Photoelectron Spectroscopies K e n n e t h W . N e b e s n y , Brian L. Maschhoff, and N e a l R. Armstrong Laboratory for Electron Spectroscopy and Surface Analysis and Department of Chemistry The University of Arizona Tucson, AZ 85721
Surface analysis using electron spectroscopies is now a well-established and continuously expanding area. With appropriate data treatment procedures, both Auger electron spectroscopy (AES, not to be confused with atomic emission spectroscopy) and Xray photoelectron spectroscopy (XPS or ESCA) can routinely supply reliable
with binding energies of less than 1000 eV. The kinetic energy of the electron escaping the solid and successfully traversing the analyzer to the detector is specific to the element of origin and is further varied by changes in the oxidation state of that element. Shifts in spectral lines are sizable in both AES and X P S , but more easily interpreted for XPS. Molecular information about the solid can generally be obtained together with its elemental makeup and an estimate of concentration. Since the development of the first modern commercial surface spectrometers in the late 1960s and early 1970s, there has been a steady refinement and improvement in t h e instrumentation for surface electron spectroscopies (see
INSTRUMENTATION qualitative and semiquantitative characterization of the near-surface region (top 1-100 À) of most solids. A schematic of the spectroscopic processes is shown in Figure 1 (using the S(2p) photoemission (XPS) and S (LMM) Auger emission as examples). Both X P S and AES typically involve ionization of core and valence electrons 0003-2700/89/0361 -469A/$01.50/0 © 1989 American Chemical Society
Gardella's forthcoming article in the May 1 issue of ANALYTICAL CHEMISTRY [1]). These include better vacuum and sample handling, improved excitation source designs (multiple-energy X-ray sources with higher photon fluxes (XPS) and brighter, higher spatial resolution electron beams (AES)), high-resolution and high-throughput
Figure 1. Schematic of the spectroscopic emission processes: (a) X-ray photoelectron process for sulfur, (b) Auger process for sulfur, and (c) the near-surface electron emission process.
ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989 · 469 A
INSTRUMENTATION efficiency electron kinetic energy analyzers, new detector designs (multichannel versions are an attractive, developing alternative), and, of course, better computer control and data-processing packages. Multiple-technique surface analytical systems, whose price tags exceed several hundred thousand dollars, are the norm these days for most "routine" surface electron spectrometers. Most instrument vendors have also recognized that there is a growing countertrend in the demand for singletechnique instruments, sometimes attached to materials processing systems, that reflects the general philosophy of taking analysis to the sample rather than vice versa. As predicted in David Hercules' 1978 article (2), AES and XPS are the preeminent surface analytical techniques because of their widespread availability. Secondary ion mass spectroscopy (SIMS) is considerably more sensitive but is more difficult to quantitate. Electron diffraction techniques such as low-energy electron diffraction (LEED) can provide surface structural information. The wider availability of synchrotron radiation sources has provided options for analysis of other forms of local surface structure through the use of extended X-ray absorption fine structure (EXAFS) and related spectroscopies (3, 4). Along with the changes in instrumentation, there has been an increasing interest in understanding (and removing) the limitations to the quantitative analytical capabilities of surface analytical methods in general and surface electron spectroscopies in particular (5-10). Surface electron spectroscopies are not trace analysis techniques; 0.1-1% concentration ranges are typical detection limits for most elements. Even in these concentration ranges, AES and XPS are not considered as quantitative as other analytical techniques used for materials characterization. The electron microprobe combined with X-ray fluorescence is one example of a "quantitative" materials characterization technique. The electron microprobe, however, is not a true surface analysis technique, primarily because the sampling depth extends up to micrometers versus 1-1000 Â for AES and X P S . Both sample matrix and instrumental problems described in this article for AES and XPS have often been considered too formidable for reliable quantitation. Today, surface analysis techniques are used to characterize new technology materials whose dimensions are small (length, width, and depth in the range of 100 A - l μηι). It is foreseeable that surface analytical information will
be used to define device specifications and to differentiate competing tech nologies. Reliable quantitative infor mation from these surface analytical techniques is therefore becoming es sential. Recognition of this fact has led to numerous publications and to several new conferences on quantitative sur face analysis. The Topical Conference on Quantitative Surface Analysis, held biennially (1985, 1987,1989), generally precedes the American Vacuum Soci ety National Symposium. A larger topi cal conference on quantitative surface analysis is held yearly in Europe. Sev eral detailed reviews describe some of the factors that must be considered to obtain quantitative compositional in formation from electron spectroscopies (5-10). Quantitative relationships in AES and XPS We first consider the problems in quantitation for AES. The detected current (IA) (generally the peak area or a measured parameter proportioned to that area) in an electron beam excited Auger emission signal from a solid is given by the formalism of Seah (6), Ι
Α = Ι0χ T
σΑ(£ρ) Χ ί 1 + rM(EA,tt)J Χ
(EOxD(EA)xfNA(z)X
exp - ζ / λ Μ £Α cos θ dz
(1)
where IQ represents the electron beam excitation source current (amps-cm -2 ), σ Α(£ρ) represents the electron impact ionization cross section (at primary beam energy Ep) leading to Auger elec tron emission (11), 1 + ΓΜ(£Α,α) repre sents the additional population of Au ger electrons produced at energy Ε A by backscattering of primary source elec trons and other secondary electrons; r M is the backscattering coefficient exam ined at angle a to the surface normal (12), T(EA) represents the transmission efficiency of the analyzer at E& (the kinetic energy of the detected Auger electron), and D(£A) represents the de tector efficiency. The integral term contains the con centration of the analyte (N\) modified by the exponential decay term, which takes into account that the Auger emis sion signal decays as the distance ζ be low the surface plane increases (with decay constant λ, the electron escape depth at energy ΕA) (13-15). The angle of analysis, Θ, to the surface normal is included, and it is clear that as θ in creases, the surface sensitivity also in creases. For θ = 90°, and assuming that all of the detected Auger emission oc
470 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
curs within the depth ζ = 5λ, most Au ger spectra in the kinetic energy range from 50 to 1500 eV arise from within 1 to 100 À of the solid-vacuum interface. The principal uncertainties in Equation 1 arise from σΑ(£ρ), ru, and ^M,£ A ' assuming that the instrumentally dictated parameters, T(EA) and D(E A ),
are known or can be determined in a straightforward manner. For adsorbates (A) at submonolayer to monolayer levels on well-ordered surfaces (Figure 2a), Schoeffel and Hubbard showed several years ago that it is possible to fully account for the uncertainties in Equation 1 and to cal culate absolute surface coverages from the measured Auger emission current (16). This method, or related ap proaches, is extensively used to quantitate surface coverages of a wide variety of ordered and disordered adsorbates on well-ordered surfaces. Such data are routinely correlated with surface coverages determined from electro chemical (voltammetric) data, thermal desorption mass spectrometry, and low-energy electron diffraction. The experimenter is greatly aided here by the fact that scattering of Auger elec trons (described below) that arises from the analyte adsorbate layer is minimal. Adsorbates on well-ordered surfaces at submonolayer to monolayer coverages generally are the easiest sys tems to quantitate absolutely using surface electron spectroscopies (either AES or XPS). The next easiest case is when the sol id can be considered homogeneous within the analysis depth (ca. 5λ) for all the elements (e.g., A and B) of inter est (Figure 2b). The uncertainties in Equation 1 can be partially cancelled by considering relative atomic ratios (or the atomic percentage) of a pair of elements
"**>
( ι + ***>)
^Λ X ^ X1 ^ X iUV Μ,£ Β
EB
A
/iV
B
(2)
EB
If Τ and D are known accurately, modi fications can subsequently be made to the spectral intensities (7A —*• IA') and Equation 2 reduces to
σ
Β(ΕΒ)
Ιι , _ \ U + ΓΜ(£Β) Ι
^M,£A
., , „
,„.
— ^ Χ ΝΑ/ΝΒ
(3)
λ
Μ,£ Β
If pure element standards are available for A, B, and all other elements under
consideration, then an atomic percent age of A or Β can be computed from IA/IB, Ik°HvT (the Auger current ratio from the pure element standards) and a "matrix factor," FAB, which corrects for differences in the backscattering coefficients and in the atom densities between the standards and the un knowns (5, 6,17). Unfortunately, pure element (vacu um-compatible) standards are diffi cult, or even impossible, to obtain for many solids of interest. An alternative, recommended whenever possible, is to use standards that are near the sus pected composition (and have the same matrix) of the unknown. The relative atomic ratio or atomic percentage of the unknown (NA/NB)ul± is computed from the measured Auger signal ratios for the unknown and the standard— (/A/^B)unk and ( J A / Z B W . respectively—
and from the stoichiometry of the stan dard, (ΝΑ/ΝΒ)Μ,
according to
(NA/NB)mi
= (J A // B ) u n k X
VMM
x WMM
(4)
or, for atomic percentage (X A ) calcula tions, •^A(unk)
=
f A(unk)
Σ ^i(std) X
Σ ^i(unk) ι
1 X
^A(std)
(5) -^A(etd)
Another option is the correction of the measured intensity ratios, using sensitivity factors for each element, that are calculated, measured, or esti mated from commercially available ta bles (18). The best approach is to mea sure these sensitivity factors so that they are specifically correct for the an alyzer, operating conditions, and sam ple matrices that are of interest. There is still considerable risk in the use of sensitivity factors obtained from other instruments and laboratories. For X-ray photoelectron spectrosco py and X-ray excited Auger electron emission, there are similar consider ations for the quantitation of composi tion of homogeneous solids. The range of kinetic energies of the photoelec trons emitted from the solid is similar to Auger spectroscopy, so the sampling depths are comparable. Backscattering does not enter into the production of photoelectrons, but there are more crit ical angular dependencies involving the angle of the source to the sample normal and the takeoff angle of analy sis (6). A relationship similar to Equa tion 2 can be written for relative inten sity ratios, which includes small correc tions for angular asymmetries (L) (7),
Figure 2. Electron emission events in the near-surface region, (a) Auger electron or photoelectron emission from monolayer adsorbates on the surface, (b) scattered or nonscattered electron emission, and (c) electrons emitted from the overlayer or emitted from the substrate and then scattered in the overlayer.
/ A / / B =
! ^ > X ^ Β(ΕΒ) λΜ(£Β)
X
σ
Lk/LB
X NA/NB
(6)
where most of the terms have the defi nitions assigned above and σ is now the photoionization probability (values tabulated from Scofield's calculations or Wagner's sensitivity tables generally are used) (19, 20). Equations 4 and 5 are once again more convenient if stan dards are available. Another factor of importance in both AES and XPS is that the original pho
toionization event does not always lead to a single spectroscopic peak. The ki netic energy of the detected photoelec tron is dependent on the energy differ ence between the initial state (before photoemission) and final state (after photoemission) of the atom and its sur roundings. Photoionization of elec trons from p, d, and f orbitals always leads to two peaks (because of spin or bit coupling in the final state). Relative intensities (R) are predicted by the ra tio of the quantum numbers (j = I + s) for those orbitals, R = (2/ + l ) / ( 2 / + 1). If the peaks are sufficiently resolved
ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989 · 471 A
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(>5 eV apart), only one is used in quantitative analysis; otherwise, the collective area of both peaks should be used. The S(2pi/2,3/2) lines (unresolved) and the Sn(3d3/2,5/2) lines (resolved) in Figure 4b on p. 476 A illustrate examples of this phenomenon. Photoelectrons may also gain or lose energy at the site of photoemission through shake-off or shake-up processes (common for some transition metal compounds). From Equations 2,3, and 6, it is clear that for homogeneous materials where no standards exist, reasonable quantitation might still result if good estimates can be made for the variables in those relationships. However, the analyst must be assured of four things. First, the probability of ionization of the Auger or photoelectron or a corresponding relative yield factor must be available or calculable, and reasonably accurate. Second, good descriptions are needed to quantitate electron backscattering processes in solids. Third, the electron transport (energy loss) processes in solids that determine the escape depth must be well described. Finally, the analyzer transmission efficiency and the detector efficiency must be quantitatively described over the entire kinetic energy range of interest. Determinate (unidirectional) errors in any of these parameters can be expected. These errors will prevent the analyst from determining absolute concentrations of the analyte, but relative atomic ratio or atomic percentage calculations will generally cancel most of these errors. Factors that affect peak shapes in AES and XPS Now the question becomes, "How does the analyst obtain accurate peak areas in both AES and XPS, with which to proceed toward quantitation?" This critical question, if answered properly, can lead to good quantitative characterization of many solid surfaces (2128). Unlike many atomic emission spectroscopies where the line shapes are relatively simple, the detected peaks in either photoelectron or Auger spectroscopy of solids can often be obscured by spectral background contributions from a large number of other electron emission events (described below) in the near-surface region of the sample, making peak area determination difficult. Some of these are shown schematically in Figure 2. Both Auger and photoelectrons may lose energy at the emission site—an intrinsic energy loss process seen mainly in free electron metals—because of the relaxation of conducting electrons accompanying photoemission. It is also possible that
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472 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
they lose energy away from the emission site, before escaping the solid—an extrinsic energy loss process. This energy loss is attributable to energy exchange between the emitted electron and the population of conducting electrons in the near-surface region of the solid {21). This last process includes the so-called plasmon loss processes that actually lead to new peaks, displaced up to 40 eV below the kinetic energy of the parent Auger or photoelectron peak (most pronounced for metal systems). All of these energy losses are the factors that limit the sampling depth of XPS or AES in solids (13). The spectral background in AES arises from the following: • electrons originally at the kinetic energy of the source (typically 2000-5000 eV) that have been scattered from surface and subsurface atoms and lost energy in the process, • electrons arising from Auger emission events of higher kinetic energy than for the element of interest, • asymmetry in the spectral line shape (to the low kinetic energy side of the peak) because of the aforementioned "intrinsic" energy loss processes at the point of origin of the Auger electron in the solid, and • "extrinsic" energy loss processes that arise from scattering events occurring between the subsurface point of origin of the electron and the solidvacuum interface (29,30). For the first two processes, the population of scattered electrons builds exponentially to lower kinetic energies, resulting in a "secondary cascade" on which the Auger electrons are superimposed (30). The analytically relevant data may easily be less than 1% of the total secondary emission from the sample. This fact is one of the principal reasons why the detection limit for most elements using this technique is not better than 1 part per thousand. Because Auger events produce an electron whose kinetic energy is independent of the source energy, the spectral properties of the electron beam or Xray source that create the Auger electron do not enter into the final spectrum. The resolution and transmission efficiency of the analyzer and the energy-dependent response of the detector, however, do play a role in determining the spectral shapes and relative intensities for AES data. These complications are so extreme that for years AES was exclusively conducted using electrostatic analyzers whose pass energies were modulated, and Auger spectra were only presented in first-derivative form, after lock-in amplifier demodulation. The pitfalls of this approach to
INSTRUMENTATION quantitation are well documented (610,22,23). For XPS, the spectral background is still a problem but is generally lower in intensity. The principal origins of this background are electrons from photoemission events of higher kinetic ener gy than the one of interest, which con tribute to the cascade of secondary electrons; Bremsstrahlung emission from the X-ray source, which creates a continuum of photoelectron emission from the sample (largely missing when monochromatic X-ray sources are used); and the same extrinsic energy losses described above for Auger elec trons. In XPS, the asymmetry of the Xray source can contribute slightly to the final spectral line shape (a few per cent asymmetry is introduced into the peak shapes) and can be accounted for if it is considered important (31,32). As in AES, the resolution and transmis sion efficiency of the analyzer play a role in the signal-to-background ratios as well as the spectral line shapes and relative intensities of each spectral peak of interest.
tensities of derivative peaks, can be di rectly measured. This often requires the use of much smaller beam currents (so as not to saturate the electron mul tiplier detector) and, as a bonus, elec tron beam damage problems in AES can be made less severe. Methods for correct peak area mea surements in AES and XPS are sum marized in the panels of Figure 4, where the major Auger and photoelec tron transitions for a well-character ized material, SnS2, are taken through a series of modifications to the final, corrected (ready-for-quantitation) form (28). SnS2 is one member of a family of transition metal dichalcogenides (Table I has more examples) that appear to provide good standards with which to test the various AES and XPS data treatment procedures now under development. These materials are van der Waals solids and layered structures and are readily cleaved to produce ho mogeneous, stoichiometric, chemically inert (and therefore almost always con
taminant-free) surfaces (34-36). The Sn(MNN) and S(LMM) Auger transitions cover a wide kinetic energy range and are distorted by all of the spectrometer and sample-related ener gy loss processes described above. Step 1 in Figure 4a calls for the removal of the kinetic energy dependence of ana lyzer transmission efficiency. This would seem to be a trivial step at first, but it has proved to be complicated in many instances. The present generation of hemi spherical electron energy analyzers, with their associated electrostatic col lection lenses (1), can generally operate in a constant pass energy mode (AE = constant, normally used for XPS) or a constant relative resolution mode (ΔΕ/ Ε = constant, normally used for AES) that yields different analyzer transmis sion efficiencies as a function of elec tron kinetic energy (5-10). It is neces sary to know exactly how this transmis sion efficiency varies in order to properly correct the data in that first
Determination of the analytically relevant Auger or photoelectron intensity In AES, the practice of presenting and analyzing spectral data in the first-de rivative mode is still widespread for qualitative and semiquantitative anal ysis. Examples of this are shown in Fig ure 3 for Auger spectra of Sn in a SnC>2 thin film and as a component in an in dium-tin oxide thin film. (Similar and more detailed examples are available in Reference 22.) The peak-to-peak in tensity of the Sn, 0 , and In Auger sig nals is related to the actual peak areas for these spectra, but it also contains contributions attributable to the sec ondary electron background, separate energy loss peaks, and the analyzer transmission efficiency and detector efficiency functions. In addition, the Auger signal in the spectrum of the in dium-tin oxide thin film appears to be well resolved—an artifact of the modu lation/demodulation process that pro duced these derivative mode peaks. The actual Sn concentration is less than is apparent from the peak-topeak intensity in that spectrum (22). Substantial line shape changes are observed in these spectra as the oxida tion states of the metals change, mak ing the use of these derivative mode data in Equation 2 or 3 even less desir able (6,22, 33). All of the recently pro duced commercial spectrometers ac quire data for both AES and XPS using electron-counting techniques. For elec tron beam excited Auger spectra, this means that peak areas, rather than in
Figure 3. Auger spectra of Sn in (a) Sn02 thin film and (b) as a component in an indium-tin oxide thin film.
474 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
INSTRUMENTATION step. In the constant AE mode, the image of electron emission from the sample must completely fill the entrance slit of the analyzer at all energies to ensure a constant transmission efficiency function. Many surface analysts are still not aware of this problem. The situation is further complicated because many instrument manufacturers find it difficult to fully characterize their analyzer systems, especially in the constant pass energy mode of operation. Needed improvements in this critical area are anticipated. Alternatively, during operation in the AE/E = constant mode for both AES and XPS, the analyzer transmission efficiency generally is directly proportional to the kinetic energy of the detected electron over a wide kinetic energy range and is most useful for quantitative purposes. The spectral intensities need only be divided by kinetic energy to obtain the corrected form. Upon correction for transmission efficiency, the data are left superimposed on a secondary electron cascade arising principally from electron sources at higher kinetic energies. Step 2 removes the contributions of higher kinetic energy electrons to the cascade background by a simple linearization of the log-log form of the data and subtraction (22, 30). At this point the Auger spectrum represents the actual peak of interest, all of the peaks caused by discrete energy losses, and the large background attributable to Auger electrons, which lost appreciable energy on the way out of the solid and no longer appear as a peak of any sort (see Figure 2). In Figure 4b we pick up the two XPS peaks after having already carried out Steps 1 and 2 (not shown, although similar manipulations are necessary). How to proceed at this point becomes a question of the level of accuracy desired by the analyst versus the computational time and effort expended to obtain that accuracy. The simplest option is to use either a straight line or a polynomial fitted function to describe the background (37, 38). Neither of these approaches gives a physically realistic result, and they may introduce considerable error in the final spectrum. An alternate approach is to assume that the background beneath the peak at any kinetic energy is simply proportional to the scaled sum of intensities from spectral data at higher kinetic energies (integral background method) (39). This approach is simple, more accurate than the first methods, and available in virtually all of the software packages supplied with XPS systems. However, it still leaves some energy
Figure 4. Methods for correction of peak area measurements in (a) AES and (b) XPS. loss contributions in the spectrum that should be removed, and it may overcorrect for energy losses near the major spectral peaks (21, 25, 26). More sophisticated approaches involve deconvolution methods that correct the background, remove energy loss peaks, and can also enhance resolution and reduce noise (23, 24, 31, 32). A separate experiment is necessary, as shown in Step 3, Figure 4. An electron beam is reflected off of the sample at the kinetic energy of the spectral peak of interest to create an electron energy loss spectrum (EELS). The energy of this electron beam is too low to cause Auger emission in the vicinity of either the AES or XPS peaks. One obtains a large peak at Ea, represented by electrons elastically scattered (without energy loss) from the sample, and resolved peaks and a background arising from electrons originally at E0, which penetrated the subsurface region, were scattered with loss of energy and then escaped the solid. The portion of the spectrum away from the peak at EQ can be used to model the energy losses experienced by Auger or X-ray photoelectrons generated in this same subsurface region. The EELS data also experience the same analyzer broadening as the XPS or AES spectra. Thus we often call the EELS data a sample instrument re-
476 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
sponse function (SIRF), because most of the information not of interest for quantitation, arising from both the sample and the instrument, is contained in these data. The data seen at Step 3 of Figure 4 can be described to a first approximation as a convolution of the SIRF and the desired spectrum. Iterative or Fourier domain deconvolution procedures can then be applied, although the Fourier domain method is often favored for its speed, flexibility, and noise suppression characteristics (24). One can take advantage of the fact that convolved functions in a data (time or energy) domain (i.e., the data of Figure 4, Step 4, (g(x)) and the EELS (f(x)) can be deconvolved by Fourier transformation of both functions, FFT
g ( x ) ® f ( x ) - » G ( X ) X F ( X ) (7) followed by division of the data function with the EELS function in the Fourier domain and then an inverse transform back to the data domain (Equations 7, 8, and 9). n m
_G(X)XF(X)
G(X)
Fffl
(8)
FFT - 1
G(X) -* g(x) (9) This type of approach is similar to what one can use to treat most forms of
INSTRUMENTATION spectroscopic data (UV-vis, FT-IR, NMR, etc.), mainly for resolution en hancement (40-42). In this case, how ever, we measure the instrument re sponse (similar in some respects to the slit function in optical spectroscopies) rather than guess or model it. The final forms of the Auger and XPS data are shown in Figure 4, Step 5. Resolution enhancement is slight for the Auger data because the Auger emission pro cess inherently leads to broad spectral peaks. Certain precautions must be taken with the EELS data when decon volving X P S spectra, because the fwhm of the electron beam may be comparable to the fwhm of a photoelectron peak. The asymmetry in energy of the electron beam may also need to be accounted for, because its shape will be reflected in the final form of the XPS data. These corrections can be readily incorporated into the data reduction scheme just described. For quantita tion purposes, however, the data are now in a form whereby reliable peak areas can be measured. Determination of relative atomic ratios or atomic percentages in homogeneous solids After each spectral peak has been treated in one of the ways described above, the computation of the atomic percentage of a particular element be comes straightforward, provided one of the above equations (Equations 2, 3, or 6) can be used. Table I shows how good the agreement can be between expect ed compositions and those actually de termined for many metal oxides, metal sulfides, and sulfur oxyanion salts. These may seem at first like trivial ana lytical situations, but determinations like these have actually been a chal lenge for the surface analysis commu nity. To date, little trace (i.e., part-perthousand) analysis has been attempted using any of the data treatment proce dures described. Many real-world sur face analytical problems, however, in volve high elemental concentrations, albeit in a small near-surface region. To date, concentration determina tions have been difficult when the spec tral peaks are closely spaced (less than 5 eV) and background adjustments are difficult, when the spectral peaks are widely spaced in kinetic energy (i.e., greater than 500 eV) so that inaccura cies in the estimates for Τ and D are not canceled completely, when the sample has a large contaminant overlayer whose thickness is unknown, or when the sample is not truly homogeneous throughout the sampling depth. One very interesting and relevant case, not involving homogeneous sol-
ids, is the characterization of a solid with a thin overlayer. The overlayer thickness is typically greater than monolayer but less than the total sampling depth of the electron spectro scopic technique (e.g., a thin oxide lay er over a metal or semiconductor, Figure 2c) (6-10,21). As device dimen sions shrink in materials used in micro electronics, information storage, and other technologies, this problem is en countered with increasing frequency. One generally wishes to obtain an esti mate of the overlayer thickness, the concentration of all elements within the overlayer and their oxidation states, and the concentration and oxi dation states of all elements in the sub strate material. AES can be used in this type of analysis, but XPS, with its higher spectral resolution, is ultimately more useful if the overlayer contains the same elements as the substrate, but in different oxidation states (as in ox ide overlayers). The direct deconvolution approach es described above are not always ap plicable to this kind of characteriza tion. A combination of deconvolution and spectral fitting is more useful to fully analyze the XPS spectra from the overlayer and the substrate (21, 26). Careful attention to the shape of the background for a spectral peak from the substrate material can provide use ful information about the overlayer thickness and about whether the overlayer is continuous or has formed in isolated islands (43-45). This kind of overlayer analysis, combined with sputter/depth profiling techniques, is complementary to Rutherford back-
scattering spectrometry, which has a lower thickness limit for characteriza tion of most overlayers of approximate ly 100 À (46). Future prospects Will surface spectroscopies ever lend themselves to absolute concentration determinations? Probably not in the near future. However, the questions to be answered by the surface analyst rarely require that degree of rigor. We probably can look forward to a wider variety of "routine" matrix correction factors and iterative approaches to concentration determinations, as were developed early on for X-ray fluorescence analysis of solids (17,47,48). Because of the extremely small sampling depths involved, the analyst will always have to be attentive to factors that are ignored by the user of spectroscopic probes with larger sampling depths. An encouraging sign is the continued interest in this area (e.g., research carried out by the National Institute of Standards and Technology, formerly the National Bureau of Standards, and activities of the ASTM E-42 committee as well as research being done at the National Physical Laboratories in the United Kingdom and in other organizations in Europe). Using well-characterized materials against which to test data treatment methodologies, we expect that the capabilities for quantitative analysis of most vacuum-compatible solids with Auger spectroscopy and XPS will rapidly improve. Much of the research reported here was supported by grants from the National Science Foundation, Department of Energy—Sandia National Labora-
Table 1. Relative atomic ratios from AES and XPS: Examination of materials with known composition Materials (technique)
Expected stoichiometry
Metal alloys, oxides, and sulfur oxyanion salts O/Ti = 2.0 Ti0 2 (AES) Si0 2 (AES) O/Si = 2.0 Na2S04 (AES) O/S = 4.0 O/S = 3.0 Na2S03 (AES) O/S = 1.5 Na2S203 (AES) O/S = 2.0 Na2S204 (AES) Metal sulfides SnS2 (XPS)3 SnS2 (AES)6 MoS2 (XPS)° WTe2 (XPS) WSe2 (XPS)
S/Sn S/Sn S/Mo Te/W Se/W
=2.0 =2.0 = 2.0 = 2.0 = 2.0
" Average based on 11 trialsSip/Sn^ peaks. " Average based on 5 trials, S (LMM)/Sn (MNN). c Average based on 4 trials.
478 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
Determined stoichiometry
Ref.
1.9 2.08 3.9 3.1 1.3 2.7
23 27 24 24 24 24
1.93 1.95 1.80 1.83 2.07
28 28 28 28 28
INSTRUMENTATION tories, and the Optical Data Storage Center and the Materials Characterization Program at the University of Arizona. Many of the metal dichalcogenide samples used in our studies were a gift from Bruce Parkinson, Du Pont. References
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Circle 42 for literature. Circle 43 to have a representative call. 480 A · ANALYTICAL CHEMISTRY, VOL. 61, NO. 7, APRIL 1, 1989
(1) Gardella, J. Anal. Chem., in press. (2) Hercules, D. M. Anal. Chem. 1978, 50, 743 A. (3) Fay, M. J.; Proctor, Α.; Hoffman, D. P.; Hercules, D. M. Anal. Chem. 1988, 60, 1225 A. (4) Abruna, H. D.; White, J. H.; Albarelli, M. J.; Bommarito, G. M.; Bedzyk, M. J.; McMillan, M. J. Phys. Chem. 1988, 92, 7045. (5) Powell, C. J.; Seah, M. P. Surf. Inter face Anal. 1986,9, 79. (6) Seah, M. P. In Practical Surface Analy sis by Auger and X-ray Photoelectron Spectroscopy; Briggs, D.; Seah, M. P., Eds.; John Wiley and Sons: New York, 1983, pp. 181-216. (7) Seah, M. P. J. Vac. Sci. Technol. A, 1985 3 1330 (8) Seâh,'M. P.' Vacuum 1986,36,399. (9) Powell, C. J. Surf. Interface Anal. 1988, 11,103. (10) Grant, J. T.; Williams, P.; Fine, J.; Powell, C. J. Surf. Interface Anal., in press. (11) Gryzinski, M. Phys. Rev. 1965, 138, A366. (12) Ichimura, S.; Shimuza, R. Surf. Sci. 1981,112, 386; 1983,124, L49. (13) Penn, D. J. Electron Spectroscopy and Related Phenomena 1976,9, 29. (14) Tanuma, S.; Powell, C. J.; Penn, D. Surf. Sci. 1987,192, L849. (15) Seah, M. P.; Dench, W. A. Surf. Interface Anal. 1979,1,2. (16) Schoeffel, J. Α.; Hubbard, A. T. Anal. Chem. 1977,49,2330. (17) Hall, P. M.; Morabito, J. M. Surf. Sci. 1979 83 391 (18) Davis, L. È.; MacDonald, N. C; Palmburg, P. W.; Reach, G. E.; Weber, P. E. Handbook of Auger Electron Spectroscopy; Perkin-Elmer Corp.: Eden Prairie, MN, 1976. (19) Scofield, J. H. J. Electron Spectroscopy and Related Phenomena 1976,8,129. (20) Wagner, C. D. In Quantitative Surface Analysis of Materials; Mclntyre, N. S., Ed.; American Society for Testing and Materials: Philadelphia, PA, 1978; ASTM STP 643, p. 31. (21) Maschhoff, B. L.; Nebesny, K. W.; Zavadil, K. R.; Fordemwalt, J. W.; Armstrong, N. R. Spectrochim. Acta, Part Β 1988,43B, 535. (22) Burrell, M. C; Kaller, R. C.; Arm strong, N. R. Anal. Chem. 1982,54, 2511. (23) Burrell, M. C.; Armstrong, N. R. Appl. Surf. Sci. 1973,17,53. (24) Nebesny, K. W.; Armstrong, N. R. J. Electron Spectroscopy and Related Phe nomena 1986,37,355. (25) Maschhoff, B. L.; Zavadil, K. R; Ne besny, K. W.; Armstrong, N. R. J. Vac. Sci. Technol. 1988, A6, 907. (26) Maschhoff, B. L., Ph.D. Dissertation, University of Arizona, 1988. (27) Burrow, B. J.; Armstrong, N. R.; Bun ker, B.; Quinn, R. K.; Salmi, D. Appl. Surf. Sci. 1984,20,167. (28) Nebesny, K. W.; Armstrong, N. R., submitted for publication in J. Vac. Sci. Technol. (29) Tougaard, S.; Sigmund, P. Phys. Rev. Β 1982,25,4452. (30) Sickafus, Ε. Ν. Surf. Sci. 1980, 100, 529. (31) Hawn, D. D.; DeKoven, B. M. Surf.
Interface Anal. 1987,10,63. (32)- Koenig, M. F.; Grant, J. T. J. Electron Spectroscopy and Related Phenomena 1984 33 9 (33) Seah.'M. P.; Holbourn, M. W. J. Elec tron Spectroscopy and Related Phenom ena 1987,42,255. (34) Stickney, J. J.; Rosasco, S. I >.; Schardt, B. C; Solomon, T.; Hubbard, A. T.; Par kinson, Β. A. Surf. Sci. 1984,136,15. (35) Sarid, D.; Henson, T. D.; Armstrong, N. R.; Bell, L. S. Appl. Phys. Lett. 1988, 52, 2252. (36) Tributsch, H. Structure and Bonding; 1982,49,128. (37) Proctor, Α.; Hercules, D. H. Appl. Spectrosc. 1984,30,505. (38) Sherwood, P.M.A. In Practical Sur face Analysis; Biggs, D.; Seah, M. P., Eds.; John Wiley and Sons: New York, 1983, pp. 445-76. (39) Shirley, D. A. Phys. Rev. Β 1972, 5, 4709. (40) Brigham, E. O. The Fast Fourier Transform; Prentice Hall: New Jersey, 1974. (41) Horlick, G. Anal. Chem. 1972,44,943. (42) Lam, R. B.; Wiebolt, R. C; Isenhour, T. L. Anal. Chem. 1981,53,887 A. (43) Tougaard, S. Surf. Interf. Anal. 1986, 8 257 (44) Tougaard, S. J. Vac. Sci. Technol. 1987, A5,1230,1275. (45) Tougaard, S. Appl. Surf. Sci., in press. (46) Chu, W. K.; Mayer, J. W.; Nicolet, M.-A. Backscattering Spectrometry; Ac ademic Press: New York, 1974. (47) Beamen, D. R.; Isai, J. A. Electron Beam Microanalysis; American Society for Testing and Materials: Philadelphia, 1972; ASTM STP 506. (48) Heinrich, K.F.J. Anal. Chem. 1972,44, 350.
Kenneth W. Nebesny (left) received his B.A. degree in chemistry from Queens College, City University of New York, and his Ph.D. in analytical chemistry from the University of Arizona in 1984. Currently he is the research specialist in surface science in the Department of Chemistry, University of Arizona. His research interests include quantitative surface analysis, surface crystallogra phy, and new methods for deposition of novel thin-film materials. Brian L. Maschhoff (center) received his B.S. degree in chemistry from the University of New Mexico in 1981 and his Ph.D. in analytical chemistry from the University of Arizona in 1988. In addition, he spent two years at Los Alamos National Laboratories. He is now a postdoctoral fellow at Rutgers University. Neal R. Armstrong (right) received his Ph.D. from the University of New Mexico in 1974 after completing graduate research at Sandia National Labora tories. Following a postdoctoral fellowship at Ohio State University and a faculty appointment at Michigan State University, he joined the faculty at the University of Arizona, where he is professor and head of chemistry. His interests are in the areas of surface chemistries and electrochemistries of active metals, development of quantitative surface analysis methodologies, and the develop ment and characterization of new molecular electronic materials for photoelectrochemical, chemical sensor, and nonlinear optical applications.
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