Ferrante, J. et. al. “Surface Physics in Tribology”
Handbook of Micro/Nanotribology.
Ed. Bharat Bhushan
Boca Raton: CRC Press LLC, 1999
© 1999 by CRC Press LLC© 1999 by CRC Press LLC

3

Surface Physics

in Tribology

John Ferrante and Phillip B. Abel

3.1 Introduction
3.2 Geometry of Surfaces
3.3 Theoretical Considerations

Surface Theory • Friction Fundamentals

3.4 Experimental Determinations of Surface Structure

Low-Energy Electron Diffraction • High-Resolution Electron
Microscopy • Field Ion Microscopy

3.5 Chemical Analysis of Surfaces

Auger Electron Spectroscopy • X-Ray Photoelectron

Finally, we will examine the relationship of tribological experiments to these more fundamental
atomistic considerations. The primary goals of this section will be to again provide sources for further
study of tribological experiments and to raise critical issues concerning the relationship between basic
surface properties with regard to tribology and the ability of certain classes of experiments to reveal the
underlying interactions. We will attempt to avoid overlapping the material that we present with that
presented by other authors in this publication. This chapter cannot be a complete treatment of the physics
of surfaces due to space limitations. We recommend an excellent text by Zangwill (1988) for a more
thorough treatment. Instead, we concentrate on techniques and issues of importance to tribology on the
nanoscale.

3.2 Geometry of Surfaces

We will now discuss simply from a geometric standpoint what occurs when you create two surfaces by
dividing a solid along a given plane. We limit the discussion to single crystals, since the same arguments
apply to polycrystalline samples except for the existence of many grains, each of which could be described
by a corresponding argument. This discussion will start by introducing the standard notation for describ-
ing crystals given in many solid-state texts (Ashcroft and Mermin, 1976; Kittel, 1986). It is meant to be
didactic in nature and because of length limitations will not attempt to be comprehensive. To establish
notation and concepts we will limit our discussion to two of the possible Bravais lattices, face-centered
cubic (fcc) and body-centered cubic (bcc), which are the structures often found in metals. The unit cells,
i.e., the structures which most easily display the symmetries of the crystals, are shown in Figure 3.1. The
other descriptions that are frequently used are the primitive cells, which show the simplest structures
that can be repeated to create a given structure. In Figure 3.1 we also show the primitive cell basis vectors,
which can be used to generate the entire structure by the relation
(3.1)
where

n

1


→

a

3

are the unit basis vectors.
Since we are interested in describing surface properties, we want to present the standard nomenclature
for specifying a surface. The algebraic description of a surface is usually given in terms of a vector normal
to the surface. This is conveniently accomplished in terms of vectors that arise naturally in solids, namely,
the reciprocal lattice vectors of the Bravais lattice (Ashcroft and Mermin, 1976; Kittel, 1986). This is

FIGURE 3.1

(a) Unit cube of fcc crystal structure with primative cell basis vectors indicated. (b) Unit cube of bcc
crystal structure, with primative cell basis vectors indicated.
r
rr r
Rnana na=+ +
12233

© 1999 by CRC Press LLC

convenient since these vectors are used to describe the band structure and diffraction effects in the solid.
They are usually given in the form
(3.2)
where

h, k,

123
r
rr
rr r
b
aa
aa a
i
jk
=π
×
×
()
2
12 3

© 1999 by CRC Press LLC

as surface density and interplanar spacings. A modern reprinting of this NASA publication is called for.
In many cases, this simple description is not adequate since the surface can reconstruct. The two most
prominent cases of surface reconstruction are the Au(110) surface (Good and Banerjea, 1992) for metals
and the Si(111) surface (Zangwill, 1988) for semiconductors. In addition, adsorbates often form structures
with symmetries different from the substrate, with the classic example the adsorption of oxygen on
W(110) (Zangwill, 1988). Wood (1963) in a classic publication gives the nomenclature for describing
such structures. In Figure 3.3 we show an example of 2

×

2 structure, where the terminology describes
a surface that has a layer with twice the spacings of the substrate. There are many other possibilities, such

G. et al. (1994),

Surf. Sci.

315, 204–214. With permission.)

© 1999 by CRC Press LLC

to this behavior where the interplanar spacing increases between the first two layers due to bonding
effects (Needs, 1987; Feibelman, 1992). However, the pattern shown in Figure 3.4 is the usual behavior
for most metallic surfaces. There can be similar changes in position within the planes; however, these
are usually small effects (Rodriguez et al., 1993; Foiles, 1987). In Figure 3.5, we show a side view of a
gold (110) surface (Good and Banerjea, 1992). Figure 3.5a shows the unreconstructed surface and Figure
3.5b shows a side view of the (2

×

1) missing row reconstruction. Such behavior indicates the complexity
that can arise even for metal surfaces and the danger of using ideas which are too simplistic, since more
details of the bonding interactions are needed in this case and those of Needs (1987) and Feibelman
(1992).
Crystal surfaces encountered typically are not perfectly oriented nor atomically flat. Even “on-axis”
(i.e., within a fraction of a degree) single-crystal low-index faces exhibit some density of crystallographic
steps. For a gold (111) face tilted one half degree toward the (011) direction, evenly spaced single atomic
height steps would be only 27 nm apart. Other surface-breaking crystal defects such as screw and edge
dislocations may also be present, in addition to whatever surface scratches, grooves, and other polishing
damage which remain in a typical single-crystal surface. Surface steps and step kinks would be expected
to show greater reactivity than low-index surface planes. During either deposition or erosion of metal
surfaces, one expects incorporation into or loss from the crystal lattice preferentially at step edges. More
generally on simple metal surfaces, lone atoms on a low-index crystal face are expected to be most mobile

1988). This can greatly affect results since sulfur, known to be a strong poisoning contaminant in catalysis,
can affect interfacial bond strength. Sulfur is often a component in many lubricants. For alloys similar
geometric surface reconstructions occur (Kobistek et al., 1994). Again, alloy surface composition can vary
dramatically from the bulk, with segregation causing one of the elements to be the only component on
a surface. In Figure 3.6 we show the surface composition for a CuNi alloy as a function of bulk composition
with both a large number of experimental results and some theoretical predictions for the composition

FIGURE 3.5

Side view of gold (110) surface: (a) unrecon-
structed; (b) 1

×

2 missing row surface reconstruction.
(From Good, B. S. and Banerjea, A. (1992),

Mater. Res. Soc.
Symp. Proc.,

278, 211–216. With permission.)

© 1999 by CRC Press LLC

(Good et al., 1993). In addition, nascent surfaces typically react with the ambient, giving monolayer films
and oxidation even in ultrahigh vacuum, producing even more pronounced surface composition effects.
In conclusion, we see that even in the most simple circumstances, i.e., single-crystal surfaces, the situation
can be very complicated.

3.3 Theoretical Considerations

, still is.

FIGURE 3.6

Copper (111) surface composition vs. copper-nickel alloy bulk composition: comparison between the
experimental and theoretical results for the first and second planes. (See Good et al., 1993, and references therein.)

© 1999 by CRC Press LLC

The process usually proceeds by solving the one-electron Kohn–Sham equations (Kohn and Sham,
1965; Lundqvist and March, 1983), where a given electron is treated as though it is in the mean field of
all of the other electrons. The LDA represents the mean field in terms of the local electron density at a
given location. The Kohn–Sham equations are written in the form (using atomic units where the constants
appearing in the Schroedinger equation along with the electron charge and the speed of light,

ប

=

m

e

=
e = c

= 1).
(3.4)
where


ρ

(

→

r

) is the electron density (the brackets
indicate that it is a functional of the density), and

Φ

(

→

r

) is the electrostatic potential given by
(3.6)
in which the first term is the electron–electron interaction and the second term is the electron–ion
interaction,

Z

j

is the ion charge, and the electron density is given by
(3.7)

is the kinetic energy contribution to the energy,

E

es

is the electrostatic contribution,

E

xc

is the
exchange correlation contribution, and the brackets indicate that the energy is a functional of the density.
Thus, the energy is an extremum of the correct density. Determining the surface energy accurately from
such calculations can be quite difficult since the surface energy, or indeed any of the energies of various
structures of interest, are obtained as the difference of big numbers. For example, for the surface the
energy would be given by
(3.9)
where

a

is the distance between the surfaces (a = 0 to get the surface energy) and

A

is the cross-sectional
area.
−∇+

rr r
r
rdr
r
rr
Z
rR
j
j
j
()
=
′
()
−
′
−∑
−
∫
ρ
ρ
r
r
r
rkr
i
()
=
()
ΣΨ

model is only expected to give reasonable results for the densest packed planes of simple metals.
In Figures 3.7 and 3.8 we show the electron distribution at a jellium surface for Na and for an
Al(111)–Mg(0001) interface (Ferrante and Smith, 1985) that is separated a small distance. In Figure 3.7
we can see the characteristic decay of the electron density away from the surface. In Figure 3.8 we see
the change in electron density in going from one material to another. This characteristic tailing is an
indication of the reactivity of the metal surface.
In Figure 3.9 we show the electron distribution for a nickel (100) surface for the fully three-dimensional
calculations performed by Arlinghouse et al. (1980) and that for a silver layer adsorbed on a palladium
(100) interface (Smith and Ferrante, 1985) using self-consistent localized orbitals (SCLO) for approxi-
mations to the wave functions. First, we note that for the Ni surface we see there is a smoothing of the
surface density characteristic of metals. For the adsorption we can see that there are localized charge
transfers and bonding effects indicating that it is necessary to perform three-dimensional calculations in
order to determine bonding effects. Hong et al. (1995) have also examined metal–ceramic interfaces and
the effects of impurities at the interface on the interfacial strength.
In Figure 3.10 we schematically show the results of determining the interfacial energies as a function
of separation between the surfaces with the energy in Figure 3.10a and the derivative curves giving the
interfacial strength. In Figure 3.11 we show Ferrante and Smith’s results for a number of interfaces of
jellium metals (Ferrante and Smith, 1985; Smith and Ferrante, 1986; Banerjea et al., 1991). Rose et al.
(1981, 1983) found that these curves would scale onto one universal curve and indeed that this result
applied to many other bonding situations including results of fully three-dimensional calculations. We
show the scaled curves from Figure 3.11 in Figure 3.12. Somewhat surprisingly because of large charge
transfer, Hong et al. (1995) found that this same behavior is applicable to metal–ceramic interfaces. Finnis
(1996) gives a review of metal–ceramic interface theory.
The complexities that we described earlier with regard to surface relaxations and complex structures
can also be treated now by modern theoretical techniques. Often in these cases it is necessary to use
“supercells” (Lambrecht and Segall, 1989). Since these structures are extended, it would require many
atoms to represent a defect. Instead, in order to model a defect and take advantage of the simplicities of
periodicities, a cell is created selected at a size which will mimic the main energetics of the defects. In
conclusion, we can see that theoretical techniques have advanced substantially and are continuing to do
so. They have and will shed light on many problems of interest experimentally.

ideally flat and were formed by asperities (a hill-and-valley structure), proposed that interlocking asper-
ities could be a source of the friction force. This model has many limitations. For example, if we picture
a perfectly sinusoidal interface there is no energy dissipation mechanism, since once the top of the first
asperity is attained the system will slide down the other side, thus needing no additional force once set
in motion. Bowden and Tabor (1964), recognizing the existence of interfacial forces, proposed another
mechanism based on adhesion at interfaces. Again, recognizing the existence of asperities, they propose
that adhesion occurs at asperity surfaces and that shearing occurs on translational motion. This model
explains a number of effects such as the disparity between true area of contact and apparent area of
contact and the tracking of friction force with load, since the asperities and thus the true area of contact
change with asperity deformation (load). The actual arguments are more complex than indicated here
and require reading of the primary text for completeness. These considerations also emphasize the basic
topic of this chapter, i.e., the important effect of the state of the surface and interface on the friction
process. Clearly, adsorbates, the differences of materials in contact, and lubricants greatly affect the
interaction.
We now proceed to briefly outline some models of both the friction force and frictional energy
dissipation. As addressed elsewhere in this book, there have recently been a number of attempts to model
theoretically the friction interaction at the atomic level. The general approaches have involved assuming
a two-body interaction potential at an interface, which in some cases may only be one dimensional, and

FIGURE 3.8

Electron number density

n

and jellium ion charge density for an aluminum (111)–magnesium (0001)
interface. (From Ferrante, J. and Smith, J. R. (1985),

Phys. Rev. B


both surfaces to adjust and examine the effects of velocity with attention to the three rules of friction
stated above. They argue, not based on their calculations, that the Bowden and Tabor argument is not
consistent with flat interfaces having no asperities. Since an adhesive force exists, there is a normal force
on the interfaces with no external normal load. Consequently, rules of friction 1 and 2 break down. With
respect to rule 3, they find it restricted to certain circumstances. They found that the dynamic friction
force, in general, is sliding velocity dependent, but with a decreasing velocity dependence with increasing
maximum static friction force. Hence, for systems with large static friction forces, the kinetic friction
force shows behavior similar to classical rule 3, above. Finally, Zhong and Tomanek (1990) performed a
first-principles calculation of the force to slide a monolayer of Pd in registry with the graphite surface.

FIGURE 3.10

Example of a binding energy curve: (a) energy vs. separation; (b) force vs. separation. (From Banerjea,
A. et al. (1991), in

Fundamentals of Adhesion

(Liang-Huang Lee, ed.), Plenum Press, New York. With permission.)

© 1999 by CRC Press LLC

FIGURE 3.11

Adhesive energy vs. separation: (a) commensurate adhesion is assumed; (b) incommensurate adhe-
sion is assumed. (From Rose, J.H. et al. (1983),

Phys. Rev. B

28, 1835–1845. With permission.)


Scaled adhesive binding energy as a function of scaled separation for systems in Figure 3.11. (From
Rose, J.H. et al. (1983),

Phys. Rev. B

28, 1835–1845. With permission.)

© 1999 by CRC Press LLC

scattering (Niehus et al., 1993), low-energy backscattered electrons (De Crescenzi, 1995), and even sec-
ondary electron holography (Chambers, 1992), which we will not discuss. Other contributors to this
book address scanning probe microscopy and tribology, which are also nicely covered in an extensive
review article by Carpick and Salmeron (1997).

3.4.1 Low-Energy Electron Diffraction

Since LEED is a diffraction technique, when viewing a LEED pattern, you are viewing the reciprocal
lattice structure and not the atomic locations on the surface. A LEED pattern typically is obtained by
scattering a low-energy electron beam (0 to 300 eV) from a single-crystal surface in ultrahigh vacuum.
In Figure 3.13 we show the LEED pattern for the W(110) surface with a half monolayer of oxygen adsorbed
on it (Ferrante et al., 1973). We can first notice in Figure 3.13a that the pattern looks like the direct lattice
W(110) surface, but this only means that the diffraction pattern reflects the symmetry of the lattice.
Notice that in Figure 3.13b extra spots appear at

½

order positions upon adsorption of oxygen. Since
this is the reciprocal lattice, this means that the spacings of the rows of the chemisorbed oxygen actually
are at double the spacing of the underlying substrate. In fact, the interpretation of this pattern is more
complicated since the structure shown would not imply a


is the wavelength of the incident radiation,
and

n

is an integer indicating the order of diffraction. Only certain values of

θ

are allowed where
diffractions from different sets of parallel planes add up constructively. There is another simple method
for picturing the diffraction process known as the Ewald sphere construction (Kittel, 1986), where it can
be easily shown that the Bragg condition is equivalent to the relationship

FIGURE 3.13 LEED pattern for (a) clean and (b) oxidized tungsten (110) with one half monolayer of oxygen. The
incident electron beam energy for both patterns is 119 eV. (From Ferrante, J. et al. (1973), in Microanalysis Tools and
Techniques (McCall, J. L. and Mueller, W. M., eds.), Plenum Press, New York. With permission.)
2dnsin θλ=
© 1999 by CRC Press LLC
(3.11)
where
→
k is the wave vector (2π/λ) of the incident beam,
→
k′ is the wave vector of the diffracted beam, and
→
G is a reciprocal lattice vector. The magnitude of the wave vectors k = k′ are equal since momentum is
conserved; i.e., we are only considering elastic scattering. Therefore, a sphere of radius k can be con-
structed, which when intersecting a reciprocal lattice point indicates a diffracted beam. This is equivalent

composition, processing history, and structural characteristics, the highest resolution examination tools
are needed. In this section we will limit the discussion to electron microscopy techniques using commonly
available equipment and capable or achieving atomic-scale resolution. Traditional scanning electron
microscopy (SEM), therefore, will not be discussed, although in tribology SEM has been and should
continue to prove very useful, particularly when combined with X-ray spectroscopy. Many modern Auger
electron spectrometers (discussed in the next section on surface chemical analysis) also have high-
resolution scanning capabilities, and thus can perform imaging functions similar to a traditional SEM.
Another technique not discussed here is photoelectron emission microscopy (PEEM). While PEEM can
routinely image photoelectron yield (related to the work function) differences due to single atomic layers,
lateral resolution typically suffers in comparison to SEM. PEEM has been applied to tribological materials,
however, with interesting results (Montei and Kordesch, 1996).
Both transmission electron microscopy (TEM) and scanning transmission electron microscopy
(STEM) make use of an electron beam accelerated through a potential of, typically, up to a few hundred
thousand volts. Generically, the parts of a S/TEM consist of an electron source such as a hot filament or
field emission tip, a vacuum column down which the accelerated and collimated electrons are focused
by usually magnetic lenses, and an image collection section, often comprising a fluorescent screen for
immediate viewing combined with a film transport and exposure mechanism for recording images. The
sample is inserted directly into the beam column and must be electron transparent, both of which severely
limit sample size. There are numerous good texts available about just TEM and STEM (e.g., Hirsch et al.,
1977; Thomas and Goringe, 1979).
An advantage to probing a sample with high-energy electrons lies in the De Broglie formula relating
the motion of a particle to its wavelength
(3.12)
where λ is the electron wavelength, h is the Planck constant, m is the particle mass, and E
k
is the kinetic
energy of the particle. An electron accelerated through a 100-kV potential then has a wavelength of
0.04 Å, well below any diffraction limitation on atomic resolution imaging. This is in contrast with LEED,
for which electron wavelengths are typically of the same order as interatomic spacings. As the electron
beam energy increases in S/TEM, greater sample thickness can be penetrated with a usable signal reaching

trometer can be added to the S/TEM. Particularly for STEM, due to minimal beam spreading during
passage through the sample the analyzed volume for either spectrometer can be as small as tens of
nanometers in diameter. X-ray and electron energy-loss spectrometers are somewhat complementary in
their ranges of easily detected elements. Characteristic X rays are more probable when exciting the heavier
elements, while electron energy losses due to light element K-shell excitations are easily resolvable.
Both TEM and STEM rely on transmission of an electron beam through the sample, placing an upper
limit on specimen thickness which depends on the accelerating voltage available and on specimen
composition. Samples are often thinned to less than a micrometer in thickness, with lateral dimensions
limited to a few millimeters. An inherent difficulty in S/TEM sample preparation thus is locating a given
region of interest within the region of visibility in the microscope, without altering sample characteristics
during any thinning process needed. For resolution at an atomic scale, columns of lighter element atoms
are needed for image contrast, so individual atoms are not “seen.” Samples also need to be somewhat
vacuum compatible, or at least stable enough in vacuum to allow examination. The electron beam itself
may alter the specimen by heating, by breaking down compounds within the sample, or by depositing
carbon on the sample surface if there are residual hydrocarbons in the microscope vacuum. In short,
S/TEM specimens should be robust under high-energy electron bombardment in vacuum.
3.4.3 Field Ion Microscopy
For many decades, FIM has provided direct lattice images from sharp metal tips. Some early efforts to
examine contact adhesion used the FIM tip as a model asperity, which was brought into contact with
various surfaces (Mueller and Nishikawa, 1968; Nishikawa and Mueller, 1968; Brainard and Buckley,
1971, 1973; Ferrante et al., 1973). As well, FIM has been applied to the study of friction (Tsukizoe et al.,
1985), the effect of adsorbed oxygen on adhesion (Ohmae et al., 1987), and even direct examination of
solid lubricants (Ohmae et al., 1990).
In FIM a sharp metal tip is biased to a high negative potential relative to a phosphor-coated screen in
an evacuated chamber backfilled to about a millitorr with helium or other noble gas. A helium atom
impinging on the tip experiences a high electric field due to the small tip radius. This field polarizes the
atom and creates a reasonable probability that an electron will tunnel from the atom to the metal tip
leaving behind a helium ion. Ionization is most probable directly over atoms in the tip where the local
radius of curvature is highest. Often, only 10 to 15% of the atoms on the tip located at the zone edges
and at kink sites are visible. The helium ions are then accelerated to a phosphorescent screen at some

multiplier for ions or electrons. And, finally, the spectrogram tells what materials are present and, it is
hoped, how much is there.
FIGURE 3.15 Field ion microscope pattern of a clean tungsten tip oriented in the (110) direction. (From Ferrante,
J. et al. (1973), in Microanalysis Tools and Techniques ( McCall, J. L. and Mueller, W. M., eds.), Plenum, Press New
York. With permission.)
© 1999 by CRC Press LLC
3.5.1 Auger Electron Spectroscopy
The physics of the Auger emission process is shown in Figure 3.16. An electron is accelerated to an energy
sufficient to ionize an inner level of an atom. In the relaxation process an electron drops into the ionized
energy level. The energy that is released from this de-excitation is absorbed by an electron in a higher
energy level, and if the energy is sufficient it will escape from the solid. The process shown is called a
KLM transition, i.e., a level in the K-shell is ionized, an electron decays from an L-shell, and the final
electron is emitted from an M-shell. Similarly, a process involving different levels will have corresponding
nomenclature. The energy of the emitted electron has a simple relationship to the energies of the levels
involved, depending only on differences between these levels. The relationships for the process shown are
(3.13)
giving
(3.14)
Consequently, since the energy levels of the atoms are generally known, the element can be identified.
There are surprisingly few overlaps for materials of interest. When peaks do overlap, other peaks peculiar
to the given element along with data manipulation can be used to deconvolute peaks close in energy.
AES will not detect hydrogen, helium, or atomic lithium because there are not enough electrons for the
process to occur. AES is surface sensitive because the energy of the escaping electrons is low enough they
cannot originate from very deep within the solid without detectable inelastic energy losses. The equipment
is shown schematically in Figure 3.17. The dispersion of the emitted electrons is usually accomplished
by any of a number of electrostatic analyzers, e.g., cylindrical mirror or hemispherical analyzers. Although
the operational details of the analyzers differ somewhat, the net result is the same.
An example spectrum is shown in Figure 3.18 for a wear scar on a pure iron pin worn with dibutyl
adipate with 1 wt. % zinc-dialkyl-dithiophosphate (ZDDP). This spectrum corresponds to the first
derivative of the actual spectral lines (peaks) in the spectrum (Brainard and Ferrante, 1979).

useful in tribology since you are often dealing with rough, inhomogeneous surfaces. We show a sample
SAM map in Figure 3.19.
Depth profiling is the process of sputter-eroding a sample by bombarding the surface with ions while
simultaneously obtaining AES or other spectra. This enables one to obtain the composition of reaction-
formed or deposited films on a surface as a function of sputter time or depth. Consequently, AES has
many applications for studying tribological and other surfaces. Some examples will be given in subsequent
sections.
3.5.2 X-Ray Photoelectron Spectroscopy
The physical processes involved in XPS are diagrammed in Figure 3.20. XPS is a simpler process than
AES. An X-ray photon ionizes the inner level of an atom and in this case the emitted electron from the
ionization is itself detected, as opposed to AES where several levels are involved in the final electron
production. The dispersion and detection methods are similar to AES.
FIGURE 3.19 Example scanning Auger microscopy results. Sample is silicon carbide fiber-reinforced titanium
aluminide matrix composite. Single element images as labeled, with higher concentrations represented as brighter
regions. (Courtesy of Darwin Boyd).
FIGURE 3.20 XPS transition diagram for an atom. (From Ferrante, J. (1993), in Surface Diagnostics in Tribology
(K. Miyoshi and Y. W. Chung, eds.), World Scientific, Singapore. With permission.)
© 1999 by CRC Press LLC
Monochromatic, incoming X-ray photons are generated from an elemental target such as magnesium
or aluminum. Measurement of the energy distribution of emitted electrons from the sample permits the
identification of the ionized levels by the simple relation
(3.15)
Since the final energy is measured and the X-ray energy is known, one can determine the binding
energy and consequently the material. AES peaks are also present in the XPS spectrum. AES peaks can
be distinguished from the fact that the energies of the Auger electrons are fixed because they depend on
a difference in energy levels, whereas the XPS electron energies depend on the energy of the incident
X ray. A sample XPS spectrum is shown in Figure 3.21 and a schematic diagram of the apparatus is shown
in Figure 3.22.
XPS can perform chemical as well as elemental analysis. As stated earlier, when an element is in a
compound, there is a shift in energy levels relative to the unreacted element. Unlike AES, where energy

elements in the ppm range (Wilson et al., 1989). A comprehensive discussion of the SIMS technique has
been published by Benninghoven et al. (1987).
The SIMS technique typically used in surface studies gives partial monolayer sensitivity using small
incident ion currents (“static” SIMS). Higher ion beam currents, often rastered, give species information
as a function of sputter depth (“dynamic” SIMS or SIMS depth profiling). SIMS instrumentation can be
roughly categorized by the type of ion detector used, e.g., quadrupole, magnetic sector, or time-of-flight,
with their inherent differences in sensitivity and lateral and mass resolution. As well, the incident angle,
energy, and type (e.g., noble gas, cesium, or oxygen) of the primary ion sputtering beam employed can
greatly affect the magnitude and character of the secondary ion yield.
SIMS has several complexities. SIMS only detects secondary ions, rather than all of the sputtered
species, which can lead to difficulty in quantification. Large molecules on the surface such as hydrocarbon
lubricants or typical additives can exhibit complex patterns of possible fragments. A knowledge of the
adsorbate and cracking patterns is often needed for interpretation. As well, multiply ionized fragments
or simply different species may overlap in the spectra, having nearly identical charge-to-mass ratios. As
a simple example, carbon monoxide (CO) and diatomic nitrogen (N
2
) overlap, requiring examination
of other mass fragments to distinguish between the two. As with depth profiling for either AES or XPS,
depth resolution “smearing” can occur either due to ion beam mixing of near-surface species or due to
the development of surface topography after long times under the ion beam. Despite these potential
limitations, SIMS should remain the technique of choice for many low detection limit, high surface
sensitivity studies (Zalm, 1995).
3.5.4 Infrared Spectroscopy
IRS is particularly useful in detecting lubricant films on surfaces. It can provide binding and chemical
information for adsorbed large molecules. It has an additional advantage in that it is nondestructive.
Incident electrons in AES can cause desorption and decomposition even for aluminum oxide, and can
be very destructive for polymers. Similarly, the emitted electrons can cause destruction of some films for
both AES and XPS. In IRS, the specimen is illuminated with infrared light of well-defined energy. If the
FIGURE 3.22 Schematic diagram of XPS apparatus. (From Ferrante, J. (1993), in Surface Diagnostics in Tribology
(K. Miyoshi and Y. W. Chung, eds.), World Scientific, Singapore. With permission.)