Improvements in the Reliability of X-ray Photoelectron Spectroscopy

Waters Symposium: Electron Spectroscopy for Chemical Analysis edited by

Waters Symposium

John P. Baltrus National Energy Technology Laboratory U.S. Department of Energy Pittsburgh, PA 15236

Improvements in the Reliability of X-ray Photoelectron Spectroscopy for Surface Analysis Cedric J. Powell Surface and Microanalysis Science Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8370; [email protected]

X-ray photoelectron spectroscopy (XPS) or electron spectroscopy for chemical analysis (ESCA) has been used successfully to solve many scientific and technological problems, as described in the other articles of this Waters Symposium. For many applications, XPS is used for qualitative analyses, that is, for identification of the elements present and their chemical states in the region of a surface extending to depths of generally between 1 nm and 10 nm. XPS has also been used for quantitative analyses, that is, for determination of chemical stoichiometry and for measurement of thicknesses of overlayer films between 1 nm and 10 nm. An overview is given here of efforts made over the past ∼30 years to improve the reliability of surface analyses by XPS. After some brief historical remarks, consideration is given first to reliable measurements of core-electron binding energies (BEs) and chemical shifts. Interlaboratory comparisons (also known as round robins) conducted in the 1970s disclosed serious inadequacies in the calibration of the BE scales of XPS instruments. These results led to new measurements of reference energies for Cu, Ag, and Au that could be used for instrument calibration, more detailed understanding of XPS lineshapes, the development of a recommended procedure for calibration of the BE scales, and the development of recommended BEs for many elemental solids that could be used for the determination of chemical shifts. The early round robins also indicated appreciable differences in ratios of measured photoelectron intensities for Cu and Au. Subsequent work at the U.K. National Physical Laboratory has identified the sources of the variations in instrumental intensity measurements and has led to the development of a calibration service for XPS instruments. There was early interest in determinations of the surface sensitivity of XPS, but early measurements of what are now termed effective attenuation lengths showed considerable scatter; reasons for this scatter are now understood. Improved algorithms were developed for the calculation of the inelastic mean free paths for electrons in solids, and these data provided a more consistent guide to the XPS surface sensitivity. It was later realized that elastic scattering of the XPS signal electrons during transport in the specimen material should be considered. As a result, it is now possible to compute effective attenuation lengths and mean escape depths for the signal electrons in different materials and for different XPS configurations. This work also led to a clearer understanding of how the surface sensitivity in an experiment can be varied. In early XPS work, it was commonly assumed that the sample surface was homogeneous over the XPS information 1734

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depth. While this assumption might be a useful first approximation, many samples of practical interest can have different types of inhomogeneities. Modern XPS instrumentation and improved data-acquisition strategies and data-analysis algorithms can now be applied to identify a particular specimen morphology and to obtain a more reliable analysis. Finally, NIST has developed a number of data products for application in XPS. Four databases are currently available together with a set of XPS standard test data that can be used to assess uncertainties of peak parameters derived from fits to spectra with overlapping peaks. Historical Remarks Jenkin et al. (1, 2) have published a history of the development of XPS from 1900 to 1960. Although some early photoemission experiments were described in articles published between 1905 and 1914, it was the sustained work of H. R. Robinson at several British universities between 1914 and 1940 that identified some basic XPS phenomena (1, 2). Two major developments in the XPS history and one personal event will be briefly mentioned here as well as some comments on the growth and pervasiveness of XPS in current science and technology. Steinhardt and Serfass (3, 4) appear to be the first authors to suggest that XPS could be used for the chemical analysis of surfaces. In the early 1950s, Steinhardt et al. at Lehigh University published three articles in Analytical Chemistry that explored the feasibility of this technique for qualitative surface analysis (3–5). Their experiments were, not surprisingly, crude by current standards. They nevertheless succeeded in demonstrating characteristic spectra with broad structures for metals such as Cu, Zn, Rh, Ag, and Au and in showing that they could make a qualitative analysis of a Cu– Zn alloy and a quantitative analysis of a Ag–Au alloy (3). In addition, they were able to detect changes in the photoelectron intensity from a gold substrate following deposition of monolayers of barium stearate despite the fact that their measurements were made with their sample materials in a conventional high vacuum (4). This experiment clearly indicated that their instrument had sensitivity to the outermost atomic or molecular layers of a sample. In the late 1950s, a group led by K. Siegbahn of Uppsala University in Sweden developed an electron energy analyzer with sufficient energy resolution to detect photoelectrons that had not been inelastically scattered in the sample material. With this instrumental breakthrough, they were able to measure elemental core-electron binding energies with an accu-

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Waters Symposium: Electron Spectroscopy for Chemical Analysis

racy of 1 eV (6). Siegbahn and coworkers soon found evidence for so-called chemical shifts of the elemental binding energies. In their initial measurements, the K, L1, L2, and L3 binding energies of Cu in CuO were between 2.5 eV and 4.4 eV larger than in metallic Cu (7). Many articles on these and related topics were published by Siegbahn et al. in following years, but a key event was the publication of a book in 1967 that clearly described the capabilities of ESCA for surface analysis and its potential for solving many scientific and practical problems (8). This potential has, of course, been realized. Siegbahn was a winner of the Nobel Prize for Physics in 1981 for his development of high-resolution ESCA. It is worth noting that Siegbahn coined the acronym ESCA to include not only photoelectron spectroscopy but also Auger-electron spectroscopy (AES) since Auger-electron features are generally also observed in X-ray photoelectron spectra and are analytically useful (9). Separate instruments have been developed for electron-beam-excited AES, also for surface analysis. While it is convenient to have an acronym such as ESCA to refer generically to the use of electron spectroscopy for surface analysis, as Siegbahn intended, it is often desirable to utilize separate acronyms (XPS and AES) so that clear reference can be made to a particular process or technique. In their 1967 book, Siegbahn et al. reported the first direct measurement of the surface sensitivity of XPS (8). They deposited single and multiple monolayers of α-iodostearic acid on chromium-plated brass slides and found that the effective attenuation length (defined below) was about 10 nm for a photoelectron energy of 867 eV. This first measurement was assumed to be representative of other materials. By an unlikely coincidence, my own early research career overlapped with a scientist who had worked with H. R. Robinson, one of the early developers of XPS (1, 2). Robinson’s last graduate student, C. J. Birkett Clews, became chairman of the physics department of the University of Western Australia in 1952. As a graduate student in this department between 1956 and 1959, I investigated the inelastic scattering of 750–2000 eV electrons by surfaces and, in one experiment, utilized AES for what may have been the first time to monitor the presence of carbon contamination on a W wire (10). Clews was an aloof person, and I was unfortunately unaware at the time of his XPS experience. The association of Clews and Robinson only became known to me following the publication of the XPS history (1). Largely as a result of the Siegbahn et al. book (8), commercial XPS instruments became available in the late 1960s and were rapidly introduced into industrial and other laboratories. A 1986 article (11) shows a plot of number of published articles with data from XPS, AES, and other surface-analysis techniques versus publication year. This plot indicates that 1969 was the year when surface analysis by XPS and AES “took off ”. Since 1989, NIST has made available an XPS database containing core-electron binding energies, chemical shifts, and other data for thousands of materials (more information on this database is given below). This database was developed initially by Charles D. Wagner, one of the pioneers in the industrial application of XPS. Computer-based literature searches are made by NIST at regular intervals to locate possible XPS data for inclusion in the database using selected www.JCE.DivCHED.org

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words or phrases (such as XPS, ESCA, and X-ray photoemission) in the title, abstract, or key words of a published article. In a search of articles published in 1995 and 1996, a total of 5057 articles in 523 different journals were identified in this way. From these articles, it can be seen that XPS has extensive applications and impacts in research and technologies ranging from catalysis, corrosion, polymers, semiconductor materials, and biomaterials to adhesion, wear, ceramics, geochemistry, clays, wood chemistry, food chemistry, dental materials, brain research, and fertility research, amongst others. Reliable Measurement of Core-Electron Binding Energies and Chemical Shifts Calibrations of the binding-energy scales of XPS instruments are required for four principal reasons. First, meaningful comparison of BE measurements from two or more XPS instruments requires that the BE scales be calibrated, often with an uncertainty of about 0.1–0.2 eV. Second, identification of chemical state is based on measurements of chemical shifts of photoelectron and Auger-electron features, again with an uncertainty of about 0.1–0.2 eV; individual measurements should therefore be made and literature sources need to be available with comparable or better accuracies. Third, the availability of databases of measured BEs for reliable identification of elements and determination of chemical states by computer software requires that published data and local measurements be made with uncertainties of about 0.1–0.2 eV. Finally, the growing adoption of quality management systems, such as ISO 9000, in many analytical laboratories has led to requirements that the measuring and test equipment be calibrated and that the relevant measurement uncertainties be known. An overview is given here of efforts extending from the 1970s to the present time to improve the reliability of BE measurements and chemical-shift determinations.

1970s Round Robins It was possible with the early commercial XPS instruments to be able to measure core-electron binding energies with a precision of approximately 0.1 eV and it was tacitly assumed by users at the time that the accuracy of BE measurements was also 0.1 eV. Nevertheless, it soon became clear from the spread in published BE values for the same photoelectron line that the accuracy must be worse than 0.1 eV. In the mid-1970s, ASTM Committee D-32 on Catalysts organized a round robin to compare BE measurements for highsurface-area, powdered samples of silica, alumina, and a sodium zeolite. The reported BEs for the principal core levels showed variations of up to 3 eV and ratios of peak intensities varied by up to a factor of four among instruments from the same manufacturer (12). The D-32 round robin demonstrated the need for calibration procedures in XPS for both BE and intensity measurements. It was thought at the time that at least part of the variations found for the catalyst BEs could be due to inadequacies of the correction procedures used to minimize charging on the insulating samples. Similar measurements made with metal samples (in a planned new round robin) would not have this uncertainty. In addition, the surfaces of most


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Figure 1. Plot of the measured BE of the Au 4d5/2 peak versus the measured BE of the Au 4f7/2 peak (13). Each point is a result from a single laboratory. A given symbol represents measurements made with XPS instruments from the same manufacturer. Points with nearby arrows indicate outliers that actually occur beyond the plotted position by the amount (in eV) indicated next to each arrow.

Figure 2. Plot of the BE for the Cu 3p3/2 peak versus the BE for the Au 4f7/2 peak (13). Each point is a result from a single laboratory. A given symbol represents measurements made with XPS instruments from the same manufacturer. Points with nearby arrows indicate outliers that actually occur beyond the plotted position by the amount (in eV) indicated next to each arrow.

Figure 3. Plot of individual deviations of BE measurements, E0, from the median values, Emed, as a function of BE for the 4f7/2, 4d5/2, and 4p3/2 levels of Au and the 2p3/2 level of Cu (13). All points should lie on a vertical line, for each level, but where necessar y for clarity, points have been displaced horizontally. Lines have been drawn through points for measurements made on the same instrument to illustrate some of the trends. A given symbol represents measurements made with XPS instruments from the same manufacturer. Points with nearby arrows indicate outliers that actually occur beyond the plotted position by the amount (in eV) indicated next to each arrow.

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metallic elements could be readily cleaned by ion sputtering, with respect to the median BEs for the group. This error funcand it should then be possible to obtain BE and intensity tion would be expected to be a smooth function of BE, and measurements of comparable quality from each participant. there are examples of this behavior in Figure 3. There are ASTM formed a new Committee E-42 on Surface Analysis also other examples where the trends are more erratic. in 1976 (see below), and this Committee decided to conSeparate plots of the data in Figure 3 for the three types duct parallel XPS and AES round robins with metal speciof XPS instruments for which there were the largest number mens, primarily Cu and Au. of participants are shown in Figure 4; that is, each panel of The E-42 round robin was conducted in the late-1970s, Figure 4 shows data for instruments from the same manuwith the XPS results published in 1979 (13) and the AES facturer. There are examples in each panel of a relatively slowly results in 1982 (14). Each participant was sent sample foils varying error function and other examples where the error and detailed instructions concerning specimen cleaning, meafunction shows larger or more erratic deviations. The variety surements to be made, and results to be reported. Useful reof behavior for each panel in Figure 4 suggests that some insults were received from measurements made on 38 different struments from each manufacturer can give satisfactory reinstruments for the XPS round robin and on 28 instruments sults, presumably those calibrated regularly and operated for the AES round robin. carefully, while those that give less satisfactory results may The XPS results (13) were qualitatively similar to the not have been calibrated as frequently or operated as careearlier D-32 round robin in that the spread in reported BE fully as the others. In other words, reliable BE measurements values was typically greater than 2 eV while the spread in depend on both the capabilities of the instrument and the intensity ratios was up to a factor of ten. Figure 1 shows an capabilities and practices of the operator. example of the reported BE results in which a plot is made Reference Energies for Calibration of BE Scales of the Au 4d5/2 BE versus the 4d7/2 BE. This figure is an example of a Youden plot (15), which is a convenient and useThe ASTM E-42 XPS (13) and AES (14) round robins ful means of distinguishing systematic variations from stimulated efforts at NIST and at the U.K. National Physical random effects in measurement. It is clear from Figure 1 that there is a correlation between the Au 4d5/2 and 4f7/2 BEs; for example, a laboratory that measures low on one peak will generally measure low on the other. This correlation is exhibited by the fact that most points appear to lie close to a straight line of unit slope with a scatter that is related to the imprecision of measurement (15). There is an outlier in Figure 1 (located off the plotted position by 4.15 eV) that is due either to a measurement mistake or to a mistake in reporting the data. Results generally similar to those in Figure 1 were found in comparisons of BEs for the Au 4p3/2 and 4f7/2 peaks and of the several Cu peaks (13). The use of two sample materials in the round robin, Au and Cu, provided useful insight on the consistency of the BE measurements. For example, the Cu 3p3/2 and Au 4f7/2 peaks have similar BEs. A Youden plot in which the BE measurements for these two peaks are compared is shown in Figure 2. The correlation of the points in Figure 2 is generally similar to that in Figure 1 although there is a greater scatter. This scatter could be due to instrumental drifts with time or to variations in the alignment of the samples. Figure 3 shows a plot of deviations of individual BE values from median BEs for the 4f7/2, 4d5/2, and 4p3/2 photoelectron lines of Au and the 2p3/2 line of Cu (13). A number of lines have been drawn to connect data obtained from the same instrument to indicate some of the trends. It is clear from Figure 3 that the range of reported BE values for each photoelectron line is more than 2 eV. The root-mean-square deviations of the reported values about the median BE varied from 0.35 eV Figure 4. Plot of individual deviations of BE measurements from median valfor the Au 4f7/2 line to 0.51 eV for the Cu 2p3/2 ues, as in Figure 3, for three types of instruments originating from the same line. The connecting lines show an error function manufacturer (13). Lines have been drawn to connect data obtained for the (or calibration curve) for an individual instrument same instrument. www.JCE.DivCHED.org

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Laboratory (NPL) to make traceable measurements of selected photoelectron BEs and Auger-electron kinetic energies that could be used as reference values for instrument calibration. While some preliminary NIST results were published (16) and led to additional work to characterize the electron energy analyzer (17, 18), this activity eventually had to be curtailed because of budgetary problems. The NPL work progressed in a number of stages from the early 1980s (19, 20) through the late 1990s (21, 22). While it might seem straightforward to measure an absolute BE, there were a series of obstacles to be overcome to ensure that any recommended BEs would be robust and suitable for use in different XPS configurations and with analyzers of varying energy resolution. Issues associated with peak location such as peak asymmetry, the surface core-level shift, and avoidance of systematic error associated with a sloping background had to be addressed (23, 24). The zero point on the BE scale also had to be satisfactorily located (22, 25).

Recommended Procedure for Calibration of the BE Scales of XPS Instruments A draft procedure was prepared in the early 1990s for consideration by the ASTM E-42 Committee to calibrate the BE scales of XPS instruments. Before formal balloting of this procedure, it was tested with another round robin (24). The calibration was based on measurements at two points on the working BE scale, one at relatively low BE (the Au 4f7/2 line) and the other of relatively high BE (the Cu 2p3/2 line), and the NPL reference BEs for these lines. The initial working assumption that the BE scale was linear was then checked at other points on the BE scale with measurements of the Ag 3d5/2 photoelectron line and the Cu L3VV and Ag M4VV Auger lines (and again with the corresponding NPL reference energies). While the round robin showed that most of the procedures in the draft calibration procedure were satisfactory, improvements were found to be necessary in two areas. First, small offsets (up to about 0.05 eV) could arise if peaks were located with assumed backgrounds of nonzero slope or if multipeak fits were made to the Cu and Ag Auger peaks. Second, the Auger peaks were shifted by an average value of 0.13 eV on instruments equipped with a monochromated Al X-ray source. This systematic offset occurred because the average X-ray energy from the monochromator was slightly larger than the average energy for a non-monochromated Al X-ray source. As a result, linearity tests of the BE scale on instruments with a monochromated Al X-ray source would have to be made with a photoelectron line (such as the Ag 3d5/2 peak). It also became clear from this round robin that the BE scales had to be separately calibrated for each set of operating conditions (e.g., the analyzer pass energy, aperture sizes, and X-ray source). This XPS round robin later led to an analysis of the suitability of fitting functions commonly found on the software of modern XPS instruments for peak location (23). For the determination of the NPL reference energies (19, 22), a parabola had been fitted to the group of data points comprising the top 5% of each peak. Since fitting a peak with a parabola is not generally possible with the software on XPS instruments, comparisons were made of the accuracy and precision of peak location with the parabola method and with the commonly available Lorentzian, Gaussian, and asymmet1738


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ric Gaussian fitting functions (23). These functions were found to be satisfactory for peak location if fits were made to data comprising the top 10–20% of a line. It also became clear that it would be useful to develop an uncertainty budget for BE measurements following a calibration (23). An analysis was made of the expanded uncertainty at the 95% confidence level following a calibration with a certain number of measurements of the calibration peaks, a value of the repeatability standard deviation (for repeated BE measurements of the same calibration peak), and a value of the BE-scale nonlinearity. This analysis led to a tolerance for BE-scale drift based on a user-specified tolerance, δ, such as 0.1 eV or 0.2 eV, for subsequent BE measurements. A user should select a value for this tolerance based on the needs of the analytical work, the stability of the instrument, and the cost of calibrations. The International Organization for Standardization (ISO) formed Technical Committee 201 on Surface Chemical Analysis in 1991, and ISO兾TC 201 began operation in 1992 (as described further below). A working group of the Subcommittee on X-ray Photoelectron Spectroscopy has now developed an ISO standard for calibration of the BE scales of XPS instruments (26, 27). This ISO standard has a more detailed procedure than that contained in the draft ASTM standard prepared earlier (24). A brief description of the ISO standard has been published (28). A flowchart that summarizes the steps of the calibration procedure is shown in Figure 5; references are given to relevant sections of the standard. The analyst should initially

Figure 5. Flowchart indicating the sequence of operations for calibrating the BE scale of an X-ray photoelectron spectrometer (after ISO 15472; ref 26, 27 ). The number associated with each step indicates the section in the standard in which the operation is described.


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choose some desired value for δ and then make tests to determine whether BE measurements were made within the limits ±δ over some period of time. Information is given in the standard on how to evaluate the uncertainty of a BE measurement for a material of interest that is associated with the uncertainty of the calibration procedure. This information is provided for four common analytical situations. It is important to note that some BE measurements may have uncertainties larger than δ as a result of poor counting statistics, large peak widths, uncertainties associated with peak fits, and effects of surface charging. The ISO standard also has an optional procedure to determine the average X-ray energy on XPS instruments equipped with a monochromated Al X-ray source (based on measurements of the Cu L3VV Auger peak). This information is needed for the determination of modified Auger parameters and Auger-electron kinetic energies. An example of a control chart showing the (hypothetical) drift in the calibration at the Au 4f7/2 and Cu 2p3/2 peaks (26, 27) is shown in Figure 6. A control chart of this type is a simple and effective means of demonstrating and documenting that the BE scale of the instrument is in calibration; that is, the instrument is operating within the specified tolerance limits for a certain period of time. The solid horizontal lines indicate tolerance limits δ of ±0.2 eV in this example and the dashed horizontal lines indicate warning limits (±0.7 δ). If the drift in the calibration exceeds a warning limit, a new adjustment of the instrument or the software is necessary. The ASTM E-42 Committee has adopted a practice for calibrating the BE scale of XPS instruments that is based on the ISO standard (29, 30). The ASTM standard is consis-

Figure 6. A schematic control chart to indicate the calibration status of an XPS instrument. Values of the drifts in the BE scale for the Au 4f7/2 and Cu 2p3/2 photoelectron peaks (∆1 and ∆4, respectively) are plotted as a function of calibration date (from ISO 15472; ref 26, 27 ). The error bars indicate the calibration uncertainty determined at the 95% confidence level. The horizontal solid lines indicate the tolerance limits, ±δ, here chosen (as an example) to be ±0.2 eV. The horizontal dashed lines show warning limits, ±0.7 δ. The plotted points are illustrative values to indicate possible drifts in the values of ∆1 and ∆4. In this example, the sum of the drift and the calibration uncertainty has first exceeded the warning limit in May, and the instrument should have been recalibrated at that time.

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tent with the calibration methodology of the ISO standard although there are differences in some minor procedural details. A brief summary of the ASTM standard has been published (31).

Recommended Elemental Binding Energies for XPS The draft ASTM procedure described above (24) for the calibration of BE scales of XPS instruments was utilized to, in effect, recalibrate three XPS instruments that had each been used to make measurements of core-level BEs for many elements (32). The resulting revised BEs from these instruments (33–35) were then compared with BEs from a fourth instrument (36) that had been calibrated to the NPL reference BEs (19, 20) and that had also been used to measure BEs for many elements. Prior to recalibration of the three instruments, the reported Au 4f7/2 BE ranged from 83.80 to 84.00 eV (compared to the NPL value of 83.98 eV) and the reported Cu 2p3/2 BE ranged from 932.47 eV to 932.80 eV (compared to the NPL value of 932.67 eV). Not surprisingly, there were then systematic differences of up to 0.33 eV in reported BEs for the same element and photoelectron line among the four sources of data. After recalibration of the BE scales of the three instruments, mean BEs were computed for the elements and photoelectron lines for which there had been at least two independent measurements. Individual differences from these mean BE values were then plotted as a function of BE for measurements made on the same instrument. An example of one such plot made from data reported in one XPS Handbook (36) is shown in Figure 7. It can be seen that the dif-

Figure 7. Plot of the differences in the BE values (䊉) in the Handbook of X-ray Photoelectron Spectroscopy (36) from the corresponding mean BE values from four sets of BE data after recalibration of the BE scales of three instruments as a function of binding energy (32). Three outliers are identified. (Note: The identification of any commercial product does not imply endorsement or recommendation by the National Institute of Standards and Technology.)


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ferences in Figure 7 are very close to zero, as indicated by the horizontal dashed line, although in this particular case most of the differences are positive. This result is probably associated with the fact that there were differences in measurement conditions and peak-location algorithms for the four data sets. The data in Figure 7 also indicate that there are no systematic trends in the deviations as a function of BE that would be symptomatic of a nonlinearity of the BE scale. Finally, there are some outliers in Figure 7, particu-

larly for B 1s and Se 3d5/2, that occur for elements that are difficult to handle and clean. In two other cases (not shown here), outliers were found that suggested the likelihood of surface impurities or possible mistakes in these measurements (32). Post-measurement recalibration of the BE scales of three XPS instruments was successful in reducing the original systematic differences among the four BE-data sets by nearly an order of magnitude (32). The combined standard deviation of the derived mean elemental BEs was found to be 0.061 eV. These mean elemental BEs are therefore believed to be a useful reference set of secondary standards for checking the linearity of BE scales (26, 29) and for determining chemical shifts in XPS. Reliable Measurement of Photoelectron Intensities

Figure 8. Plot of the normalized transmission function, defined in the text, as a function of photoelectron kinetic energy for (a) a Mg X-ray source and (b) an Al X-ray source (13). This function has been normalized to unity at the kinetic energy of photoelectrons from the Cu 3p and Au 4f7/2 levels. All other points should lie on vertical lines corresponding to the kinetic energies of photoelectrons from the Cu 2p3/2, Au 4p3/2, and Au 4d5/2 levels but, where necessary for clarity, points have been displaced horizontally. Symbols have been used, as in Figures 1–4, to designate measurements made on instruments from the same manufacturer. Points with nearby arrows indicate outliers that actually occur with the ordinate values indicated in parentheses. Lines have been drawn to connect data obtained with the same instrument to illustrate some of the trends.

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The XPS round robin conducted by the ASTM E-42 Committee in the late 1970s showed spreads in intensity ratios from the cleaned Au and Cu samples of about a factor of ten (13). These comparisons were made after making firstorder corrections for the analyzer transmission functions, T(EK), as a function of photoelectron energy, EK. For one group of instruments in the round robin, T(EK) was expected to be at least approximately proportional to EK while for the other group of instruments T(EK) was expected to be approximately inversely proportional to EK. In a further analysis of the reported intensity ratios, calculations were made of a parameter called the normalized transmission function, N(EK), that was derived from the product of the intensity ratios, inverse ratios of differential photoionization cross sections and inelastic mean free paths for the specific photoelectron lines and X-ray sources of interest, and EK±, where EK± = EK᎑1 for instruments with T(EK) approximately proportional to EK and EK± = EK1 for instruments with T(EK) approximately inversely proportional to EK. In this way, a more detailed analysis of the measurements could be made after adjusting for expected variations associated with material parameters and the analyzer transmission. It was convenient to normalize the values of N(EK) to unity for the photoelectron kinetic energies corresponding to the nearly equal kinetic energies of the Cu 3p and Au 4f7/2 photoelectron peaks; separate normalizations were performed for measurements made with Mg and Al Kα X-ray sources. Plots of N(EK) = EK±1T(EK) versus EK are shown in Figure 8. This function was expected to be a slowly varying function of EK since appropriate corrections had been made for most of the known material and instrumental dependencies on EK. Some of the trends in Figure 8 are slowly varying, as expected, but others show substantial and unexpected fluctuations. Finally, there is evidence of either mistakes or gross instrumental malfunctions. Figure 9 shows plots as in Figure 8 for the three types of instruments for which there were the greatest number of participants (as in Figure 4 for the BE data). There appear to be systematic electron–optical differences in the normalized transmission functions for these instruments, although these differences are masked by erratic trends, particularly for the instruments in Figure 9(b). Seah and coworkers at NPL have investigated many possible reasons for the variations in intensity responses of XPS instruments of the type shown in Figures 8 and 9 (37–46).


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Figure 9. Plots of the normalized transmission function as a function of photoelectron kinetic energy, as in Figure 7, for three different sources of instruments (as in Figure 4) (13). Lines have been drawn to connect data obtained with the same instrument. Panels (a) and (c) contain data obtained with both Mg and Al X-ray sources; there is the possibility of a small inconsistency between the data for these two sources. See also caption to Figure 7.

They have shown that variations in detector efficiency with energy from instrument to instrument, contamination of the X-ray anode, and internal scattering in the analyzer need to be considered (41) as well as specimen alignment (43) and linearity of the counting electronics (44). Photoelectron intensities measured on a calibrated instrument are now in reasonable agreement with those predicted (46). The intensity scales of individual XPS instruments can also be calibrated with software available for purchase from NPL (42, 47).

empirical guidance on the likely surface sensitivity of their measurements. A plot of AL versus electron energy on logarithmic scales from one of the 1974 reviews (48) is shown in Figure 10. It can be seen that the ALs generally increase with energy in the range of practical interest for AES and XPS. It is also apparent that measurements for the same material (e.g., Au)

Surface Sensitivity of XPS

Early Measurements of Effective Attenuation Lengths As noted earlier, Siegbahn et al. (8) deposited a single monolayer and multilayers of a Langmuir–Blodgett film, αiodostearic acid, on chromium-plated brass slides, and found that what is now called the effective attenuation length (EAL) was about 10 nm for a photoelectron energy of 867 eV. Similar XPS and AES experiments were soon performed by other workers. The results of the early experiments were referred to as attenuation lengths (ALs) since these values were reasonably viewed as measures of the opacity of overlayer films for photoelectrons from the substrate material. It was later realized (see below) that elastic scattering of the detected photoelectrons complicates the analysis and leads to the result that the probability of electron attenuation may not depend exponentially on distance traveled in a material. Three reviews published in 1974 summarized the status of the early AL measurements (48–50). Most of these measurements were made for elemental solids, and plots of AL values on a logarithmic scale versus electron energy on a logarithmic scale seemed to cluster about what was frequently referred to in the literature of the time as the “universal curve”. While there was no theoretical foundation for the assumed universal curve, this presumed relationship was useful in the early years of practical AES and XPS in giving analysts some www.JCE.DivCHED.org

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Figure 10. Measured or derived values of electron attenuation lengths (ALs) for different materials as a function of electron energy on logarithmic scales (53). Different symbols denote data from particular articles published prior to 1974. The lines indicate AL values derived from low-energy electron diffraction experiments for Ag, W, and Al.


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have considerable scatter. Finally, we note that the AL reported by Siegbahn et al. (8) for α-iodostearic acid (10 nm) was much larger than AL values for elemental solids at the same energy (between 1 nm and 2 nm). In 1979, Seah and Dench analyzed the available AL data and proposed simple empirical formula relating the AL to the electron energy and a single material parameter (the average monolayer spacing) for elements, inorganic compounds, and organic compounds (51). Although again there was no theoretical basis for these relations (and particularly for the existence of different relations for different classes of materials), the Seah and Dench expressions provided improved and useful guidance for estimates of surface sensitivity of AES and XPS experiments and for measurements of overlayer-film thicknesses. Two major types of problems are associated with the overlayer-film method of determining ALs. First, there are numerous sources of uncertainty in the experimental measurements (52–55). These uncertainties are associated with the lack of film uniformity, effects of surface-electronic excitations, the effects of interferences between so-called intrinsic (or shake-up) excitations that occur in the photoionization process and extrinsic excitations that occur during photoelectron transport, atomic reconstructions at the surface and the substrate-overlayer interface, intermixing at the substrateoverlayer interface, roughness at the surface and at the substrate-overlayer interface, film-thickness measurement, and the effects of angular anisotropies in photoelectron transport. It is very difficult to make estimates of the magnitudes of these uncertainties, particularly in retrospect. Concerning the issue of overlayer-film uniformity, it has only been possible with the advent of scanning tunneling microscopy and atomic force microscopy instruments during the past 15 years to characterize overlayer-film morphologies in the early stages of film growth. These investigations have shown that film growth is generally more complex than was thought to be likely in the early experiments to measure ALs (54). The second major problem with the overlayer-film method is conceptual. The experimental measurements were analyzed with what is now known to be an oversimplified model. Elastic scattering of the photoelectrons was assumed to be insignificant and, as a result, the electrons were thought to move on straight-line trajectories between any inelasticscattering events. It is now well established that elastic-scattering effects cannot be neglected in these experiments and, more generally, in analyses of electron transport in AES and XPS (56–62). As a result, the signal electrons have, on the average longer trajectories than would be the case if elastic scattering were negligible. The effects of elastic scattering are particularly pronounced in XPS because the photoionization process is anisotropic (56–62). The dependence of AES and XPS signal intensities on overlayer-film thickness will, in general, not be exponential although for some common experimental conditions the dependence is at least approximately exponential. In these cases, the experimental parameter describing the attenuation is the AL (or now the EAL). The magnitude of the AL depends on the experimental configuration and is generally less than the corresponding electron inelastic mean free path; these issues will be discussed further below.

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Calculations of Inelastic Mean Free Paths The electron inelastic mean free path (IMFP) is defined as “the average of distances, measured along the trajectories, that particles with a given energy travel between inelastic collisions in a substance” (63). It was expected from general considerations (64) that most inelastic-scattering events were associated with excitations of valence electrons. Early calculations of IMFPs were based on the “jellium” model for a solid for which the inelastic scattering is entirely due to excitation of bulk plasmons. Quinn (65) Lundqvist (66) and Shelton (67) reported calculations of electron IMFPs for electron energies less than about 500 eV. A review of IMFP calculations relevant to AES and XPS has been published (55). The probability of inelastic electron scattering in a solid can be described by the energy-loss function, Im[᎑1Ⲑε(ω,q)], which can be derived from the complex dielectric constant, ε(ω,q), a function of frequency ω, and momentum transfer q. Experimental measurements of optical constants can be used to obtain ε(ω,0) and thus Im[᎑1Ⲑε(ω,0)]. The latter function is proportional to the probability of inelastic scattering for zero momentum transfer and is a useful basis for an IMFP calculation if reasonable estimates can be made for the q dependence of the energy-loss function. This approach is useful because all inelastic-scattering modes for a particular solid are included and correctly weighted. It is then unnecessary to make an artificial distinction in the calculation between those modes associated with valence-electron excitations and those associated with core-electron excitations (and to determine the relevant weightings for these excitations). Powell (68) used this approach in 1985 to estimate IMFPs of 100– 2000 eV electrons in C, Mg, Al, Al2O3, Cu, Ag, Au, and Bi. Penn (69) developed an improved algorithm in 1987 for computing IMFPs from experimental optical data. This algorithm made use of experimental optical data to give the energy-loss function that represented the dependence of the inelastic-scattering probability on energy loss and the theoretical Lindhard dielectric function (70) that represented the dependence of the inelastic-scattering probability on momentum transfer. Tanuma et al. utilized the Penn algorithm in a series of articles (71–75) that reported calculated IMFPs for 27 elemental solids, 15 inorganic compounds, and 14 organic compounds. For each material, they checked the internal consistency of the optical data using two useful sum rules (76). These internal consistency checks were satisfied within an average of about 10 % although larger deviations were found for some inorganic compounds (73). Calculated IMFPs for Al, Cu, Ag, Au, and K from the work of Tanuma et al. (72, 77, 78) are shown in Figure 11. The calculated IMFPs for the first four of these elements are of similar magnitudes for electron energies greater than 200 eV. The IMFPs for K (which has the smallest density), however, are about three to four times larger than the corresponding IMFPs for the element with the largest density (Au) at energies greater than 200 eV. For electron energies less than 200 eV, the behavior of the IMFP-versus-energy curves is more complicated, with the minimum in each curve appearing at substantially different energies. These results are expected from the different energy-loss functions for each element (78). Calculated IMFPs on a linear scale for


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polymethylmethacrylate (PMMA) (75), silicon dioxide (73), Si (72), Cu (72), and W (72) are shown in Figure 12. The computed IMFPs for PMMA are almost a factor of three larger than those for W. It is clear from Figures 11 and 12 that the calculated IMFPs do not lie on some “universal curve.” In addition, it is clear that at least some of the scatter in the plot of AL data in Figure 10 is due to material differences and to different shapes of the IMFP-versus-energy curves for different materials. Tanuma et al. (75) analyzed the dependence of the calculated IMFPs for the elemental solids and organic compounds on electron energy and on material parameters; the group of inorganic compounds was excluded from this analysis because of the greater uncertainty of the optical data for these compounds. The calculated IMFPs for each material (72, 75) were first fitted to a modified form of the Bethe equation (64) for inelastic-electron scattering in matter:

E

λ = E p2

β ln (γ E ) −

C D + 2 E E

(1)

Figure 11. IMFPs calculated for Al, Cu, Ag, Au (72), and K (77) as a function of electron energy (78). The IMFPs shown for energies between 10 eV and 40 eV illustrate trends but are not considered reliable for such low energies.

In eq 1, λ is the IMFP (in Å), E is the electron energy (in eV), Ep = 28.8(Nv ρ兾M)1/2 is the free-electron plasmon energy (in eV), ρ is the density (in g cm᎑3), Nv is the number of valence electrons per atom (for elements) or molecule (for compounds), and M is the atomic or molecular weight. The terms β, γ, C, and D in eq 1 are adjustable parameters in the fits to the calculated IMFPs. The modified form of the Bethe equation (that is, the addition of the final two terms in the denominator of eq 1) was previously suggested by Inokuti (79) and Ashley (80) and was needed here to describe the IMFP dependence on energy for energies less than 200 eV (72). Values of β, γ, C, and D derived from the fits to the calculated IMFPs for the 27 elements and 14 organic compounds were then analyzed to yield the following predictive expressions in terms of material parameters (75): β = −0.10 +

0.944 ( E p2 + E g2 )

1

+ 0.069 ρ0.1 2

(2a)

γ = 0.191 ρ−0.5

(2b)

C = 1.97 − 0.91U

(2c)

D = 53.4 − 20.8U

(2d)

E p2 Nv ρ = M 829.4

(2e)

U =

where Eg is the bandgap energy (in eV) for nonconductors. If appropriate values of material constants are used in eq 2, the average root-mean-square (RMS) deviations of the IMFPs calculated with eq 1 from the values calculated directly from optical data were found to be 10.2% for the group of 27 elements and 8.5% for the group of 14 organic compounds.

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Figure 12. IMFPs calculated for polymethylmethylacrylate (PMMA) (75), silicon dioxide (73), Si (72), Cu (72), and W (72).

These deviations were considered acceptably small taking into account the empirical nature of eq 2 and the sum-rule errors of the optical data (75). Equations 1 and 2 provide a convenient means to estimate IMFPs for materials other than those for which direct IMFP calculations have been made. These relations have been referred to collectively as the TPP-2M equation (75). Similar IMFP calculations have been made by other groups although with some variations in technical approach (55, 81). IMFPs calculated for the same material by different groups typically agree to better than 5% (55, 81). These calculated IMFPs have been compared with IMFPs measured by elastic-peak electron spectroscopy (55). The root-meansquare deviation of the measured IMFPs to a function fitted


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Figure 13. Plot of the ratio of the practical EAL, L, to the IMFP, λ, for Cu 2p3/2 photoelectrons (solid lines) as a function of overlayer thickness (for excitation by Al Kα X-rays with an angle ψ between the X-ray source and the analyzer axis of 55⬚) at different emission angles α (82). The short-dashed lines show L/λ values for film thicknesses for which the Cu 2p3/2 photoelectron intensity from an assumed substrate was reduced to 1%, 2%, 5%, and 10% of the value for the substrate without an overlayer film.

Figure 14. Plots of L1ave and L10ave for Cu 2p3/2 photoelectrons (as for Figure 13) as a function of emission angle, α, for Condition A (short-dashed line) and Condition B (solid line) (82). The long-dashed lines show EAL results from Cumpson and Seah (85) as described in the text.

to the calculated IMFPs for a group of seven elemental solids was 17.4% (55).

different overlayer thicknesses, and for different electron emission angles (84). This algorithm accounts for elastic scattering along the electron trajectories in the solid. As an example, we present plots of the ratio of the practical EAL to the IMFP in Figure 13 as a function of overlayer-film thickness for Cu 2p3/2 photoelectrons excited by Al Kα X-rays for an XPS configuration in which the angle between the axes of the X-ray source and the analyzer, ψ, was 55⬚ (82). The solid lines show values of this ratio for various values of the electron emission angle with respect to the surface normal. The shortdashed lines in Figure 13 are loci of constant relative intensity of Cu 2p3/2 photoelectrons from an assumed Ag substrate. These loci were calculated to show L兾λ values corresponding to film thicknesses for which these substrate intensities were 1%, 2%, 5%, and 10% of the values found for no overlayer film. We consider now two ranges of overlayer-film thicknesses in Figure 13 that are believed to be representative of practical XPS measurements. First, for each α, we obtain the average values, L1ave兾λ, by averaging the L兾λ values in Figure 13 (solid lines) for values of t from zero to the value corresponding to attenuation of the substrate intensity to 1% of its original value for t = 0 (condition A). Second, we obtain similar averages, L10ave兾λ, for film thicknesses from zero to the value corresponding to attenuation of the substrate intensity to 10% of its original value (condition B). Plots of L1ave兾λ and L10ave兾λ as a function of emission angle (82) are shown in Figure 14. For 0⬚ ≤ α ≤ 60⬚, the L1ave兾λ and L10ave兾λ values are of similar magnitude and vary slowly with α. Average values of L can be obtained from these ratios and used as the “lambda parameter” to obtain film thicknesses with the familiar equations derived from the assumption that elastic-electron scattering could be neglected. For emission angles larger than about 60⬚, the L1ave兾λ and L10ave兾λ values in Figure 14 change more rapidly with α, and

Calculations of Effective Attenuation Lengths Although there is a formal definition of the effective attenuation length (EAL) (63), a recent analysis has shown that this is applicable to measurements of the depths of thin marker layers (a relatively uncommon application) and not to measurements of the thicknesses of overlayer films (a relatively common application) (82, 83). For this latter application, it is more useful to define a “practical” EAL, L, from changes of substrate photoelectron (or Auger-electron) intensities as:

L =

1 t cos α ln I 0 − ln It

(3)

where I0 and It represent the substrate-signal intensities before and after deposition of an overlayer-film of thickness t and where α is the angle of electron emission from the surface with respect to the surface normal. Equation 3 is the simple equation that was derived on the assumption that elastic-scattering effects were negligible and that has been used to determine ALs of the type plotted in Figures 10 and 11. We now use eq 3 with the understanding that elastic-scattering effects will generally be significant and that, as a result, the practical EALs will be a function of t and α. Nevertheless, we will show an example to illustrate that, over some useful ranges of t and α, L does not vary significantly with these parameters. EALs have been calculated with an algorithm based on solution of the kinetic Boltzmann equation within the transport approximation to obtain substrate and overlayer-film signal intensities for a specified experimental configuration, for 1744


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values of L should be obtained for specific values of α and t (e.g., from the solid lines in Figure 13). In such cases, it may be necessary to estimate a film thickness, determine L for this thickness, and then refine the film thickness by iteration. For α ≤ 60⬚, the EALs obtained from the L10ave兾λ values in Figure 14 are in good agreement with EALs derived from the Monte Carlo simulations of Cumpson and Seah (85), designated CS(a) in Figure 14. There is poorer agreement (as expected) with results from their more approximate predictive EAL formula (their CS2 formula), designated CS(b) in Figure 14. The plots of L1ave兾λ and L10ave兾λ in Figure 14 for the case of Cu 2p3/2 photoelectrons excited by Al Kα X-rays indicates that the values of L1ave and L10ave are about 28% less than λ for α ≤ 60⬚. These differences are directly due to the effects of elastic scattering of the signal photoelectrons. The rapid increase of L1ave and L10ave, particularly L1ave, for α > 60⬚ is similarly due to elastic scattering. While the IMFP is a useful material parameter (for a given electron energy), Figure 14 shows that the EAL depends not only on the IMFP but also on the specific XPS configuration. Practical EALs have been calculated for representative photoelectron and Auger-electron lines in elemental solids (82, 83) and for SiO2 (86–88). Good agreement was again found between these EALs and those reported by Cumpson and Seah (85) from Monte Carlo calculations, with an RMS deviation of 1.6% for the elemental solids at an emission angle of 45⬚ between the EALs from the two approaches (82). This degree of agreement is considered very satisfactory given the different approaches and approximations in each work. A comparison of twelve measured EAL values for Si 2p photoelectrons in SiO2 excited by Mg and Kα X-rays with corresponding calculated L10ave values in an XPS configuration with ψ = 54⬚ (87) are shown in Figure 15. The measured EALs were obtained from many different types of XPS instruments. Although generally few details of the measurement configurations were given in the original articles, five of these measurements were made on instruments with ψ = 54⬚ or 49⬚ and with emission angles generally less than 60⬚. The mean of the measured EALs for Mg Kα X-rays (29.2 Å) is very close to the calculated value of L10ave (30.0 Å), but the mean of the measured EALs for Al Kα X-rays (30.5 Å) is somewhat smaller than the calculated value of L10ave (35.0 Å). Although the overall agreement between the measured and calculated values would be improved if the calculated IMFPs of SiO2 (73) were reduced by about 10%, it should be noted that there is considerable scatter in the measured EALs (as seen in Figure 10). In addition, the difference between the mean measured EALs for SiO2 and the corresponding L10ave values is comparable to the estimated uncertainty of the calculated practical EALs (82).

Calculations of Mean Escape Depths The electron mean escape depth (MED) is a useful measure of surface sensitivity in AES and XPS. If elastic-electron scattering of the signal electrons were neglected, the MED, ∆, would be simply: (4) ∆ = λ cos α When elastic scattering is considered, however, the MED, now denoted D, is generally different from ∆ (89). Test calwww.JCE.DivCHED.org

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Figure 15. Measured effective attenuation lengths for silicon dioxide at two electron energies corresponding to photoemission from the Si 2p subshell by Al Kα X-rays (䊉) and Mg Kα X-rays (䊊) reported by 12 investigators (87). The error bars indicate one-standard-deviation uncertainties of the measured EALs when these were given. The points for investigator 13 are calculated L10ave values for ψ = 54⬚ with Al Kα X-rays (䊏) and Mg Kα X-rays (ⵧ), and the error bars indicate estimated one-standard-deviation uncertainties. The data points for investigators 1, 9, 10, and 13 were displaced horizontally to show the EAL values for the two X-ray sources more clearly.

culations for illustrative photoelectron lines have shown that D can be up to about 30% less than ∆ for near-normal emission angles and that D can be up to about a factor of two larger than ∆ for near-grazing emission angles (89a). Jablonski and Powell (89b) have reported additional calculations of the MED and new calculations of the information depth for AES and XPS measurements. They find that, as a result of elastic scattering of the signal electrons, measurements at grazing emission angles are less surface sensitive than if elastic scattering had been neglected (as indicated by eq 4). Conversely, measurements made with electron emission angles of less than 50⬚ are more surface sensitive as a result of elastic-scattering effects.

Means To Vary Surface Sensitivity The simplest and most commonly used method used for varying the surface sensitivity of XPS measurements is to record spectra at different electron emission angles (90). If, for simplicity, elastic scattering were neglected, the MED would be given by eq 4. For near-normal emission angles, the measurements would be relatively “bulklike,” while for more grazing emission angles the measurements would be more surface sensitive. The extent to which a particular measurement will be “bulklike” depends of course on the specimen material; that is, whether the material has the bulk composition at a depth comparable to the IMFP for the measurement. Most commercial XPS instruments have the capability to record XPS data at two or more emission angles, so-called angle-resolved XPS (ARXPS), in order to vary the surface sensitivity of the measurements. Algorithms have been developed to extract composition-versus-depth information


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from such measurements (91, 92). The effects of elastic scattering were neglected in the development of these algorithms, and the practical EAL rather than the IMFP should be used as the “lambda parameter” in determinations of overlayerfilm thicknesses, for example, from such measurements (82, 83). As indicated by the example for Cu 2p3/2 photoelectrons in Figure 14, the average practical EAL (e.g., L10ave) does not vary significantly with emission angle for emission angles less than about 60⬚, and L10ave can be used as the lambda parameter in the analysis of ARXPS data for these emission angles. For α > 60⬚, however, a value of the EAL should be found for the (estimated) film thickness and emission angle of interest. The surface sensitivity in XPS may also be varied, where feasible, by choosing to make measurements with photoelectron lines at different electron energies. If the IMFPs and EALs for these energies are sufficiently different for a particular material, the corresponding measurements may be more “surfacelike” or “bulklike”. This approach can be extended by making XPS measurements at a synchrotron-radiation X-ray source (e.g., the X-ray energy could be chosen so that the resulting photoelectron energy would be about 100 eV in order to obtain maximum surface sensitivity, as indicated by the illustrative IMFPs in Figure 12). Alternatively, measurements can be made with a conventional XPS instrument equipped with an X-ray source giving characteristic X-rays of higher energy than the more common Al and Mg Kα sources (e.g., through use of the Cr Kβ source with an energy of 5946.7 eV to obtain greater sensitivity to the bulk; ref 93). Additional surface sensitivity can be attained for samples with flat surfaces by performing grazing-incidence XPS (94– 98). If the angle of X-ray incidence with respect to the surface plane is varied in the vicinity of the critical angle for total external reflection, there will be appreciable changes in the sampling depth for the XPS data. This technique has been used to obtain useful information on the thickness and composition of layered structures on Si and GaAs surfaces (94– 98). Sample Morphology It was often necessary in early surface analyses by XPS to assume that the specimen material was homogeneous over the XPS sampling depth. The same assumption is often made today, sometimes for simplicity (e.g., to obtain a “rough” surface composition). The software on most commercial XPS instruments performs “quantitative” analyses with an algorithm based on this assumption and also makes use of elemental sensitivity factors (i.e., no account is taken of so-called matrix factors in the analysis; ref 99). Idealized examples of possible surface morphologies (99) are shown in Figure 16. Practical samples may have various combinations of these inhomogeneities together with finite roughness and various types of surface defects. An analyst may know from experience or from knowledge of a sample’s history that inhomogeneities of a certain type are likely. Information on the extent of lateral inhomogeneities can be derived from imaging XPS instruments (with lateral resolu-

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Figure 16. Idealized surface morphologies that illustrate the relation between surface structure and surface composition (99): (a) plane homogeneous surface; (b) a surface with depth inhomogeneities (the circles and the crosses represent different types of atoms); (c) a surface with lateral inhomogeneities consisting of several different surface phases; (d) a surface phase consisting of a submonolayer of foreign atoms on an otherwise homogeneous surface; and (e) an interface between two homogeneous bulk phases.

tions now approaching 1 µm). Similar information on depth inhomogeneities can be obtained from angle-resolved XPS experiments, from ratios of spectra at two emission angles (100) or from analyses of the photoelectron energy distributions in the vicinity of major peaks (101, 102). Information on sample morphology is critical for selection of the appropriate equation to be used for a quantitative analysis (103, 104). Phillips et al. (105), for example, have shown how drastically different dependences of composition versus depth can alter observed intensity ratios. Tougaard (106) has similarly shown that an observed Cu 2p3兾2 photoelectron intensity could correspond (depending on the morphology) to a fractional monolayer of Cu, a surface alloy extending to a depth of 5 nm, a 1 nm Cu layer located 2 nm below the surface, or to a Cu substrate covered by a 2.5 nm overlayer. In each of these cases, analysis of the spectral region extending from the Cu 2p3/2 peak to lower energies can identify which of these different morphologies is likely to be present (101, 102, 106). Castle and Baker (107a) have pointed out the richness of information available in XPS data. They propose the development of an expert system for XPS that can be utilized by both novices and experts to design suitable experiments and to analyze the resulting data. As an example, they demonstrate the feasibility of an expert system designed to test whether carbon is present on a sample as overlayer contamination. A 2002 Workshop organized to consider a possible expert system for XPS produced many recommendations for elements of such a system (107b). These recommendations are also a valuable source of “best practices” for XPS and should be useful as an educational resource for both novice and experienced users.


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NIST Databases for XPS

Electron Effective-Attenuation-Length Database

NIST currently provides four databases for applications in AES and XPS (108). These will be briefly described.

Version 1.0 of the NIST Electron Effective-AttenuationLength Database (SRD 82) was released in 2001 and is available without charge (113). This database, to be used on a PC, provides EALs for measurements of overlayer-film thicknesses and for determinations of the depths of thin marker layers. The EALs are calculated for experimental configurations specified by the user from the algorithm of Tilinin et al. (84). The EALs are computed with IMFPs from SRD 71 and transport cross sections from SRD 64. The database also provides values of other parameters useful for describing the effects of elastic-electron scattering in AES and XPS.

XPS Database Version 3.0 of the NIST X-ray Photoelectron Spectroscopy Database (SRD 20) was released in 2000 and four enhancements have since been released. This database is available for online access through the Internet and is free (109). The database, developed initially by C. D. Wagner, now contains 22,000 line positions, chemical shifts, doublet separations, and energy separations of photoelectron and Auger-electron spectral lines. The main uses of the XPS database are to identify unknown spectral lines (photoelectron lines, Auger-electron lines, Auger parameters, and doublet separations), to retrieve data for selected elements (binding energy, Auger kinetic energy, Auger parameter, doublet separation, chemical shift, surface or interface core-level shift, and elemental reference data), to retrieve data for selected compounds (containing selected groups of elements, containing a selected element, by chemical name, and by chemical classes), to display Wagner plots, and to retrieve data by scientific citation. Work is ongoing to provide additional data.

Electron Elastic-Scattering Cross-Section Database Version 3.1 of the NIST Electron Elastic-Scattering Cross-Section Database (SRD 64) was released in 2003 and is available without charge (110). This database, to be used on a personal computer (PC), provides calculated differential and total elastic-electron-scattering cross sections, phase shifts, and transport cross sections for elements with atomic numbers from 1 to 96 and for electron energies between 50 eV and 20,000 eV in steps of 1 eV. These data are useful for modeling the transport of signal electrons in AES and XPS.

Electron Inelastic-Mean-Free-Path Database Version 1.1 of the NIST Electron Inelastic-Mean-FreePath Database (SRD 71) was released in 2000 and is available without charge (111). This database, to be used on a personal computer, contains IMFPs calculated from experimental optical data for certain elements and compounds and IMFPs measured by elastic-peak electron spectroscopy (55) for certain elements. If no calculated or measured IMFPs are available for a material of interest, values can be estimated from the TPP-2M formula of Tanuma et al. (75) or a more approximate formula proposed by Gries (112). Values of IMFPs are needed in AES and XPS for quantitative analyses (for correction of matrix effects), calculations of effective attenuation lengths (for measurement of overlayer-film thicknesses), determination of mean escape depths (as measures of surface sensitivity), determination of specimen morphology, and film thicknesses from analyses of spectral lineshapes (101, 102), and modeling of the transport of signal electrons.

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NIST Standard Test Data for XPS Standard test data (STD) are simulations of instrument responses that can be used to assess data-analysis procedures involving different algorithms and different operator choices. NIST has developed a set of STD for XPS that analysts can use for detecting, locating, and measuring the intensities of overlapping peaks in a doublet (114–116). The XPS-STD simulate varying degrees of peak overlap, varying relative intensities, and varying levels of random noise. These XPS-STD were constructed by adding scaled spectra (derived from C 1s spectra for selected polymers) according to a factorial design. The XPS-STD doublet spectra are shown in Figure 17. These spectra are simulations of XPS measurements for specimen materials consisting of two chemical phases; that is, of a material with an element in two chemical compounds for which there are different chemical shifts with respect to the pure elemental solid. The XPS-STD were assessed by a group of 20 analysts who used different software and different equations for fitting the component peaks of each spectrum (114–116). While most spectra in the XPS-STD were doublets, some were singlets. Analysts therefore had to decide whether a particular spectrum was a doublet or a single, but this decision was frequently not made correctly (114). Analysts were asked to report peak positions and peak intensities. These results were analyzed to give information on the bias and random error for particular spectra in the XPS-STD set and for particular curve-fitting equations (114–116). The XPS-STD can be downloaded and individual results can be uploaded for analysis and comparison with results from the group of 20 analysts (117). The largest biases and random errors in the relative intensities of the doublet spectra occurred, as expected, when the peak separation was the smallest (i.e., 0.32 eV for spectra a, b, and c in Figure 17). For these doublets, the biases and random errors were largest for spectrum c. Test fits with different starting values for the lineshape parameters showed that equally satisfactory results could be obtained with ratios of peak intensities varying by a factor of three. For this spectrum, it is clear that the peak parameters from each fit were highly correlated and had large uncertainties. XPS analysts should therefore not assume that a single “good” fit, as judged by statistics or by eye, to a measured spectrum will necessarily lead to reliable values of the peak parameters if the peak


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Figure 17. Standard test data showing only the doublet spectra for XPS with intensity (counts per channel) as a function of binding energy increasing to the left (114–116). These spectra were constructed from a design with three factors: factor 1 (component peak separation) and factor 2 (relative peak height) have three levels, while factor 3 (fractional Poisson noise) has two levels.

separations are small (i.e., particularly spectra a–c in Figure 17 and, to a lesser extent, spectra d–f ) and if similar counting statistics are acquired. Detailed guidance on the evaluation of uncertainties for peak parameters in fits to overlapping peaks has been published by Cumpson and Seah (118). While the STD in Figure 17 were designed with parameters that are representative of those encountered in everyday XPS, spectra with overlapping peaks are also observed with many other analytical methods. It is therefore believed that the XPS-STD will be a useful set of test spectra for the training of students and for the guidance of other analysts. In particular, the XPS-STD can be utilized as a tool to obtain more realistic estimates of the uncertainties in peak parameters derived from fits to complex spectra. Concluding Remarks Although the history of XPS extends over almost a century, the technique was shown to be of scientific and practical value by Kai Siegbahn and his coworkers at the University of Uppsala in the 1950s and 1960s. Commercial XPS instruments were introduced in the late 1960s and are now widely employed for a vast range of applications. While XPS has clearly been successful for many problems, the reliability of analyses, particularly quantitative analyses, was sometimes unsatisfactory. This article is a survey of progress made over the past ∼30 years to improve the reliability of XPS analyses.

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The basic principles of XPS are very simple yet there is considerable complexity in designing experiments, interpreting data, and analyzing the results for the many different modes of operation and many different types of specimen materials. It is hoped that the reliability and efficiency of XPS analyses can be further improved through the development of more powerful data systems (i.e., expert systems; ref 107). Such systems should enhance the utility of XPS in the coming years. Acknowledgments The author is greatly indebted to the many colleagues with whom he has collaborated on the work summarized in this review. Literature Cited 1. Jenkin, J. G.; Leckey, R. C. G.; Liesegang, J. J. Electron Spectrosc. Relat. Phenom. 1977, 12, 1. 2. Jenkin, J. G.; Riley, J. D.; Leckey, R. C. G.; Liesegang, J. J. Electron Spectrosc. Relat. Phenom. 1978, 14, 477. 3. Steinhardt, R. G.; Serfass, E. J. Anal. Chem. 1951, 23, 1585. 4. Steinhardt, R. G.; Serfass, E. J. Anal. Chem. 1953, 25, 697. 5. Steinhardt, R. G.; Granados, F. A. D.; Post, G. I. Anal. Chem. 1955, 27, 1046. 6. Nordling, C.; Sokolowski, E.; Siegbahn, K. Phys. Rev. 1957, 105, 1676.


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Waters Symposium: Electron Spectroscopy for Chemical Analysis 7. Nordling, C.; Sokolowski, E.; Siegbahn, K. Phys. Rev. 1958, 110, 776. 8. Siegbahn, K.; Nordling, C.; Fahlman, A.; Nordberg, R.; Hamrin, K.; Hedman, J.; Johansson, G.; Bergmark, T.; Karlsson, S. E.; Lindgren, I.; Lindberg, B. ESCA—Atomic, Molecular and Solid State Structure Studied by Means of Electron Spectroscopy; Almqvist and Wiksells: Uppsala, Sweden 1967. 9. Interview with K. Siegbahn. European Spectroscopy News 1982, 44, 25. 10. Powell, C. J.; Robins, J. L.; Swan, J. B. Phys. Rev. 1957, 110, 657. 11. Hoffman, S. Surf. Interface Anal. 1986, 9, 3. 12. Madey, T. E.; Wagner, C. D.; Joshi, A. J. Electron Spectrosc. Relat. Phenom. 1977, 10, 359. 13. Powell, C. J.; Erickson, N. E.; Madey, T. E. J. Electron Spectrosc. Relat. Phenom. 1979, 17, 361. 14. Powell, C. J.; Erickson, N. E.; Madey, T. E. J. Electron Spectrosc. Relat. Phenom. 1982, 25, 87. 15. Youden, W. J. Industrial Quality Control 1959, 15, 24. Youden, W. J. Anal. Chem. 1960, 32, 23A. 16. Powell, C. J.; Erickson, N. E.; Jach, T. J. Vac. Sci. Tech. 1982, 20, 625. 17. Erickson, N. E.; Powell, C. J. Surf. Interface Anal. 1986, 9, 111. 18. Erickson, N. E.; Powell, C. J. J. Vac. Sci Tech. A 1986, 4, 1551. 19. Anthony, M. T.; Seah, M. P. Surf. Interface Anal. 1984, 6, 95. 20. Anthony, M. T.; Seah, M. P. Surf. Interface Anal. 1984, 6, 107. 21. Seah, M. P.; Gilmore, I. S.; Spencer, S. J. Surf. Interface Anal. 1998, 26, 617. 22. Seah, M. P.; Gilmore, I. S.; Beamson, G. Surf. Interface Anal. 1998, 26, 642. 23. Powell, C. J. Surf. Interface Anal. 1997, 25, 777. 24. Powell, C. J. Surf. Interface Anal. 1995, 23, 121. 25. Miller, A. C.; Powell, C. J.; Gelius, U.; Anderson, C. R. Surf. Interface Anal. 1998, 26, 606. 26. ISO 15472: 2001. Surface Chemical Analysis—X-ray Photoelectron Spectrometers—Calibration of Energy Scales; International Organization for Standardization: Geneva, 2001. 27. Figure 6 is reproduced from ISO 15472: 2001 and Figure 5 is based on a figure in this document. Permission has been granted by the International Organization for Standardization (ISO) for the use of these figures. ISO 15742 can be obtained from any ISO member and from the Web site of the ISO Central Secretariat at the following address: http://www.iso.org (accessed Aug 2004). Copyright remains with ISO. 28. Seah, M. P. Surf. Interface Anal. 2001, 31, 721. 29. ASTM Standard E 2108-00. Standard Practice for Calibration of the Electron Binding-Energy Scale of an X-ray Photoelectron Spectrometer. In Annual Book of ASTM Standards; ASTM: West Conshohocken, PA, 2001: Vol. 3.06, p 839. 30. Practice E 2108-00 is available for purchase from the ASTM Web site, http://www.iso.org (accessed Aug 2004), or by contacting the ASTM Customer Service Department, 100 Barr Harbor Drive, West Conshohocken, PA 19428-2959. 31. Powell, C. J. J. Vac. Sci. Tech. A 2001, 19, 2689. 32. Powell, C. J. Appl. Surf. Science 1995, 89, 141. 33. Svensson, S.; Martensson, N.; Basilier, E.; Malmqvist, P. A.; Gelius, U.; Siegbahn, K. J. Electron Spectrosc. Relat. Phenom. 1976, 9, 51. Berndtsson, A.; Nyholm, R.; Martensson, N.;

www.JCE.DivCHED.org

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34.

35. 36.

37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47.

48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63.

64. 65. 66. 67.

Nilsson, R.; Hedman, J. Phys. Stat. Solidi (b) 1979, 93, K103. Martensson, N.; Berndtsson, A.; Nyholm, R. J. Electron Spectrosc. Relat. Phenom. 1980, 19, 299. Nyholm, R.; Martensson, N. J. Phys. C (Solid State Phys.) 1980, 13, L279. Nyholm, R.; Martensson, N. J. Phys. C (Solid State Phys.) 1980, 13, L1091. Lebugle, A.; Axelsson, U.; Nyholm, R.; Martensson, N. Phys. Scripta 1981, 23, 825. Ikeo, N.; Iijima, Y.; Niimura, M.; Sigematsu, M.; Tazawa, T.; Matsumoto, S.; Kojima, K.; Nagasawa, Y. Handbook of X-ray Photoelectron Spectroscopy; JEOL: Akishima, Japan, 1991. Crist, B. V. private communication. Moulder, J. F.; Stickle, W. F.; Sobol, P. E.; Bomben, K. D. Handbook of X-ray Photoelectron Spectroscopy; Perkin-Elmer: Eden Prairie, MN, 1992. Seah, M. P.; Anthony, M. T. Surf. Interface Anal. 1984, 6, 230. Seah, M. P.; Jones, M. E.; Anthony, M. T. Surf. Interface Anal. 1984, 6, 242. Smith, G. C.; Seah, M. P. Surf. Interface Anal. 1990, 15, 751. Smith, G. C.; Seah, M. P. Surf. Interface Anal. 1990, 16, 144. Seah, M. P. Surf. Interface Anal. 1993, 20, 243. Seah, M. P. J. Electron Spectrosc. Relat. Phenom. 1995, 71, 191. Seah, M. P.; Spencer, S. J.; Bodino, F.; Pireaux, J. J. J. Electron Spectrosc. Relat. Phenom. 1997, 87, 159. Seah, M. P. Appl. Surf. Science 1999, 144–145, 132. Seah, M. P.; Gilmore, I. S.; Spencer, S. J. J. Electron Spectrosc. Relat. Phenom. 1999, 104, 73. Seah, M. P.; Gilmore, I. S.; Spencer, S. J. Surf. Interface Anal. 2001, 31, 778. Information on the NPL XPS calibration software is available over the Internet at: http://www.npl.co.uk/nanoanalysis (accessed Sep 2004). Powell, C. J. Surf. Science 1974, 44, 29. Brundle, C. R. J. Vac. Sci. Tech. 1974, 11, 212. Lindau, I; Spicer, W. E. J. Electron Spectrosc. Relat. Phenom. 1974, 3, 409. Seah, M. P.; Dench, W. A. Surf. Interface Anal. 1979, 1, 2. Powell, C. J. J. Electron Spectrosc. Relat. Phenom. 1988, 47, 197. Powell, C. J. Surf. Science 1994, 299–300, 34. Barbier, A. Surf. Science 1998, 406, 69. Powell, C. J., Jablonski, A. J. Phys. Chem. Ref. Data 1999, 29, 19. Baschenko, O. A.; Machavariani, G. V.; Nefedov, V. I. J. Electron Spectrosc. Relat. Phenom. 1984, 34, 305. Jablonski, A. Surf. Science 1987, 188, 164. Jablonski, A.; Ebel, H. Surf. Interface Anal. 1988, 11, 627. Jablonski, A. Surf. Interface Anal. 1990, 15, 559. Tilinin, I. S.; Jablonski, A.; Werner, W. S. M. Prog. Surf. Science 1996, 52, 193. Nefedov, V. I. J. Electron Spectrosc. Relat. Phenom. 1999, 100, 1. Jablonski, A.; Powell, C. J. J. Electron Spectrosc. Relat. Phenom. 1999, 100, 137. ASTM Standard E 673-98, Standard Terminology Relating to Surface Analysis. In Annual Book of ASTM Standards; ASTM: West Conshohocken, PA, 2001; Vol. 3.06, p 735. Bethe, H. Ann. der Physik 1930, 5, 325. Quinn, J. J. Phys. Rev. 1962, 126, 1453. Lundqvist, B. I. Phys. Status Solidi 1969, 32, 273. Shelton, J. C. Surf. Science 1974, 44, 305.


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Waters Symposium: Electron Spectroscopy for Chemical Analysis 68. Powell, C. J. Surf. Interface Anal. 1985, 7, 263. 69. Penn, D. R. Phys. Rev. B 1987, 35, 482. 70. Lindhard, J.; Scharff, M. Kong. Danske Videns. Selsk. Mat.Fys. Medd. 1953, 27, (15), 1. Lindhard, J.; Scharff, M.; Schiott, H. E. Danske Videns. Selsk. Mat.-Fys. Medd. 1963, 33, (14), 1. 71. Tanuma, S.; Powell, C. J.; Penn, D. R. Surf. Interface Anal. 1988, 11, 577. 72. Tanuma, S.; Powell, C. J.; Penn, D. R. Surf. Interface Anal. 1991, 17, 911. 73. Tanuma, S.; Powell, C. J.; Penn, D. R. Surf. Interface Anal. 1991, 17, 927. 74. Tanuma, S.; Powell, C. J.; Penn, D. R. Surf. Interface Anal. 1993, 20, 77. 75. Tanuma, S.; Powell, C. J.; Penn, D. R. Surf. Interface Anal. 1994, 21, 165. 76. Tanuma, S.; Powell, C. J.; Penn, D. R. J. Electron Spectrosc. Relat. Phenom. 1993, 62, 95. 77. Tanuma, S.; Powell, C. J.; Penn, D. R. submitted for publication. 78. Powell, C. J.; Jablonski, A.; Tilinin, I. S.; Tanuma, S.; Penn, D. R. J. Electron Spectrosc. Relat. Phenom. 1999, 98–99, 1. 79. Inokuti, M. Rev. Mod. Phys. 1971, 43, 297. 80. Ashley, J. C. J. Electron Spectrosc. Relat. Phenom. 1988, 46, 199. 81. Powell, C. J.; Jablonski, A. Surf. Interface Anal. 2000, 29, 108. 82. Powell, C. J.; Jablonski, A. Surf. Interface Anal. 2002, 33, 211. 83. Jablonski, A.; Powell, C. J. Surf. Science Reports 2002, 47, 33. 84. Tilinin, I. S.; Zemek, J.; Hucek, S. Surf. Interface Anal. 1997, 25, 683. 85. Cumpson, P. J.; Seah, M. P. Surf. Interface Anal. 1997, 25, 430. 86. Powell, C. J.; Jablonski, A. J. Electron Spectrosc. Relat. Phenom. 2001, 114–116, 1139. 87. Powell, C. J.; Jablonski, A. J. Vac. Sci. Tech. A 2001, 19, 2604. 88. Powell, C. J.; Jablonski, A. Surf. Science. 2001, 488, L547. 89. (a) Jablonski, A.; Tilinin, I. S.; Powell, C. J. Phys. Rev. B 1996, 54, 10927. (b) Jablonski, A.; Powell, C. J. J. Vac. Sci. Tech. A 2003, 21, 274. 90. Fadley, C. S.; Baird, R. J.; Siekhaus, W.; Novakov, T.; Bergstrom, S. A. L. J. Electron Spectrosc. Relat. Phenom. 1974, 4, 93. 91. Cumpson, P. J. J. Electron Spectrosc. Relat. Phenom. 1995, 73, 25. 92. Cumpson, P. J. Appl. Surf. Science. 1999, 144–145, 16. 93. Diplas, S.; Watts, J. F.; Morton, S. A.; Beamson, G.; Tsakiropoulos, P.; Clark, D. T.; Castle, J. E. J. Electron

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Spectrosc. Relat. Phenom. 2001, 113, 153. 94. Chester, M. J.; Jach, T. Phys. Rev. B 1993, 48, 17262. 95. Jach, T.; Chester, M. J.; Thurgate, S. M. Nucl. Instr. Meth. Phys. Res. A 1994, 347, 507. 96. Jach, T.; Landree, E. Surf. Interface Anal. 2001, 31, 768. 97. Kawai, J.; Kawato, S.; Hayashi, K.; Horiuchi, T.; Matsushige, K.; Kitajima, Y. Appl. Phys. Lett. 1995, 67, 3889. 98. Kawai, J.; Hayakawa, S.; Kitajima, Y.; Maeda, K.; Gohshi, Y. J. Electron Spectrosc. Relat. Phenom. 1995, 76, 313. 99. Powell, C. J.; Seah, M. P. J. Vac. Sci. Tech. A 1990, 8, 735. 100. Seah, M. P.; Qiu, J. H.; Cumpson, P. J.; Castle, J. E. Surf. Interface Anal. 1994, 21, 336. 101. Tougaard, S. Surf. Interface Anal. 1998, 26, 249. 102. Werner, W. S. M. Phys. Rev. B 1995, 52, 2964. 103. Powell, C. J. In Quantitative Surface Analysis of Materials, ASTM STP 643; McIntyre, N. S., Ed.; ASTM: Philadelphia, 1978; p 5. 104. Seah, M. P. Vacuum 1986, 36, 399. 105. Phillips, L. V.; Salvati, L.; Carter, W. J.; Hercules, D. M. In Quantitative Surface Analysis of Materials, ASTM STP 643; McIntyre, N. S., Ed.; ASTM: Philadelphia, 1978; p 47. 106. Tougaard, S. J. Vac. Sci. Tech. A 1996, 14, 1415. 107. (a) Castle, J. E.; Baker, M. A. J. Electron Spectrosc. Relat. Phenom. 1999, 105, 245. (b) Castle, J. E.; Powell, C. J. Surf. Interface Anal. 2004, 36, 225. 108. Powell, C. J.; Jablonski, A.; Naumkin, A.; Kraut-Vass, A.; Conny, J. M.; Rumble, J. R. J. Electron Spectrosc. Relat. Phenom. 2001, 114–116, 1097. 109. X-ray Photoelectron Spectroscopy Database. http:// srdata.nist.gov/xps/ (accessed Aug 2004). 110. NIST Electron Elastic-Scattering Cross-Section Database. http://www.nist.gov/srd/nist64.htm (accessed Aug 2004). 111. NIST Electron Inelastic-Mean-Free-Path Database. http:// www.nist.gov/srd/nist71.htm (accessed Aug 2004). 112. Gries, W. H. Surf. Interface Anal. 1996, 24, 38. 113. NIST Electron Effective-Attenuation-Length Database. http:// www.nist.gov/srd/nist82.htm (accessed Aug 2004). 114. Conny, J. M.; Powell, C. J.; Currie, L. A. Surf. Interface Anal. 1998, 26, 939. 115. Conny, J. M.; Powell, C. J. Surf. Interface Anal. 2000, 29, 444. 116. Conny, J. M.; Powell, C. J. Surf. Interface Anal. 2000, 29, 856. 117. Further information on the XPS-STD can be obtained from the following internet address (from which the XPS-STD can be downloaded and individual results uploaded for analysis): http://www.acg.nist.gov/std (accessed Aug 2004). 118. Cumpson, P. J.; Seah, M. P. Surf. Interface Anal. 1992, 18, 345.


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