More than 30 years ago, Sam Houk, professor of chemistry at Iowa State University (Ames, Iowa), and a scientist in the Ames Laboratory of the United States Department of Energy, was the first scientist to use an inductively coupled plasma (ICP) as an ionization source for mass

In what new applications areas is ICP-MS being used?

 ICP-MS is still very widely used in its traditional applications — environmental analysis, semiconductor analysis, isotopic and materials analysis in the nuclear industry, and so on — but there are some very interesting new ones, such as forensic matching of evidence based on its trace-element composition. There's much more work in biological analysis now, including speciation or measurement of the chemical forms of the elements, at trace and ultratrace levels. Usually that requires coupling chromatographic separations with ICP-MS. And there's even a group that is finding previously undiscovered elements by doing ICP-MS experiments at very high mass. This is done mainly by a group in Israel, and [they have] found evidence for low levels of unexpected elements with reasonably long radioactive half lives. So there are some very interesting new applications. 

What kinds of analysis are you doing in forensics?

 Well, we are supported by the [United States] Department of Energy to develop and evaluate ICP-MS for measurement of trace actinides, particularly to try and diagnose illicit enrichment of uranium or production of plutonium. So there's a large area within the Department of Energy that is tasked with supporting possible programs to look for nuclear weapons development. We work on laser ablation (LA)-ICP-MS to this end. 

We also use LA-ICP-MS for forensic matching of material. We just recently had a program supported by the [United States] National Institute of Justice for that, in which we tried to match evidence, say collected from a crime scene, with evidence collected from a suspect, based on their trace-element composition. This has been shown to work by other groups as well, and I will mention particularly John Watling in Australia and José Almirall at Florida International University in Miami. A lot depends on whether the trace-element signature is diagnostic and unique. This is being sorted out for a number of kinds of materials. 

José Almirall is also using laser-induced breakdown spectroscopy (LIBS) in that work. How do you see the balance between LA-ICP-MS and LIBS for this kind of application?

 LIBS is another way, in general, to do the same sort of analysis. Isotopic information, which is of value for some elements — I would say mainly uranium and lead — is a lot easier to extract from ICP-MS measurement. As usually done, the detection limit is probably better in ICP-MS, although LIBS is improving to close to those levels, with a variety of experiments. So LIBS is another way to do most of what ICP-MS would do for that. 

In the forensic matching of materials, what kinds of samples are you talking about?

Well, to my knowledge, the original application of this, done by John Watling of Australia, was for matching trace elements in gold. José Almirall, and perhaps others, did comprehensive analysis of glass samples and found that the trace-element composition can be compared to a database of many kinds of glass samples for matching purposes. Other materials of interest are metals. For example, we have been looking at copper speaker wire. We've also been looking at duct tape, which is often used to commit crimes. 

One thing we find is that the spatial homogeneity of the trace-element levels in these materials is something of an issue. So experiments need to include comprehensive evaluations of the spatial heterogeneity of the trace elements in the materials. I should say that [the analysis of] many such materials can be envisioned, but before they can properly be used, some sort of database or global information is needed about the general trace-element composition of all the sources of the particular kind of material. There has been a lot said about trace elements in bullet lead being used improperly. 

Can you explain a bit further the issue of the spatial homogeneity of the trace materials?

Suppose you have a solid sample, and you want to analyze it and still keep it intact; you don't want to put the entire thing in solution. So one thing we have found in recent times, and perhaps others found this earlier, is that before you can try to match two different kinds of paint samples, for example, you have to be sure that the trace-element composition in the section you're sampling represents that of the whole material. And we've found that we end up having to ablate much larger portions of the material than we thought would be necessary initially. 

This interview was edited for length and clarity.

To read the full interview, please visit: 

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Spectroscopy Spotlight

A critical review focused on the Raman spectroscopy of carbonaceous materials and of polymer-based nanocomposites that contain carbonaceous (nano) materials as fillers is presented. The origin, assignment, and parameters (position, intensity, area, width, and shape) of main Raman modes (radial breathing mode, D-mode, G-mode, G'-mode, and so forth) as well as the effect of the interactions of carbonaceous materials on the parameters of these modes is briefly discussed. The effect of dopants and of polymeric matrices on the parameters of Raman bands is succinctly analyzed. The review will provide the basic and most elementary knowledge required to understand and discuss the Raman spectra of carbonaceous materials. 

Carbonaceous materials have a wide range of physical and chemical properties derived from the spatial organization of carbon atoms and their chemical covalent bonds. Diamonds, nanodiamonds, single-walled carbon nanotubes, double-walled carbon nanotubes, carbon nanofibers, and carbon fibers are characterized by an impressive mechanical strength. With the exception of diamond and nanodiamond, the Young modulus of one-dimensional carbonaceous materials decreases as their diameter is increased. This is one of the reasons that nanocomposites based on one-dimensional carbon are extremely attractive. While diamond and nanodiamond are electrical and thermal insulators, one-dimensional carbon nano- and micromaterials, graphene, and graphite are characterized by good electrical and thermal conductivity, exhibiting either semiconducting or conducting features. This wide range of physical properties explains the complex and abundant applications of carbonaceous materials. 

Raman spectroscopy investigates the molecular vibrations of atoms and molecules. In a Raman experiment an incoming monochromatic electromagnetic wave (originating from a laser) excites the atoms and molecules of a sample, starting the emittance of electromagnetic radiation. The Raman spectrum is the collection of all these emitted electromagnetic waves, except for the exciting wave (the incident one). This spectrum is generally obtained by using charge-coupled device (CCD) cameras combined with an adequate optics system consisting of prisms or gratings. The position of the Raman spectrum is typically measured in wavenumbers (cm

) starting from the frequency of the exciting radiation (that has a Raman shift of zero and is not recorded). Most spectrometers start the recording of the Raman spectrum at 50–100 cm

. The resolution of Raman spectrometers is not critical in the analysis of carbonaceous materials because their lines are not extremely narrow. Typically, Raman spectrometers with a resolution of about 1–3 cm

Several Raman lines (or bands) have been reported in carbonaceous materials and polymer-based nanocomposites containing carbonaceous fillers or nanofillers. The intensity of all these lines depend on the orientation of the polarization relative to the axis of nanotubes (5), the power of the incident laser beam, and the number of accumulations. A typical Raman line for a single-walled carbon nanotubes is shown in Figure 1. The most important Raman lines are discussed in the following sections. 

Figure 1: Raman spectrum of single-walled carbon nanotubes. 

The radial breathing mode (RBM) is related to the diameter of carbon nanotubes and was observed solely in single-walled carbon nanotubes (SWCNT) and double-walled carbon nanotubes (DWCNT) in the range 150–350 cm

  (7) for diameters of 1–2 nm (8). Typically, RBM is a collective and symmetric movement of all atoms along the radius of the nanotube. In some multiwall carbon nanotubes (MWCNT) and carbon nanofibers (CNF) a broad line can be observed in the region of the RBM, but it is not clear if this line can be actually related to the size diameter of these structures. 

The position of the RBM mode in SWCNTs and DWCNTs (ω

) depends on the diameter of the nanotube (

 describes the interactions between nanotubes and is of the order of 10 cm

. For narrow, single-walled carbon nanotubes (

 < 1 nm), the lattice distortions are large, thereby making simple dependencies no longer valid. For SWCNTs with a diameter equal to or larger than 2 nm, the intensity of the RBM mode is too small to be observed (8). 

It was reported (4) that the RBM located at 160 cm

  is broadened and slightly shifted toward higher positions (ω) as the isolated nanotubes collapse into a bundle. For an isolated SWCNT, the width of the RBM mode is of the order of 3 cm

The RBM has also been reported in fullerenes, typically below 250 cm

  although it also was reported at 490 cm

  (11). The position of the RBM mode in fullerenes depends on the energy (wavelength) of the incoming laser beam (12). 

Table I: Most important lines in carbonaceous materials 

The disorder- or distortion-band (D-band) is typically located between 1300 and 1450 cm

  carbon, and is strongly influenced by the amount of carbon impurities present. The D-band is highly dispersive, and its position is dependent on the wavelength of the incident laser beam. With an acceptable accuracy, the position of the D-band depends linearly on the energy (wavelength) of the incoming laser beam (7). The position of the D-band in diamond crystals is affected by local stresses σ (in GPa) (3):  

The graphite-band (G-band) is a first-order Raman process located between 1500 and 1600 cm

  and is assigned to graphitic structures. Typically, the G-band is not dispersive; for instance, the position of this band is not affected by the wavelength of the incoming laser beam (4). The G-band is usually associated with sp

  component was observed in insulating carbon nanotubes (4,5). This line is narrow, has a typical Lorentzian shape, and corresponds to vibrations along the direction of the nanotube; its position is not affected by the diameter of carbon nanotubes. The G-component was noticed at smaller Raman frequencies and corresponds to circumferential vibrations (5). The G-line is broader than the G

  line and deviates from the Lorentzian shape (this typically has a Breit-Wigner-Fano [BWF] shape [5]). This component has been reported (4,5) in semiconducting and conducting nanotubes and depends on the diameter of the nanotubes (the Raman frequency of the G-component increases as the diameter of nanotube is increased [3]). 

  is related to the diameter on nanotubes, 

  for conducting nanotubes (5). The advantage of this expression derives from the fact that ω

  does not depend on the wavelength of the incoming laser beam. 

The G'-band (or the D*-band (7) or the 2D band [14]) is an overtone (2 phonon process) of the D-band located between 2450–2950 cm

. Both the D- and G'-bands exhibit a more pronounced dependence of the Raman line position on the energy (frequency) of the incoming electromagnetic radiation compared to the G-band (1). The G'-band is related to the presence of sp

  (graphitic) bonds (13). This shift (expressed as dω/d

 where ω defines the position of the G'-band in cm

 defines the energy of the incoming laser beam (which can exceed 100 cm

 /eV [4]). An acceptable equation for the G'-band position is    

It is speculated that the ratio between the (integrate) intensity of the G'-band and the (integrated) intensity of the D-band is more sensitive to the purity of MWCNTs and less affected by the energy (frequency) of the incoming electromagnetic radiation. The G'-line in graphene depends on the number of graphene layers (13,14).  

In irradiated graphene a new line located at about 1625 cm

  was noticed (labeled D') and associated with local disorder (13). There also was a report in graphene (6) that there was a strong G + D line located at 2940 cm

 (15). The G*-line also is a dispersive line, but the position of the Raman peak shifts toward a smaller Raman shift (in cm

) as the energy (frequency) of the incident laser beam is increased (for the G'-line the Raman peak shifts towards a larger Raman shift as the energy of the incident laser beam is increased) (15). 

An additional line (named T-line) has been reported in amorphous carbons when the incoming laser beam is in the UV range (17) and assigned to sp

  carbons. In hydrogenated amorphous carbons this shift is shifted up to 980 cm

. This line should not be confused with the tangential mode, sometimes labeled as T-mode. 

A general expression for the Raman lineshape can be written as follows   

Equation 5 degenerates into a BWF lineshape if δ= ε

For BWF lineshapes, the parameter ε is typically replaced with 1/

. The advantage of this notation comes from the immediate identification of the physical significance of the parameters δ or ε, that describe the deviation of the lineshape from the simple symmetrical Lorentzian lineshape. 

The situation in which ε is very small, hence, the term in ε

  can be neglected, was briefly discussed (10). Assuming γ= δ= 0, the generalized expression of the lineshape degenerates into a classical symmetric Lorentz lineshape. Equation 5 shows that the parameter γ is associated with an asymmetric distortion of the Lorentz lineshape and the parameter δ corresponds to a symmetrical distortion of the Lorentz lineshape. The parameter δ measures the interaction of phonons with a continuum of states and was found to be negative in metallic single-walled carbon nanotubes.  

The Raman linewidth can be expressed as (12) 

) is the density of the electrons at the Fermi level and λ is the electron-phonon coupling constant for the mode "i" (12). 

Facts and Artifacts in Raman Spectroscopy

Typically, the degree of disorder is measured by the ratio of the D- (some authors prefer D') and G-bands. There are two possible ratios: The first one is the ratio of the amplitude of the Raman lines, labeled as 

) and the second is the ratio between the integral or integrated amplitude 

). The integral (or integrated) intensity is actually the area of the Raman peak and contains both the contribution of the line amplitude and width. From the spectroscopic point of view, the number of carbon atoms contributing to the D-, D'-, or G-lines is proportional to the area of the recorded line and not to its intensity. Hence, all data that are using 

) should be considered with caution. We suggest using the notation 

) to specify that the ratio refers to the areas of the peaks. 

Another source of error originates from using high densities (the ratio between the laser power and the exposed area) of incoming light. Under such circumstances, the sample is heated by the incoming laser beam and the parameters of the Raman spectrum are modified. Although it is difficult to specify a limit for the ratio between the power of the laser beam and the area exposed to the beam for all materials, a simple rule of thumb might be sufficient for accurate answers. This means the successive recording of three Raman spectra. If all three are identical, then the sample's heating is negligible and the data, as obtained, are solid. 

While the position of G', D*, or 2D is almost twice the position of the D-band, the terminology 2D-band or D*-band is misleading because the line was observed even in the absence of defects (15). 

To have reliable data in a confocal Raman microscope, it is mandatory to focus on the sample and if possible to check that at the end of the measurement the image of the sample is still focused. 

Raman Lines in Carbonaceous Materials and Polymer-Based Nanocomposites with Carbonaceous Fillers 

In the case of carbon nanoclusters, it was reported that the thermal annealing in the temperature range 200–800 °C ignites a graphitization process that enhances the degree of disorder, narrows the D- and G-lines, decreases the energy gap, and is responsible for a weak blue shift of the G-line as the annealing temperature is increased (9). A linear dependence of the position of the G'-line on temperature has been reported in graphene (14). The oxidation of graphene converts the almost symmetric D- and G-Raman bands into strongly asymmetric spectra (16). 

In graphite, the 2D peak is a superposition of two peaks 2D

 (17). Typically, the Raman lines of carbonaceous materials dispersed in polymeric materials are dominating over the spectrum of the polymeric matrix, for concentrations of carbonaceous materials in excess of 5 % (wt) (18). The dispersion of carbon nanofibers within isotactic polypropylene shifts the position of the D- and G-lines, moving them toward a larger value as the concentration of carbon nanofibers is increased up to 15 % (wt) and broadens them (18). As expected, the degree of disorder is enhanced by increasing the amount of carbon nanofibers in the polymeric matrix. Ionizing radiation changes the distribution of the diameters of single-wall carbon nanotubes and enhances the disorder within them (19). Complex changes were reported in chemically modified carbon nanostructures (20). 

Raman spectroscopy is extremely sensitive to the presence of carbonaceous materials. Specific line parameters (position, width, shape, and relative integral amplitude) can provide additional information about dopants, physical and chemical modification of the surface, and the effect on the dispersion of such materials within polymers. The Raman spectrum is usually dominated by sp

  bonds, interactions, and clustering, as well as the disorder introduced within carbonaceous materials, the presence of sp

  ratio, and the presence of sp structures. However, Raman alone cannot always be used to uniquely assign a spectrum to a given carbonaceous material. Raman lines are sensitive to temperature, pressure, and stress or strain. Physical and chemical modifications including doping and grafting of new chemical residues affect the parameters of Raman lines because of local modifications of symmetry. Dispersion of carbonaceous materials within polymers showed changes in the parameters associated to Raman lines of the fillers. 

A critical review focused on the Raman spectroscopy of carbonaceous materials and of polymer-based nanocomposites that contain carbonaceous (nano) materials as fillers

Raman Spectroscopy of Carbonaceous Materials: A Concise Review

31 Advanced Impedance Spectroscopy for Fuel Cells (Electrochemical Society sponsored short course at the Fuel Cell Seminar)

 High-Throughput Drug Analysis by LC–MS

 Hands-on FTIR, NIR and Data Analysis — What Is the Right Tool to Solve Your Problem  

 Introduction to Near-Infrared Spectroscopy: Applications in the Pharmaceutical and Biotech Industries

 Interpretation of Mass Spectra with Practical Solutions to Problems

Practical Introduction to Raman  Spectroscopy

14 Impurity and Degradant Identification: Strategies for Structure Elucidation via Chromatography, MS, and NMR

14–15 LC–MS: Theory, Instruments, and Applications

14–15 Interpretation of Mass Spectra with Practical Solutions to Problems

14–15 Infrared (IR) Spectral Interpretation I & II 

17 Practical Introduction to Raman Spectroscopy 

12 Introduction to Inductively Coupled Plasma Atomic Emission Spectrometry

12 Side Illuminated Optical Fiber Sensor with a High Density of Sensing Points

13 Fundamentals of Particle Size Analysis with an Emphasis on Light Scattering Techniques

Short Courses

Ellipsometry is a spectroscopic technique used to measure dielectric properties of thin films. Spectroscopic ellipsometry (SE), which is the largest subset of the technique, is a very useful research tool, and is a popular analytical tool in many fast-growing industries. The market for SE is currently in the midst of a very strong upswing in demand. 

Spectroscopic ellipsometry demand by industry for 2010.			

Ellipsometry is the analysis of the change in the state of polarized light after it has reflected from the surface of a thin film sample. SE, as opposed to single-wavelength or laser ellipsometry, utilizes broad band light sources within the infrared, UV, and visible region. Although SE is not as adept for imaging applications, it can analyze complex multilayer films, whereas laser ellipsometry is limited to single-layer analysis. 

The largest application for SE continues to be the broad semiconductor industry, in which the ability to characterize ever-smaller and more-complex architecture is critical to development and production monitoring. New technologies, such as LED lighting, solar cells, and organic electroluminescent displays are growing extremely fast, despite the muddled economy, and require SE as well. 

The global market for SE was worth more than $40 million in 2010, and it is expected to see strong growth in 2011. Because it is so heavily tied to the semiconductor and electronics industry, demand can be somewhat more cyclical than other spectroscopy technologies, and so is not likely to see consistent double-digit growth. 

The foregoing data were based on SDi's market analysis and perspectives report entitled 

Global Assessment Report, 11th Edition: The Laboratory Life Science and Analytical Instrument Industry, October 2010

. For more information, contact Stuart Press, Vice President – Strategic Analysis, Strategic Directions International, Inc., 6242 Westchester Parkway, Suite 100, Los Angeles, CA 90045, (310) 641-4982, fax: (310) 641-8851, 

Market Profile

Ellipsometry is a spectroscopic technique used to measure dielectric properties of thin films. Spectroscopic ellipsometry (SE), which is the largest subset of the technique, is a very useful research tool, and is a popular analytical tool in many fast-growing industries. The market for SE is currently in the midst of a very strong upswing in demand.

Market Profile: Spectroscopic Ellipsometry

Jose Almirall of Florida International University and Andrzej Miziolek of the US Army Research Laboratory present a review of the 2011 NASLIBS conference, which was held in Clearwater Beach, Florida, July 18–20.

The Third North American Symposium on Laser-Induced Breakdown Spectroscopy (NASLIBS) was held July 18–20, 2011, in Clearwater Beach, Florida, and by all accounts, it was a great success. NASLIBS 2011 was dedicated to capturing rapid developments in the fundamental science and applications of laser-induced breakdown spectroscopy (LIBS). A unique feature of this technique is the potential to make remote, real-time determinations of the chemical composition of any sample, whatever its nature or physical state, at close contact as well as at standoff ranges in excess of 100 m. 

In the Program: Expert Discussions and Sessions  

NASLIBS 2011 brought together 170 experts and young researchers in the field, specialists from analytical laboratories, and engineers from industries concerned with applications and instrument development to examine recent developments and define current needs. The central theme of NASLIBS 2011, "Transition from Research to Application," emphasized important developments in the application of LIBS in analytical chemistry including field applications and contributions in fundamental knowledge. In addition, developments in instrumentation, instrument control, and LIBS data analysis were highlighted. Progress in the development of several key applications of LIBS also were touched upon.  

The NASLIBS 2011 program included three tutorial sessions, 15 invited oral presentations, and 24 additional contributed oral presentations, as well as 78 poster presentations from the participants. We are especially proud that 45 of the participants were students, most of whom were supported on travel grants from the Army Research Office (15 awards) and from Oak Ridge Associated Universities (ORAU) (13 awards). 

Special Panel Discussion — LIBS in the Courtroom: Recent Examples and Future Potential 

A highlight of the NASLIBS 2011 conference was the special panel devoted to the introduction of LIBS and other new technology into the courtroom. The audience heard from leading experts in new technology who have had the opportunity to present reports and testimony in cases involving LIBS and canine olfaction. A recent high-profile Florida case (the Casey Anthony murder trial) was highlighted by the presenters, two of which had involvement in the case. 

The panelists were Madhavi Martin, senior scientist at Oak Ridge National Laboratory (ORNL) in Oak Ridge, Tennessee; Ken Furton, Dean, College of A&S at Florida International University in Miami, Florida; George Borghi, retired, Analytical Section, Miami Dade Police Department Forensic laboratory (Miami, Florida); John Lewoczko, ORAU, Quantico, Virginia; and Jose Almirall, Director of the International Forensic Research Institute (IFRI) at Florida International University in Miami, Florida. The panel was moderated by Andrzej Miziolek of the US Army Research Laboratory. 

Several other highlights from this year's conference include									

increasing the use of LIBS for nuclear and radiological materials analysis, including isotopic specificity

new results on using LIBS for pathogen identification

instrument exhibit of the first person-portable battery-powered LIBS analyzer suitable for field studies

LIBS studies related to the upcoming mission to Mars

analysis and identification of conflict minerals

The scientific and executive committees of NASLIBS decided to merge the meeting with the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) conference starting in 2013. This important new development is a result of the maturation of the North American LIBS community and the desire for NASLIBS to expand the exposure of the scientific presentations. The committee also decided to create a society named North American Society of LIBS (NASLIBS) and organize the business of gathering in future meetings as a society. 

 will publish a feature issue containing peer-reviewed manuscripts highlighting the papers presented during the NASLIBS 2011 conference. The 

 special issue announcement can be found at 

www.opticsinfobase.org/ao/journal/ao/feature_announce/LIBS.cfm

The final conference program and proceedings can be found on the conference website: 

 is a professor of chemistry and biochemistry at Florida International University in Miami, Florida, and was Program Chair for the NASLIBS 2011 conference.  

 is with the US Army Research Laboratory and was General Co-chair for the NASLIBS 2011 conference.

This year's theme, "Transition from Research to Application," emphasized important developments in the field application of LIBS and fundamental knowledge of the technique.

Review of the Third North American Symposium on Laser-Induced Breakdown Spectroscopy (NASLIBS) 2011 Conference

We continue our discussion of the classical least squares approach to calibration, focusing on the reconstruction of mixtures in this installment.

Before continuing with our discussion, we need to report some errata that a sharp-eyed reader found in our previous column (1). Fortunately, although the worst one is widespread in the column, it is editorial rather than substantive and we suspect that most readers caught it and realized what was intended. This error was the interchange of the axis labels on all those plots where the spectra were plotted as absorbance; the correct axis labels should be that the 

-axis represents absorbance. Unfortunately, we have to confess that it was our fault, apparently the incorrect information was put into the plot generator program and was thus used repeatedly for all those plots. The article was not proofread for that type of error because the plots were computer-generated and we relied on the computer not making a mistake. (Which it didn't!) In addition, because the data was collected using a Fourier-transform near-infrared (FT-NIR) instrument, the correct units for the wavelength scale are wavenumbers, rather than wavelengths. 

Another type of error in that column is that for Figures 4c, 5e, and 6e, the wavelength ranges in the figure captions disagree with the wavelength ranges in the spectral plots. In all of those cases, the wavelength range indicated on the plots are the correct ones.  

We thank Karl Norris for finding and reporting those errors to us. Karl also pointed out that one of our statements in the prior column (2), while, strictly speaking, correct, might lead someone to misinterpret our intentions. We stated, "Only one spectrum appears, because the spectra are so similar that they completely and exactly overlap each other, thus the spectrum from one reading hides the spectrum of each of the other two." Karl pointed out that someone might interpret that as indicating that the spectra were exactly matched, even down to the noise. Of course that's not the case; a better wording might have been something like ". . . because the spectra are so similar that they overlap each other to within a pixel of the display . . . ," which would have better indicated our intended meaning. 

This column is the next continuation of our discussion of the classical least squares (CLS) approach to calibration (1–6).  

Where do we stand? We have just finished presenting the data spectra, measured in the NIR spectral region, for a series of clear liquid samples comprising binary and ternary mixtures of three materials that are all miscible in all proportions.  

In the previous installments, we presented the spectra of the pure materials, as well as the spectra of the mixtures. However, we did not present these spectra in absorbance format. Because we will be comparing the spectral recreations to the original data spectra in absorbance format, it is appropriate to present the mixture spectra in absorbance format before we do that. These spectra are shown in Figure 1. As previously stated, when plotting absorbance we do not include the spectral region below 4500 cm

. Therefore, all of our future spectra plots, as well as the calculations to be performed on the spectra, will exclude the spectral region below 4500 cm

Figure 1: Absorbance spectra of all mixtures: (a) full spectrum, (b) 4500â5000 cm-1, (c) 5000â6500 cm-1, (d) 6500â7500 cm-1, and (e) 7500â9000 cm-1. Note how the original experimental design can be seen in the spectra. 

Note that the experimental design can be seen in parts b, c, d, and e of Figure 1, similarly to what we noted in the transmission spectra of the mixtures. In Figure 1e, we have indicated the spectra of the pure components, to assist in visualizing the design. 

We will now turn our attention to the earlier columns in this subseries (Parts II, V, and VI), in which we developed the mathematics relating the spectra of a mixture to the spectra of the components of samples, weighted by their concentrations.  

Having presented the data, both of the pure materials and the mixtures we worked with, we will now present the spectra of the mixtures overlaid with the spectra recreated according to the mathematics as we described it. In doing so, we illustrated how we can recreate the spectrum of the mixture when we know the composition and the spectra of the components. Similarly, we showed how we can calculate the composition when we know the spectrum of the mixture and the spectra of the components. 

Science progresses, among other means, by confirming theoretical predictions with experimental results. To do this for our CLS calibration modeling procedure, we will now combine the two operations we described. We will use the spectra of the components and the spectra of the mixtures to ascertain their compositions, and then use those calculated compositions to recreate the mixture spectra. By doing all of this we will verify the mathematical approach, because if it is all working properly the recreations of the mixture spectra and the actual mixture spectra should be essentially identical. As almost a side effect, the ability to reconstruct the spectrum of a mixture also verifies that Beer's law is operative for the materials and mixture involved.  

If that were not the case, then the reconstruction of the spectra would be poor, as we found with the water–methanol–acetic acid mixtures (4). In that case, it is clear that the underlying cause of the failure of Beer's law to hold is due to interactions between the chemical species. There are at least two contributions to that interaction. One is the distortion of the –OH species in all three materials as a result of changes in the hydrogen bonding of the materials in the different environments. A second cause, which we thank Marvin Margoshes for pointing out, is the generation of H

  from ionization of the acetic acid. This actually introduces a fourth component into the mixtures that is not accounted for in the mathematics. 

Our experimental design included three ternary mixtures, as indicated in Table I. 

Table I: Compositions of the three ternary mixtures 

We therefore apply the mathematics to the data from these three mixtures to see how well we can reproduce the actual mixture spectra from the spectra of the pure materials. In Figures 2, 3, and 4 we present the plots of the recreated spectra, the original data spectra, and their residuals. 

Figure 2: Plots of actual and recreated spectra of the ternary mixtures: (a) full spectrum, (b) 4500â5000 cm-1, (c) 5000â6500 cm-1, (d) 6500â7500 cm-1, (e) 7500â9000 cm-1. Toluene = 50%, dichloromethane = 25%, and n-heptane = 25%. In all parts of the figure, blue = actual spectrum, red = recreated spectrum, and green = residual. 

We note that the largest residual (for example, the difference in the recreation of the data spectrum), is 0.06 absorbance at 5880 cm

; this deviation corresponds to roughly 7.5% of the spectral value. Over the rest of the spectrum the residual is, to a great extent, too small to be observed. 

Overall, then, we see that the ability of the mixture components to recreate the actual mixture spectrum is excellent. Except for a few localized sections of each spectrum, which correspond to the peak absorbances of the constituents of the mixtures, the recreation is extremely good. Similarly good spectral reconstructions were found for the various binary mixtures, as well.

Figure 4: Plots of actual and recreated spectra of the ternary mixtures: (a) full spectrum, (b) 4500â5000 cm-1, (c) 5000â6500 cm-1, (d) 6500â7500 cm-1, (e) 7500â9000 cm-1. Toluene = 25%, dichloromethane = 25%, and n-heptane = 50%. In all parts of the figure, blue = actual spectrum, red = recreated spectrum, and green = residual. 

Figure 3: Plots of actual and recreated spectra of the ternary mixtures: (a) full spectrum, (b) 4500â5000 cm-1, (c) 5000â6500 cm-1, (d) 6500â7500 cm-1, (e) 7500â9000 cm-1. Toluene = 25%, dichloromethane = 50%, and n-heptane = 25%. In all parts of the figure, blue = actual spectrum, red = recreated spectrum, and green = residual. 

In our next installment we will look at the quantitative results we obtained from this experiment. 

. serves on the Editorial Advisory Board of 

 and is the executive vice president of Engineering at Unity Scientific, LLC, (Brookfield, Connecticut). He is also an adjunct professor at U.S. National University (La Jolla, California), and Liberty University (Lynchburg, Virginia). His email address is 

 serves on the Editorial Advisory Board of 

 and runs a consulting service, Mark Electronics (Suffern, NY). He can be reached via e-mail: 

The editors congratulate Howard Mark and Jerry Workman for 25 years of statistics and chemometrics columns in 

Chemometrics in Spectroscopy

Continued discussion of the classical least squares approach to calibration, with a focus on the reconstruction of mixtures

Classical Least Squares, Part VII Spectral Reconstruction of Mixtures

Molecular vibrations can be exquisitely sensitive to molecular structure, and as such, measurements detecting them have gained favor for analytical purposes. Easy-to-use instrumentation to detect molecular vibrations is well developed in the mid-infrared (IR), near-IR (NIR), and visible (Raman) regions of the spectrum. The instrumentation has been optimized for each spectral range, but the physical processes producing the spectra are all different. Deciding which technique will be the measurement of choice will depend on the sample format, the required sample environment, the available database, and which process provides the most relevant information to answer the required question. In this installment, I will attempt to guide you through the maze of choices and describe what is being measured, how it is being measured, and what the advantages and disadvantages of these techniques are.  

What is being measured? Vibrations can be detected by direct absorption of light into fundamental levels, by absorption into overtones and combinations of those levels, and by scattering off those levels with lasers. The first process is called mid-infrared (IR) absorption, named as such because the vibrational energies are in the mid-IR part of the electromagnetic spectrum. While at Cornell University (Ithaca, New York), William W. Coblentz measured IR absorption spectra of a large number of organic compounds from which he was able to catalog group characteristic bands. Even though he was not the first to measure mid-IR spectra, he is credited with developing the application of IR spectroscopy for structural diagnostics (1). The second process is near-infrared (NIR) absorption, named as such because the overtones and combinations of CH, NH, and OH vibrations and their angle-deformations occur in the near-IR part of the electromagnetic spectrum. According to Jerry Workman (2), the development of NIR spectroscopy for analytical purposes goes back to about 1960 when spectra–structure correlations for a number of functional groups were documented (3). The scattering process is called 

 because C.V. Raman was the first to report the phenomenon (4,5) that had actually been predicted about 5 years earlier by Smekal (6). In fact, Raman received the Nobel Prize for this work in 1928.   

By its nature, a scattering experiment is quite different from any absorption experiment. In an absorption experiment, one is always ratioing the spectrum of transmitted or reflected light to the spectrum of the light source; thus the signal intensity is absolute and the spectrum should be invariable from instrument to instrument, unless there are effects of spectral resolution. On the other hand, it is very difficult to normalize the scattering intensity to absolute units; one can correct for the laser intensity, but that is only the first of the phenomena that affect the spectral intensity. One important effect is that of the laser wavelength; everything else being equal, a shorter-wavelength laser will produce a stronger signal than a longer-wavelength laser because of the physics of the scattering phenomenon itself. In addition, if the sample is colored (has an electromagnetic absorption in the vicinity of the laser wavelength), the signal will be enhanced and the relative intensities will change drastically. Another factor affecting the signal is the volume of excitation (laser-irradiated volume). Then the optics used to image the laser-irradiated volume on the entrance slit will determine the angular aperture from which the light is collected, as well as the size of the image on the slit, which will, in turn, determine how much light is detected. And if the sample is turbid or opaque, the size of the illuminated volume will be affected. To conclude this topic, one can see that it is not easy to produce a Raman spectrum representing absolute scattering intensity, thereby making the application of the technique less straightforward than the two absorption phenomena. 

There also is the issue of the polarity of the photons. Who among us remembers group theory? The point is that a photon is a shorthand name for a bundle of energy described by coupled oscillating electric and magnetic fields that move through space. The smallest unit of energy (the energy of a photon or light quantum) is proportional to the reciprocal of the wavelength (λ), called the wavenumber.  

 The interaction between the photons and the molecules is by the coupling with the photon's electric field, which of course is a polar quantity. That means that for a molecular vibration to absorb radiation, not only must the energy of the vibration match the photon energy (

), but the vibration has to produce an electric dipole. That is why polar groups like carbonyls are strong IR absorbers. In the case of Raman scattering, there are two photons, so the molecular vibration must have even character. (Two odd photons make "even" character and will couple with a symmetric-type vibration.) That is why a vibration like a C=C double bond is strongly Raman active. The implication of this is that IR and Raman spectroscopies are complementary — vibrations that appear in one do not appear in the other if there is a center of symmetry; or, when there is no center of symmetry, a vibration tends to be strong in one effect and weak in the other.   

So what about NIR absorption? Again we have an absorption process, but each photon makes a transition to more than one vibration so that the energy range is high enough to reach the NIR range of the spectrum. The observed spectra are attributed to overtones of CH, NH, and OH stretches and combinations of the stretches and angle deformations; the region between 700 and 1600 nm is typically assigned to overtones (14,300–6250 cm

), and the region between 1600 and 2500 nm to combinations (6250–4000 cm

). Because there is only one photon, the symmetry of the sum of the vibrations has to be compatible with the odd character of the electric field. That would imply, for instance, that a combination of a symmetric and asymmetric XH vibrations would occur in the "overtone" region. It should be noted that the longer-wavelength detectors that are sensitive to the combination region are noisier and more expensive (in the case of the multichannel arrays this is quite significant) than the shorter-wavelength detectors that can measure overtones. An important point that should be made is that because of the overall weakness of the absorptions in the NIR, relatively thick materials can be measured, even in transmission.   

The biggest factor in the definition of the instrumentation for each measurement is what is compatible with the wavelength range. For instance, the NIR region is still compatible with glass optics, which means that fiber optics can be used. However, the detectors used in this region of the spectrum are different from those used in the visible and tend to be based on materials like InGaAs (to 1.7 μm) and extended InGaAs (to 2.5 μm), but other materials such as InSb, Ge, and Pb salts have also been used. The light can be analyzed into a spectrum by using either a grating-based dispersive spectrometer or a Fourier-transform (FT) interferometer. When the dispersive instrument is equipped with a multichannel detector, such as an InGaAs array, all wavelengths are detected simultaneously. Such a dispersive instrument with a multichannel detector will benefit from the multiplex or Fellget's advantage, which was originally defined on FT systems. 

For mid-IR measurements, FT instruments are now used almost exclusively. Before the 1960s, IR measurements were made with prism-based dispersive systems equipped with single-channel detectors. The development of digital control and then computers of manageable size provided much of the computing power necessary to engineer FT-IR instruments compatible with industrial and university laboratories. The conversion from dispersive to interferometer-based systems provided powerful new capabilities. Compared to a spectrometer with a light-limiting entrance slit, the entrance aperture of an interferometer accepts essentially all of the available energy (Jacquinot advantage). During the acquisition of the interferogram, the detector is "seeing" all of the wavelengths simultaneously so every point in the transformed spectrum reflects the same state (or combination of states) of the sample (Fellget's advantage). To accurately perform the conversion from the interferogram to a spectrum, the instruments use a laser to search for the zero-crossing of the interferogram; this provides superb wavelength tracking, so the instruments are much less susceptible to environmentally caused drift (Connes' advantage). Because of the rapid evolution of FT-IR instruments, their usage has become universal — thousands and even tens of thousands of instruments have been delivered with ever more sampling accessories. A corollary of this is the assembly of rather large IR data bases that have enormous benefits for identification of unknowns.   

As will be discussed later, NIR was developed largely for commercially interesting products because of several technical advantages, not the least of which is the use of glass optics. NIR instruments are easier to construct than mid-IR instruments. They can be small (grating-based) spectrometers or small interferometers, either one with a single-channel detector, and they can also be constructed with a multichannel detector (MCD) on a grating-based spectrograph. The downside of the use of NIR spectra is the lower information content in the spectra that is exhibited in broad overlapping bands superimposed on a large scattering background which has to be dealt with in data treatment (this aspect will be discussed in the next section). However, the limitation of low information content has been overcome by the extremely high signal-to-noise in the data that enables sophisticated multivariate analysis to extract composition information from the data sets.    

Raman instruments come in essentially two designs — dispersive and Fourier transform. In fact, the earliest instruments built during the 1930s and 1940s were prism-based dispersive systems. In the 1960s grating-based instruments became the rule, with the Toronto mercury lamp source getting replaced by gas lasers that became available. But the universal implementation of Raman equipment was hindered by fluorescence, which was experienced in almost all industrial materials. In 1986, Bruce Chase at Dupont, in collaboration with Tomas Hirschfeld, experimented with Raman detection on the emission port of an FT-IR instrument, using a Nd:YAG laser emitting at 1064 nm (7). The motivation for this effort was that the laser photons have energy low enough that they are unable to excite fluorescence, at least in organic systems. FT-Raman systems were commercialized first as accessories to FT-IR instruments, and then as stand-alone products.  

FT-Raman systems became quite popular and reinvigorated interest in Raman spectroscopy by the analytical community. The instruments were continuously improved until they came close to hitting the photon shot-noise limit. During this period, dispersive Raman instrumentation also reinvented itself. Large double monochromators with water-cooled lasers and single-channel detectors were replaced by compact spectrographs with air-cooled lasers and multichannel detectors. Spectral acquisition times for equivalent spectral resolution and signal-to-noise dropped by two orders of magnitude. Red lasers eliminated much of the fluorescence interference seen with green argon laser excitations. In addition, the microscope as a sampling accessory, which had been introduced much earlier in 1972, provided ease of sampling and added fluorescence rejection. Today, these instruments are being used with lasers between 1064 nm and 244 nm for a wide range of applications.   

An important advantage of Raman spectroscopy is that the spectrum can include frequencies between 5 cm

  — a region that is inaccessible to routine IR systems. This provides information on metal oxide vibrations and phonon modes in molecular crystals. Metal oxides are of importance to the paint industry, to catalysis, to conservation of cultural heritage, to additives in textiles and paper, and so forth. Molecular phonons are of high importance in the pharmaceutical industry where the crystalline form of the active pharmaceutical ingredient (API) can determine bioavailability. 

Vibrational spectroscopy is valuable not only because of the information that it can potentially provide. Sampling is often done in a noncontact mode, sometimes in controlled, isolated environments (such as reactors), and the measurement is nondestructive. Furthermore, in the visible and NIR region of the spectrum, light can penetrate many containers made of glass or plastic so a measurement can be made without breaching the container integrity. On top of this, visible and NIR light can be transmitted via fiber optics to and from a container making remote sampling a reality.   

The serious reader can obtain more information on these types of instrumentation in Volume I of 

, edited by John Chalmers and Peter Griffiths (8). 

Figure 1: Jablonski diagram illustrating mid-IR absorption, NIR absorption, Raman processes, Rayleigh scattering, and fluorescence. 

To enable the reader to have a feeling for the differences in spectral characteristics of IR, Raman, and NIR spectra, the following figures have been included. Figure 2 shows Raman and IR (corrected attenuated total reflection [ATR]) spectra from the same materials. (Keep in mind that these spectra were not generated from the same samples. The Raman spectra came from our spectral collection, and the FT-IR spectra were generously provided by Pauline Leary of Smiths Detection, Danbury, Connecticut.) The spectra can be overlaid along the 

-axis because both are detecting fundamental vibrations. Clearly the spectra are different and the analysis of these differences is beyond what I am hoping to do in this column. The point is to note that the spectral characteristics are different, as well as the sampling possibilities. These are the factors that would determine the choice of the technique for a particular situation. 

Figure 2: FT-IR (top) and Raman (bottom) spectra of (from top to bottom on each plot) tendon, wool, nylon, starch, cotton, polypropylene, and polyethylene. The FT-IR spectra were generously supplied by Pauline Leary of Smiths Detection. 

Figure 3 shows NIR spectra generously supplied by Linda Kidder and Gerald Sando of Malvern Instruments (Columbia, Maryland). Note that most of these spectra span the region between 1400 to 2400 nm which corresponds to 7143 to 4167 cm

, and can be compared to the IR or Raman region that is about 3500 cm

. Because of the limited number of spectral features and the widths of the bands, the spectra are considered to be less information-rich. But because the signal-to-noise ratio of the NIR spectra is so high, and sampling can be done in situ, for industrial applications the spectra are quite useful, especially when taking advantage of electronic data processing, which will be discussed in the next section of this article. 

Figure 3: NIR spectra (from top to bottom) of aspartame, caffeine, lactose monohydrate, sucrose, polypropylene, Avicel, starch, and polyethylene. These spectra were kindly provided by Linda Kidder and Gerald Sando of Malvern Instruments. 

Because of the almost universal use of IR absorption measurements in analytical laboratories for more than 30 years, the spectroscopy software for these measurements was developed the earliest. It goes without saying that the interferograms need to be converted to absorbance from transmission or reflectance (diffuse, specular, or ATR). These algorithms are now well-developed. Routines for smoothing, taking derivatives, fitting and subtracting baselines, scaling two spectra, subtracting one spectrum from another, band-fitting, and so forth are available in most commercial products.  

Raman also requires Fourier transformation if the spectrum is acquired on an FT instrument, but that only applies to FT-Raman instruments that are equipped with 1064-nm Nd:YAG lasers. Dispersive Raman instruments provide spectra directly, although there are extensive algorithms behind the user interface to convert the data into wavenumber space from the CCD pixels. The same treatment functions that are used for IR are applied to Raman spectra — smoothing, derivatization, baseline treatment, spectral scaling and subtraction, band-fitting, and so forth. The Raman spectra, however, tend to be significantly noisier than the FT-IR spectra, and there are often much more intense baselines relative to the spectral bands, so smoothing and baseline correction have to be done with care.  

Often spectra are acquired to identify material for a variety of reasons — manufacturing contaminants, incoming product identification, seized illicit drugs, forensics matching, and so on. Identification can be done by spectral matching with a database of spectra of a library of materials that represents the universe of possibilities. Because FT-IR has been a mature measurement technique for so long, the available libraries are quite large and can be easily located. More than half of the compounds are organic in nature. Raman libraries have appeared more recently and are not as extensive, but the situation is improving as time goes on.   

How can you navigate the maze of choices for detecting molecular vibrations with mid-infrared (IR), near IR (NIR), and visible (Raman)? Understanding what is being measured, how it is measured, and the advantages and disadvantages of each technique, will help.

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