one integration period in duration, denotes the detection of one or more particles with nonrepresentative elemental concentrations.
The detection of nonstoichiometric particles can dramatically affect the ability to perform accurate semiquantitative analysis. The accuracy of both the peak area and discrete average techniques will be degraded by the existence of such particles, but the averaging nature of these techniques will diminish the effect of the particles. In contrast, the linear regression technique can be dramatically affected by the presence of nonstoichiometric particles. The detection of a population of particles with a selectively enriched concentration profile following the main analyte transient would result in significant quantitation errors, including the possible calculation of a negative slope or concentration. Although the calculation of a negative concentration signals the existence of nonrepresentative particles, the user must visually inspect each transient trace to confirm the absence of such particles. Percent Composition Accuracy and Precision. Table 2 summarizes the quantitative information generated from the single-shot LA analysis of 15 standards. Measurement accuracy was found to be highly dependent on concentration. The accuracy of the three quantitation techniques was found to be similar for elements present at concentrations between 10 and 100% composition by mass, ranging from 3 to 4% error. Likewise, the accuracy of the three techniques was found to be ∼16% error for elements (25) Outridge, P. M.; Doherty, W.; Gregoire, D. C. Spectrochim. Acta, Part B 1996, 51, 1451-1462.
Figure 5. Accuracy of the linear regression technique as a function of percent composition. Similar distributions were seen for the peak area and discrete average methods.
present between 9.9 and 1.0% composition. At lower concentrations, ranging from 0.9 to 0.1% composition, the accuracy of the three quantitation techniques was found to differ significantly. Although the peak area and linear regression methods provide an average accuracy of ∼20% error, the discrete average technique resulted in a 34% error. The degraded accuracy of the discreteaverage technique is due to the method’s inherent susceptibility to low S/N data at the beginning and end of each transient signal. The peak area and linear regression methods are affected to a much lesser extent by the low S/N data points at the temporal extremes of the transient signal. In a peak area measurement, the low S/N data points are integrated with the more significant high S/N points and their effect is greatly diminished. Similarly, the low S/N data serve to anchor the point of origin in the linear regression technique while the high S/N points dictate the overall slope of the line. Figure 5 demonstrates the measurement accuracy of the linear regression technique as a function of percent composition. Both the peak area and discrete average methods produced similar error distributions. With the exception of two data points, Figure 5 shows a gradual degradation of measurement accuracy with lower percent composition. In the 1.0-9.9% composition range, zinc from the copper standard CKD 304 resulted in a 112% error. Although zinc has historically been difficult to determine with laser ablation because of elemental fractionation, no other zinc measurement in this study (five samples) resulted in abnormally poor accuracy, suggesting that the R term from eq 2 was chosen correctly. With a laser power density of 0.6 GW/cm2, elemental Analytical Chemistry, Vol. 73, No. 13, July 1, 2001
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fractionation could be the cause of the elevated error associated with this sample.26 However, the good accuracy achieved for other zinc-containing samples, combined with the lack of significant change in calculated zinc composition from the repetitive ablation of the same location, suggests that fractionation is not the dominant source of error. Another possible explanation for the poor accuracy associated with the CKD 304 standard could be sample inhomogeneity. In the 0.1-0.9% composition region, nickel from the steel standard BNRM 91E was calculated at a concentration of 0.41% by mass (certified at 0.18%), resulting in an error of 145%. The incomplete correction of the isobaric overlap between a minor isotope of iron and the most significant isotope of nickel at m/z ) 58 caused the elevated nickel concentration measured in this sample. In a sample composed mainly of iron (certified at 82.01%) with a low concentration of nickel, a small error in subtraction of an isobaric interference would result in a large contribution to the calculated nickel concentration. Calculation of nickel percent composition in BNRM 91E with 60Ni resulted in an error of 9.2%. In the absence of the outlying two data points in Figure 5, the average accuracy for the linear regression method in the 1.09.9% composition range was 10%, while in the 0.1-0.9% composition region, an average error of 15% was calculated. Single-shot laser ablation is highly sensitive to variations in sample composition due to the limited mass that is analyzed. Inhomogeneous samples will result in large fluctuations in measured concentration. Because the peak area method provides only one value per laser pulse, no statistical information is available to calculate the confidence of the determined percent composition. However, both the discrete average and linear regression techniques use several independent measurements of analyte concentration to determine elemental composition, allowing the precision of a single LA transient to be calculated. With the discrete average method, precision is dependent upon the number of independent ratios used to determine the average and is calculated as the precision of the mean. The precision of the linear regression technique is determined from the variance of the individual analyte slopes. For all concentration ranges explored in this study, the linear regression technique provided measurement precision at least 1 order of magnitude superior to the discrete average method (Table 2). As mentioned previously, the discrete average technique is highly susceptible to the low S/N data points found at the beginning and end of a transient signal. A comparison of the overall quantitative capabilities of the mathematical techniques used in this study shows that the linear regression method is superior to calculations performed with peak areas or the average of several discrete points. Although the peak area method provided accuracy similar to that of the linear regression technique for all concentration ranges, it provided no statistical information for an individual transient signal. The discrete average method produced slightly poorer accuracy, and although it generates statistics for single laser pulses, its precision was inferior to that of the linear regression method. The significant shortcoming of the linear regression method is its susceptibility to nonrepresentative particles. Figure 6 shows the certified and experimentally measured elemental composition of BNRM H-3A for the transient shown in (26) Mao, X. L.; Ciocan, A. C.; Russo, R. E. Appl. Spectrosc. 1998, 7, 913-918.
2964 Analytical Chemistry, Vol. 73, No. 13, July 1, 2001
Figure 6. Certified and experimental concentrations for 11 elements detected from a single laser ablation pulse from sample BNRM H-3A. All elements at concentrations greater than 0.5% by mass were measured with an accuracy better than 5%. All experimental concentrations were determined to within 16% error.
Figures 1 and 2 as determined by the linear regression technique. Eleven elements with concentrations greater than 0.08% were detected. Measurement accuracy was found to be highly dependent on concentration. With the exception of tungsten, the percent composition of all elements present at concentrations higher than 0.12% by mass was calculated with less than 5% error. The percent composition of all of the detected elements was accurate to better than 16%. The empirical method used to calculate the R term simultaneously minimized the accuracy errors for each element in every matrix. As a result, the accuracy error for a given element was found to fluctuate slightly from sample to sample, particularly at low concentrations. The elevated error measured for tungsten during the analysis of BNRM H-3A was not a sign of the miscalculation of the tungsten R term, but rather a random fluctuation. Figure 6 demonstrates the potential of this method for the unique identification of a sample from its elemental fingerprint. After the R term in eq 2 had been calculated for each element, an additional stainless steel sample (BNRM 84E) was analyzed to validate the semiquantitative method. Seven elements with concentrations ranging from 0.18 to 67.61% were measured from a single laser ablation pulse. With the exception of cobalt, all elements were measured with accuracies of less than 13% error. Present at a concentration of 0.18%, cobalt was calculated with an accuracy of 28%. Sample Matrix Effects. Quantitative analysis by LA has historically been hindered by the influence of sample matrix on analyte signals. The quantitation techniques described in this paper inherently require the simultaneous measurement of all elements in the sample. The resulting relative measurement of elemental concentration has proven to be largely independent of sample matrix composition. Figure 7 shows that elemental concentrations can be determined accurately from aluminum-, brass-, cobalt-, copper-, iron-, and nickel-based samples with the same calibration procedure and equation (see eq 2 and Table 1). A slope near unity of this correlation plot demonstrates the agreement between certified and experimental elemental concentrations ranging from 0.1 to 94% by mass. Additional proof of the ability of this technique to reduce matrix effects is the calculated
Figure 7. Multielemental correlation plot of certified and experimental percent composition for analytes measured from 15 standards. The same calibration equation was used for all matrixes, which include aluminum (O), brass (0), cobalt (4), copper (b), iron (9), and nickel (2).
R2 value of 0.999. Once this method has been trained with a range of matrixes, no additional matrix-matched standards are required to perform semiquantitative analysis. Elimination of the need for additional standards simplifies measurement, while simultaneously reducing cost and analysis time. Effect of Mass Ablated on Percent Composition Accuracy. Ideally, the relative concentration of elements ablated from a sample will remain constant, independent of the mass ablated. However, a number of factors can lead to the selective enhancement or loss of specific elemental signals observed at the detector. These factors can be divided into two categories, those that cause a shift in relative elemental composition ablated from the sample surface and those that arise from detector-related shortcomings. Elemental fractionation is the main cause of nonrepresentative analyte sampling with laser ablation. In the nanosecond laser pulse regime, the fractionation process is thought to be largely dependent upon thermal vaporization pathways, in which more volatile elements are enriched in the ablated aerosol while simultaneously the same elements are depleted in the remaining sample.27 Fractionation has been shown to be strongly dependent on several instrumental properties, including laser pulse width, irradiance, and wavelength.26-30 Laser power densities above 0.3-0.6 GW/ cm2 have been shown to significantly reduce elemental fractionation.26,28 Additionally, a comparison of infrared, visible, and ultraviolet laser light has shown that fractionation is dramatically less when shorter wavelengths are employed.26,29,30 Finally, the aspect ratio (depth/width) of ablation craters has been suggested as a cause of selective enrichment.28,31 In the current study, instrumental characteristics including laser wavelength and power density were chosen to minimize the (27) Cromwell, E. F.; Arrowsmith, P. Appl. Spectrosc. 1995, 49, 1652-60. (28) Liu, H.; Borisov, O. V.; Mao, X.; Shuttleworth, S.; Russo, R. E. Appl. Spectrosc. 2000, 10, 1435-1442. (29) Figg, D.; Kahr, M. S. Appl. Spectrosc. 1997, 51, 1185-1192. (30) Jeffries, T. E.; Pearce, N. J. G.; Perkins, W. T.; Raith, A. Anal. Commun. 1996, 33, 35-39. (31) Mank, A. J. G.; Mason, P. R. D. J. Anal. At. Spectrom. 1999, 14, 11431153.
effects of fractionation. As was indicated previously, laser power density was found to be constant at 0.6 GW/cm2 for spot diameters ranging from 50 to 260 µm in diameter. Additionally, the relatively shallow ablation craters should not result in significant fractionation caused by crater aspect ratio. Elemental fractionation is often gauged on a relative scale, with a value of one signifying a lack of fractionation.32 Copper has a relatively high fractionation value (1.75), while cobalt has a low value (1.2). Ablation of the steel standard BNRM 81F over a range of spot diameters from 100 to 260 µm produced a ratio of copper-to-cobalt signals that remained constant to within 2.0% RSD, suggesting that spot diameter-related fractionation was not significant. However, since elemental fractionation is a dynamic process, the quantitation techniques discussed in this study cannot compensate for fractionation when it does occur. Assuming that the particles transported to the ICP are representative of the sample under investigation (i.e., that fractionation has not occurred during ablation), several detectorrelated issues could result in incorrect relative elemental signals. Introduction of a high mass load into the ICP can result in a diminished local temperature in the ICP and affect analyte atomization and ionization.33 Reduced plasma ionization capability would most seriously affect elements with high first-ionization potentials. Ciocan and co-workers34 have demonstrated that, with low gas flow rates (0.2 L/min), ICP conditions were not influenced by changes in the ablated mass. At high gas flow rates (2.0 L/min), closer to those used in the present study, Leach and Hieftje35 showed that the signals produced by several plasma matrix ions including Ar+, Ar2+, and N+ were found to decline in proportion to increased sample mass introduced into the ICP. This reduction in plasma matrix ion signals suggests a lowering of the ionization capabilities of the ICP under high mass loads. However, although plasma species with high ionization potentials were affected by ablated mass, no significant deviations were noted for analyte elements. Following atomization and ionization within the ICP, ions are transported to the TOF extraction region through a three-stage differentially pumped vacuum interface. Although the ion beam remains largely neutral through the first vacuum stage, charge separation within the second stage results in an ion beam with a net positive charge.36 Coulombic repulsion, which causes the dense ion beam to radially expand, can be significant at high ion currents such as those produced by large analyte concentrations. Light ions will expand at an elevated rate compared to heavy ions due to their lower momentum.37,38 Passage of the ion beam through subsequent vacuum apertures and ion optics will result in more significant losses of light ions than heavy ions causing measurement errors. (32) Fryer, B. J.; Jackson, S. E.; Longerich, H. P. Can. Mineral. 1995, 33, 303312. (33) Huang, M.; Hanselman, D. S.; Yang, P.; Hieftje, G. M. Spectrochim. Acta, Part B 1992, 47, 765-85. (34) Ciocan, A. C.; Mao, X. L.; Borisov, O. V.; Russo, R. E. Spectrochim. Acta, Part B 1998, 53, 463-470. (35) Leach, A. M.; Hieftje, G. M. J. Anal. At. Spectrom. 2000, 15, 1121-1124. (36) Niu, H.; Houk, R. S. Spectrochim. Acta, Part B 1996, 51, 779-815. (37) Gillson, G. R.; Douglas, D. J.; Fulford, J. E.; Halligan, K. W.; Tanner, S. D. Anal. Chem. 1988, 60, 1472-1474. (38) Tanner, S. D. In Plasma Source Mass Spectrometry; Holland, G., Tanner, S. D., Eds.; Royal Society of Chemistry: Cambridge, 1997; Vol. 202, pp 1327.
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In the current study, use of the largest ablation spot size (260 µm) resulted in the removal of ∼50 ng of material from a steel sample. Complete ionization of this particle cloud (0.25 s wide) will result in production of as many as 5 × 1013 iron ions. In a matrix effect study conducted with a similar ICP-TOFMS system but with continuous solution nebulization, equivalent matrix concentrations (2 × 10-3 M, for a 0.25-s peak width, 1 mL/min solution uptake rate, and 1% nebulization efficiency) resulted in between 2 and 10% suppression of analyte signals.39 Although the high matrix concentration resulted in some loss of sensitivity, the suppression did not exhibit a significant mass dependence except when a uranium matrix was used. This low mass dependence suggests that, in the current study, the signal levels from all elements would produce the correct quantitative information. Detector saturation by sample matrix elements could dramatically affect the accuracy of calculated compositions. Near saturation, the nonlinear response of the detector to increasing analyte concentration will result in the calculation of an incorrectly low percent composition for the matrix element while simultaneously elevating the calculated concentration of other elements. To avoid the possibility of detector saturation, all m/z used to calculate percent composition here were limited to less than 300 mV per integration period. To accurately determine relative composition values, all analytes ranging from major to trace in concentration must be quantified from the same temporal window. Although the generation of fast transient signals enhances analyte S/N through the compression of broad sample plugs into narrow peaks,40 the temporal width of the LA signals restricts the choice of possible detection systems. The TOFMS used here is equipped with a simultaneous analog and ion-counting detection system that provides a concentration dynamic range of greater than 6 orders of magnitude.20 However, the limited analysis time associated with fast transient signals restricts the use of ion counting, which is limited to approximately one count per m/z per mass spectrum. For very fast transients, the precision of ion-counting measurements quickly becomes dominated by counting statistics.41 The use of analog detection by itself provides a dynamic range of ∼4 orders of magnitude. The combination of sensitivity and limited dynamic range can greatly affect the ability to perform accurate relative composition measurements. Figure 8 shows the effect of decreased ablated mass on the accuracy of relative concentration determinations for several major elements from the steel sample BNRM 81F. Although the relative elemental composition of a sample plug will remain constant as ablated mass goes down, the detection of lowconcentration elements will be impaired by reduced S/N. As more analytes fail to be detected, the computed percent composition of the remaining elements will be altered. For very small ablated masses, even major elements will fall below the detection limit and cause a rapid change of computed percent composition. In the extreme case where only a single element is detected, that element will appear to comprise 100% of the sample mass. For the experiment shown in Figure 8, detector gain was reduced to avoid saturation at the highest ablated masses. The (39) Ray, S. J.; Hieftje, G. M. J. Anal. At. Spectrom., in press. (40) Leach, A. M.; Hieftje, G. M., submitted to Appl. Spectrosc. (41) Kennedy, J. B.; Neville, A. M. Basic Statistical Methods for Engineers and Scientists, 3rd ed.; Harper & Row Publishers: New York, 1986.
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Figure 8. Theoretical (lines) and experimental (points) relative percent composition of iron (b), chromium (9), nickel (O), and manganese (0) from the steel standard BNRM 81F as a function of mass ablated. As ablated mass goes down, elements at low concentration approach their detection limits, resulting in altered calculated relative compositions of remaining elements. Error bars represent three times the standard deviation of the average measured concentrations for 10 discrete ablation events.
calculated percent composition as a function of ablated mass was found to be strongly dependent upon element concentration. Over the range of ablated masses from 50 to 2 ng, iron concentration, certified at 69.56% by mass, was experimentally measured to increase by 1.8%, corresponding to a relative percent composition change of 1.2% by mass. Over the same mass range, manganese, certified at 1.53% by mass, experienced a 10% drop from its initial value, resulting in a 0.2% change in calculated percent composition. Additionally, several less abundant elements failed to be detected at the lower ablated masses. The experimentally measured percent composition shifts were in good agreement with those predicted by theory and were significant at the 95% confidence interval. To avoid sensitivity-related accuracy problems, the ablated mass should be chosen such that all measurements exploit the full dynamic range of the detection system. Dynamic Range. As mentioned previously, percent composition was measured mainly for elements present at concentrations ranging from 0.1 to 100% by mass. The lower concentration limit was dictated not by lack of instrumental sensitivity but rather by the dynamic range of the detection system. This limitation arises from the need to measure major and trace elements simultaneously. Sufficient signal is needed for low-concentration elements while avoiding detector saturation caused by elements of high concentration. The dynamic range of these techniques can be increased to at least 4 orders of magnitude for samples in which the major elements have multiple isotopes. By measuring a less abundant isotope of the matrix element, a greater amount of sample (i.e., a larger laser ablation spot size) can be employed to improve the signal-to-noise levels of the lower concentration elements. Table 3 demonstrates that, by measuring iron at 54Fe in a steel sample, elements present at concentrations as low as 0.02% can be determined. As mentioned previously, attention must be paid to detector saturation when elevated ablated masses are used.
Table 3. Increased Dynamic Range through Use of Less Abundant Isotopes BRNM 91E % composition
element
certified valuea
exptl value, 100-µm-diameter spotb
exptl value, 260-µm-diameter spotc
Co Cr Cu Fe Mn Mo Ni Si V
0.02 16.55 0.06 82.01 0.42 0.04 0.18 0.53 0.09
