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Growth and in-depth distribution of thin metal films on silicon (111) studied by XPS: inelastic peak shape analysis
ELSEXIER
Surface Science 331-333 (1995) 942-947
Growth and in-depth distribution of thin metal films on silicon ( 111) studied by XPS: inelastic peak shape analysis M. Schleberger, D. Fujita, C. Scharfschwerdt, S. Tougaard * Fysisk Institut, Odense Universitet, DK-5230 Odeme M, Denmark
Received 3 August 1994; accepted for publication 25 November 1994
Abstract We have studied by XPS the growth of thin metal films on silicon at mom temperature. The following metals were studied: Cu, Ag, Pt, and Au. These systems are of cutrent interest for technological applications. The growth structure and interdiffusion of thin metallic layers into silicon is very difficult to determine by conventional surface analysis. We have therefore applied a new formalism, developed by Tougaard et al., in the form of the commercially available software package QUASESTM for quantitative analysis of surface nanostructnres by XPS. As deposited we find island formation for Cu, Pt, and Au. For Ag a Stranski-Kmstanov growth mechanism is identified. Keywords: Gold; Platinum; Polycrystalline thin films; Silicon; Silver; X-my photoelectron spectroscopy
1. Introduction A major problem in quantitative surface analysis by XPS is the contribution of inelastically scattered electrons to the spectrum. The measured intensity depends critically on the in-depth profile of the corresponding element. Therefore a correct procedure for background subtraction is vital to any analysis. Tougaard et al. [ 1] developed a method which takes into account the indepth composition. Recent investigations of many different systems using this method gave good quantitative results and proved the validity of the background correction algorithms [ 2-71 In the present work we used the commercially available software package QUASEP [2] to study the growth mechanisms at room temperature (RT) of four systems: Thin films of Cu, Ag, Pt, and Au evaporated
* Comsponding author.
on Si( 111). The software is based on the Tougaardmethod and thus allows for quantitative surface structure de&mined by inelastic background analysis of XPS-spectra.
2. Theory The basic algorithms for quantitative surface analysis from the shape of a measured XPS-spectrum have been developed some years ago and are described in detail elsewhere [ 1,3]. Here we briefly summarize the principle. Assume that the electrons initially constitute a distribution around the primary energy EObut that this distribution is independent of depth. On their way through the solid the electrons lose energy due to inelastic scattering. This will distort peak shape, peak height and the background of the measured spectra. The degree of distortion depends on the in-depth distribution f(x) of the emitters and the differential
0039~6028/95/$09.50 @ 1995 Elsevier Science B.V. All rights reserved HDZOO39-6028(95)00313-4
M. Schleberger et aL /Surface Science 331-333 (1995) 942-947
inelastic cross-section K(E,T) [4]. Thus the background corrected spectrum is given by:
F ( E, g2D) = ~--~ x /
dE J ( E, g~D) dse -is(E-E')
1 P(s) '
tungsten filament onto the single crystal Si(111) surfaces at RT. XPS-spectra were taken before and after deposition. The stability of the system was checked regularly by measuring spectra from pure reference samples.
(1)
4. Data analysis
where O0
P(s) = : f ( x ) e -(xlc°s°) ~-]~(s) dx ,I
o
and
(2) OO
~(S)
943
=
K ( T ) e -isT dr
-o
with E the kinetic energy,/2D the solid angle of the detector, K(T) the differential inelastic scattering cross section, A(E) the inelastic mean free path, J(E, 1"2D) the measured spectrum, F(E, ~D) the atomic spectrum, f ( x ) the depth profile and 0 the angle between surface normal and detector. By using this formalism one may correct any XPSspectrum for inelastic scattering if the in-depth profile f ( x ) is known. Vice versa can the formalism be used to determine the in-depth profile.
3. Experiment The measurements were performed with a VSW HA100 electron spectrometer (concentric hemispherical type) and a Mg Ka X-ray source at a base pressure below 10 - l ° Torr. The energy dependence of the analyzer transmission was determined by calibration against the NPL metrology spectrometer [ 5 ]. The analyzer was operated at a pass energy of 90 eV (Cu 2p3/2, Au 4d) and 22 eV (Ag 3d, Pt 4d), respectively. The Si-KLL peaks were recorded with the analyzer operated with a fixed retardation ratio (FRR) of 5. The energy range recorded was _> 150 eV for all systems. The angle between the incoming light and the analyzer axis was kept fixed at an angle of 70 ° , while the angle of detection was 15 ° with respect to the surface normal. The Si ( 111 ) samples were mounted and the surface region was cleaned by sputtering/annealing cycles in UHV. High purity metals were evaporated from a hot
Using QUASES TM to analyze a spectrum one first corrects for the energy dependence of the analyzer response function. It is possible to use either a given transmission function from a datafile or to use the functional dependency t(E) = E -m, where m can be chosen. Also a straight line fitted to the high energy side of the peak is subtracted, in order to account for intensity contributions from excitations at higher energies. After this there is mainly two basic ways of analyzing data. Analyse: Assuming a specific in-depth distribution, the spectral shape and intensity of F(E,/2D ) is calculated from J(E, OD). This corrected spectrum is compared to the intrinsic XPS-spectrum of a corresponding pure sample. This procedure is iterated until the in-depth profile f ( x ) is determined which produces the best possible fit. The intrinsic spectrum is obtained by analyzing the measured data of a pure sample assuming a homogenous depth profile of infinite thickness. Generate: Using this part of the program package, one starts with the measured XPS-spectrum of a corresponding homogenous, pure sample. From this a spectrum corresponding to an assumed depth profile is calculated. The so generated spectrum is then compared to the measured XPS-spectrum to be analyzed. B in the universal cross-section [6] is varied until the background corrected spectrum of the pure homogenous reference sample is _~ 0 in a sufficiently wide energy range below the peak structure, The inelastic mean free path (IMFP) enters the caculation as a parameter and the routines do not account for the possibility of different IMFP's for the film and for the substrate. Note that a measured spectrum of a corresponding pure sample is needed in both cases. The programs both allow for the use of different models for the in-depth profile: rectangular (buried), island growtfi (overlayer and substrate), exponential, and delta function. During analysis the structural parameters describ-
944
M. Schleberger et al./Surface Science 331-333 (1995) 942-947
ing the chosen model (height, depth, coverage, number of islands, number of delta functions .... ) can interactively be varied and the resulting spectrum is immediately displayed on the screen. These parameters and/or the model are varied until peak shape and absolute intensity are as close to the reference as possible. Finally the structural parameters are adjusted so that the peak area of the background corrected spectrum is identical to the peak area of the reference. In the case of an adsorbate/substrate system, more complete quantitative information is obtained if the spectra of both materials are analyzed (see Section 5). All necessary data handling can be done within QUASES TM.
a
i
-iv
=>,
b
36.5% 18AI~
c-
/ 1I~" ...... Lo \
,,,~ 800
850 900 Kinetic Energy (eV)
950
5. Results and discussion Analyzing the data for the metal evaporations, we found an exceptionally good agreement between the background corrected spectra and the reference spectra from the pure samples. Both peak shape and absolute intensities are almost identical. Minor deviations from the reference spectra are mainly due to statistical noise, shake-up features, and chemical shifts. The structure that accounts for the intensity distribution in the measured spectra could therefore be determined. In Fig. 1 the spectra for the deposited platinum are analyzed assuming two different growth models. Fig. la shows the best fit that could be obtained assuming a layer-by-layer growth model, namely a 5.25/k thick rectangular layer on the surface. In Fig. lb the best fit assuming a single island model is shown. The island being 18/~ high and covering 36.5% of the surface. Within our errors (4-5%) every other combination of structural parameters, e.g. using a lower coverage while simultaneously increasing the height gave worse fits. The island model structure clearly gives the better fit. A Stranski-Krastanov (SK) growth, a single island (40/~ high, covering 11%) in addition to a 3/k thick layer fully covering the surface resulted in a fit almost as good as the one for the single island structure. We are not able to distinguish clearly between those two types of structure. In Fig. 2 an example is given on how sensitive the fits are to a change of the structural parameters. In
Fig. 1. Fits for Pt 4d using different structures. (a) rectangular layer on top of the substrate, 5.25/~ thick. (b) single island, 18/~ high, covering36.5% of the surface. Fig. 2a the same height was used as in Fig. lb, but the coverage was changed from 36.5% to 55%. In Fig. 2b the same coverage as in Fig. lb was used, but the height was changed from 18 to 12 /~. Both fits are
55% e"
-'
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I
i
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i
v
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, 800
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, 850
i
i 900
950
Kinetic Energy (eV)
Fig. 2. Fits for Pt 4d using different parameters for the single island. (a) Single island 18/~ high, covering55% of the surface. (b) single island 12 .~ high, covering36.5% of the surface.
M. Schleberger et al./Surface Science 331-333 (1995) 942-947 Stranski-Krastanov
buried rectangular
5
E 840
860
880
900
840
1550
1600
1650 1500
860
880
900
1550
1600
1650
5
1500
Kinetic Energy (eV)
Kinetic Energy (eV)
Fig. 3. The left part shows the best fits obtained using a buried rectangular beginning at a depth of 1.5 A, ending at a depth of 13.7/~. The tight part shows the fits obtained using a single island being 20 ,~ high and coveting 54% of the surface plus a 3/~ thick layer fully covering the surface.
clearly worse than the fit in Fig. lb. Analyzing the Ag 3d-spectra we found that two different models gave an equally good fit. This is demonstrated in Fig. 3. The upper left picture shows the fit achieved using a buried rectangular layer beginning at a depth of 1.5 A and ending at a depth of 13.7/~. The upper right picture shows the fit for silver obtained by assuming a thin 3/~ layer covering the whole surface plus a single island being 20/k high and covering 54% of the surface. A third equally good solution is a pure single island model, the island being 19/k high and covering 59% of the surface. Note that all structures give about the same total amount of silver. For adsorbate/substrate systems the measured spectrum J(E, OD) is simply the sum of the substrate spectrum and the adsorbate spectrum: J(E, f2D) = Js( E, O) + JA ( E, [2) [7]. Since the two distribution functions are complementary, we know f ( x ) for the substrate if f ( x ) for the adsorbate is known. Thus, in order to determine the correct model we also analyzed the corresponding spectra of the Si-KLL peak using the complementary model. In the lower two panels of Fig, 3 we used the same two sets of parameters that had been determined for the Ag 3d-spectrum to analyze the Si-KLL spectra. It is obvious that the
945
agreement for the Stranski-Krastanov structure is significantly better than for the rectangular depth-profile. Optimizing the parameters the best possible fit for the buried rectangular was obtained by assuming a buried rectangular layer beginning at a depth of 10/~ and ending at a depth of 20/~. In the case of SK growth the best fit could be obtained with similar parameters as found for the Ag 3d-spectra: a single island being 19/~ high, covering 52% of the surface and an additional 3/~ thick layer fully covering the surface. Therefore the buried rectangular cannot be the right structure. It should be noted though, that the fits for the spectra of the Si-KLL peak are not as sensitive to a change in parameters as are the fits for the metal spectra. This is of course due to the very small ratio of metal/silicon. Especially if there is only a small amount of metal left on the surface, only very limited information can be obtained from the analysis of the spectra of the SiKLL peak alone. Using the described procedure, Cu and Au were found to grow as a single island, that is always a certain amount of free silicon was needed to accomplish a good fit (see Table 1). The structural parameters are unambigous, that is they could not be changed by more than 5% without notably worsening the fits and no other structure would give equally good fits. Ag and Pt grow either by the formation of a thin layer followed by island formation (SK) or by island formation only (see Table 1 ). The formation of islands may take place either at the surface or at the interface. Note that with the inelastic peak shape analysis, what is determined is the in-depth distribution of atoms. Thus, a distribution corresponding to island formation may also be interpreted as alloy formation. These two possibilities may be distinguished by a chemical shift of the metal peak, which is expected if an alloy is formed. For copper at RT an island growth mode has been observed with AES [9] and STM [ 10], which is consistent with our results. For silver it is well known [ 11, 12] that three-dimensional islands are formed in addition to a two-dimensional layer (Stranski-Krastanov growth mode) and this has recently again been confirmed by SEM studies [13]. These findings are in agreement with our data, although we are not able to verify whether it is a single island or island plus thin layer structure. For gold it has been reported that for coverages exceeding 5 monolayers (ML), a 5 ML thick Au3Si
946
M. Schleberger et al./Surface Science 331-333 (1995) 942-947
Table 1 Parameters determined for the deposited material Metal on Si( 111 )
A (/~)
B (eV)
Height (/~)
Coverage (%)
Total (ML)
Cu Ag
7.8 13.09
3050 3000
13.09
3000
Pt Au Au
12.5 12.09 12.09
2700 2830 2830
88.0 53.0 100.0 76.0 100.0 34.8 57.8 56.5
33.7 11.8
Ag
38.25 19.5 3.0 28.0 3.0 18.0 17.5 27.5
22.0 6.3 10.1 15.5
For Ag and Au two samples with different amount of material deposited have been measured. The values represent the average of the parameters found by analyzing both the metal and the Si-KLL spectra. The ,t-values were taken from Ref. [8], the parameter B was determined as described earlier (see Section 4 analysis). alloy is formed. Between this silicide-like layer and the silicon substrate metallic A u nucleates [ 14]. Since we found a chemical shift o f the gold peak, the structure cannot be pure island formation. Combining the results in Ref. [ 14] with the results in Table 1, we arrive at the following conclusions: On top o f the Si-substrate we have a metallic gold layer covering roughly 60% o f the surface, on top o f which a 5 M L thick Au3Si alloy is formed. In the case o f platinum it has been reported that film growth at RT involves the formation o f threedimensional islands and that the deposited layer consists o f unreacted metal grains covered with silicidelike material [ 15, 16]. This is fully consistent with the results o f the present work, which points to strong island formation (see Table 1).
were explained. Using an island growth model consisting o f one island only, good fits for substrate and adsorbate could be accomplished for Cu, Pt, and Au. For A g a Stranski-Krastanov growth mode was determined. Both peak shape and absolute intensity were reproduced. The total amount o f material deposited was determined.
Acknowledgement This work was supported by a grant from the Danish Natural Science Research Foundation for M. Schleberger.
References 6. Conclusions We analyzed the inelastic background o f the XPSspectra o f four different m e t a l / s i l i c o n systems. We studied the nanostructure o f the metal after deposition on single crystal S i ( l l l ) surfaces. For the analysis we used the program QUASES TM, that is based on the method for background correction developed by Tougaard et al. The program turned out to be very well suited for the analysis o f the systems studied. Since a single typical calculation takes not more than ca. 1 s (66 M H z 486) it is possible to try many different parameters within many different models in order to find the best possible fit. Some details about the software package
[1] S. Tougaard, J. Vac. Sci. Technol. A 4 (1987) 1230. [2l S. Tougaard, QUASESTM Vers. 1.1: Software Packet for Quantitative XPS/AES of Surface Nano-Struetures by Inelastic Peak Shape Analysis, 1994, (Contact S. Tougaard for more information.). [3l S. Tougaard, J. Vac. Sci. Technol. A 8 (1990) 2197. [4] S. Tougaard, Surf. Interface Anal. 11 (1988) 453. [5] M. Seah, Surf. Interface Anal. 20 (1993) 243. [6l S. Tougaard, Solid State Commun. 61 (1987) 547. [7] H. Hansen and S. Tougaard, Vacuum 10 (1990) 1713. [8] S. Tanuma, C. Powell and D. Penn, Surf. Interf. Anal, 11 (1988) 577. [9] E. Daugy E Mathiez, E Salvan and J. Layet, Surf. Sci. 154 (1985) 267. [ 10] T. Yasue T. Koshikawa, H. Tanaka and I. Sumita, Surf. Sci. 287/288 (1993) 1025. [ t l ] G.L. Lay, Surf. Sci. 132 (1983) 169.
M. Schleberger et al./Surface Science 331-333 (1995) 942-947 [12,] R. Kern, G.L. Lay and M. Manville, Surf. Sci. 72 (1978) 405. [13] S. lno and A. Endo, Surf. Sci. 293 (1993) 165. [14] J.J. Yeh J. Hwang K. Bertness D. Friedmann, R.Cao and I. Lindau, Phys. Rev. Lett. 70 (1993) 3768.
947
[15] P. Morgen M. Szymonski J. Onsgaard, B. JCrgensen and G. Rossi, Surf. Sci. 197 (1988) 347. [16] R. Matz R. Purtell Y. Yokota, G. Rubloff and E Ho, J. Vac. Sci. Technol. A 2 (1984) 253.
Surface Science 331-333 (1995) 942-947
Growth and in-depth distribution of thin metal films on silicon ( 111) studied by XPS: inelastic peak shape analysis M. Schleberger, D. Fujita, C. Scharfschwerdt, S. Tougaard * Fysisk Institut, Odense Universitet, DK-5230 Odeme M, Denmark
Received 3 August 1994; accepted for publication 25 November 1994
Abstract We have studied by XPS the growth of thin metal films on silicon at mom temperature. The following metals were studied: Cu, Ag, Pt, and Au. These systems are of cutrent interest for technological applications. The growth structure and interdiffusion of thin metallic layers into silicon is very difficult to determine by conventional surface analysis. We have therefore applied a new formalism, developed by Tougaard et al., in the form of the commercially available software package QUASESTM for quantitative analysis of surface nanostructnres by XPS. As deposited we find island formation for Cu, Pt, and Au. For Ag a Stranski-Kmstanov growth mechanism is identified. Keywords: Gold; Platinum; Polycrystalline thin films; Silicon; Silver; X-my photoelectron spectroscopy
1. Introduction A major problem in quantitative surface analysis by XPS is the contribution of inelastically scattered electrons to the spectrum. The measured intensity depends critically on the in-depth profile of the corresponding element. Therefore a correct procedure for background subtraction is vital to any analysis. Tougaard et al. [ 1] developed a method which takes into account the indepth composition. Recent investigations of many different systems using this method gave good quantitative results and proved the validity of the background correction algorithms [ 2-71 In the present work we used the commercially available software package QUASEP [2] to study the growth mechanisms at room temperature (RT) of four systems: Thin films of Cu, Ag, Pt, and Au evaporated
* Comsponding author.
on Si( 111). The software is based on the Tougaardmethod and thus allows for quantitative surface structure de&mined by inelastic background analysis of XPS-spectra.
2. Theory The basic algorithms for quantitative surface analysis from the shape of a measured XPS-spectrum have been developed some years ago and are described in detail elsewhere [ 1,3]. Here we briefly summarize the principle. Assume that the electrons initially constitute a distribution around the primary energy EObut that this distribution is independent of depth. On their way through the solid the electrons lose energy due to inelastic scattering. This will distort peak shape, peak height and the background of the measured spectra. The degree of distortion depends on the in-depth distribution f(x) of the emitters and the differential
0039~6028/95/$09.50 @ 1995 Elsevier Science B.V. All rights reserved HDZOO39-6028(95)00313-4
M. Schleberger et aL /Surface Science 331-333 (1995) 942-947
inelastic cross-section K(E,T) [4]. Thus the background corrected spectrum is given by:
F ( E, g2D) = ~--~ x /
dE J ( E, g~D) dse -is(E-E')
1 P(s) '
tungsten filament onto the single crystal Si(111) surfaces at RT. XPS-spectra were taken before and after deposition. The stability of the system was checked regularly by measuring spectra from pure reference samples.
(1)
4. Data analysis
where O0
P(s) = : f ( x ) e -(xlc°s°) ~-]~(s) dx ,I
o
and
(2) OO
~(S)
943
=
K ( T ) e -isT dr
-o
with E the kinetic energy,/2D the solid angle of the detector, K(T) the differential inelastic scattering cross section, A(E) the inelastic mean free path, J(E, 1"2D) the measured spectrum, F(E, ~D) the atomic spectrum, f ( x ) the depth profile and 0 the angle between surface normal and detector. By using this formalism one may correct any XPSspectrum for inelastic scattering if the in-depth profile f ( x ) is known. Vice versa can the formalism be used to determine the in-depth profile.
3. Experiment The measurements were performed with a VSW HA100 electron spectrometer (concentric hemispherical type) and a Mg Ka X-ray source at a base pressure below 10 - l ° Torr. The energy dependence of the analyzer transmission was determined by calibration against the NPL metrology spectrometer [ 5 ]. The analyzer was operated at a pass energy of 90 eV (Cu 2p3/2, Au 4d) and 22 eV (Ag 3d, Pt 4d), respectively. The Si-KLL peaks were recorded with the analyzer operated with a fixed retardation ratio (FRR) of 5. The energy range recorded was _> 150 eV for all systems. The angle between the incoming light and the analyzer axis was kept fixed at an angle of 70 ° , while the angle of detection was 15 ° with respect to the surface normal. The Si ( 111 ) samples were mounted and the surface region was cleaned by sputtering/annealing cycles in UHV. High purity metals were evaporated from a hot
Using QUASES TM to analyze a spectrum one first corrects for the energy dependence of the analyzer response function. It is possible to use either a given transmission function from a datafile or to use the functional dependency t(E) = E -m, where m can be chosen. Also a straight line fitted to the high energy side of the peak is subtracted, in order to account for intensity contributions from excitations at higher energies. After this there is mainly two basic ways of analyzing data. Analyse: Assuming a specific in-depth distribution, the spectral shape and intensity of F(E,/2D ) is calculated from J(E, OD). This corrected spectrum is compared to the intrinsic XPS-spectrum of a corresponding pure sample. This procedure is iterated until the in-depth profile f ( x ) is determined which produces the best possible fit. The intrinsic spectrum is obtained by analyzing the measured data of a pure sample assuming a homogenous depth profile of infinite thickness. Generate: Using this part of the program package, one starts with the measured XPS-spectrum of a corresponding homogenous, pure sample. From this a spectrum corresponding to an assumed depth profile is calculated. The so generated spectrum is then compared to the measured XPS-spectrum to be analyzed. B in the universal cross-section [6] is varied until the background corrected spectrum of the pure homogenous reference sample is _~ 0 in a sufficiently wide energy range below the peak structure, The inelastic mean free path (IMFP) enters the caculation as a parameter and the routines do not account for the possibility of different IMFP's for the film and for the substrate. Note that a measured spectrum of a corresponding pure sample is needed in both cases. The programs both allow for the use of different models for the in-depth profile: rectangular (buried), island growtfi (overlayer and substrate), exponential, and delta function. During analysis the structural parameters describ-
944
M. Schleberger et al./Surface Science 331-333 (1995) 942-947
ing the chosen model (height, depth, coverage, number of islands, number of delta functions .... ) can interactively be varied and the resulting spectrum is immediately displayed on the screen. These parameters and/or the model are varied until peak shape and absolute intensity are as close to the reference as possible. Finally the structural parameters are adjusted so that the peak area of the background corrected spectrum is identical to the peak area of the reference. In the case of an adsorbate/substrate system, more complete quantitative information is obtained if the spectra of both materials are analyzed (see Section 5). All necessary data handling can be done within QUASES TM.
a
i
-iv
=>,
b
36.5% 18AI~
c-
/ 1I~" ...... Lo \
,,,~ 800
850 900 Kinetic Energy (eV)
950
5. Results and discussion Analyzing the data for the metal evaporations, we found an exceptionally good agreement between the background corrected spectra and the reference spectra from the pure samples. Both peak shape and absolute intensities are almost identical. Minor deviations from the reference spectra are mainly due to statistical noise, shake-up features, and chemical shifts. The structure that accounts for the intensity distribution in the measured spectra could therefore be determined. In Fig. 1 the spectra for the deposited platinum are analyzed assuming two different growth models. Fig. la shows the best fit that could be obtained assuming a layer-by-layer growth model, namely a 5.25/k thick rectangular layer on the surface. In Fig. lb the best fit assuming a single island model is shown. The island being 18/~ high and covering 36.5% of the surface. Within our errors (4-5%) every other combination of structural parameters, e.g. using a lower coverage while simultaneously increasing the height gave worse fits. The island model structure clearly gives the better fit. A Stranski-Krastanov (SK) growth, a single island (40/~ high, covering 11%) in addition to a 3/k thick layer fully covering the surface resulted in a fit almost as good as the one for the single island structure. We are not able to distinguish clearly between those two types of structure. In Fig. 2 an example is given on how sensitive the fits are to a change of the structural parameters. In
Fig. 1. Fits for Pt 4d using different structures. (a) rectangular layer on top of the substrate, 5.25/~ thick. (b) single island, 18/~ high, covering36.5% of the surface. Fig. 2a the same height was used as in Fig. lb, but the coverage was changed from 36.5% to 55%. In Fig. 2b the same coverage as in Fig. lb was used, but the height was changed from 18 to 12 /~. Both fits are
55% e"
-'
f
I
i
f
i
v
-£
b
£
12A36~
, 800
/i
, 850
i
i 900
950
Kinetic Energy (eV)
Fig. 2. Fits for Pt 4d using different parameters for the single island. (a) Single island 18/~ high, covering55% of the surface. (b) single island 12 .~ high, covering36.5% of the surface.
M. Schleberger et al./Surface Science 331-333 (1995) 942-947 Stranski-Krastanov
buried rectangular
5
E 840
860
880
900
840
1550
1600
1650 1500
860
880
900
1550
1600
1650
5
1500
Kinetic Energy (eV)
Kinetic Energy (eV)
Fig. 3. The left part shows the best fits obtained using a buried rectangular beginning at a depth of 1.5 A, ending at a depth of 13.7/~. The tight part shows the fits obtained using a single island being 20 ,~ high and coveting 54% of the surface plus a 3/~ thick layer fully covering the surface.
clearly worse than the fit in Fig. lb. Analyzing the Ag 3d-spectra we found that two different models gave an equally good fit. This is demonstrated in Fig. 3. The upper left picture shows the fit achieved using a buried rectangular layer beginning at a depth of 1.5 A and ending at a depth of 13.7/~. The upper right picture shows the fit for silver obtained by assuming a thin 3/~ layer covering the whole surface plus a single island being 20/k high and covering 54% of the surface. A third equally good solution is a pure single island model, the island being 19/k high and covering 59% of the surface. Note that all structures give about the same total amount of silver. For adsorbate/substrate systems the measured spectrum J(E, OD) is simply the sum of the substrate spectrum and the adsorbate spectrum: J(E, f2D) = Js( E, O) + JA ( E, [2) [7]. Since the two distribution functions are complementary, we know f ( x ) for the substrate if f ( x ) for the adsorbate is known. Thus, in order to determine the correct model we also analyzed the corresponding spectra of the Si-KLL peak using the complementary model. In the lower two panels of Fig, 3 we used the same two sets of parameters that had been determined for the Ag 3d-spectrum to analyze the Si-KLL spectra. It is obvious that the
945
agreement for the Stranski-Krastanov structure is significantly better than for the rectangular depth-profile. Optimizing the parameters the best possible fit for the buried rectangular was obtained by assuming a buried rectangular layer beginning at a depth of 10/~ and ending at a depth of 20/~. In the case of SK growth the best fit could be obtained with similar parameters as found for the Ag 3d-spectra: a single island being 19/~ high, covering 52% of the surface and an additional 3/~ thick layer fully covering the surface. Therefore the buried rectangular cannot be the right structure. It should be noted though, that the fits for the spectra of the Si-KLL peak are not as sensitive to a change in parameters as are the fits for the metal spectra. This is of course due to the very small ratio of metal/silicon. Especially if there is only a small amount of metal left on the surface, only very limited information can be obtained from the analysis of the spectra of the SiKLL peak alone. Using the described procedure, Cu and Au were found to grow as a single island, that is always a certain amount of free silicon was needed to accomplish a good fit (see Table 1). The structural parameters are unambigous, that is they could not be changed by more than 5% without notably worsening the fits and no other structure would give equally good fits. Ag and Pt grow either by the formation of a thin layer followed by island formation (SK) or by island formation only (see Table 1 ). The formation of islands may take place either at the surface or at the interface. Note that with the inelastic peak shape analysis, what is determined is the in-depth distribution of atoms. Thus, a distribution corresponding to island formation may also be interpreted as alloy formation. These two possibilities may be distinguished by a chemical shift of the metal peak, which is expected if an alloy is formed. For copper at RT an island growth mode has been observed with AES [9] and STM [ 10], which is consistent with our results. For silver it is well known [ 11, 12] that three-dimensional islands are formed in addition to a two-dimensional layer (Stranski-Krastanov growth mode) and this has recently again been confirmed by SEM studies [13]. These findings are in agreement with our data, although we are not able to verify whether it is a single island or island plus thin layer structure. For gold it has been reported that for coverages exceeding 5 monolayers (ML), a 5 ML thick Au3Si
946
M. Schleberger et al./Surface Science 331-333 (1995) 942-947
Table 1 Parameters determined for the deposited material Metal on Si( 111 )
A (/~)
B (eV)
Height (/~)
Coverage (%)
Total (ML)
Cu Ag
7.8 13.09
3050 3000
13.09
3000
Pt Au Au
12.5 12.09 12.09
2700 2830 2830
88.0 53.0 100.0 76.0 100.0 34.8 57.8 56.5
33.7 11.8
Ag
38.25 19.5 3.0 28.0 3.0 18.0 17.5 27.5
22.0 6.3 10.1 15.5
For Ag and Au two samples with different amount of material deposited have been measured. The values represent the average of the parameters found by analyzing both the metal and the Si-KLL spectra. The ,t-values were taken from Ref. [8], the parameter B was determined as described earlier (see Section 4 analysis). alloy is formed. Between this silicide-like layer and the silicon substrate metallic A u nucleates [ 14]. Since we found a chemical shift o f the gold peak, the structure cannot be pure island formation. Combining the results in Ref. [ 14] with the results in Table 1, we arrive at the following conclusions: On top o f the Si-substrate we have a metallic gold layer covering roughly 60% o f the surface, on top o f which a 5 M L thick Au3Si alloy is formed. In the case o f platinum it has been reported that film growth at RT involves the formation o f threedimensional islands and that the deposited layer consists o f unreacted metal grains covered with silicidelike material [ 15, 16]. This is fully consistent with the results o f the present work, which points to strong island formation (see Table 1).
were explained. Using an island growth model consisting o f one island only, good fits for substrate and adsorbate could be accomplished for Cu, Pt, and Au. For A g a Stranski-Krastanov growth mode was determined. Both peak shape and absolute intensity were reproduced. The total amount o f material deposited was determined.
Acknowledgement This work was supported by a grant from the Danish Natural Science Research Foundation for M. Schleberger.
References 6. Conclusions We analyzed the inelastic background o f the XPSspectra o f four different m e t a l / s i l i c o n systems. We studied the nanostructure o f the metal after deposition on single crystal S i ( l l l ) surfaces. For the analysis we used the program QUASES TM, that is based on the method for background correction developed by Tougaard et al. The program turned out to be very well suited for the analysis o f the systems studied. Since a single typical calculation takes not more than ca. 1 s (66 M H z 486) it is possible to try many different parameters within many different models in order to find the best possible fit. Some details about the software package
[1] S. Tougaard, J. Vac. Sci. Technol. A 4 (1987) 1230. [2l S. Tougaard, QUASESTM Vers. 1.1: Software Packet for Quantitative XPS/AES of Surface Nano-Struetures by Inelastic Peak Shape Analysis, 1994, (Contact S. Tougaard for more information.). [3l S. Tougaard, J. Vac. Sci. Technol. A 8 (1990) 2197. [4] S. Tougaard, Surf. Interface Anal. 11 (1988) 453. [5] M. Seah, Surf. Interface Anal. 20 (1993) 243. [6l S. Tougaard, Solid State Commun. 61 (1987) 547. [7] H. Hansen and S. Tougaard, Vacuum 10 (1990) 1713. [8] S. Tanuma, C. Powell and D. Penn, Surf. Interf. Anal, 11 (1988) 577. [9] E. Daugy E Mathiez, E Salvan and J. Layet, Surf. Sci. 154 (1985) 267. [ 10] T. Yasue T. Koshikawa, H. Tanaka and I. Sumita, Surf. Sci. 287/288 (1993) 1025. [ t l ] G.L. Lay, Surf. Sci. 132 (1983) 169.
M. Schleberger et al./Surface Science 331-333 (1995) 942-947 [12,] R. Kern, G.L. Lay and M. Manville, Surf. Sci. 72 (1978) 405. [13] S. lno and A. Endo, Surf. Sci. 293 (1993) 165. [14] J.J. Yeh J. Hwang K. Bertness D. Friedmann, R.Cao and I. Lindau, Phys. Rev. Lett. 70 (1993) 3768.
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[15] P. Morgen M. Szymonski J. Onsgaard, B. JCrgensen and G. Rossi, Surf. Sci. 197 (1988) 347. [16] R. Matz R. Purtell Y. Yokota, G. Rubloff and E Ho, J. Vac. Sci. Technol. A 2 (1984) 253.