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LITERATURE CITED (1) Binnlg, G.; Rohrer. H. He&. phys. Acta 1982, 55, 726. (2) Bhnlg, G.;Quete, C.; Qerber, C. phys. Rev. Lett. 1988, 56, 930. (3) HeIlSIlla, P. K.: Drake, 8.: Merti, 0.; Oould, S. N. C.; Prater, C. B. Science 1989, 243, 641 and references therein to other types of scanning microscopes.
(4) Bard, A. J.: Fan, F.4. F.; Kwak, J.; Lev, 0. Anel. C t ” . 132.
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(5) Bard, A. J.: Denuauit. G.; Lee, C.; Mandier, D.; Wipf, D. 0. ACC. Chem. Res. 1990, 23, 357. (6) Kwak, J.; Bard, A. J. Anal. Chem. 1989, 61, 1794. (7) Lee, C.: Bard, A. J. Anal. Chem. 1990, 62, 1906. (8) Lee, C.: Miller. C. J.; Bard, A. J. Anal. Chem. 1991, 63, 78. (9) Kwak, J.; Lee, C.: Bard, A. J. J . Electrochem. Soc. 1990, 137, 1481. (10) Lee, C.: Kwak, J.; Bard, A. J. Roc. Natl. Acad. Scl. U . S . A . 1990, 87. 1740. (11)~nistrom,R. c.; ~ e a n e y T.: , TOW, R.; Wightman, R. M. AMI. c h m . 1987, 59, 2005. (12) Engstrom. R. C.; Weber, M.; Wunder, D. J.; Burgess, R.; Winquist, S. Anal. Cham. 1988, 58, 844. (13) Scott, E. R.; White, H. S.; Phipps, J. B. J . Membr. Scl. 1991, 58, 71.
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(14) Kwak. J.: Bard. A. J. Anal. Chem. 1989. 61. 1221. Andrews; H. C;; Hunt, B. R. @?it81 Ima& Restoration: Prentice-Hall: Englewoods Cliffs. NJ, 1977. Rosenfeld, A.; Kak, A. C. D@talplctve Rocesslng, 2nd Ed.; Academ ICPress: New York. 1982;Vol. 1. Marr, D. Vlsbn: W. H. Freeman and Co.: New York. 1982.
Barteis, K.; Bovik, A. C.; Lee, C.; Bard, A. J. Proceedings of the SPIEISPSE Symposium on Electronic Imaghg Science and Technology, San Jose, California, Feb 24 to March 1, 1991. Wipf, D. 0.; Bard, A. J. J . Electrochem. SOC.1991, 138, 469. Wipf, D. 0.; Bard, A. J. J . Electrochem. Soc.1991, 138, L4. Gewirth, A. A.; Craston, D. H.; Bard, A. J. J . Electroanel. Chem. Interfeciel. Electrochem. 1989, 67, 1630. Penner, R. M.; Heben, M. J.; Lewis, N. S. Ana/. Chem. 1989, 61,
1630.
RECEIVED for review May 20,1991. Accepted August 12,1991. We gratefully acknowledge the support of the study by the National Science Foundation (Grant CHE8901450) and the Texas Advanced Research Program.
Quantitative Surface Analysis of Organic Polymer Blends Using a Time-of-Flight Static Secondary Ion Mass Spectrometer Patrick M. Thompson Surface Science Section, Research Laboratories, Eastman Kodak Company, Rochester, New York 14650-2132
The surface composition of organic polymer blends can be determined using X-ray photoelectron spectroscopy (XPS) provided that each component in the blend has a unique ekment or tunctlonai group present. However, for Mends not amenable to XPS, a relatively new technique with greater molecular specificity called static secondary ion mass spectrometry (SSIMS) holds the potential for determining the degree of surface segregation. Although SSIMS is generally considered to be a semiquantitative technique at best, arguments will be presented along with results showing that energy-focusing timesf-flight (TOF) mass spectrometers can overcome some of the possible instrumental artifacts associated with polymer surface analysis done by quadrupole SSIMS and that the SIMS matrix effect is not necessarily a major problem when organic polymer blends are analyzed. I n this study, the surface compositions of an immiscible and a miscible pdycarbonate/polystyreneblend were determined by TOF SIMS and XPS and these results were compared. The results for these two blends suggest that the accuracy for both TOF SSIMS and XPS can be within f0.1 monomer fraction, w h b the typlcai precision of the TOF SSIMS results were primarily determined by counting statistics and were generally better than those from XPS.
INTRODUCTION The application of static secondary ion mass spectrometry (SSIMS) toward the qualitative analysis of inorganic and organic surfaces has been well documented (1-6). Success has been achieved with SSIMS as a semiquantitative or quantitative technique for organic surface analysis when calibrated by an independent technique such as X-ray photoelectron spectroscopy (7, 8). Briggs et al. have shown that SSIMS alone can do semiquantitative if not quantitative surface analysis on random 0003-2700/91/0363-2447$02.50/0
copolymers of ethyl methacrylate/ hydroxyethylmethacrylate, thus showing the potential for its use on other random copolymers (9). In random copolymers the surface composition should be similar to that of the bulk, therefore only a set of known bulk composition standards would be required to calibrate the SSIMS results. In a study reported by Bhatia et al., XPS was used to calibrate static SIMS measurements made on a miscible blend of polystyrene and poly(viny1methyl ether) (10).In that paper a sensitivity factor was calculated using XPS results which related the molar concentration of constituents to appropriate ion intensity ratios. This sensitivity factor was assumed to be independent of blend composition. These results suggested that matrix effects may be negligible in certain cases of miscible polymer blends. In this paper a quantitative analysis scheme is proposed which uses the advantages of an energy-focusingtime-of-flight mass spectrometer for determining the surface composition of miscible and immiscible organic polymer blends without necessarily requiring calibration by other surface-sensitive techniques. Similarly to Bhatia et al., this analysis scheme assumes that matrix effects are independent of the blend composition (10).In this paper some consideration is given to how matrix effects can effect the observed results depending on the type of instrument used and why they may be relatively independent of organic polymer blend composition. Most methods proposed for SSIMS semiquantificationand quantification involve comparisons of intensities of appropriately selected mass peaks, usually through a procedure involving their relative peak intensities (RPIs). In the simplest case, such as a two-component polymer blend, a RPI could be obtained between two different mass peaks, each primarily composed of a fragment ion or ions of the same nominal mass that uniquely represent one of the two polymers. By production of a series of blend compositions, a plot of the bulk composition versus RPI could be made. This plot would have 0 1991 American Chemical Society
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limited utility however, because the bulk composition seldom reflects the surface composition in organic polymer blends. In addition, major changea in the degree of surface segregation can be made by changing the polymer-processingconditions (i.e., different solvents, drying conditions, curing conditions, molecular weights of the polymer components, etc.). To improve the quantification, an established method of surface analysis, such as X-ray photoelectron spectroscopy (XPS), could be used to independently determine the surface composition of the blend. It has been demonstrated that the surface sensitivity of glancing-angle XPS is close to that of SSIMS (top 2 nm of surface) (7,11). By plotting appropriate RPIs versus the surface compositions determined by glancing-angle XPS,one obtaines a standard curve that can be used to establish the surface composition for this polymer blend system that should be independent of any processing conditions. Unfortunately, XPS has certain limitations, such as the requirement for each component in the blend to have a unique element or functional group present. For example, XPS can easily distinguish between a blend composed of a simple polyester and polyurethane based on the atomic percent of oxygen and nitrogen at the surface or the relative amounts of ester carbon functionality and urethane carbon functionality at the surface. With this hypothetical polymer blend, these XPS results could be compared for internal consistency. However, when the blend is composed of two similar polymers such as poly(methy1methacrylate) and poly(ethy1acrylate), there are no XPS-distinct elements or functionalities present to separate the two components and, thus, the XPS technique would fail. SSIMS, however, does have the specificity to separate these two polymers based upon the unique secondary ions emitted. In this type of case the SSIMS results would have to “stand alone” in order to establish the surface composition of the blend. Stand-alone quantitative SSIMS analysis of inorganic and organic surfaces is difficult for many reasons; however, only the three most important will be discussed here. The first involves the well-known and often strong matrix effect, where the secondary ion yield for the same secondary ion can vary over several orders of magnitude depending upon the chemical bonding and type of environment with which the presecondary ion was associated. Unfortunately, methods developed to minimize this matrix effect in dynamic SIMS analyses (Le. the production of similar composition standards, by generating an internal standard through ion-implantation technology, etc.) do not usually apply in the case of SSIMS. This matrix effect can also change the secondary ion energy distribution for a given ion (12,13); with potentially important consequences to be discussed later. Atomic secondary ion energy distributions are generally broad with the maximum in the distributions typically between 5 and 15 eV, but it can be anywhere from near 0 out to -50 eV. The high-energy tail of this energy distribution can extend out to the energy of the primary ion beam. In general, atomic secondary ions have broader energy distributions than molecular secondary ions. Molecular secondary ions have the maximum in their energy distributions that are typically between 0 and 10 eV, a width of a few electronvolts, and a shorter high-energy tail than atomic ions. Unfortunately, very little can be done at this time to minimize the matrix effects in SIMS unless some type of positionization scheme is employed. (At this time, most positionization methods are not suitable for obtaining quantitative information on organic systems because they induce further fragmentation.) A second problem involves instrument specific artifacts. For example, in a quadrupole-based SSIMS (QSSIMS) instru-
ment, which is probably the most common type, the relative intensities obtained for the various mass peaks in a spectrum are dependent on how the instrument is “tuned up” for each sample analyzed. This mainly results from the ion-energy requirements of the quadrupole mass filter, which can only effectively mass separate secondary ions with fairly low energies (C15 eV). Therefore, because of the inherently broad secondary ion energy distributions, some type of secondary ion optical column incorporating an electrostatic energy analyzer or “prefilter” (i.e., parallel plates, hemispherical or spherical sector analyzers, cylindrical mirror analyzer, etc.) must be utilized in order to transfer the correct energy secondary ions from the sample into the entrance of the quadrupole mass filter. In QSSIMS instruments, these ion optics have fairly well defined transmission characteristics, with the incorporated prefilter functioningas an Y e n e wwindow“ with a typical ion pass energy centered between 5 and 15 eV and a typical width in the range 2-5 eV. The “band-pass” of a prefilter is the energy range over which secondary ions will be transmitted through the prefilter and is equal to the pass energy f (widthl2). There are at least two common methods employed to “tuneup” a QSSIMS instrument. The first involves tuning-up on a single mlz peak. In this method the maximum in the secondary ion energy distribution for a selected secondary ion is “moved” onto the pass energy of the prefilter by electrically biasing the sample. This should maximize transmission through the ion optics and, ultimately, maximize the detected signal for that ion. The second method uses the quadrupole in the rf-only mode, which allows all ions to pass through the QMS instrument without mass filtering. This gives a total ion signal which is maximized in an analogous manner as the single-ion optimization described above. In general, any method of tuneup used requires some retuning of the lenses in the ion optics, and there is no guarantee that the maximized signal is the global maximum for all of the potential instrument variables. When the QSSIMS instrument is tuned, the signals from the other secondaqyions are usually not at a maximum because of their different secondary ion energy distributions. Even small energy shifts in the energy distribution can move portions of the secondary-ion energy distributions in or out of the band-pass of the prefilter. Thus, as the composition of the binary blend changes, the actual matrix effect may not be large, but it may have a significant effect on the RPIs obtained. Even if the RPIs are reproducible for each sample analyzed in a QSSIMS, this RPI may not be equal to the RPI obtained if the measured ion intensities better represented their total secondary ion energy distributions, and not just the portions allowed through the prefilter. The analytical method to be described in this paper requires having RPIs which are reproducible and represent the total secondary ion energy distributions or have secondary ion energy dBtributions which are not affected by the sample matrix for the chosen ions. How usable the RPIs obtained on a QSSIMS instrument are depends on how insensitive the secondary ion energy distributions are to the matrix, the widths of the secondary ion energy distributions of the chosen ions, and the width of the energy window of the prefilter. Small matrix effects, narrow secondary ion energy distributions, and a wide energy window will produce more usable RPIs. The final problem to be considered is sample charging. Many samples that are analyzed are not conductive. Without some type of “charge compensation”, the ion signal obtained from insulators on a QSSIMS instrument is very low, due to the secondary ion energy distribution being shifted far outside
ANALYTICAL CHEMISTRY, VOL. 63, NO. 21, NOVEMBER 1, 1991
of the band-pass of the prefilter. The most common method employed to minimize the effects of charging is the use of an electron flood gun. The flood gun is used to focus electrons having a few hundred electronvolts of energy onto or near the sample in order to reduce the primary ion beam induced positive charge. For “tuning-up” on nonconductive samples, an iterative technique is used, where the current, location, and perhaps electron energy of the flood gun is adjusted while the primary ion beam location and current is held constant in order to maximize the desired secondary ion signal. Maximizing the secondary ion signal results from moving the maximum in the secondary ion energy distribution of the chosen secondary ion or, if the QMS is used in the rf-only mode, the maximum of the convoluted secondary ion energy distributions back onto the pass energy of the prefilter. Ideally, this charge compensation would lead to a uniform and stable potential on the surface of the sample. However, differential sample charging, where different areas of the sampled area have slightly different levels of charge, and any drift in the ion-gun and electron-gun supplies could change the intensity of the detected signal or move the secondary ion energy distributions relative to the energy window of the prefilter. Considering the above, it can be seen why a standard QSSIMS instrument is not necessarily a good candidate for potential quantitative surface studies. Some QSSIMS systems now have the ability to scan the sample potential while doing data acquisition. This scanning of the sample potential helps to minimize the possible changes in RPIs discussed earlier. This procedure does not necessarily correct the problem entirely, however, because the secondary ion transmission may not be constant over the energy range scanned and there will usually be loss of ion intensity as the ion energy exceeds some value primarily determined by the characteristics of the secondary ion transfer optics. A potentially better choice of instrument for quantitative studies on insulators would be a double-focusing mass-spectrometer-based system because it can accept a larger spread (- 100 eV) of ion energies than a quadrupole. Thus, minimizing any problems associated with changes in the secondary ion energy distributions. When operating with a large energy window, the double-focusinginstrument will suffer some loss in its mass resolution, but it would still be better than a QSSIMS system. However, charge compensation of insulating samples is still a problem because the samples are normally held at a constant high voltage of several kiloelectronvolts during the entire analysis. This requires the electron gun used for charge compensation to be biased at an appropriate potential in order to have the correct quantity and energy of charge-compensating electrons at the proper location on the sample surface. Another instrument that can accept a large range of ion energies while allowing for sufficient charge compensation is the energy-focusing time-of-flight (TOF) mass spectrometer. There are two principal types of energy-focusing instruments: the reflectron (14)and the Poschenrieder (15) design. Both instruments can accept ions with energies up to a few hundred electronvolts, with the Poschenrieder type excepting a slightly larger energy spread than the reflectron instrument. This virtually minimizes the problems associated with shifting secondary ion energy distributions because typically more than 95% of the molecular secondary ion emitted have energies less than 100 eV. The problems associated with charge compensation are minimized through the use of a pulsed lowenergy electron flood gun in a method pioneered by Benninghoven’s group (16),where a self-compensatingsample charge is maintained during the analysis. Even if the remaining local charge on the sample is nonzero, because of incomplete charge
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compensation or differential charging, the detected signal is virtually unchanged because of the energy acceptance of these TOF analyzers. Now, what can be easily done to minimize the matrix effect? Perhaps not much at this time. However, there is a large class of very important materials for which the matrix effects appear be small. This class is composed of organic polymer blends. These can be broken down into at least two general cases for quantitative TOF SSIMS analyses. The first case, and probably most common, would be a blend of two immiscible polymers where phase separation would occur with separate phase domains of 0.l-lO-Nm diameter in the bulk material. The surface of the immiscible blend could be composed entirely of one of the two components; therefore, no matrix effect should be observed. It is possible that there could be changes in the secondary ion yield of some fragments if the emission processes are sensitive to the surface orientation of the polymer resulting from different crystallinity or hydrogen bonding, etc. However, it may be possible to choose appropriate secondary ions that are insensitive to these secondary effects. Immiscible blends could also have the surface composed of separate domains of each component with an unknown size distribution. If the domain areas are large, compared to the boundary areas, there may be an insignificant contribution from matrix effects. A case will be made shortly where the expected matrix effect at the boundary areas may be negligible also. The second general case is that of a miscible polymer blend. In a thermodynamically equilibrated miscible polymer blend the material with the lowest surface energy will be the major component at an uncontaminated surface. The amount of the other blend constituents at the surface, to a first approximation, would depend on the balance between the lowest surface energy component and the entropy of mixing. The thickness of these segregated layers varies from case to case. Angle-resolved XPS has shown that the change from surface to bulk composition occurs within the upper 10 nm of the surface in many cases. In other cases the change is more gradual. In real samples, produced under nonequilibrium conditions, the actual surface compositionsseldom reflect the equilibrium case. In miscible polymer blends, matrix effects would be expected to be more important because of the interactions between groups on the different neighboring chains. It is suggested that the matrix effect in miscible polymer blends may be small because of the “general” elemental and chemical similarities in organic polymers. To introduce this idea, some of the major properties affecting secondary ion desorption yields in organic and inorganic systems will be compared in a brief discussion. From polymer to polymer, the energy required to break one bond (typically 3-5 eV), but more usually two bonds (6-10 eV), desorb (- 1eV), and ionize (6-13 eV typical) the same organic fragment will likely vary. Any variations in this energy result primarily from the electronic environment at or near the bond to be broken. As an example, the energy required to produce the same m / z = 55 fragment ion CH,=CH-C= O+ from poly(ethy1acrylate) would likely be different than that from Nylon-6 (17). However, the amount of this energy for each case should be nearly independent of the neighboring polymer chains. Making a case for negligible matrix effects resulting from near-neighbor interactions with the other components in a blend is not a clear-cut matter. The large changes observed in the secondary ion yield for an atomic or molecular ion in inorganic systems is mainly from the different bond energies, coordination number, crystal field potentials, and other types
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of short- and long-range interactions that are part of, or result from, the preions environment. In organic polymers the chemical functionalities, composed mainly of C, H, 0, N, and occasionally S, have a smaller range of bond energies and ionization energies when compared to the much wider range for these properties in inorganic materials. In addition, the short-range and long-range interactions are generally smaller than those observed in inorganic systems. Therefore, the only obvious perturbation resulting from the different interchain neighbors should be a small change in the energy required for desorption, which is already small compared to the energy required for the intrachain breaking of one or two bonds and the ionization step. As mentioned before, there should be no relative changes in secondary ion intensities from this change in desorption energy if an energy-focusing TOF instrument is used. If the surface is composed of a "true" blend of miscible polymers, as opposed to very small domains, then the ability of the surface to form a crystalline structure should be minimized and the majority of the area sampled should be amorphous. How important these secondary effects are in determining changes in secondary ion yields is unknown a t this time. The small ( m / t
