07 Nasdala et al.qxd

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EMU Notes in Mineralogy, Vol. 6 (2004), Chapter 7, 281–343
Raman spectroscopy: Analytical perspectives in
mineralogical research
LUTZ NASDALA1*, DAVID. C. SMITH2, REINHARD KAINDL3 and
MARTIN A. ZIEMANN4
1
Institut für Geowissenschaften – Mineralogie, Johannes Gutenberg-Universität,
D-55099 Mainz, Germany
2Muséum National d’Histoire Naturelle & CNRS, Bâtiment de Minéralogie,
61 Rue Buffon, 75005 Paris, France
3Institut für Mineralogie und Petrologie, Karl-Franzens-Universität,
A-8010 Graz, Austria
4Institut für Geowissenschaften – Mineralogie, Universität Potsdam,
D-14476 Potsdam, Germany;
*e-mail: [email protected]
Introduction
It is said that during a voyage to Europe in the summer of 1921, the Indian physicist
Chandrasekhara Venkata Raman (1888–1970) looked at the wonderful blue opalescence of
the Mediterranean Sea and questioned where the sea’s blue colour came from and why it
should be different from the sky’s blue. Raman started a series of experiments to address
these questions, and he found the blue colour of the sea was not merely due to simple
reflection of the sky in water, as most people imagined, but was additionally affected by
molecular scattering of light. This led to the discovery of a new inelastic scattering process
that is the optical analogue of the “Compton effect”; it is nowadays known as the “Raman
effect”. It describes a change in the wavelength of light that occurs when a light beam
interacts with molecular vibrations. The possibility for such interaction between matter and
light had already been predicted theoretically by Smekal (1923). The first verification was
obtained by Raman and Krishnan (1928) in light scattering experiments on liquids. Only
two years later, Sir C.V. Raman (who was knighted in 1929) was the Nobel laureate in
physics, honoured for his work on the scattering of light and the discovery of the effect
named after him. In his Nobel lecture, given on 11th December 1930, Sir C.V. Raman said
“The frequency differences determined from the spectra, the width and character of the
lines appearing in them, and the intensity and state of polarization of the scattered
radiations enable us to obtain an insight into the ultimate structure of the scattering
substance. […] It follows that the new field of spectroscopy has practically unrestricted
scope in the study of problems related to the structure of matter.” In 1948, he founded the
Raman Research Institute in Bangalore, India, with funds from private sources.
Raman spectroscopy has become an important and versatile spectroscopic
technique that is nowadays commonly used in many scientific and industrial disciplines.
The traditional fields in which Raman spectroscopy has a long and well-established
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history and tradition are condensed matter physics and chemistry. In the Earth sciences,
in contrast, Raman was for long applied with restraint, even though the second
publication dealing with the Raman effect (Landsberg & Mandelstam, 1928) had already
described the Raman scattering observed in mineralogical samples. With this statement,
we would not like to discount many excellent Raman studies on minerals that were done
prior to the 1980s. It is, however, a fact that for a long time there existed only a limited
number of Raman laboratories dealing with geoscientific problems (in contrast, there
exists at least one infrared spectrometer system at almost every mineralogy institute
across Europe). The formerly hesitant use of Raman spectroscopy in mineralogy was
most probably related to experimental difficulties, which in turn are due to the fact that
natural minerals are, in contrast to synthetic chemical substances or semiconductor
samples, rich in chemical impurities, microinclusions and structural defects. These
sample-related problems do still exist, but they can be managed today owing to the
availability of particularly powerful Raman spectrometer systems equipped with
sensitive detectors.
This paper is written for mineralogists and geologists who are interested in Raman
spectroscopy and would perhaps like to start using this technique in their own research.
Correspondingly, this paper will be focussed on the two major questions that are of
interest for “Raman beginners”, namely, how Raman works, and to what kinds of
samples it may be applied. The theoretical and experimental sections will indeed remain
on an introductory level, and techniques such as RRS (resonance Raman spectroscopy),
SERS (surface-enhanced Raman scattering) and nano-Raman spectroscopy (also known
as near-field Raman) will not be discussed. We consider that it is more important to deal
in depth with selected aspects and potential problems related to the recording and
interpretation of Raman spectra, and to provide the reader with some basic information
on the Raman terminology that is needed when working with the Raman literature. The
overview of applications is a selection of examples chosen by the authors, aiming to
underline the versatility of the Raman technique. Even though this paper provides the
reader with an extensive list of references, these references do not claim to be
comprehensive, as they cover only a small fraction of what has been done thus far. As a
demonstration of the practical use of particular analytical advantages of the Raman
technique, we discuss in more detail five examples of its application to mineralogy.
Theoretical background and practical aspects
The Raman Effect
Electrodynamical model
The electric field vector of visible light (wavelength = 400–750 nm) oscillates at a high
frequency 0 in the range 4.0–7.5 · 1014 s–1. When such radiation is applied to a molecule or
crystal lattice, a coherence between the electrons rotating around the atomic nuclei and the
radiation is established, and a charge separation oscillating at the same frequency as the
electromagnetic wave (0) is produced. This vibrational energy is in most cases immediately
released by the production of diffuse, elastically scattered light having the same frequency
and wavelength as the incident beam of light. This process is called Rayleigh scattering.
Raman spectroscopy: Analytical perspectives in mineralogical research
283
Atoms in a mineral, as well as in liquids and gases and other forms of matter,
vibrate at frequencies 1 on the order of 1012–1014 s–1 (i.e., 1 0). Due to the
considerable frequency difference, the excitation of vibrations of the nuclei through
simple absorption of incident light is impossible. However, the oscillating electric
field of the light can interact with atomic vibrations in an inelastic scattering process,
the so-called Raman scattering. The possibility of such interaction is visualised by the
following consideration. The nuclei of atoms in the sample are too heavy to follow
the high-frequency vibration (0) of the electric field vector of the incident light. As
a result, a time-dependent dipole moment () is induced by the electromagnetic wave.
(In contrast, in the absence of radiation on average there is no charge separation and
no dipole moment is created, or no variation of the dipole moment is created if the
molecule possesses a dipole moment.) This induced dipole moment changes with
time according to
(t ) E0 cos( 0t ) ,
(1)
in which E0 cos( 0t ) describes the strength of the oscillating electric field of the light, and is the electric polarisability tensor of the molecule or crystal. The polarisability is also
not a constant but varies with time, because the ability of electrons to be displaced with
respect to their corresponding nuclei must depend on the actual positions of nuclei.
Therefore, is strongly controlled by the vibrations of atoms (1) in the sample.
Raman scattering can, largely simplified, be described as the product of the
interaction of the time-dependent dipole moment induced by the electromagnetic wave
and the electromagnetic wave itself. It is possible that the light-induced deformation of
the electron cloud excites the nuclei to vibrate. However, deformation of the electron
cloud as induced by vibrations of nuclei may also have an exciting effect on the electric
field and, with that, the vibration of the light. Both of these cases have in common that
two vibrations with significantly different frequencies (0 and 1) modulate one another.
Their interaction – called the Raman effect – is controlled by the polarisability . This
is the main difference to infrared (IR) absorption, where vibrations of light and
vibrations of the sample have the same frequency and the interaction depends on the
dipole moment (see Fig. 1).
Fig. 1. Raman and infrared activity depending on the dipole moment () and polarisability (), elucidated with
the example of stretching vibrations of the linear CO2 molecule. The symmetric stretching vibration is Ramanactive ( oscillates) but not IR-active (no induced dipole moment). By contrast, the anti-symmetric stretching
vibration is IR-active but nearly Raman inactive. Picture redrawn from Schmidt (1994).
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It can be seen from Figure 1 that in a first, very rough, approximation, symmetric
vibrations (which are connected with significant changes of ) are strongly Raman-active
whereas antisymmetric vibrations (connected with the induction of a dipole moment )
are strongly IR-active. This rule, however, holds strictly only for molecules possessing a
centre of symmetry. The Raman and/or IR activity or inactivity of vibrational modes,
respectively, is described by the “selection rules” (e.g., Rousseau et al., 1981).
Quantum-mechanical model
Another way to describe the Raman Effect is based on the quantisation of the matter by
taking into account the vibrational states of molecules and crystals. Similar to light
energy, vibrational levels cannot have any arbitrary amount of energy; rather there exist
smallest possible energy portions (vibrational quanta, in solids, are usually called
phonons). Correspondingly, the vibrational states of a molecule or crystal are
characterised by a limited number of allowed, discrete energies. Upon irradiation with a
beam of light, a molecule or crystal can be transferred to a higher energy (excited) state
through the absorption of a light photon and the excitation of a vibrational phonon. A
necessary condition for the absorption, however, is that the energy of the incoming
photon (E = h0; where h is Planck’s constant) is equivalent to the energy difference
between two allowed vibrational states of the molecule or crystal. This is the case for
light in the infrared (IR) range, and such genuine absorption is detected using the IR
absorption spectroscopy technique (Fig. 2, sketch 1).
Fig. 2. Elucidation of the light-molecule interaction using a simplified energy level diagram. (1) Light can be
absorbed when its photon energy corresponds to the energy difference between two allowed vibrational levels.
The absorption of a photon generates a phonon (vibrational quantum) with the same energy. Such interaction
of molecules is possible with middle to far infrared light. (2) Visible light, by contrast, cannot be absorbed
through phonon excitation in the molecule, because its photon energy is much higher than energy differences
between vibrational states of the molecule. The excitation with visible light leads to a virtual electronic state
from which the system recovers immediately. The molecule will in most cases have the same vibrational state
as before the interaction and, correspondingly, the photon energy of the scattered light (Rayleigh scattering)
corresponds to the initial value. (3) Very rarely, the molecule may reach a higher or lower vibrational state than
before the interaction. The phonon energy of such scattered light (Raman scattering) is either somewhat
decreased or increased with respect to the exciting photon. This photon energy difference (energy shift; Raman
shift) corresponds to the energy difference between vibrational levels of the molecule.
Raman spectroscopy: Analytical perspectives in mineralogical research
285
The phonon energy of visible (and ultraviolet and near IR) light is, by contrast, much
higher than energy differences between the vibrational states of molecules and crystals and,
therefore, direct photon absorption under simultaneous excitation of a phonon is
impossible. The incident light will excite the system to a virtual high-energy state from
which it recovers immediately. As a rule, the diffusely scattered light will then have the
same photon energy and, thus, the same frequency as the incident light (Rayleigh
scattering; Fig. 2, sketch 2). It may, however, also happen (even though with low
probability) that the system recovers to a higher or lower energetic state when compared to
the initial value. If the system gains energy through the excitation of a phonon (E = h1),
the scattered photon [E = h(0 1)] has lost the same energy portion (Stokes-type Raman;
Fig. 2, sketch 3a). At temperatures above absolute zero, all matter vibrates. Therefore, it is
also possible that an already vibrating system is excited, and such a system may instead
lose vibrational energy through the interaction with the light. Here, the scattered photon
(anti-Stokes Raman; Fig. 2 sketch 3b) has increased in energy [E = h(0 + 0)]. It is clear
that the intensity ratio of Stokes and anti-Stokes type Raman light must depend on the ratio
between molecules in the ground and excited state; it therefore depends on temperature.
Interpretation of spectra
The Raman spectrum
The above considerations describe the Raman effect as comprising two possible
interactions. When a portion of the energy of the exciting light is used to excite a
vibration in the sample, the Raman scattered light (Stokes; = 0 1) will, due to its
partial energy loss, experience a red shift in the electromagnetic spectrum. The opposite
case is the loss of vibrational energy in the sample in favour of an increase in light
energy. The anti-Stokes Raman light ( = 0 1) is, therefore, blue-shifted with respect
to the excitation frequency. Consequently, the spectrum of scattered light obtained from
a sample irradiated with an incident beam of light consists of three principal parts,
namely, the intense Rayleigh line and weak Raman bands in the Stokes and anti-Stokes
parts of the spectrum (Fig. 3). For a liquid, the ratio between Rayleigh and Raman
scattered light is expected to be about 105:1. Note that generally only the Stokes Raman
bands are recorded. This is because the shifts of a Stokes Raman band and its
corresponding anti-Stokes counterpart are equal in energy [E = (h1)] but Stokes
bands are always higher in intensity (Fig. 3) and, therefore, are more easily detected.
ARaman spectrum is a plot of light intensity (usually given in counts, counts per second
or arbitrary units) versus photon energy. In vibrational spectroscopy, it is unusual to express
the photon energy by the frequency or wavelength of the light (an exception is Brillouin
spectroscopy; light scattered through the interaction with low-frequency acoustic vibrations
is mostly plotted as intensity versus frequency). Instead, frequencies or wavelengths are
generally transformed into wavenumbers (v~). The wavenumber is defined as
1
~ ,
c (2)
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Fig. 3. Comparison of the Stokes and anti-Stokes parts of the Raman spectrum. Spectrum of crocoite
(Callenberg, Germany) excited with the Ar+ 514.5 nm line (which corresponds to 19435 cm–1). Raman bands
in the Stokes and anti-Stokes parts of the spectrum have the same Raman shift values (= relative wavenumbers,
with 0 cm–1 Raman shift set at the Rayleigh line). Note that Stokes bands are always higher in intensity than
their anti-Stokes counterparts, with the intensity ratio increasing with increasing Raman shift. Note also that
some workers use an opposite convention, with Stokes called negative and anti-Stokes called positive on the
grounds that the Stokes Raman bands are actually lower in absolute cm–1 than the Rayleigh line. To elucidate
the interrelation of absolute and relative wavenumbers, frequencies and wavelengths, the x axis is given with
three additional scales at the top.
where c is the speed of light; the unit of the wavenumber is cm–1. Wavenumbers (or more
exactly, absolute wavenumbers) are generally also used for the presentation of IR
absorption spectra. In Raman spectroscopy, however, the use of absolute wavenumbers
would be impractical, because the wavelength and, with that, the absolute wavenumber
of each obtained Raman band (v~) must always depend on the wavenumber of the
v 1, which corresponds to a
incident light (v~0). However, only the wavenumber shift ~
specific vibration in the sample, is of analytical interest. It has, therefore, become usual
to express Raman shifts using their relative wavenumber (i.e., the wavenumber
v 0–v~). By convention, the Rayleigh
difference between incident and scattered light; ~
v1 = ~
line is set at zero Raman shift and anti-Stokes Raman bands have negative and Stokes
Raman bands have positive relative wavenumbers (despite the fact that Stokes Raman
bands have a decreased absolute wavenumber). For the interdependence of relative and
absolute wavenumber, wavelength and frequency see Figure 3.
Vibrations of molecules and crystal lattices
We have elucidated above that Raman shifts correspond to frequencies of vibrations in the
sample, i.e., each band in a Raman spectrum represents the interaction of the incident light
with a certain vibration of the nuclei. The vibrations of the nuclei, in turn, are controlled
by the sizes, valences and masses of the atomic species of which the sample is composed,
the bond forces between these atoms, and the symmetry of their arrangement in the crystal
structure (bond directions). These factors affect not only the frequencies of atomic
vibrations and the observed Raman shifts, respectively, but also the number of observed
Raman spectroscopy: Analytical perspectives in mineralogical research
287
Raman bands, their relative intensities, their widths (typically expressed as FWHM, “full
width at half band maximum intensity”) and their polarisations. Therefore, Raman spectra
are highly specific for a certain type of sample and can be used for the identification and
structural characterisation of unknown samples.
One of the most challenging tasks in vibrational spectroscopy (Raman as well as IR
absorption and Brillouin spectroscopy) is the reliable assignment of observed bands to
certain vibrations in the sample. All vibrations, i.e., collective movements of atoms, are
complicated combinations of the so-called normal vibrations or normal modes of the
respective molecule or crystal. The number of potentially occurring normal vibrations
(note: not necessarily all of them are Raman-active) depends on the number of
dynamical degrees of freedom of the system. For a single molecule consisting of n
atoms, there are 3n – 6 degrees of vibrational freedom (three for each atom, minus three
rotational and three translational principal movements of the entire molecule in the three
dimensions of space). Linear molecules have 3n – 5 degrees of vibrational freedom,
because the rotation around the main molecule axis does not produce any change of
rotational energy. To give two examples, for the hydroxyl group (a diatomic molecule)
we calculate only (3 2) – 5 = 1 vibration (stretching along the OH bond) and for the
triatomic, non-linear water molecule (3 3) – 6 = 3 vibrations (symmetric and
antisymmetric stretching along the OH bonds and bending of the HOH angle; see
Fig. 1 in Beran et al., 2004 in this volume). A mineral or other crystal (normally
consisting of >> 1020 atoms) can be considered as a single molecule of almost infinite
size, which would result in a correspondingly huge number of degrees of vibrational
freedom. In contrast, the number of observed vibrations is always limited. This is due to
the periodic arrangement of atoms in the crystal lattice (i.e., identical environments give
identical energy shifts), which leads to a comparably small number of longitudinal and
transversal lattice vibrations. In general, consideration of the vibration of a mineral
lattice can be reduced to the corresponding primitive unit cell and its degrees of
vibrational freedom.
It has become commonplace to subdivide the vibrations of a crystal lattice into
internal vibrations of molecular units and external vibrations. An example is given in
Figure 4, which elucidates the general band assignment for four different minerals
4–
containing PO3–
4 or SO4 molecular groups. Internal stretching and bending vibrations of
these tetrahedral XO4 groups have Raman shifts in the range 400–1200 cm–1 whereas
external vibrations (involving movements of the entire XO4 groups as well as their
neighbouring ions) are observed well below 400 cm–1. Differences between the four
spectra are due to (1) the tetrahedra having different central ions, (2) different degrees of
distortion of the XO4 groups in the four crystal structures, and (3) different bond strengths
between tetrahedra and neighbouring atoms. Other typical examples for internal
vibrations in minerals are hydroxyl stretching vibrations in OH-bearing species, internal
CO3 vibrations in carbonates, or internal SiO4 vibrations in nesosilicates. By contrast, it is
not meaningful to discuss internal SiO4 modes in tectosilicates. Here, internal and external
bond forces are rather similar and, therefore, the SiO4 tetrahedron is decidedly not a more
or less isolated molecule. It is likewise difficult to discuss the occurrence of independent
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Fig. 4. Assignment of Raman bands, shown with the example of spectra obtained from apatite (Slyudyanka,
Siberia), monazite (Moss, Norway), anglesite (Tsumeb, Namibia) and barite (Freiberg, Germany). Despite the
four minerals having different lattice types and containing tetrahedral XO4 groups (X = S, P) that are surrounded
by different ions, all four spectra show widely similar fingerprint patterns of four groups of internal vibrations
of the XO4 groups, and all spectra are dominated by an intense 1(XO4) band (symmetric stretching of XO4
tetrahedra) in the range 960–990 cm–1. Examples for movements of atoms as they would occur in an isolated
tetrahedron are shown with small sketches (compare Siebert, 1966; Smith & Carabatos-Nédelec, 2001).
internal vibrations of (Al,Mg,Fe)(O,OH)6 octahedrons in sheet silicates. Due to strong Si
O bond forces, any atomic movement in the octahedral sheet may be accompanied by
similarly intense atomic movements in the tetrahedral sheet and, consequently,
octahedrons ought not be treated as if they would occur isolated in the structure
(McKeown et al., 1999a, 1999b). Such coupling of internal vibrations with the
surrounding lattice does always exist but varies widely in strength. The subdivision into
internal and external modes is meaningful only if internal bond forces of the molecular
unit are much stronger than bond forces to the surrounding atoms in the mineral structure.
There exists in the Raman literature several nomenclatures for the description of
Raman modes and their corresponding vibrations and, unfortunately, these are not used
uniformly in the literature. We cannot give a complete overview here; rather we will
briefly discuss three of the most common nomenclatures. Vibrational modes are often
described by symbols that refer to irreducible representations (cf. group theory;
references listed below); these symbols consist of capital letters with subscript letters
and numbers (for example, A1g mode or Eu mode). Here, the capital letter gives
information on the degeneration (if two different vibrations have the same frequency,
i.e., they are equal in phonon energy, this is referred to one degenerate mode) and
symmetry. A and B modes are single vibrations (expressed as either not degenerate or
single degenerate), with A modes being symmetric and B modes antisymmetric with
respect to the main symmetry axis. E modes are doubly and F modes (the latter only
occurring in lattices with high symmetry) are triply degenerate. The subscripts g and u
are used to describe modes that are respectively symmetric (g = gerade) and
antisymmetric (u = ungerade) with respect to the symmetry centre. It is clear from the
Raman spectroscopy: Analytical perspectives in mineralogical research
289
above elucidations that g-type vibrations are in general Raman-active whereas u-type
vibrations are IR-active (see again Fig. 1). The subscript numbers may refer to
symmetries that are different with respect to the main symmetry axis, or they are simply
used to number consecutively types of vibrations which otherwise would not be
sufficiently distinguished. Another common nomenclature is the notation for modes.
The notation should not be confused with the Greek letters symbolising types of
vibrational movements (Table 1). Vibrations (or rather groups of vibrations) in a
molecule or crystal are numbered consecutively 1, 2, 3, … to avoid the need to specify
symmetry details. For internal vibrations, it has become usual to put the respective
molecule or group in brackets. Although a generally accepted international standard does
not exist, there are agreements especially for notations of molecular or internal
vibrations. For instance, it is generally agreed to describe the symmetric stretching
vibration of phosphate groups (an A mode) as 1(PO4) mode (cf. Fig. 4).
Table 1. Basic types of vibrations and their description with Greek symbols.
Symbol
, Description
stretching (s = symmetric; a or as = antisymmetric)
bending
(s = symmetric; a or as = antisymmetric)
rocking
wagging
twisting
It is beyond the scope of the present paper to elucidate the band assignment
procedure and how frequencies of normal vibrations can be estimated. The least difficult
task is the assignment of internal modes (provided there exist more or less isolated
molecular units in the mineral structure), whereas the assignment of external modes is
much more challenging. Conclusions by analogy may be drawn from the Raman spectra
of unknowns through comparison with spectra of known phases with more simple
structures; however, such conclusions may remain tainted with some uncertainty. One
empirical approach is to systematically synthesise minerals with just one atom type
replaced by another of identical charge but different atomic mass and hence ionic radius,
such as Si4+ by Ge4+ or Al3+ by Ga3+ (e.g., Tlili and Smith, 1996), or by another isotope
of the same atom type, such as H+ by D+. In the latter case one can for example easily
identify O–H deformation vibrations (which occur at low wavenumbers and may be
easily confused with other Raman bands) as O–D shifts distinctly (Tlili, 1990). The
mathematical prediction of theoretical Raman spectra for a given mineral (including
information on band frequencies, intensities and polarisation) is extremely complex and
involves group theoretical calculations (e.g. Banerjee et al., 2003). This complexity is
underlined by the fact that it is not a static, but rather a dynamic system which is dealt
with (i.e., one does not only need to know atomic positions but also precise values for
inter-atomic bond forces, directions of atomic movements etc.). As a consequence, fully
reliable and detailed band assignment may be difficult, especially for minerals having a
low-symmetry lattice or/and a large number of atoms per unit cell.
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In a given mineral structure with only one kind of cation occupying a specific
site (e.g. Al3+ in the octahedra of garnet) a certain Raman band may be attributed to
vibration of this atom or of other atoms affected by this atom (regardless of precisely
which atoms vibrate, and how in terms of symmetry). This is the general case and is
called a unimodal vibration. In a solid solution like garnet there are numerous
homovalent cation exchanges, especially replacement of Ca2+ by Mg2+, Mn2+ or Fe2+
and also of Al3+ by Cr3+ or Fe3+. Many natural garnets contain all of these elements but
some Raman bands remain unimodal (e.g. internal SiO4 modes) and thus only shift in
their wavenumber which varies continously from one end-member to another (Pinet
& Smith, 1993). However, other bands are duplicated (bimodal behaviour) but at
different wavenumbers as a function of the different atomic masses and ionic radii,
and hence vibrational energies, of each of two isomorphous cations. Trimodal
behaviour was deduced in the Al3+–Cr3+–Fe3+ Ca-garnet ternary system by Pinet &
Smith (1993). Likewise in micas, a strong unimodal mode has often been described
as T–O–T vibration across the bridging oxygen between two adjacent TO4 tetrahedra.
Regardless whether this description is correct or not (there is some discussion on this
topic as the bridging oxygens are basal oxygens which compose a 2[Si2O3]2+ sheet
network), this unimodal vibration becomes trimodal as soon as some Si4+ is replaced
by Al3+ and it has been possible to distinguish Si–O–Si, Si–O–Al and Al–O–Al
vibrations (Tlili et al., 1989); this becomes hexamodal when some Si4+ is replaced by
Ge4+ or Al3+ is replaced by Ga3+ (Tlili, 1990; Tlili & Smith, 1996). Thus for a single
physically defined Raman vibration mode there are six chemically different Raman
bands, and it is of course rather difficult to distinguish which is which without
systematically synthesising pure end-members and also many mixed compositions
step by step along binary joins in order to be sure to correctly identify a band when
several Raman bands are simultaneously moving in wavenumber and also in relative
intensity (as well as overlapping).
Directional dependence of Raman scattering
The Raman scattering process is strongly controlled by geometrical factors (i.e., it
depends on the polarisation of the atomic vibration and the geometry of the scattering
experiment). An example of this is a hydroxyl stretching vibration. Here, Raman
scattering is only possible if the electric field vector of an incident beam of light is not
perpendicular to the OH bond direction (the oscillating electric field must have a vector
component other than zero parallel to the direction of the stretching movement to be
excited). In a trioctahedral mica such as phlogopite, all OH bonds of hydroxyl groups
in the octahedral sheets are oriented along c* (which is the direction perpendicular to the
crystallographic a–b plane; cf. Schroeder, 1990). Consequently, if a phlogopite is
irradiated with a laser beam propagation direction parallel to c*, no interaction is
possible, independent of the polarisation of the laser light (Fig. 5, beam 1). By contrast,
the hydroxyl stretching Raman band is obtained with maximum intensity if the incident
laser beam is irradiated along a direction within the crystallographic a-b plane and the
electric field vector is polarised perpendicular to this plane and thus vibrates parallel to
Raman spectroscopy: Analytical perspectives in mineralogical research
291
Fig. 5. An incident beam of light does only interact with the hydroxyl molecule (shown black) and excites it
to vibrate along the OH bond if the vibrating electric field has at least a vector component parallel to the O
H bond direction. In our case (simplified sketch of a part of a sheet silicate structure), beams 1 and 2 cannot
interact with the hydroxyl group. The OH Raman band is detected when the sample is excited with beam 3.
c* (Fig. 5, beam 3). This has been documented, for example, by Loh (1973) and Tlili et
al. (1989). Two analogous examples, showing extensive intensity changes of observed
Raman bands depending upon the sample orientation with respect to the polarisation
plane of the laser light, are presented in Figure 6.
Fig. 6. Two examples demonstrating that Raman-active vibrations may have strong directional dependence.
(a) Raman spectra of a gem-quality zircon crystal (non-metamict) from Haddam, Connecticut. For the band
assignment cf. Dawson et al. (1971) and Kolesov et al. (2001). (b) Raman spectra of a synthetic -quartz single
crystal (from Nasdala et al., 2004a; redrawn and modified). For the band assignment cf. Scott & Porto (1967)
and Etchepare et al. (1974). Scattering geometries are reported using the so-called Porto notation (cf. Damen
et al., 1966). Note that apparently different Raman band patterns may simply be due to internal variations of
band intensity ratios, which must be considered when applying Raman as a fingerprinting technique.
The geometry of the scattering experiment, including the polarisations and directions of
propagation of incident and analysed scattered light with respect to the crystallographic
orientation of the sample, is usually given by the so-called Porto notation (Damen et al., 1966).
For example, in X(YZ)Y, or analogously x(yz)y or a(bc)b, the first and last letter describe the
directions of the incident beam and the analysed Raman scattered light, and the two letters
inside the brackets describe their respective polarisation. The Porto notation Y(XZX)Ȳ (see Fig.
6a) contains the following information: In the brackets, information on the polarisation plane
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
of the laser light with respect to the crystallographic c axis is given, and it is said that no
polariser was used for the scattered light (i.e., all polarisation directions perpendicular to the
crystallographic a axis were allowed). According to the Y before the brackets, the light was
irradiated along the crystallographic b axis. TheȲ after the brackets gives the information that
incident and analysed light had opposite directions, i.e., the measurement was done in 180°
backscattering geometry. For completeness, the two other principal scattering geometries are
90° scattering (Raman light collected perpendicular to the direction of the incident beam) and
0° forward scattering (Raman light parallel to the incident beam, i.e., analysed straight behind
the sample). Note that backscattering (or, more exactly, quasi-backscattering, because genuine
backscattering requires to use a parallel beam instead of a convergent beam) is mostly applied
for the Raman analysis of minerals, especially via a microscope objective, mainly because the
application of the other two geometries presumes suitable preparation of the sample.
The Porto notation gives complete geometric information for a certain scattering
experiment. However, a part of this information (namely, both of the light directions) is merely
of interest for the experimentalist, whereas only the information on the polarisation is
necessary for the band assignment. Therefore, it has become usual in the more recent literature
to use expressions that could be understood as “abbreviated Porto notations”. An expression
such as “aa geometry” or “aa polarisation” means that both the incident light and the Raman
scattered light were polarised parallel to the crystallographic a axis. This expression represents
six principally possible scattering geometries, namely b(aa)b, b(aa)b̄, b(aa)c, c(aa)b, c(aa)c
and c(aa)c̄, and in all of them Raman spectra would be obtained in which bands show the same
polarisation behaviour. Analogously, each “abbreviated Porto notation” giving non-identical
polarisation directions in brackets represents five principally possible scattering geometries
(for instance, b(ab)a, b(ab)c, c(ab)a, c(ab)c and c(ab)c̄ will yield the same polarisational
information and can be summarised by “ab polarisation”). There exists a total of 48 principal
permutations of the full Porto notation. Since, for instance, scattering experiments under ab
and ba geometry will give the same results, not more than six combinations (aa, ab, ac, bb, bc,
cc) are necessary to obtain the full information on the polarisation behaviour of Raman bands.
In the following, we will show briefly with the example of fluorapatite how the
directional dependence of vibrations and Raman bands affects the obtained spectra. This
mineral (Ca5(PO4)3F; Z = 2; hexagonal space group P63/m) has 33 Raman-active in
addition to 20 IR-active modes according to
vib = 12 Ag + 8 Au + 8 E1g + 12 E1u + 13 E2g
(3)
(e.g., Kravitz et al., 1968; Boyer & Fleury, 1974; Devarajan & Klee, 1981). The
polarisation and directional dependence of Raman-active modes is usually described by
the Raman tensors (Loudon, 1964). For the Raman-active vibrations of fluorapatite, the
following three tensors are applicable
axx
A 0
0
0
a yy
0
0
0
bzz 0
E1 0
c
zx
0
0
d zy
cxz d yz 0 exx
E2 f yx
0
f xy
eyy
0
0
0
0 (4)
Raman spectroscopy: Analytical perspectives in mineralogical research
293
(cf. Rousseau et al., 1981). It follows that with zz polarisation, only A modes are obtained.
The xz and yz symmetries would be the best candidates for the analysis of E1 modes, because
A and E2 modes are then forbidden. Finally, E2 modes are separately analysed under xy
geometry. For the simple fingerprinting analysis (such as the study of accessory apatite
grains in rock thin sections done under backscattering geometry) it follows, for instance, that
(independent of the polarisation) E2 modes can best be observed if the apatite crystal is cut
perpendicular to the crystallographic c axis: both the incident and the registered Raman light
paths would then be oriented parallel to c and, therefore, no z polarisation is possible.
For the same experimental setup, it is analogously concluded for the 12 Ramanactive modes in zircon (ZrSiO4, Z = 4, tetragonal space group I41/amd) that, according to
a 0 0
A 0 a 0 0 0 b
c 0 0
0 c 0 0 0 0 0 0 d B1 0 c 0 B2 c 0 0 E 0 0 d , 0 0 0 (5)
0 0 0
0 0 0 0 d 0 d 0 0 (cf. Loudon, 1964; Dawson et al., 1971), all B-type Raman bands are not seen when the laser
light is polarised parallel to the crystallographic c axis. This is in particular true for the strong
B1g-type vibration [3(SiO4) mode] at ~ 1008 cm–1 (cf. Fig. 6a), which is routinely analysed
to estimate the degree of radiation damage of zircon (Nasdala et al., 1995; Nasdala et al.,
2003a, and references therein). For such purposes, it is therefore advantageous to orient
mounts in such a way that the laser light polarisation is perpendicular to the crystallographic
c axis of the zircon crystal to be analysed, in order to get maximum intensity of the B1g mode.
For the detailed band assignment procedure on the basis of oriented Raman spectra see, for
example, Boyer & Fleury (1974) and Iqbal et al. (1977) for apatite-group minerals, and
Dawson et al. (1971), Syme et al. (1977) and Kolesov et al. (2001) for zircon.
It is also important to appreciate the consequences of changes in relative band
intensities due only to the “optical trajectory orientation effect” (Smith, 1996) due to
the angular dependence of reflection efficiencies of mirrors and other optical
components in each Raman spectrometer. For example if a crystal is placed vertically
under a microscope and analysed with Y(X ZX)Ȳ geometry and then analysed again with
the crystal rotated by 90° about the vertical axis (Y) and the incident laser polarisation
also rotated 90° by a half-wave plate, then the Porto notation will still be the same (as
X and Z have been interchanged twice concerning the laser and crystal relationships)
but the spectra will be somewhat different in relative intensities as X vibrations will be
preferentially diminished by the spectrometer with one crystal orientation but Z
vibrations with the other (as X and Z have been interchanged only once concerning
crystal and spectrometer relationships).
Another related point is that the entrance slit to many Raman spectrometers is parallel
(after various mirror reflections) to the polarisation direction of the incident laser; when this
is not the case (e.g. the DILOR® model XY®) and when the Raman scattered light does not
pass through a polariser, the normally intense A1g band of garnet is significantly diminished
in intensity relative to other bands (Smith, 1996). Note that garnet, although cubic and hence
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
optically isotropic, is nevertheless orientation-dependent with Raman spectroscopy because
of its space group (which, for example, lacks a normal tetrad axis).
In regard to the above examples, we would thus like to emphasise that the observation
of significant variations in relative intensities of Raman bands may simply be due to the
crystal orientation. The absence of a certain Raman band in a spectrum does not necessarily
mean the vibration does not exist. For the simple fingerprinting analysis of unknowns it is,
therefore, often advantageous to choose truly random sample orientations containing vector
components of all possible directions (for instance, the main axis of prismatic crystals
should neither be oriented parallel nor perpendicular to the laser polarisation). Alternatively,
after one spectral acquisition, a half-wave plate may be used to rotate the incident laser
polarisation by 90° and a new acquisition made immediately without changing any other
parameter (cf. Smith, 1996); this clearly displays the degree of the orientation dependency
(for the specific crystal vs. laser orientations employed) and adding the two spectra gives a
very first approximation to a spectrum which is “average” in terms of polarisation. For more
details on the theory of the Raman effect and aspects related to the band assignment and
interpretation of spectra, the reader is referred to the literature on this subject (e.g. Wilson et
al., 1955; Weeny, 1963; Fateley et al., 1972; Wooster, 1973; Long, 1977; Hayes & Loudon,
1978; Marfunin, 1979; Orlov et al., 1985; McMillan, 1985; Griffith, 1987; McMillan &
Hofmeister, 1988; Weidlein et al., 1988; Gardiner & Graves, 1989; Kuzmany, 1989;
Schmidt, 1994; Marfunin, 1995; Lewis & Edwards, 2001; Loudon, 2001).
Potential analytical artefacts
In addition to varying band intensity ratios as controlled by the geometry of the
scattering experiment, a certain mineral sample may yield quite different spectra when
being excited with a laser beam due to analytical artefacts. In the following, we will
discuss only two of these problem cases as examples. We do this aiming to direct the
reader’s attention to the necessity of a critical evaluation of obtained spectra.
A common problem of Raman spectroscopy, especially in the analysis of natural
minerals, is the emission of photoluminescence (PL) excited by the laser beam. We have
discussed above that the Raman scattering process has comparably little probability and, thus,
Raman bands are commonly low in intensity. The simultaneous emission of luminescence, by
contrast, can easily reach much higher intensity and, depending on the sample, it may surpass
the intensity of the Raman scattered light by several orders of magnitude. If this should be the
case, the Raman spectrum is likely to be fully obscured by the much stronger luminescence
signal. An example is the strong red ruby luminescence (e.g. Nasdala et al., 2004b in this
volume), whose occurrence makes it almost impossible to obtain the Raman spectrum of ruby
with red laser excitation. However, it is often possible, especially if the luminescence emission
consists of narrow bands, to find a suitable excitation wavelength with which the Raman
spectrum lies in a spectral range that is not affected by the luminescence signal (Fig. 7a). For
example, natural apatite may show broad-band luminescence in the range 475–660 nm, which
can be avoided by choosing an excitation wavelength either below (e.g. Ar+ 457.9 nm) or
above (e.g. Kr+ 676.4 nm) this range (see Nasdala, 1992). Analogously, the Raman spectrum
of ruby is obtained without difficulty with blue excitation.
Raman spectroscopy: Analytical perspectives in mineralogical research
295
Fig. 7. Analytical artefacts I: Potential effects of laser-induced PL on the Raman spectrum. (a)
Photoluminescence bands (marked “PL”) have certain frequencies independent of the excitation whereas
Raman bands (marked “R”) have certain shifts with respect to the excitation band. It is, therefore, possible to
avoid PL bands in the obtained Raman spectrum by selecting a suitable excitation wavelength. (b) Example
Raman spectra taken from the metamict zircon sample #1486 (Sri Lanka; sample courtesy of R.C. Ewing and
C.S. Palenik). The upper Raman spectrum, which was obtained with 514.5 nm excitation, is obscured by
narrow REE emission bands (marked with asterisks). This analytical artefact may corrupt the interpretation
because narrow PL bands are easily mistaken and erroneously interpreted as Raman bands of additional phases.
The lower spectrum, obtained with 632.8 nm excitation, shows only the band pattern of ZrO2. This observation
reveals decomposition of radiation-damaged ZrSiO4 into crystalline ZrO2 and amorphous SiO2 (the Raman
spectrum of the latter phase is not seen due to its low intensity), which can be caused by heat treatment of
metamict zircon at ~ 900–1100 °C (compare Nasdala et al., 2002).
If the laser-induced luminescence has only moderate intensity, it may still interfere with
the Raman spectrum and affect band fitting and interpretation. Luminescence is often
characterised by broad-band emissions with FWHMs 50 nm (compare Nasdala et al.,
2004b in this volume), which converts to several thousand cm–1. Because such luminescence
bands are much broader than Raman bands, it is easily possible to correct Raman spectra for
the broad-band luminescence background. In the case of narrow luminescence emissions,
however, it may be difficult to distinguish between Raman and luminescence bands. For
instance, laser-induced photoluminescence emissions of 4f electron elements can have
narrow FWHMs on the order of 0.1 nm. This converts to ~ 3 cm–1 for bands in the visible
range, which would be a typical value for FWHMs of Raman bands. Narrow PL emissions
are, therefore, often mistaken as Raman bands such that it is not possible to simply assign
narrow bands in the obtained spectra to Raman modes and broad bands to luminescence
emissions. Reliable distinction is only possible by obtaining multiple Raman spectra with
different excitation wavelengths. Raman bands will appear with equal Raman shifts in all of
the spectra (except for some semi-metals like gallium and the D and D’ bands in disordered
graphite). Luminescence emissions, by contrast, are characterised by a certain fixed
wavelength and absolute wavenumber, and must show different apparent Raman shifts in
spectra obtained with different excitation wavelengths. Thus, the unwanted interference of
Raman scattered light and luminescence emission can be avoided by choosing a suitable
excitation wavelength. An example of this is shown in Figure 7b.
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Another common problem includes effects of local temperature increase due to
strong light absorption and, connected with that, alteration or decomposition of the
sample. This problem occurs in particular in the Raman microprobe analysis. Recall that
focusing a nominally “weak” laser beam of only 1 mW power to a focal-spot area 1 µm
in diameter results in a large power density of 1000 W/mm2. It is true that such power
density is in general not problematic when transparent minerals are analysed, except for
powders where it may be necessary to place the mineral grains under water to conduct
away some of the heat (cf. Smith et al., 1999a). To avoid any misinterpretation of data,
however, the experimentalist needs to check carefully for potential effects of local
temperature increase in the sample, which may result in notable temperature-induced
shifts of Raman bands towards lower wavenumbers due to longer bond distances (an
example was reported by Balan et al., 2001). More serious are cases in which significant
light absorption results in irreversible damage of the sample. Effects such as local
dewatering, degassing or complete decomposition (often recognised from colour
changes or the appearance of little “burned” holes at the sample surface) are especially
likely to occur in richly coloured or non-transparent minerals and are, therefore, a
common problem in the analysis of mineral pigments. An example for permanent sample
damage caused by significant laser light absorption is presented in Figure 8.
Fig. 8. Analytical artefacts II: Local heating of the
sample due to strong light absorption may result in
local decomposition. A crystal of magnetite,
Fe2+Fe32+O4, from Callenberg, Germany, excited with a
fully focused but considerably weakened laser beam
(632.8 nm), gave the expected magnetite Raman
spectrum. When irradiated with higher laser energy,
the very same micro-area underwent local oxidation, as
indicated by a Raman pattern reminiscent of Fe32+O3
(compare the reference spectrum of haematite from
Elba, Italy).
There are many experimental ways to avoid such unwanted effects and, with that, any
misinterpretation of results. Sample alteration and disintegration due to strong light
absorption can simply be avoided by decreasing the laser power. For instance, Nasdala et
al. (2001b) found dark brownish radiation haloes to be more sensitive to light absorption
than their host biotite, and they did Raman microprobe analyses using fully focused visible
laser beams with only 0.03 and 0.08 mW power. The significant weakening of the exciting
laser beam, however, is often connected with experimental difficulties. As a rule of thumb,
if the laser power is decreased to 1% of the initial value, the scattered light needs to be
accumulated for a 100× longer time period to receive about the same signal intensity to
background noise ratio. However, considering the unavoidable statistical variation of the
intensities of the signal and of the background, and also the rule relating the standard
deviation to the square root of the intensity of a single measurement (i.e., improving the
ratio of an intensity to its standard deviation by ×10 requires a ×100 increase in the time of
Raman spectroscopy: Analytical perspectives in mineralogical research
297
a single acquisition), for a given fixed total measurement time it is clearly better to
maximise the single measurement time and minimise the number of repeated
accumulations. It seems, therefore, more worthwhile to avoid strong light absorption by
choosing an excitation wavelength that is less absorbed by the sample (however, the use of
another wavelength may not always be possible, for example, because of the occurrence of
luminescence phenomena). An excellent example is the Raman analysis of amorphous
selenium, which is extremely sensitive to light absorption in the visible range. It was found
by A.K. Bandyopadhyay and L. Nasdala (unpublished results) that even the irradiation of
amorphous selenium with an extremely weak blue laser beam (Ar+ 488 nm, 0.0013 mW,
focal spot diameter 10 µm) led to temperature-induced alteration, including local
transformation to the crystalline state. In contrast, the same sample did not show any
alteration and yielded the Raman spectrum of amorphous selenium (compare Lucovsky et
al., 1967) when excited with an NIR laser beam (Ti-sapphire 890 nm, 5 mW, focal spot
diameter 2.5 µm), even though the effective laser power density at the sample surface was
almost five orders of magnitude higher in the latter case.
There are other, and more advanced, possibilities to avoid temperature-induced
effects, such as the application of cooling stages and sample spinning techniques. These
techniques are connected with much greater experimental effort and are, therefore,
mostly not considered for routine Raman analysis of geological samples. The main point
we aim to make in this subchapter is, however, that the successful avoidance of any
misinterpretation of artefacts presumes first of all that the artefact is recognised by the
analyst, which in turn always requires a critical checking of samples and spectra.
Instrumentation for Raman analysis
Generalities on Raman systems
In this and the following subchapters, we will refer briefly to the main technical
aspects related to the Raman spectroscopic analysis, but only as far as concerning the
routine analysis of geological samples. More details are provided in the literature
listed above, and especially via the internet (see the web pages of the leading
spectrometer manufacturers).
The main components of each Raman system are (1) the source of the incident
beam of light, (2) optical components used to illuminate the sample and to collect the
Raman scattered light, (3) components for the spectral analysis of the light, and (4) a
device for the detection of the light. Raman systems are subdivided into two principal
types according to the spectral analysis of the Raman light, namely, Fourier-transform
(FT) systems using an interferometer, and dispersive systems. Dispersive systems are
usually assigned to two major subgroups according to the way the Raman spectrum is
separated from the much stronger Rayleigh line. This can be done either only
dispersively using conventional gratings (double and triple monochromator systems) or
using a holographic Rayleigh rejection filter (also called notch filter); the latter is usually
combined with a single grating monochromator, or an “échelle” grating.
Fourier-transform systems are rarely used in geoscience research. These systems
are reasonably priced and can be interfaced to an FTIR spectrometer. Another advantage
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is that with 1064 nm excitation, luminescence problems rarely occur. Disadvantages
include the comparably poor volume resolution even if the spectrometer is coupled with
a powerful IR microscope (no confocality possible, see below), the low spectral
resolution and the fact that only two excitation wavelengths are available. Also, due to
its –4 dependence, the Raman effect is generally weak in the near-IR (the Raman
scattering intensity is about 23 times higher with Ar+ 488 nm excitation compared with
Nd:YAG 1064 nm excitation). This needs to be compensated for by relatively high
excitation energies in the NIR.
Dispersive double and triple monochromator systems reach the best spectral
resolution (better than ~ 0.05 cm–1), and they provide the option to analyse bands close
to the Rayleigh line (bands with Raman shifts as small as only about 1 cm–1) with the use
of a photomultiplier (PMT) detector. The main disadvantage of these systems (in
addition to their comparably high price) is the strong light intensity loss along the beam
path to the detector. This is of special importance for geoscience research, as
experimentalists are here often confronted with poorly scattering and/or light sensitive
samples that can only be excited with low laser energy. As a result, Raman light that is
particularly low in energy needs to be handled quite often in the analysis of
mineralogical and geological samples.
For this reason, notch filter systems seem to be the best choice. In these systems,
the light is only dispersed once and reflected by a lower number of mirrors, which results
in a much better optical throughput (or light efficiency). Notch systems are also
reasonably priced, and their only significant disadvantage (bands with Raman shifts
smaller than 50–100 cm–1 are cut off by the notch filter and cannot be analysed) seems
of minor relevance for most geoscience research tasks.
Samples are nowadays generally excited using laser light sources. Therefore, it seems
somehow unnecessary to describe Raman spectroscopy by the term “laser-Raman
spectroscopy” (emphasising the use of a laser source), which can still be found in many papers.
Lasers provide a variety of nearly monochromatic excitation wavelengths (the full range is
available using a tunable laser) in the UV, visible or near-IR. Unwanted laser emissions, such
as the broad-band spontaneous emission of tunable lasers or discharge emissions (plasma
lines) of gas ion lasers, are usually rejected by the use of interference filters. Nevertheless, the
beam irradiated to the sample is never fully monochromatic, rather the excitation has a certain
bandwidth depending on type (and age and adjustment) of the laser.
For quantitative conclusions (especially on the shapes and FWHMs of narrow
bands), one needs to consider both the intrumental broadening of Raman bands (described
by the so-called “apparatus function” of the Raman system) and the spectral resolution
with which the analysis was done. Any detected Raman signal is broadened due to
experimental limitations including the quality (sharpness) of the excitation source, the
spectral analysis (groove density on the grating used to disperse the light, focal length,
widths of internal slits), and the physical resolution of the detector. Most of the modern
systems used in geoscience research are equipped with charge-coupled device (CCD)
detectors in favour of other older detector types (e.g. diode arrays, PMTs). Here, the
physical resolution of the detector is controlled by the pixel density (in cm–1). As a rule of
thumb, the actual spectral resolution of a Raman system is generally about three times the
Raman spectroscopy: Analytical perspectives in mineralogical research
299
physical resolution. Since obtained bands are always broader than the actual Raman
signal, real FWHMs need to be calculated by correcting measured FWHMs for the
apparatus function and other factors mentioned above. Band correction procedures have
been described in detail, for example, by Irmer (1985) and Verma et al. (1995).
Confocality and the Raman microprobe
One of the most important aspects in the application of Raman spectroscopy to the study
of geological samples is the opportunity to perform analyses with high lateral resolution
on a micro-scale (i.e., “microprobe” analyses). The first Raman microprobes were
constructed in the mid-1970s in France (e.g. the “MOLE” by Delhaye & Dhamelincourt,
1975; see also Dhamelincourt & Bisson, 1977; Dhamelincourt et al., 1979;
Dhamelincourt, 1987) and in the USA (Rosasco et al., 1975a, 1975b).
The effective lateral resolution achieved by modern Raman microprobe systems is about
1–1.5 µm (Markwort et al., 1995; Nasdala et al., 1996), i.e., roughly twice the excitation
wavelength. Note, however, that coupling of a Raman spectrometer (or interferometer) with a
powerful optical microscope is a prerequisite, but clearly not sufficient, to create a genuine
Raman microprobe. The highest lateral and volume resolution is only possible with a confocal
arrangement of the optical pathway (Fig. 9). Due to the usually high numerical aperture of
highly magnifying microscope objectives, the beam that is irradiated and focused on to the
sample is significantly convergent and diverges again behind its focal plane. As a consequence,
the excited sample volume has the shape of an “hour glass” or, if the focal plane is adjusted to
the sample surface, the shape of a truncated cone. Even if the top of such a truncated cone
(corresponding to the focal plane) has a diameter of only 1 m, its base must be much broader,
and it is rather the diameter of the latter that determines the true lateral resolution of the
measurement. The spatial resolution is improved by effectively cutting off the truncated cone
at its broad base, i.e., only light scattered from areas in, or slightly above and below, the focal
plane is allowed to get to the detector, whereas the rest is rejected by a narrow confocal
diaphragm (or confocal hole; Fig. 9). Thus, both depth resolution and lateral resolution are
improved simultaneously. Modern confocal systems can operate at a depth resolution of about
± 2 µm. When focussing at the sample surface, this results in an effective volume resolution
of 5 m3 for transparent samples (e.g. Markwort et al., 1995).
The detection limit for many minerals and related phases is much smaller than the
volume resolution in the confocal mode. A sample volume of 5 µm3 corresponds to
Fig. 9. Principle of confocal Raman measurements. High depth resolution is achieved by cutting off the light that
is scattered from points outside the focal plane with a narrow diaphragm.
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~ 10–11 g, which is analysed with ease even if these 5 µm3 should contain several phases.
Even much smaller amounts of sample can be analysed in some cases (e.g. analysis of
nanotubes). To give an example from the area of routine geoscience analysis, the thin
carbon coat on the surface of an electron microprobe mount is easily detected if only one
square micrometer is excited by the laser beam (this corresponds to an amount of sample
on the order of 10–14 g). This ability has made Raman spectroscopy a powerful tool for
the analysis of small objects (powder particles, inclusions, aerosols, tiny samples in
diamond anvil cells etc.) and heterogeneities in minerals (e.g. separate analysis of zones,
reaction rims, coats/thin films).
The rejection of a major portion of the Raman scattered light by the confocal
diaphragm results in significant intensity loss at the detector. In the case of
heterogeneous samples, this disadvantage is more than compensated for by the improved
spatial resolution. Raman bands of the phase to be analysed are now less affected by
bands of neighbouring phases or zones (Fig. 10), and in addition luminescence and other
unwanted light originating from the surroundings of the analysed volume is significantly
suppressed. If homogeneous samples are analysed, however, the intensity loss as caused
by a narrow confocal hole is not accompanied by any significant gain in information.
Therefore, Raman systems are usually operated in the fully confocal mode only if
necessary, whereas finding a compromise between spatial resolution and signal yield
seems more efficient for routine analyses.
Fig. 10. As a simple example for confocality effects, we present two Raman spectra taken from a carbon
dioxide inclusion (~ 12 µm diameter) inside a topaz grain in a polished rock slice of a greisen from Cinovec,
Czech Republic. In the regular, i.e., the non-confocal mode (upper spectrum), a complex Raman spectrum is
obtained, which consists of vibrational bands of the included CO2 gas, the host mineral and also the araldite
epoxy used to attach the polished section to a glass slide (about 20 µm behind the CO2 inclusion). With a
narrow confocal diaphragm placed in the optical beam path (lower spectrum), internal CO2 vibrations are
clearly obtained whereas topaz bands are largely suppressed and araldite bands are completely suppressed.
Raman spectroscopy: Analytical perspectives in mineralogical research
301
Mobile Raman microscopy for truly in situ analysis
The introduction of a microscope into a Raman spectrometer to create the “Raman
microprobe” (RMP) made it possible to analyse individual micrometre-sized crystals
inside natural rocks or synthetic mineral assemblages (Dhamelincourt & Bisson, 1977).
Subsequently the manufacturers turned to creating another exciting development,
mobility, even if the commercial objectives were essentially industrial. It was individual
scientists who seized on the opportunity to explore new applications in the geological
and archæological sciences. The mobility was achieved by the miniaturisation of many
parts of Raman spectrometers which, along with smaller air-cooled laser sources and
photon detectors, not to mention portable computers and mobile telephones, made it
possible to envisage analysing minerals really in situ by carrying the Raman system to
the material rather than transporting a sample to an analytical laboratory.
If this did not sound especially interesting to many geologists who already had a
standard “thin section” available to be carried to any laboratory without problem,
mobility was especially interesting to archæologists and art historians, along with
restorers and curators, as it became possible to analyse their precious objects (or rather
parts thereof) not only non-destructively (as with several other modern chemical
techniques) but also without displacing the object (which always carries risks of damage
or loss). Archæometricians and their colleagues have long been faced with a terrible
dilemma: to obtain useful scientific information by deliberately damaging part of a
priceless artefact, or not to make any damage whatsoever and hence getting no scientific
information at all. For this reason the greater part of all archæological objects have never
had their mineral (or molecular) constitution verified, which in many cases left the
scientist, historian or general public frustrated by the lack of key information since many
artefacts in exhibitions are merely labelled “rock” or some supposed mineral species
name. A similar situation applied to gemmologists faced with verifying the mineral
species of gemstones mounted in an ornate structure like a crown or an altar, which could
not possibly be unmounted for traditional gemmological analysis. With the remarkable
combination of non-destructivity and of mobility afforded by Raman analysis, a new era
has emerged: “The new age of ‘don’t move it, don’t even touch it’ archæometry has now
arrived to allow remote non-destructive characterisation in all the domains of
ARCHÆORAMAN and in situ almost anywhere” (Smith, 2002a).
In order to counteract the terminological confusion caused by the variable use of
the term “in situ”, such as describing analysis of individual grains within a multiphase
sample which was not prepared in any way, but was nevertheless extracted, perhaps
destructively, from its primary source (e.g. a geological locality or an archæological
site), or its secondary source (e.g. a museum display or archived collection), and then
transported into an analytical laboratory and hence not at all analysed really in situ at its
remote site, various workers have employed terms like “remote” analysis, analysis “at
distance” or “mobile” analysis. “Mobile Raman Microscopy” (MRM) was carefully
defined by Smith (1999) as including analysis by either “portable” systems, which can
be carried by one man (e.g. the Kaiser Holoprobe®), or “transportable” systems, which
need four men (e.g. the Jobin Yvon LabRAM®). Several kinds of configurations are now
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commercially available; in general terms the smaller apparatus have a lower spectral
resolution or a shorter spectral range, or less features like having only one laser source
or no accompanying microscope nor video accessories.
Most manufacturers now provide a variety of configurations of which several can be
considered as mobile. The most relevant options are briefly mentioned as follows. A
vertical microscope can be fixed to the spectrometer (ideal for traditional point analysis, or
for motorised x-y-z 3-dimensional mapping). A horizontal microscope can be fixed to the
spectrometer (good for analysing very tall or very heavy objects like statues or other
sculptured rocks (Fig. 11a) (e.g. Smith & Bouchard, 2000; Smith, 2000, in print, a). Optical
fibres can carry a laser beam from a laser source to a remote head, and also carry the Raman
diffused light (and video signal from a TV camera) from the remote head to a spectrometer
(Fig. 11b; ideal for analysing anywhere within the perimeter defined by the length of the
fibres, currently over 100 m long, and in any orientation) (e.g. Smith, 2001a; Rondeau &
Smith, 2002), and furthermore inside complex open structures like a crown. With the
spectrometer placed on a cart, extra mobility is achieved being limited only by the length
of an ordinary electric power cable. A vertical microscope may be not fixed to the
spectrometer and hence be easily portable alone; connected by optical fibres to a portable
spectrometer this allows microscopic point analysis or Raman mapping on site. The remote
head can have a choice of objectives or longer focal length lenses; fitted to a special tripod,
the remote head can be positioned, rotated and shifted in any direction; also it can have a
built-in CCD camera allowing observation of the zone under analysis. One or more lasers
may be built in, but extra external lasers can also be coupled to the Raman system. With an
appropriate configuration, MRM analytical operations can now be achieved in situations
unimaginable a decade ago, such as verifying mineral pigments really in situ in paintings
on walls or ceilings of ecclesiastical buildings, tombs or caves (e.g. Prehistoric rock art; cf.
Smith et al., 1999a, whose early work in this field was on extracted microsamples).
Fig. 11. Two examples of the non-destructive analysis of art specimens using mobile Raman systems. (a) A
Teotihuacan sculptured mask in greenish white-to-grey rock positioned aside the horizontal microscope of a
Raman system. All analyses of whitish or greyish parts confirmed the presence of calcite. Museum of Mankind,
Paris, 1999. (b) Using a 100 m long optical fibre, a probe head on a tripod was connected with a portable MRM
standing in a different room. The remote head was orientated sub-horizontally to send the laser beam (visible
here as a tiny green spot) on to the blue-pigmented surface of this 3 m high wooden statue from Oceania on
permanent display inside the Louvre Museum, Paris in 2000. This constitutes real in situ “at distance” nondestructive analysis. Photographs taken by D.C. Smith.
Raman spectroscopy: Analytical perspectives in mineralogical research
303
Remote MRM analysis employing optical fibres (but without a video camera in
order to have no electricity at the end of the fibres) with the spectrometer placed in a boat
and the tripod set up under water by a diver or a robot has been proposed as a novel way
of conducting subaquatic archæometry (Smith, 2003) at depths not exceeding a few
hundred metres (which covers a great number of buried cities and sunken ships); this is
a very different approach from that of sending an entire MRM system to depth inside
some kind of watertight vessel (indeed a special submarine) which is rather similar to
sending another kind of special MRM apparatus into Space. Such configurations are
already being designed by other research groups (Wang et al., 1996; Wang & Haskin,
2000; Brewer et al., 2002; Wang et al., 2003), and a remarkable telescope system has
recently been developed for analysing at distances up to 60 m away from the remote head
(Sharma et al., 2002, 2003).
Images based on Raman scattered light
Raman imaging
There are two principally different ways to generate an image from Raman scattered
light. The first of these two ways is generally known as Raman imaging, direct imaging,
or global imaging technique. Here, the CCD detector of the spectrometer system is used
as a camera that photographs a rectangular area of the sample. Imaged areas are mostly
several tens of µm across; their sizes depend on the spectrometer optics (especially the
magnification of the objective). It is clear that, since a certain area is to be imaged in the
Raman mode, this whole sample area needs to be excited, which is normally done by
illuminating the sample with a largely defocused laser beam. To avoid the contribution
of all of the scattered light (consisting of Rayleigh and polychromatic Raman light) to
the obtained image, a notch filter and a band-pass filter are placed in the optical path. The
latter allows only the light in a small wavenumber range (“spectral window”) to pass
through whereas the rest is discarded. Finally, only a small portion of the Raman light
scattered from the excited sample area reaches the CCD and contributes to the image.
Consequently, Raman imaging is widely similar to regular photography, with the main
difference being that only a particular colour is used: each pixel of the CCD detects the
integral light intensity in the pre-set, narrow spectral window that was scattered from a
certain micro-area of the sample.
Using angle-tunable band-pass filters, the spectral window can be adjusted to
correspond to different Raman bands of the sample. It is, therefore, possible to obtain
multiple images of a certain sample area for the Raman signal of different phases
occurring in that area. Often some image correction is applied, for instance, to correct for
non-uniform laser intensity distribution over the imaged sample area and other
instrumental factors. The final images will yield intensity distribution patterns of Raman
light in a certain wavenumber range (and, with that, potentially a certain mineral phase).
Examples are shown in Figures 12c and d.
The greatest advantage of the direct imaging technique is that imaging is fast. To
obtain an image, it takes only about as long as it takes to record a single Raman spectrum,
which is mostly on the order of seconds. The disadvantage of the direct imaging
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 12. Three examples of Raman-based image generation. (a) Photomicrograph of a coesite inclusion that was
partially transformed to -quartz in garnet from a high-pressure gneiss (Saidenbach, Saxonian Erzgebirge,
Germany). The light is not fully cross-polarised, to make visible the internal sub-radial fracture pattern of the host
garnet (caused by the volume expansion upon coesite -quartz transformation). Sample courtesy of H.-J.
Massonne. (b) Raman spectra of coesite and -quartz. The two SiO2 polymorphs are unambiguously distinguished
from their typical fingerprint patterns of Raman bands. Intensity distribution images for the 521 cm–1 coesite band
red in (c) and the 464 cm–1 quartz band blue in (d) revealed that most of the inclusion still consists of coesite, with
the transformation to -quartz having started from the outer rim and internal fractures of the inclusion. (e) Raman
spectrum of moganite-bearing agate from St. Egidien, Germany (solid graph; sample courtesy of J. Götze). The
most striking difference between the obtained spectrum and that of moganite-free quartz (dotted) is the additional
appearance of an intense band at 502 cm–1 (compare Kingma & Hemley, 1994; Götze et al., 1998). (f) Raman map
generated from the band integral ratio of the 502 and 464 cm–1 bands, indicating rhythmic growth zoning. Bright
areas (high moganite content) are assigned to quickly grown, microcrystalline zones. Dark areas consist mainly of
coarse-grained -quartz. (g) Raman map of a gem-quality feldspar with “moonstone” cat’s eye effect from
Tanzania, revealing a perthitic internal texture (for sample description see Milisenda et al., in print). It is possible
to distinguish between orthoclase and albite because the Raman shift of the main feldspar band varies slightly with
the chemical composition (513 cm–1, orthoclase; 509 cm–1, albite) (compare Mernagh, 1991). Even though the
Raman bands of the two feldspar minerals overlap widely one another, albite lamellae in an orthoclase matrix are
clearly resolved using the ratio of signal intensities at 513 cm–1 and 509 cm–1 Raman shift.
technique is the limitation of spectral information. It is clear that the spectral window of
an image is fixed once the image has been taken, and the only non-uniform spectral
property left is then intensity assigned to lateral coordinates, whereas other spectral
information (band FWHMs, band asymmetries, background slopes etc.) is lost.
Consequently, it may become difficult to assign the obtained signal to a certain phase if
two minerals have a Raman line within the pre-set spectral window, and it may also be
difficult to distinguish between Raman and luminescence light. Raman imaging is,
therefore, mostly applied to obtain quickly qualitative or semi-quantitative information
Raman spectroscopy: Analytical perspectives in mineralogical research
305
on low-luminescent mineral samples. This technique is used much more intensely in
scientific and industrial disciplines outside the geosciences, such as materials science
(e.g. homogeneity check of semiconductors), pharmacy (for a discussion see Bugay,
2001) and in the forensic analysis (e.g. quick detection of drugs covered by sugar). For
more details on the imaging technique see, for example, Lehnert (2000).
Raman mapping
The second basic way to generate an image from Raman scattered light is the Raman
mapping technique. A map (i.e., a colour-coded image) is rather a mathematical product,
generated on the basis of a large number (typically 1000–50000) of single spectra. Here,
the Raman system is operated in the confocal mode, and a full Raman spectrum is
obtained for each pixel of the image to be generated. This is mostly done using softwarecontrolled x-y stages, i.e., the sample is moved step-by-step relative to the fixed
microscope objective. The step width can be chosen by the experimentalist. It is mostly
adjusted depending on the size of the mapped area, and in order to get a meaningful
compromise between sufficient lateral resolution and size of the resulting data file. The
whole data set is then processed (e.g. background correction and band
fitting/deconvolution for all spectra), which results in a complex data array. The full
spectral information for each Raman band is available for every x-y coordinate of the
mapped area. Finally, multiple colour-coded maps can be generated for any parameter.
An example is presented in Figure 12f. Since single spectra are obtained in the confocal
mode, maps with an excellent depth resolution may be generated (compare Fig. 19
below), and it is even possible to generate tomographic images of two-dimensional
planes inside minerals (Nasdala et al., 2003b) (see Fig. 17 below and the cover figure of
this volume). The main disadvantage of Raman maps is that obtaining a large number of
single spectra in succession may be extremely time-consuming. For instance, if a single
spectrum is recorded in only 5 seconds, a map consisting of 150 × 150 pixels/spectra will
require a total of more than 31 hours of laboratory time. To decrease the experimental
time, some companies work on the development of line scanning techniques (a line of
spectra is simultaneously obtained and an area is then mapped line-by-line). Raman
mapping is, therefore, unsuitable for quick homogeneity checks. However, the wealth of
detailed spectral information that is available has made Raman mapping an extremely
valuable technique for detailed studies of internally heterogeneous minerals.
Applications of Raman spectroscopy
Generalities on applications in mineralogy and geology
Raman spectroscopy has been used successfully in nearly all geoscience disciplines and
virtually all kinds of samples have been studied using this technique. The application of
Raman spectroscopy seems especially influenced by its experimental advantages (see
below). The simple identification of tiny particles of minerals, or inclusions in minerals,
and related substances is widely applied. This is mostly done in cases where the more
common techniques (e.g. electron microprobe or X-ray diffraction analysis) cannot be
used, for example, because of the impossibility to separate or prepare the sample to be
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
studied. The identification of rock-forming or accessory minerals is based on the
numerous papers describing the Raman spectra of these mineral species (these papers
can be found in the relevant literature databases; example references are not cited here).
One obvious advantage of Raman spectroscopy is that polymorphs with the same
chemical composition can be easily distinguished (e.g. Etchepare et al., 1974, 1978;
Sharma & Simons, 1981; Mernagh, 1991; Rodgers, 1993). Chemical information on the
composition of minerals and solid solution members can be obtained (e.g. Mernagh,
1991; Wopenka et al., 1999; Kreisel et al., 2000; Wang et al., 2001), and it is also
possible to study the isotopic composition of minerals and included phases (e.g., Sato &
McMillan, 1987; Champagnon et al., 1997; Irmer & Graupner, 2002).
An important field for the use of Raman analysis is based on its sensitivity to shortrange order. Melts, quenched melts, glasses and other amorphous or amorphised
materials have been extensively studied (e.g., Sharma, 1972; Brawer & White, 1974,
1976, 1978; Furukawa & White, 1978, 1981; Furukawa et al., 1978, 1981; Videau et al.,
1981; Piriou et al., 1981; McMillan et al., 1982; McMillan & Piriou, 1983; McMillan,
1984, Minser et al., 1984; Matson & Sharma, 1985; Mukherjee & Sharma, 1985; Mysen
& Virgo, 1985; Sprenger et al., 1993; Mysen, 1995; Henderson & Fleet, 1995; Frantz &
Mysen, 1995; Alberto et al., 1995; Sprenger, 1996), for instance to obtain information
on the coordination of ions in such “X-ray amorphous” samples. Ions in solutions have
been studied successfully as well (e.g., Sharma & Reed, 1976; Piriou & Svoronos, 1985;
Bondarenko & Gorbaty, 1999), which makes Raman spectroscopy a valuable tool in
geochemical investigations. More recently, Raman analyses have also been applied to
the study of minerals that were fully or partially amorphised due to the impact of
radioactivity, as for instance radiation-damaged zircon (Nasdala, 1995), monazite
(Seydoux-Guillaume et al., 2002) and biotite (Nasdala et al., 2001b), as well as spent
nuclear fuel including its alteration and corrosion products (Amme et al., 2002). Here,
Raman spectra provide information on the present substances and their degree of shortrange order and crystallinity, respectively. Similar structural information is obtained in
the study of order-disorder phenomena in minerals (Keramidas et al., 1975; McMillan et
al., 1984; Bischoff et al., 1985; Tlili et al., 1989).
There are numerous applications of Raman spectroscopy in biomineralogy, as for
instance the study of fossils, corals, nacre, human bones and dental enamel, and coatings
applied to medical implants (e.g. Vénec-Péyré & Jaeschke-Boyer, 1979; Daudon et al.,
1981; Nelson & Williamson, 1982; Urmos et al., 1991; Silvé et al., 1992; Pasteris et al.,
1999; Dietrich et al., 2001; Freeman et al., 2001; Miyazaki et al., 2002; Perrin & Smith,
2002; Silva et al., 2003; Taddei et al., 2003; Martini et al., 2003; Balz et al., submitted). An
example is presented in Figure 13. Raman spectroscopy has also been used to investigate
environmental processes such as weathering and corrosion (e.g. Refait et al., 2003).
In crystallography and materials science, Raman spectroscopy is routinely used to
identify and check the quality and homogeneity of synthetic growth products (e.g. Boyer
et al., 1985; Sweegers et al., 2001). Because of the opportunity to perform analyses nondestructively, Raman has become an extremely valuable tool in the study of gemstones,
which includes their identification and the identification of inclusions, and the detection
of potential treatments done to enhance colour and clarity (e.g. Délé-Dubois et al., 1980,
Raman spectroscopy: Analytical perspectives in mineralogical research
307
Fig. 13. Raman micro-spectroscopy applied to biominerals. (a) Scanning electron microscope image of assemblages
of synthetic Ca-carbonate minerals, grown at the inner skin of a chicken egg shell. Sample courtesy by M. Balz. (b)
Crystals with sizes of down to < 1 µm are easily analysed, as Raman spectra allow the unambiguous differentiation
among CaCO3 polymorphs. Note in particular the clearly different low-frequency lattice vibrations of aragonite and
calcite. Aragonite and calcite can also be clearly distinguished by the weak 702 & 707 & 717 cm–1 triplet of the
former and the 713 cm–1 singlet of the latter, and again by further Raman bands in the 1400–1600 cm–1 spectral range.
1986a, 1986b; Maestrati, 1989; Schmetzer et al., 1996, 1997; Nassau et al., 1997;
Krzemnicki, 1999; Ostroumov et al., 1999; Chalain et al., 1999, 2000); overviews are
given by Coupry & Brissaud (1996), Kiefert et al. (2001) and Smith (in print, a). Finally,
the generally increased acceptance and use of Raman analysis is also documented by the
fact that this technique is more and more applied in the description of new mineral
species or their redefinition (for instance Grice et al., 1986; Nasdala et al., 1993, 1998;
Holtstam, 1997; Bühn et al., 1999; Brugger et al., 1999; Birch et al., 2001; Witzke et al.,
2001; Wallwork et al., 2002; Kolitsch, 2003, Krause et al., 2003).
Applications to the study of inclusions in minerals
Because of its high volume resolution and the ability to measure efficiently major fluid
inclusion components such as CO2 and CH4 in situ, Raman micro-spectroscopy has
become an important, in some cases the only, tool to determine composition and density of
fluid inclusions. A list of Raman-active species in fluid inclusions and some applications
are given by Burke (2001). The primary applications in the geosciences are: (1) qualitative
identification of gaseous, liquid, supercritical, and solid components of fluid inclusions as
a “fingerprint” method; (2) semi-quantitative determination of ratios between two or more
gaseous, liquid, or supercritical species inside inclusions (such as CO2-CH4); and (3)
estimation of the origin and formation conditions of solid phases inside inclusions.
Qualitative identification of gaseous, liquid, supercritical and solid components of
fluid inclusions are some of the major applications that have successfully been applied to
the determination of the most frequently occurring polyatomic fluid components using
Raman spectroscopy (e.g. 12CO2, CH4 and N2) (Rosasco et al., 1975b; Guilhaumou et al.,
1978; Touray et al., 1985; Pasteris et al., 1986; Burke & Lustenhouwer, 1987; van den
Kerkhof 1988). In addition, minor and rare components of fluid inclusions have also been
investigated (e.g. 13CO2, H2S, SO2, CO, COS, H2, O2 and NH3) (Bény et al., 1982; Touray
et al., 1985; Pasteris et al., 1986; Frezzotti et al., 1992; Giuliani et al., 2003). Detection
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
of the important liquid and gaseous H2O components in fluid inclusions is difficult but not
impossible (e.g., Wopenka et al., 1990). Major ions in solution, such as those of Na, K,
Mg, Fe and Li, are detectable at low temperatures as solid hydrates (Dubessy et al., 1982,
1992; Winter & Roberts, 1993). Detection of hydrocarbons in inclusions is possible with
some difficulties (Stephenson, 1974; Guilhaumou, 1982; Guilhaumou et al., 1988;
Pironon, 1993; Orange et al., 1996). Raman spectra of clathrates (polymerised openstructured hydrates with cavities incorporating molecules such as CO2, CH4, N2, O2 and
H2S that are formed at low temperatures in multicomponent inclusions) have been
presented by Sum et al. (1997). Champagnon et al. (1997) distinguished isotopes of N2
and O2 in clathrates in ice cores. Numerous daughter minerals, or accidentally trapped
solids, have been identified (e.g., Dhamelincourt et al., 1979; Beny et al., 1982; Andersen
et al., 1984, 1989; Cervelle & Moëllo, 1990; Phillipot & Selverstone, 1991; Mernagh &
Trudu, 1993; Mernagh & Hoatson, 1995; Burke, 1998; Barrie et al., 1999; Vapnik &
Moroz, 2002; Koděra et al., 2003).
Semi-quantitative detection of various gas mixtures within fluid inclusions were
carried out in the chemical systems CO2–H2S–H2O–S (Beny et al., 1982), CH4–CO2 and
CO2–N2 (Guilhaumou et al., 1982; Darimont et al., 1988; van den Kerkhof, 1988;
Frezzotti et al., 1992), in systems involving additional H2O (e.g. Seitz et al., 1987; Leng
et al., 1998) and in complex systems including H2O, NaCl and further components (e.g.
Pasteris et al., 1986; Dubessy et al., 1989; Thomas et al., 1990; Nwe & Morteani, 1993;
Dubessy et al., 1999; Siemann & Ellendorf, 2001; Giuliani et al., 2003). Complementary
to microthermometry, the dissolved salt content of aqueous inclusions at room
temperature has been determined using Raman analysis (Mernagh & Wilde, 1989).
–
Furthermore, ions in aqueous inclusions such as HSO–4, SO–2
4 and HS can be quantified
(e.g. Rosasco & Roedder, 1979; Dubessy et al., 1983, 1992; Murata et al., 1997; Benison
et al., 1998; Boiron et al., 1999).
Graphite or carbonaceous material in fluid inclusions have been investigated by
Reutel (1992), Wopenka & Pasteris (1993), Frezzotti et al. (1994), Andersen & Burke
(1996), Cesare & Maineri (1999) and Kaindl et al. (1999). Furthermore, there are
numerous studies that have used Raman spectroscopy for the identification and
characterisation of solid inclusions in minerals (e.g. Smith, 1984; Liu et al., 1990; Yang et
al., 1998; Izraeli et al., 1999; Nasdala & Massonne, 2000; Sobolev et al., 2000; Ye et al.,
2001; Kunz et al., 2002; Gillet et al., 2002; Massonne & Nasdala, 2003; Chopin, 2003).
Applications in high-pressure and high-temperature studies
The Raman spectroscopic study of vibrational properties of minerals, glasses, melts and
fluids at high pressure and high temperature has important applications in material and
geosciences (Ferraro, 1984; Gillet, 1996; Gillet et al., 1998). The development of the
diamond anvil cell (DAC) has opened up new possibilities for in situ Raman
spectroscopic experiments in minerals at high pressures and at high as well as low
temperatures (Jayaraman, 1983, 1986; Ferraro, 1984; Chervin et al., 1992). Raman
spectra can be obtained from micrometre-scale specimens compressed by pressures of
Raman spectroscopy: Analytical perspectives in mineralogical research
309
up to > 135 GPa in the DAC (e.g. over the pressure range of the entire Earth’s mantle)
(Gillet et al., 1998). The sample chamber of a DAC consists of a hole (usually < 300 µm
in diameter and < 150 µm in height) in a gasket, which is pressed between two diamond
anvils. This very small volume contains the sample inside a pressure-transmitting
medium, and in most cases also an in situ pressure sensor such as a small ruby chip. Ruby
can be used for pressure determination by monitoring the frequency of the laser-induced
photoluminescence (Piermarini et al., 1975; Mao et al., 1986). Two different techniques
are used for heating up samples in the DAC: a small resistance heater for temperatures
up to 1200 °C and laser heating using a CO2 laser for temperatures up to 1700 °C in the
hot spot of the DAC (Boehler & Chopelas, 1992; Gillet, 1996). Recently the Bassett-type
DAC became a powerful tool for hydrothermal studies at simultaneous high pressures up
to 2.5 GPa and temperatures from –190 °C to 1200 °C (Bassett et al., 1993; Bassett et al.
1996; Shen et al., 1992; Bassett, 2003). Synthetic moissanite (hexagonal SiC) has been
recently proposed to be suitable as a substitute for diamond in anvils in spectroscopic
high pressure cells (Xu & Mao, 2000).
Raman spectroscopy mostly in conjuction with the DAC technique has been used
to investigate the structure and the high-pressure high-temperature behaviour, including
phase transitions, of Earth-interior related minerals (Williams et al., 1992; Reynard et
al., 1997; Schmidt & Ziemann, 2000; Shim & Duffy, 2001; Chopelas & Serghiou, 2002;
Kleppe et al., 2002, 2003), glasses (Farber & Williams, 1996), and melts and liquids
(Frantz et al., 1994; Richet et al., 1996; Williams & Knittle, 2003; Ziemann et al.,
submitted). Moreover, the study of vibrational properties of minerals as a function of
pressure and temperature (based on Raman and IR spectroscopic data) allows the
derivation of fundamental properties such as thermal conductivity (Hofmeister, 1999,
2001) and the thermodynamic functions heat capacity, vibrational entropy, internal
energy and Helmholtz free energy (Kieffer, 1979; Gillet, 1996; Gillet et al., 1998;
Hofmeister & Mao, 2002). A further application is the calibration of spectroscopic
pressure sensors, which can be used for in situ experiments at high temperatures beyond
the range of other pressure measurement techniques (Schiferl et al., 1997; Schmidt &
Ziemann, 2000).
Applications in archæometry: The Raman Microscope (RM)
The symbol RM (where the M variably refers to Microscope, Microscopy, Microprobe
or Microspectroscopy) is becoming popular in archæometry because it emphasises an
enormous advantage over most spectroscopic techniques: it is possible to observe a
sample under high magnification, to choose the precise microcrystal to be analysed and
then to analyse it immediately. Research applying RM to gemstones or pigments in art
history, archæology, conservation or restoration, whether to verify a supposed mineral
species or to recognise fakes, began in the 1980s (e.g. for gemstones: Délé-Dubois et al.,
1980; for pigments: Delhaye et al., 1985). The first significant catalogue of the Raman
spectra of gemstones appeared in Pinet et al. (1992) and of pigments in Bell et al. (1997).
Only in the late 1990s did RM become introduced as a valuable new non-destructive
analytical technique applicable to a wider range of geomaterials (e.g. polished
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
ceremonial eclogite and jade axes: Smith & Gendron, 1997), or biomaterials (e.g. skin,
resin, linen: Edwards et al., 1996a, 1996b, 1996c), or inorganic and organic pigments
from Prehistoric rock art (e.g. Smith et al., 1999a; Edwards et al., 2000).
The pseudo-acronym “ARCHÆORAMAN” was coined by Smith & Edwards (1998)
to cover this new sub-discipline; Table 7 in Smith & Carabatos-Nedelec (2001) summarises
the early bibliography in this new field. A series of international congresses has promoted
interest in this sub-discipline for RM, mostly without the help of any complementary
analytical technique (GEORAMAN-1996 in Nantes, -1999 in Valladolid, -2002 in Prague,
-2004 in Honolulu; ICORS-1998 in Cape Town, -2004 in Gold Coast, and other meetings
in London in 2001 and Ghent in 2003); the present situation is literally an explosion of
publications. It is however clear that the majority of past (and present) work has been (and
still is) on pigments of one kind or another, and that the majority of researchers in
ARCHÆORAMAN are chemists or physicists, with an insufficient number of geologists
and biologists involved as there is an evident need to identify natural mineral, animal or
vegetable species and to try to determine their geological or biological provenance.
Table 2. Ten domains of the application of Raman analysis to archaeological samples (after Smith, 2002a).
Domain
gems
ceramics
rocks
corroded metals
resins s.l.
tissues s.l.
pigments/inks/dyes on or
in an inorganic substrate
pigments/inks/dyes on or
in an organic substrate
coloured vitreous materials
climatic deterioration of
any of these materials
Example materials
gemstones (rough, cut or mounted), cameos, corals, intaglios, jewellery etc.
china, earthenware, faience, glass, porcelain, pottery, slags, tiles etc.
axe heads, building columns, ceremonial stones, inlaid rock, millstones,
mosaics, necklaces, sculptures, vitrified forts etc.
corroded bracelets, coins, cutlery, necklaces, statues, swords, tools etc.
non-cellular organic material composed of only a few different molecules or of
amorphous hydrocarbons without a growth texture: amber, bitumen, coal, glue,
gum, oil, putty, wax etc.
cellular organic molecules or biominerals with a growth texture: bone, cotton,
feather, fur, hair, horn, ivory, leather, linen, nail, papyrus, parchment, silk, skin,
teeth, wool, wood etc.
brick, ceramic, plaster, stone, stucco etc.
bone, canvas, paper, skin, textile, wood etc.
pigments on or in enamel, glass or glaze etc.
corrosive agents involved, original, intermediate and final products
The ten topics classified by Smith (2002a) may be summarised as shown in Table 2.
The first four topics and the ninth are those most concerned with minerals and of these
the first has by far the greatest number of publications. The advantages for gemstones
are considerable as RM can be employed for several different purposes: to verify the
nature of the gemstone itself, to examine for treatments (e.g. heating, resin impregnation,
pigmentation), to explore solid or fluid microinclusions, or to detect synthetic and
imitation stones (e.g. Délé-Dubois et al., 1980; Lasnier 1989; Maestrati, 1989; Pinet et
al., 1992; Schmetzer et al., 1996; Smith & Robin, 1997; Hänni et al., 1998; Chalain et
al., 1999; Kiefert et al., 2001; Smith, in print, a). Ivory is arguably a gemstone or a tissue;
distinguishing real from fake ivory is easy with RM (Brody et al., 1998). Examples of
Raman spectroscopy: Analytical perspectives in mineralogical research
311
work on rocks were published in Smith & Bouchard (2000) and Smith (in print, b).
Ceramics was the last topic to be examined, both from the point of view of the minerals
constituting pottery (e.g. Fry et al., 1998) or the pigments in glazes (e.g. Liem et al.,
2000; Colomban & Treppoz, 2001). In the meantime new projects were launched to
evaluate the potential of RM to corroded metals (e.g. Bouchard & Smith, 1999, 2000,
2001; McCann et al., 1999; Smith & Bouchard, 2002; Frost, 2003) and to stained glass
(e.g. Smith et al., 1999b; Bouchard & Smith, 2002). Burgio & Clark (2001) presented an
updated catalogue of the Raman spectra of pigments of which many are minerals; new
catalogues of the Raman spectra of minerals involved in corroded metals, stained glass
or Prehistoric pigments were recently published by Bouchard & Smith (in print).
Selected examples of Raman applications in the Geosciences
Semi-quantitative micro-Raman spectroscopy of a gas inclusion
Fluid inclusions in minerals can be used as indicators of pressure-temperature and fluid
composition, provided that chemical composition and density of individual inclusions
are well known (e.g. Rankin, 2004). The typically small size (1–10 µm diameter) and
low weight (10–9–10–12 g) renders impossible in many cases reliable microscopic
observation, this being a prerequisite for the application of standard microthermometric
methods. Modern confocal micro-Raman systems reach an effective volume resolution
better than 5 µm3 (Markwort et al., 1995; Nasdala et al., 1996) and allow semiquantitative analysis of inclusions with sizes down to 2 µm diameter (Fricke et al.,
1990). Notch filter systems coupled with comparatively low power (40–100 mW) 514.5
or 532 nm excitation laser sources and a CCD detector guarantee high spectral efficiency
and resolution (Burke, 2001). Low laser power furthermore reduces the probability of
reactions in CO2-CH4 inclusions that could be induced by local laser heating effects (e.g.
Huizenga & Touret, 1999). Semi-quantitative estimations of two or more component
fluids within inclusions requires knowledge of the so-called Raman scattering “cross
sections”, a measure for the Raman activity of a certain component in mixtures
(Schrötter & Klöckner, 1979). Empirical calibration of the Raman spectrometer by gas
mixtures of known composition and density is nowadays used for the quantification of
fluid mixtures (e.g. Wopenka & Pasteris, 1986, 1987; Dubessy et al. 1989; Chou et al.,
1990; Seitz et al., 1993, 1996). The reproducibility of an analysis is usually better than
5% (van den Kerkhof & Kisch, 1993).
The following example illustrates a semi-quantitative estimation of the gas
composition of a natural CO2-CH4-N2 inclusion (supercritical at room temperature) in
quartz (Fig. 14a). The studied sample was taken from an Archean amphibolite-facies
lode gold mineralisation in Western Australia (Neumayr et al., 1993). The Raman
spectrum of the inclusion was excited with the 514.5 nm emission of an Ar+ laser. It
can be seen in Figure 14b that, in the spectral range between 600 and 3400 cm–1, bands
of three gas phases have been obtained, in addition to a number of low-intensity bands
of the surrounding host quartz. Band fitting, assuming symmetric GaussianLorentzian peak shapes, yielded the parameters given in Table 3. Note that the
observed Raman shifts of CO2, N2 and CH4 bands are slightly lowered when compared
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 14. Raman spectroscopy applied to gas analysis. (a) Photomicrograph of a gas inclusion in a quartz crystal
from a gold deposit in the Pilbara Block, Western Australia (for sample description see Neumayr et al., 1993).
(b) Raman spectrum taken from the central inclusion in (a). Bands of CO2, N2 and CH4 were obtained. Raman
bands of the host quartz are marked with asterisks.
Table 3. Band parameters for four Raman bands obtained from a fluid inclusion in quartz, and calculated molar
gas portions
Species
Observed Raman shift
[cm–1]
1282
CO2 (–)
1385
CO2 (+)
2327
N2
CH4
2912
Integrated peak area
Ai [cts cm–1]
3.5
7.1
1.5
116.8
Raman cross section
i (514 nm)
1.0
1.5
1
7.5
Instrumental Gas portion
efficiency i
[mol%]
1
20
1
1
7
1
73
to the 1 bar values (1285, 1388, 2331 and 2917 cm–1; Burke, 2001), which is taken as
evidence for elevated internal gas pressure in the inclusion. The determined Raman
band integrals are the basic input parameters to calculate relative molar fractions of the
three fluid species. Due to numerous influencing factors it is more accurate to calculate
relative molecule ratios in contrast to absolute numbers. The following formula is
based on Placzek’s polarisability theory (Placzek, 1934; Schrötter & Klöckner, 1979;
Dubessy et al., 1989):
Aa
a a
Xi .
Ai
i i
(6)
The parameters Xa, Aa, a and a are molar fraction, integrated band area, Raman crosssection and instrumental efficiency of species a in a fluid mixture, respectively.
For our sample inclusion, the integrated band areas Ai, Raman cross-sections i
and instrumental efficiency parameters i are given in Table 3. The i values, an
empirical calibrated instrumental parameter using synthetic gas mixtures of known
composition and density (van den Kerkhof, 1988), equals 1 for all species and the
specific instrument in our example. Insertion of the appropriate parameter for CO2
into Equation 6 leads to
Raman spectroscopy: Analytical perspectives in mineralogical research
X CO 2
3 .5 7 .1
2 .5 1
0.20 20 mol%.
3.5 7.1 1.5 116.8
2 .5 1 1 1 7 .5 1
313
(7)
According to Dubessy et al. (1989), the CO2 component should be calculated using the sum
of the two peak areas and the sum of their 2.5 in case of the 514.5 nm laser)!"In the same
way the N2 component is determined as 7 mol% and the CH4 component as 73 mol%.
Semi-quantitative chemical analysis by Raman spectroscopy
Semi-quantitative chemical analysis using Raman spectroscopy is usually assumed to
involve some kind of calibration of the absolute intensity or surface area of a specific
Raman band and its proportionality to the concentration of a particular chemical group,
on condition that the variation of spectral intensity with crystal orientation is adequately
dealt with (cf. FTIR using finely ground powders in KBr pellets). A completely different
approach is discussed here; this uses the wavenumber shifts and not at all the intensities,
since the wavenumber shift of a Raman band due to a chemical substitution is
independent of crystal orientation, and hence of polarisation effects (except where
modes overlap and may lead to confusion), and is a viable indicator of chemical
composition. It should be noted that the chemical elements detected may have no direct
involvement in the Raman vibration being used. For example wavenumber shifting of
the supposed Si–O–Si vibration in inosilicates like pyroxene and internal SiO4 vibrations
in nesosilicates like garnet is very dependent upon the cation charge and ionic radius of
the cations in nearby octahedral sites which do indeed have an indirect effect upon the
bond lengths and angles of the Si–O–Si and SiO4 vibrations respectively; thus one can
identify other cations simply by observing the behaviour of Si–O bonds.
Early work on binary systems was made on the natural system jadeite–diopside of
the pyroxene group, (Na1 – xCax)(Al1 – xMgx)Si2O6, by Smith & Boyer (1985) to examine
the heterovalent substitution of Na+Al3+ (jadeite: Jd) by Ca2+Mg2+ (diopside: Di), and on
the synthetic system spinel–magnesiochromite of the spinel group, Mg(CrxAl2 – x)O4, by
Malézieux et al. (1983) to examine the homovalent substitution of Al3+ by Cr3+. In both
systems the variation of Raman wavenumber with chemical composition was seen to be
at least close to linear, if not truly linear. A mathematical and statistical method for
determining the composition of an unknown sample in an n-dimensional chemical space
using the intersection of (n – 1) different Raman bands, and assuming linear variations
throughout, was presented by Smith & Pinet (1989). It was used by Smith et al. (1988)
for the ternary garnet system pyrope–almandine–grossular, and by Smith et al. (1989)
for the ternary pyroxene system diopside–hedenbergite–aegirine. Of course in a ternary
system where only two Raman bands are required (because the constant sum of all
considered end-members provides one constraint), the analysis may be done graphically
(Fig. 15); for a greater number of end-members in the solid solution, a mathematical
treatment by simultaneous equations is necessary.
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 15. A ternary system of end-members (A, B and C) where the wavenumber isopleths W1 for Raman peak
P1 are subhorizontal and the wavenumber isopleths W2 for peak P2 are subvertical. The intersection of the
measured wavenumbers of an unknown sample u for these two peaks (W1u and W2u) gives the semiquantitative analysis in terms of proportions of A, B and C.
The methodological approach and several related problems were discussed by
Smith (2001b, 2002b) where some example Raman analyses were presented using
ternary, quaternary, pentary or hexary garnet systems (i.e. including grossular, andradite
and uvarovite). For example, a composition of Gro0.53And0.43Uva0.03 was determined
using Raman bands I and II (Pinet & Smith, 1993, 1994) in the ternary system
Gro–And–Uva whereas Gro0.51And0.46Uva0.00 was determined for the same sample from
electron microprobe (EMP) analysis (i.e., an absolute discrepancy of ±3 mol%). A
Raman-based analysis (using bands I, II, IV and XII) of a garnet in the pentary system
Pyr–Alm–Spe–Gro–And gave Pyr0.01Alm0.20Spe0.53Gro0.26And0.01, whereas the EMP gave
Pyr0.04Alm0.27Spe0.43Gro0.20And0.06 (i.e., an absolute discrepancy of –7 to +10 mol%).
Of the eight problems cited in Smith (2001b), the three most important ones are
mentioned here. Firstly, the method is based on the wavenumber values of the pure endmember compositions, but these are not always known; hence they have to be estimated
statistically in multivariate chemical space or observed from experimental syntheses
(which do not always produce well-crystallized on-composition grains). Secondly, the
necessity to be sure that band Z of the unknown corresponds to band Z of the reference
data set. For many mineral groups this is not at all obvious and requires a timeconsuming calibration by means of obtaining both Raman spectra and electron
microprobe analyses on precisely the same region in a long series of natural standards in
order to be able to follow band Z “step by step” from one end-member to the other (Pinet
& Smith, 1993, 1994), since extrapolating from one to the other is very risky. Plotting
wavenumber shifts against chemical exchanges in order to observe the behaviour of each
Raman band in garnets reveals valuable information that can be used to select which
bands show the most consistent spectral appearances and the most linear trends, and
should provide the sharpest intersections because of varying in a different way (cf. Fig. 15).
Thirdly, the most difficult problem encountered is the low intersection angle of some isowavenumber isopleths in multidimensional chemical space (when no alternative Raman
bands are available); this can lead to large uncertainties and often carries the intersection
point out of the system’s boundaries and thus yield negative values (obviously
Raman spectroscopy: Analytical perspectives in mineralogical research
315
impossible chemically but perfectly normal mathematically). Work on this and other
problems is continuing gradually. At the moment it is not possible to give error bars with
this method, not just because of the complexity of error propagation through
simultaneous equations, but because it is difficult to put a value on the estimated error of
each Raman or EMP value.
A simple formula for obtaining the jadeite proportion (cJd) of jade in the ternary
diopside–hedenbergite–jadeite was given by Smith (in print, b) as:
cJd [mol%] = 2.5 (Unk – 663 cm–1),
(8)
with Unk being the Raman shift of the unknown in cm–1. Applying this simple formula
to a newly discovered Guatemalan jade (Gendron et al., 2002), a jadeite proportion of 95
mol% was calculated; subsequent EMP analysis confirmed 97 mol% Jd. Here the
accuracy is rather good, around ±2 mol% Jd, despite the fact that this is a short-cut
method of less accuracy for estimating the jadeite proportion in jadeite-jade in the
Di–Hd–Jd ternary with only one Raman band, because the difference between the
Si–O–Si symmetrical stretch wavenumbers for diopside (666 cm–1) and hedenbergite
(660 cm–1) are similar (Pinet et al., 1992) and their small difference is ignored; using a
second band for a proper ternary solution will give more accurate results, but ±2 mol%
is already the best that can be expected. This short-cut is recommended only for rapid
rough work on jade. In the Di–Hd–Ae ternary, proper full use of two Raman bands
yielded the following results: this semi-quantitative Raman method gave
Di0.56Hd0.02Ae0.42 whereas EMP analysis gave Di0.56Hd0.06Ae0.38 (Smith et al., 1989). Some
recent work on clinopyroxenes and orthopyroxenes was presented by Mernagh &
Hoatson (1997), but this only involved binary systems.
Smith & Périn (2003) used the same method to show non-destructively that many
Middle-Age Barbarian garnets in cloisonné gold jewellery from Vicq, France, were solid
solutions between pyrope and almandine (often called “rhodolite” by gemmologists
although this term is not recognised by the IMA). However when dealing with similar
incrusted stones from Brut in North Ossetia, Russian Federation, Smith et al. (2003)
noted that the ternary system Pyr–Alm–Spe, and also the quaternary system with
grossular added, was totally useless as they yielded extreme negative mol% values. It
was necessary to include andradite, and hence a pentary system, and this revealed
approximately 80 mol% andradite even if minor negative values occurred for some of
the other members and the accuracy is at least as bad as ±20 mol%. Thus whatever the
true composition, it is quite certain that the andradite makes up the bulk, and this was a
significant (non-destructive!) discovery for archæology as andradite was previously
unknown in cloisonné gold jewellery. If the reader has some reservations about the
validity of this method, it is sufficient to observe that andradite has the lowest
wavenumber of all six common natural garnets for several key Raman bands (e.g. bands
I & II at 994 & 873 cm–1, respectively, for andradite; similarly 1014 & 874 cm–1 for
grossular, 1027 & 904 cm–1 for spessartine, 1034 & 914 cm–1 for almandine, 1062 & 925
cm–1 for pyrope; values from Pinet & Smith, 1993, 1994). The wavenumbers for certain
crystals from Brut were so close to the pure end-member andradite that no other
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
algebraic combination of end-members could possibly give rise to such low
wavenumbers. Figure 16 shows the Raman spectra of a crystal from Brut with bands I &
II at respectively 995 & 876 cm–1 and of an andradite-rich standard (99.99 mol% And),
to display their similarity, and of two pyrope–almandine solid solutions also from Brut
to display their considerably higher wavenumbers.
Fig. 16. Raman spectra of cloisonné-gold garnets in a fibula from Brut, North Ossetia, Russian Federation. From
the top downwards a pyrope-rich Pyr–Alm solution, an almandine-rich Pyr–Alm solution, an andradite (from
Smith et al., 2003; Smith et al., in prep.) and finally an andradite reference (And0.999Uva0.001) from Pinet & Smith
(1993). Note the down wavenumber shifts of band I (on the right) and of band II (the most intense band in this
spectral zone) as one approaches andradite. This confirms that the crystal from Brut, deduced to be very rich in
andradite from the semi-quantitative method, really is very rich in andradite from comparison with a standard.
The usefulness of the semi-quantitative analytical method of Smith & Pinet (1989)
depends on the problem at hand; it was designed for the non-destructive analysis of
precious samples whether from the cultural heritage or of rare scientific samples such as
meteorites, or inclusions of olivine, pyroxene or garnet inside diamonds without the need
to extract them. It is very useful for sub-binary jadeite jade and has been shown to be
useful for pentary garnets. “Step-by-step” data sets have been built up for other mineral
groups such as olivines, spinels and tourmalines (Smith, in prep.). The method is easy
and moderately accurate for binary and ternary solid solutions, but becomes less easy
and less accurate with each new extra chemical dimension.
Characterisation of the real structure of natural carbon
Internal heterogeneities of diamond crystals
The Raman spectrum of diamond (#-C; cubic space group Fd3̄m) is dominated by one
intense first-order Raman band with a Raman shift of ~ 1332 cm–1 at room temperature and
ambient pressure, with second-order Raman bands occurring mainly in the range 2100–2700
Raman spectroscopy: Analytical perspectives in mineralogical research
317
cm–1 (Solin & Ramdas, 1970). The 1332 cm–1 band is assigned to the main zone-centre optical
phonon of diamond, and it is often referred to as LO=TO mode (longitudinal optical and
transversal optical lattice vibrations are degenerate, i.e., they have the same frequency,
because of the high symmetry of the diamond lattice). Even though consisting virtually of
only one band, the Raman spectrum is highly typical of diamond and allows the unambiguous
identification of this mineral. For instance, petrologists use Raman microprobe analyses to
verify the identity of microdiamonds in high-pressure rocks and, with that, to conclude about
depths of rock formation and metamorphic conditions (e.g. Sobolev & Shatsky, 1990; Izraeli
et al., 1999; Nasdala & Massonne, 2000; Massonne & Nasdala, 2003; for an overview see
Chopin, 2003, and references therein). Many recent applications of the Raman technique are
related to materials science research, for instance the analysis of thin films, substrates and
layers of (cubic) diamond, as well as (amorphous) diamond-like carbon (DLC), that are
applied to the surface of various materials (e.g. Shroder et al., 1990; Knight & White, 1996).
As an example for the potential of Raman spectroscopy for the investigation of
natural diamond, we discuss recent Raman studies on diamond crystals from the Panda
kimberlite in the Ekati diamond mine, Northwest Territories, Canada, that contain large,
single-crystal graphite inclusions. These graphite inclusions exhibit a pseudo-hexagonal,
plate-like habit (cf. Fig. 18a below) and are oriented with their (001) face parallel to a
(111) face of their diamond host. Glinnemann et al. (2003) found that the graphite
inclusions have remnant pressures up to 2.6 GPa (estimated from unit cell parameters).
Raman spectra obtained from the neighbouring host diamond have confirmed these
pressure estimates (Nasdala et al., 2003b); this was possible because it is well known
how much the Raman shift of the LO=TO mode increases with increasing pressure
(Grimsditch et al., 1978; Hanfland et al., 1985; Boppart et al., 1985).
Raman maps produced by Nasdala et al. (2003b) showed that inclusions are
surrounded by haloes of enhanced intracrystalline pressure/strain (cf. “inhomogeneouslydistributed isobars”; Smith, 1984), several hundred µm across (cover picture). It is
obvious that the external pressure relaxation during the uplift of the diamond crystals
must have resulted in heterogeneous expansion of the diamond-inclusion couples. Caused
by particularly extensive volume expansion of graphite crystals along their c axes (Zhao
& Spain, 1989), complete pressure relaxation in the neighbouring diamond was hindered
and, therefore, distinct haloes of enhanced remnant pressures (compressive strain) in the
diamond are observed in areas next to graphite (001) faces (see blue-black areas in the
cover picture). The volume expansion of graphite along [001] has also led to the opening
of disc-shaped cracks in the surrounding diamond parallel to the graphite (001) plane (cf.
Fig. 18a below). Diamond areas close to the ends of such cracks are affected by strong
dilative strain (see red-yellow areas in the cover picture).
It has been discussed controversially whether the well-shaped graphite single crystals
are primary and diamond is secondary in nature, or graphite and diamond are syngenetic and
grew more or less simultaneously. Nasdala et al. (submitted) found that Raman maps based
on the FWHM of the LO=TO mode show often patterns that reveal the growth zoning of
diamond. Based on such patterns indicating that the internal diamond growth texture starts
from, and virtually surrounds, the graphite inclusions (Fig. 17), it is now possible to
conclude that graphite must be the primary phase and has been overgrown by diamond.
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 17. Two-dimensional (2D) tomographic Raman mapping used to reveal internal growth textures inside
diamond crystals from the Panda kimberlite, Ekati diamond mines, Canada. Samples by courtesy of J.W. Harris
and J. Glinnemann. For a more detailed sample description see Glinnemann et al. (2003). (a) Diamond PAG02,
view along [110] (modified from Nasdala et al., 2003b). (b) Diamond PAG03, view along [111] (modified from
Nasdala et al., submitted). Both diamond crystals contain one large graphite inclusion. Slight variations of the
FWHM of the diamond LO=TO mode reveal patterns that are interpreted as growth zoning of the diamond
crystals. Areas with particularly high FWHMs (caused by additional local strain) indicate the locations of the
graphite crystals and cracks in the host diamond. It can be seen that in both cases the growth zoning originates
at the graphite inclusion. This observation characterises the graphite inclusion as the primary mineral and the
host diamond as overgrowth.
Estimation of the order/disorder of graphitic carbon
Single-crystal graphite (-C; hexagonal space group P63/mmc) has nine vibrational modes,
of which only two (E2g type modes) at 42 and 1581 cm–1 are Raman active (Tuinstra &
Koenig, 1970; Nemanich et al., 1977; Dresselhaus & Dresselhaus, 1981). Since only few
mineralogical laboratories routinely obtain spectra in the low frequency range below 100
cm–1, the first-order Raman spectrum of well-crystallised, natural graphite is generally
known to be dominated by a single, intense band at ~ 1580 cm–1 (Fig. 18d). This relatively
sharp band (FWHM 20 cm–1) is assigned to stretching vibrations of carbon-carbon bonds
within the sp2 layers, which are degenerate due to the high symmetry of the hexagonal
graphite {001} planes, and it is usually referred to as the graphite G band (e.g. Knight &
White, 1989; Kawashima & Katagiri, 1995; Ferrari & Robertson, 2000). Its first overtone
was described as weak but sharp band at 3248 cm–1 by Nemanich & Solin (1977), in
addition to two more intense second-order bands at ~ 2440 and ~ 2730 cm–1 (for detailed
band assignment see, for instance, Kawashima & Katagiri, 1995).
The Raman spectra of microcrystalline graphite and disordered carbon show
additional, intense bands at ~ 1350 (the D band; a normally Raman inactive A1g mode that
is activated due to the finite crystal size) and ~ 1620 cm–1 (the D’band; related to the disorder
of graphite). Since these two bands (Fig. 18b, d) are normally not observed from single
crystal graphite, they are referred to as “disordered modes”. In disordered carbon, the D’
mode overlaps with the G mode and, as a result, only one broad band at ~ 1600 cm–1 is
obtained. The width and asymmetry of this overlap peak is, therefore, often used as a
measure of the order/disorder of carbon. Note that the intensity ratio of the G and D modes
provides only a rough estimate of the crystallinity of carbonaceous samples as long as the
orientation of the sp2 carbon layers with respect to the electric field vector of the laser beam
is unknown. This is because the D mode is also observed (even though with lower intensity)
Raman spectroscopy: Analytical perspectives in mineralogical research
319
Fig. 18. Two examples for the Raman-based structural characterisation of natural carbonaceous samples. (a)
Optical photomicrograph of a single-crystal graphite inclusion in diamond PAG07 (view along diamond [111])
from the Ekati diamond mines, Canada (Glinnemann et al., 2003; Nasdala et al., 2003b). The inclusion is
surrounded by two disc-like shaped cracks in the host diamond. (b) Two corresponding Raman spectra (632.8 nm
excitation). The large graphite crystal (measurement A) is, as expected, well ordered as only a narrow graphite G
band is obtained in addition to the intense diamond LO=TO band. The surrounding inner crack (measurement B)
shows the presence of disordered graphitic carbon. This is indicated by the graphite D’ band, seen as shoulder of
the broadened graphite G band. The tails of the strong diamond LO=TO band appear broadened due to graphite
D band (at ~ 1340 cm–1) as well as an additional band at the low-frequency side. (c) Scanning electron microscope
image showing the (001) plane of a graphite crystal from a uranium mineralisation in Saskatchewan, Canada (for
sample description see Wang et al., 1989). Hollow points were formed by either chemical alteration or radiation
effects. (d) Two corresponding Raman spectra (514.5 nm excitation). The main body of the crystal is well ordered.
The measurement placed inside a hollow point reveals strong structural disorder. The broad band at ~ 1600 cm–1
is interpreted to consist of an overlap of the broadened graphite G and D’ bands.
in the edge plane of macroscopic graphite crystals, which was explained by Katagiri et al.
(1988) as due to the breakdown of translational and local lattice symmetries. Note also that
the Raman shifts of the D and D’ bands, as well as further first-order disordered modes of
lower intensity, their overtones and combinations with other modes, vary in dependence
with the excitation frequency (Vidano et al., 1981). For instance, the D band shifts from
1365 cm–1 with 457.9 nm excitation down to 1284 cm–1 with 1064 nm excitation
(Kawashima & Katagiri, 1995; Wang et al., 1998). The appearance and spectral features
(band positions, relative intensities, widths) of the D and D’ bands (and their overtones and
combination bands) are routinely used to characterise and estimate the crystallinity of
naturally formed graphite (for example, Wopenka & Pasteris, 1993; Yui et al., 1996;
Beyssac et al., 2002) and other carbonaceous samples such as bitumen (Jehlicka et al., 1997)
and aerosols (Sze et al., 2001). In the following, we will briefly discuss three examples.
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
We have already described above that extensive volume expansion along the c axis
of single-crystal graphite inclusions in diamond crystals from the Panda kimberlite,
Canada, has typically resulted in the opening of disc-shaped cracks in the neighbouring
host diamond (Fig. 18a). Inspection under a high-power optical binocular microscope
indicated that the cracks may be partially filled by carbonaceous matter. This was
confirmed by Nasdala et al. (2003b) who showed that the pseudo-hexagonal graphite
crystal is well-ordered whereas cracks are partially filled with poorly ordered sp2 (i.e.,
graphitic) carbon (Fig. 18b). Note that spectrum B in Figure 18b gives also some
indication for the additional presence of another carbon species. The D band of
disordered graphitic carbon should have its maximum intensity at ~ 1340 cm–1 with HeNe excitation and, therefore, most of its intensity should be expected at the highfrequency tail of the strong diamond LO=TO band (signal from the diamond host). The
additional intensity at the low-frequency tail points to the presence of a sp3 carbon
species, possibly disordered nanometre-sized diamond (e.g. Yoshikawa et al., 1995).
In a comprehensive study, Wang et al. (1989) investigated graphitic samples from a
metamorphised uranium deposit in Saskatchewan, Canada. These authors observed
moderate graphite degeneration only at the surface and interpreted this as a result of a
secondary alteration process undergone by the deposit. In addition, some graphite samples
that were collected from places close to uranium concentrations exhibit numerous hollow
points with sizes of several m and smaller (Fig. 18c). These hollow points were found to
show severe structural damage, indicated by an almost amorphous structure of the carbon
(Fig. 18d). Wang et al. (1989) discussed that the higher degree of graphite alteration
observed inside the hollow points might be due to either irradiation or chemical damage.
The third example is related to an application that has been controversially discussed
in the past two years, namely, the Raman analysis of potential carbonaceous remnants of
very old microfossils (e.g. Schopf et al., 2002; Brasier et al., 2002). Schopf et al. (2002)
proposed that poor ordering of carbonaceous unknowns might be indicative of kerogen (i.e.,
maturated bio-organic matter). In Figure 19, we present Raman spectra and maps obtained
from graphite flakes occurring in an early Archaean, metasomatic rock (metacarbonate)
from the Isua Supracrustal Belt, southern West Greenland (Lepland et al., 2002; van Zuilen
et al., 2002, 2003). Analyses done on graphite flakes exposed to the polished surface yielded
Raman spectra that are typical of highly disordered carbon (Fig. 19a). However, it is well
known that graphite (Wang et al., 1989) and other minerals (e.g. Libowitzky, 1994) may
experience superficial structural damage and disorder due to the mechanical thinning and
polishing process, which draws into question the high disorder being deduced as a natural
feature of graphite having become exposed at the surface of polished sections. These doubts
were confirmed by Raman maps (Figs. 19b, c) obtained from a graphite flake that is partly
exposed at the surface of the section and partly buried under the thin cover of chlorite. It can
be seen that the graphite flake is generally well ordered in areas where it is covered by
chlorite while it is highly disordered only in three areas in which the graphite is exposed at
the surface and was affected by the mechanical polishing process. Raman spectroscopy
cannot be thus applied as an unambiguous biodiagnostic tool because the reliable distinction
between kerogen and highly disordered graphite of inorganic origin is not possible from the
spectra alone (e.g. Pasteris & Wopenka, 2002).
Raman spectroscopy: Analytical perspectives in mineralogical research
321
Fig. 19. Raman maps of a graphite flake in a metacarbonate (sample no. AL8-1; courtesy of A.
Lepland) from the 3.8 Ga Isua Supracrustal Belt, Greenland, showing that graphite disorder can be
induced by the polishing process. (a) The two Raman spectra show that graphite that has been exposed
to the surface of the thin section is disordered (spectrum A) whereas the main graphite flake, analysed
through a thin chlorite cover, appears well-ordered (spectrum B). (b) A Raman map of the surface,
generated from the integral intensity of the band at ~ 1600 cm –1, shows three micro-areas in which
graphite is exposed at the surface. This map corresponds widely to an optical microphotograph taken
in the reflected light mode (not shown). (c) A Raman map, recorded with the focus of the fully focused
beam adjusted ~ 2 µm below the surface and generated from the broadening of the ~ 1600 cm –1 band,
shows that only the three exposed areas have experienced structural disorder (large FWHMs) as a result
of the mechanical polishing process. Surrounding micro-areas that are still covered by chlorite are well
ordered (smaller FWHMs).
Gemstone identification by Raman spectroscopy analysis through glass
Three Florentine tables in stone marquetry, a large one of white marble inlaid with
precious stones representing mainly flowers and birds or insects, and two smaller ones
of black marble inlaid mainly with flowers and fruit, are conserved inside the highsecurity “Trésor” of the Muséum National d’Histoire Naturelle in Paris. These beautiful
early XVIIth century tables are each covered today by a heavy sheet, 1.6 cm thick, of
protective glass. Although the mineral species of many of the gemstones had previously
been recognised [e.g. purple amethyst (quartz), blue lapis-lazuli (lazurite)], their identity
had never been definitively proved, partly because of the overlying plate glass and partly
because of the obvious refusal to allow the extraction of any crystal or part thereof for
precise gemmological analysis. For several of the gemstones recognition was not
obvious, especially the whitish and greenish ones composing different kinds of flowers.
A mobile Raman system equipped with optical fibres and a green 532 nm laser and
a separate unit with a red 785 nm laser were carried into the Trésor. The protective glass
was not removed from the tables, partly to avoid possibly damaging the table and partly
because of its considerable weight. Successively for each table the small box containing
the laser source, photon detector and spectrometer unit was placed on a trolley on the floor
near the table and a photograph’s tripod was placed on the glass. The remote head was
suspended vertically from the tripod and the laser, arriving by an optical fibre, was
focussed through the remote lens on to a specific crystal of interest 7.5 cm away (Fig. 20).
The Raman scattered light returned by the same optical path. It was very easy to just slide
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 20. Raman analysis though a glass cover I. (a) Part of a mobile Raman system sitting on top of a very large
precious Florentine white marble table in stone marquetry protected by 1.6 cm thick plate glass (reflections
visible). Note the incrusted gemstones forming various ornamental designs, especially birds and flowers. Note
the tripod suspending the remote head with its long focal length lens (black tube with white rim at bottom
reflected on to the computer box at the side and on to the glass below). Treasure vault of the National Museum
of Natural History, Paris, in 2000. (b) A close-up view of remote identification through glass of a blue tulip-like
flower inlaid in the same marble Florentine table. In this case, the obtained PL spectrum confirmed the expected
mineral nature: lazurite (the key colorant of lapis lazuli). The white mark is at the end of the remote lens and the
shadows come from the tripod legs. (c) Verification of the mineral species of a yellowish-white petal of an inlaid
flower in a magnificent Florentine table of black marble; note that the computer keyboard and mouse as well as
the tripod were able to be placed over this precious work because it is protected by a glass plate (invisible). The
collection lens is suspended 7.5 cm above the crystal. All photographs were taken by D.C. Smith.
the tripod over the glass and analyse any crystal at will, often with no need to readjust the
focus. The results were obtained rapidly by means of their Raman spectra appearing on
the computer screen, which was also placed on top of the glass. With this configuration,
all parts of the mobile Raman unit and of the table were within reach of the analyst.
The protective plate glass could be assumed to constitute an obstacle, as it indeed is
for applying almost all, if not all, other microanalytical techniques. Five reasons explain
why the glass does not create any insurmountable problem, and in most cases no problem
at all. Firstly, it is well known that the Raman effect concerns the transmission of a beam
of light and a transparent medium like glass or water allows the beam to cross it, and to
return if 180° geometry is used (as in this case where the laser beam successively travelled
Raman spectroscopy: Analytical perspectives in mineralogical research
323
through an optical fibre, the remote lens, the air above the table, the glass on the table, and
finally the crystal being analysed; the Raman diffused light that was collected returned by
the same glass, same air and same lens and then another optical fibre). Secondly, the glass
yields its own Raman spectrum, but, although being superposed on the Raman spectrum
of the crystal being analysed, this is no problem if the glass spectrum is weaker and/or its
Raman bands are wider relative to those of the crystal. Thirdly, the Raman bands of the
glass may be in spectral zones where there are no Raman bands from the crystal, and vice
versa, hence no problematic overlap. Fourthly, if there is a problematic overlap, it is easy
to acquire a Raman spectrum of the pure glass and then simply subtract it from the
combined spectrum. Lastly, but not least, the laser beam is focussed by the remote lens
and the photon collection system collects mostly light emanating from the level of the
focal point on or in the crystal, such that most of the Raman signal from the overlying
glass is not recorded (cf. confocal analysis of a microinclusion where it is possible to
exclude the Raman signal from the host mineral).
In the larger table the matrix is a sheet of white marble, calcite being confirmed
by its Raman spectrum (Fig. 20a). The green thorax of an insect initially posed a
problem since its identification was far from obvious (pyroxene?); in fact its Raman
spectrum quickly revealed ordinary -quartz (Smith & Rondeau, 2001). Several parts
of flowers or birds or ornamental borders are composed of a deep blue material, for
example in the petals of blue tulip-like flowers (Fig. 20b; Smith, 2001a); all parts
analysed yielded an intense identical luminescence with the red laser which
corresponded to the luminescence from the lazurite in a type specimen of lapis-lazuli
from Afghanistan. Thus here the identification of lazurite in the table was made by
luminescence with a Raman spectrometer and not by Raman spectra which were
completely eclipsed by the luminescence.
In both of the smaller tables the matrix is of black marble and there are more fruit
representations than on the large white table, as well as a greater proportion of
incrustations to matrix (Fig. 20c). Purple grapes gave, as expected, the Raman spectrum
of -quartz (i.e., amethyst from its characteristic colour). The petals of some flowers
were yellowish white and could have been of calcite, quartz or even of ivory or yet some
other phase like feldspar; in fact they are of dolomite as proved rapidly by its key Raman
bands at 178, 301, 724 and 1098 cm–1 (Fig. 21; Smith, in print, a). A pomegranate has
many red pips which were presumed all to be of garnet; in fact some were of garnet but
others were of ruby; this was especially interesting as it indicated the use of two different
mineral species for the same motif and also the use of a very precious stone.
This project, the first of its kind reported, was in fact incredibly easy as the
apparatus was perfect for the job to be done and it is clear that various other projects
necessitating analysing through glass should be also feasible. The real problem was
statistical, as there were too many crystals for all of them to be analysed in the time
available; for example all of the hundreds of similar-looking blue crystals, but with
varying hues, may well be of lazurite, but to what extent can this statement be justified
on the basis of analysing only a handful of crystals? However this problem is no worse
than that for all other mixtures containing innumerable grains (cf. mineral pigments and
of course natural rocks).
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L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
Fig. 21. Raman analysis though a glass cover II. The inset photograph (corresponding to the centre of Fig.
20c) is a close-up of a yellowish-white petal being analysed under the thick protective glass by the red
632.8 nm laser beam (spot is seen as bright circle). The Raman spectrum obtained from one of the
yellowish-white petals of the flower (corrected for backgound luminescence; solid graph) is shown in
comparison with the spectrum of dolomite from Freiberg, Germany (dotted). The obtained spectrum
reveals the four principal bands of dolomite.
In situ Raman spectroscopy of quartz: A new pressure sensor
Quartz is one of the early and most extensively studied minerals in Raman spectroscopy
(e.g. Raman & Nedungadi, 1940; Gillet et al., 1990). Due to the importance of quartz in
crustal processes as well as for technical applications, a number of experimental studies of
the temperature and pressure variations in the Raman spectrum of quartz have been carried
out (e.g. Raman & Nedungadi, 1940; Pine & Tannenwald, 1969; Briggs & Ramdas, 1977;
Dean et al., 1982; Jayaraman et al., 1987; Gillet et al., 1990; Liu & Mernagh, 1992; Castex
& Madon, 1995). Furthermore, SiO2 exhibits a number of high-pressure and/or hightemperature polymorphs. These phases (Smith, 1984) and the phase boundaries among
them (Gillet et al., 1998) can be well identified by Raman spectroscopy. Thermodynamic
properties of quartz have been inferred from vibrational modelling (Kieffer, 1979; Gillet et
al., 1990; Castex & Madon, 1995). Such models are based on Grüneisen parameters, which
are calculated from experimentally derived parameters like pressure- and temperatureinduced shifts of the frequencies of vibrational modes. To improve such data, pressure
sensors are needed that work reliably at high temperatures, too.
Coupling a powerful Raman spectrometer with a hydrothermal diamond anvil cell
(HDAC; Bassett et al., 1996) permits precise in situ Raman spectroscopy of -quartz at
temperatures from 23 to 800 °C and simultaneously at hydrostatic pressures ranging between
0.1 MPa and 2.1 GPa (Schmidt & Ziemann, 2000). Due to the specific measurement
procedure reported in detail in that study, the errors of data are comparably small in the
investigated temperature and pressure ranges. The accuracy and reproducibility of the
temperature measurement is < ±1.5 °C. Determined pressures have typical errors of < ±20
MPa even at high temperatures up to 800 °C. To improve the accuracy of the Raman line
position determination, the wavenumbers are calibrated using the plasma lines of the Ar+ laser
by removing the interference filter (plasma lines at 116.0 cm–1, 266.3 cm–1, and 520.3 cm–1;
see lower spectra in Fig. 22). The resulting wavenumber accuracy is about ±0.2 cm–1.
Raman spectroscopy: Analytical perspectives in mineralogical research
325
Fig. 22. Raman spectra of -quartz, presenting examples for pressure-induced (top pair of spectra) and
temperature-induced (below) shifts of Raman-active modes. Note that in particular the 206 cm–1 band (A1 mode)
shows dramatic changes in frequency and width. In the lower pair of spectra, the 128 cm–1 -quartz band is partially
obscured by a plasma line emitted by the Ar+ laser (apparent Raman shift 116 cm–1; marked with asterisks).
The lines of the three most intense Raman modes of -quartz (464, 206 and 128
cm–1 at ambient conditions) shift towards higher wavenumbers with increasing P
(pressure) and towards lower wavenumbers with increasing T (temperature; Fig. 22).
The pressure-induced frequency shifts of these modes show very different slopes and
behaviours of linearity at room temperature (Fig. 23a). No significant deviations were
found among the data obtained from the two samples used in that study, which was done
on a synthetic and a natural quartz crystal.
Fig. 23. Pressure-induced shifts of Raman bands of -quartz. (a) Frequency shifts of the three most intense Raman
bands in the -quartz spectrum as a function of pressure (observed at room temperature). Frequency shifts are plotted
relative to the band positions at 0.1 MPa. Note that pressure-induced frequency changes of some quartz bands exceed
the pressure-induced frequency shift of the ruby luminescence (e.g. Piermarini et al., 1975; Mao et al., 1986). (b)
Pressure-induced shift of the 464 cm–1 A1 mode as a function of temperature. Provided the temperature is known, this
plot can be used for pressure determination in HP-HT experiments. Plots from Schmidt & Ziemann (2000), modified.
326
L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
The most intense A1 Raman mode of quartz (at 464 cm–1) shows simultaneously a
relatively large and quasi-linear pressure dependence and a still moderate shift with
temperature in the studied P-T range (Fig. 23b). The pressure-induced frequency change
of this band is slightly higher than that of the ruby fluorescence scale (Fig. 23a).
Therefore, the Raman shift of this band is proposed as pressure sensor in HDAC studies
of SiO2-saturated systems at temperatures between –269 °C and 560 °C. Equations for
the pressure calculation were presented by Schmidt & Ziemann (2000).
The A1 Raman mode of quartz at 206 cm–1 is strongly anharmonic (Gillet et al.,
1990; Castex & Madon, 1995). With increasing pressure, the frequency of this mode
increases non-linearly with a negative curvature at room temperature (Fig. 23a). The
pressure-induced frequency shift relative to the line position at 0.1 MPa (v~206) exceeds
that of the ruby fluorescence by about 3 times. Therefore, this mode can be used
alternatively to the ruby sensor for room-temperature experiments at pressures up to
about 5 GPa with the equation of Schmidt & Ziemann (2000):
(9)
P [MPa] = 0.4633 (v~ )2 + 31.66 (v~ ).
206
206
A first application of pressure-induced shifts of -quartz Raman bands as a
pressure sensor was presented by Ziemann & van den Kerkhof (2002). These authors
have analysed a quartz specimen from an amphibolite-grade metamorphosed migmatite
from the Colorado Front Range, USA (for the sample description, see Olsen, 1987). The
quartz crystal is were found to contain several superdense CO2 inclusions (van den
Kerkhof & Olsen, 1990). In their Raman study, Ziemann & van den Kerkhof (2002) used
the host quartz itself as a “pressure gauge” to measure the pressure field around the CO2
inclusions. They found that in Raman linescans across one of the “superdense” CO2
inclusions, the A1 -quartz mode at 206 cm–1 shifted towards higher wavenumbers,
indicating significantly increased internal pressure of the host quartz in micro-areas
close to the inclusion. The measured band upshift corresponded to internal pressures on
the order of 40 MPa (Ziemann & van den Kerkhof, 2002). The observed field of
enhanced pressure in the host quartz is assumed to stabilize the superdense inclusions.
Summary: Advantages and disadvantages
Instead of attempting to present conclusions about the Raman technique and its
applications, we complete this paper with a brief summary of the analytical
disadvantages and advantages that are most relevant for researchers who apply Raman
analysis to the study of minerals and other geological objects. It is remarkable that, in
spite of the great research progress and technical developments during the last decade,
including the advent of several new analytical methods, the principal disadvantages and
advantages of Raman spectroscopy are essentially the same as those listed almost 20
years ago by Herman et al. (1985; for more recent discussions see for instance Hope et
al., 2001; Nasdala et al., 2001a; Bugay, 2001).
One of the main disadvantages is still the limited availability of reliable reference
data for minerals. Most geoscientific applications use Raman spectroscopy as a
fingerprinting tool for the identification of minerals and related phases. In such cases it is
Raman spectroscopy: Analytical perspectives in mineralogical research
327
not absolutely necessary to know which vibrations the observed bands are assigned to,
rather it would be sufficient to have Raman data of the relevant standard species available
for comparison. Even though quite a number of institutions and Raman laboratories have
been working hard over the last few years to build up their own Raman databases for
minerals, a fully reliable and comprehensive library does not yet exist. Several catalogues
of Raman spectra have been published already, and many spectra collections can be found
on the internet. Critical evaluation of these data, however, implies that a significant
number of spectra (according to a cautious estimation of about 5%) are incorrect.
Searching for the spectrum of a certain mineral is also made difficult because of different
terminologies. For instance, to find the spectra of the minerals azurite, cuprorivaite,
lazurite, goethite and orpiment in a mineral pigment library, one may need to know
respectively names such as Mountain blue, Egyptian blue, Ultramarine, Yellow ochre and
King’s yellow. Finally, none of the presently existing databases are complete (i.e., none
contains the spectra of all common rock-forming minerals). This problem, however, will
hopefully be remedied in the not too distant future.
If a Raman analysis yields a spectrum that is unknown to the researcher, there are
basically three practical ways for the identification of the sample, namely (1) finding a
sufficiently matching spectrum by a library search (problems addressed above), (2)
partially identifying an unknown, for example as a carbonate or as a sulphate on the
basis of a strong Raman band in the appropriate range for the most intense CO3 or SO4
vibration, using existing spectra of similarly composed/structured minerals, or (3)
producing one’s own standards (i.e., obtaining a number of spectra from available or
synthesised minerals whose chemical composition might be similar to that of the
unknown). The hypothetical fourth way, namely, the calculation of the theoretical
Raman spectrum of a suspected mineral species, is mostly impossible or at least highly
impractical. There exist a number of computer codes with which it is possible to
calculate quickly a theoretical X-ray diffraction pattern from the unit cell parameters
and atomic positions of a mineral. By contrast, the calculation of a fully reliable
theoretical Raman spectrum is costly in terms of time for simple mineral structures and
still almost impossible for complex mineral structures, especially in view of the nonideal chemical and structural composition of naturally formed minerals. This difficulty
is also affected by another general problem of Raman spectroscopy, which is the often
complicated band assignment.
Furthermore, it must be mentioned that not all mineral species can be analysed
using the Raman technique. Some minerals have no first-order Raman spectrum (due to
their lattice symmetry, an example is halite). Others are in general difficult to analyse,
like manganese oxides, because of their thermal sensitivity and/or strong light
absorption, or because of their poor transparency (especially minerals with a metallic
lustre). Finally, other effects such as the occurrence of intense luminescence (of various
origins, e.g. trace elements such as Cr3+; organic detritus as occurs in biominerals, or in
dead microbes or algae in ancient pigments; patina on climate-exposed archaeological
artefacts) and the so-called “Raman background” (an extremely broad Raman signal
related to defects; see Pilz & Kriegsmann, 1987; Splett et al., 2000) may hinder the
successful Raman analysis of unknowns.
328
L. Nasdala, D.C. Smith, R. Kaindl & M.A. Ziemann
In spite of these problems, Raman spectroscopy, favoured by a number of
analytical advantages, has been successfully used in all geoscientific disciplines, and the
number of Raman-related publications per year increases rapidly. First of all, analysis is
mostly possible without any sample preparation. There is no need for powdering,
thinning, sawing, scraping, breaking, drilling, coating/sputtering or dissolving of the
sample, and often the object to be analysed does not even need to be removed from its
matrix. Sample polishing is mostly also unnecessary, but it is usually done if the same
samples are to be analysed with other techniques anyway, or to improve the beam quality
through the suppression of diffuse reflection/scattering of light at a rough sample
surface. Another important point is that Raman analysis can be done non-destructively.
This is most advantageous for complex studies applying a variety of techniques to the
very same micro-areas in minerals. Since a Raman analysis does not cause any
permanent damage to the sample (of course only under the prerequisite that any local
strong light absorption, photochemical reaction etc. was avoided by the experimentalist),
it will not affect the results of other techniques that are performed later. In contrast, it is
well known that an electron microprobe analysis is not non-destructive on a scale of
single analysis pits. Raman measurements should, therefore, generally be done before
electron microprobe point analyses. A non-destructive technique (which does not even
require any sample preparation) is also very well suitable for the analysis of valuable and
rare objects such as gemstones or unique historic treasures. Furthermore, Raman
analysis can be done without any direct contact with the sample. This advantage is used,
for example, in the in situ analysis of inclusions inside their host mineral (e.g. included
liquids and gases, fossilised pressures in and around HP inclusions), the analysis inside
many kinds of cells and containers (e.g. diamond anvil cells, heating experiments,
industrial processes) and truly at-distance analysis (e.g. environmental analysis).
The Raman technique has an excellent volume resolution down to the micrometer
scale. This allows for the analysis of tiny amounts of sample and truly microprobe
analysis. Due to the excellent volume resolution, information on the
homogeneity/heterogeneity of samples can be obtained, and images can be generated,
both with a lateral resolution of ~ 1 m. Another advantage of the Raman technique is
its sensitivity to short-range order in materials, which allows for the investigation of
glasses, fully metamict minerals, melts and other “X-ray amorphous” samples (for
example, structural information on the initial stages of recrystallisation processes, and
bonding and coordination of ions in molten rock can be obtained). Last but not least,
powerful Raman systems are comparably affordable in terms of acquisition and
maintenance (for instance, an electrical socket and a regular office table are sufficient
nowadays to run a Raman microprobe system, and beam calibration and adjustment
procedures have become really undemanding).
It is clearly not our goal to claim that Raman yields more information than other
analytical techniques. This may be true in some cases, but in other cases it is other
techniques that yield more useful data (e.g. isotopes or trace elements). No technique is
perfect for everything, and the applied technique(s) will always depend on the analytical
problem to be solved. The difference from most other analytical techniques and one of
the greatest advantages of Raman spectroscopy is that the information (mineral
Raman spectroscopy: Analytical perspectives in mineralogical research
329
identification or mineral characterisation) can often be obtained in a really
straightforward and non-destructive way. Hence it does not need much insight to foresee
that in future, with an increasing number of spectrometer systems at universities and
other research institutions and more extensive reference data available, Raman will soon
become a routine technique in mineralogy, as common as IR spectroscopy, which in
several research fields is gradually being replaced by Raman. Whereas most analytical
techniques provide only the chemical composition or the physical structure of an
analysed volume, with Raman specroscopy both are obtained simultaneously, even if
indirectly (cf. IR absorption and X-ray diffraction). Also there are not many techniques
that can analyse solids, liquids or gases, crystalline, molecular, vitreous or amorphous
inorganic or organic materials, and especially mixtures of these such as composite fluid
inclusions, biominerals or pigments. If there were one keyword which best summarises
the generally advantageous nature of the Raman spectroscopic technique, it would
probably be “versatility”.
Acknowledgements
We are indebted to Matthias Balz, Ashis K. Bandyopadhyay, Frank E. Brenker, Rodney
C. Ewing, Jürgen Glinnemann, Jens Götze, Tobias Häger, Jeffrey W. Harris, Wolfgang
Hofmeister, Aivo Lepland, Hans-Joachim Massonne and Alian Wang for providing
samples for analysis, experimental assistance and/or their permission to use data for
presentation in this paper. Thanks are due to Gert Irmer, Aivo Lepland, Christian
Schmidt, Dieter Wolf and Brigitte Wopenka for constructive comments. We are grateful
to John M. Hanchar for critical reading of the manuscript and editorial help. Constructive
reviews by E. Libowitzky and an anonymous expert are gratefully acknowledged.
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