Of the arc/spark optical emission spectrometers in service today, 99% are used for the routine spectrochemical analysis of metals. Alloys of iron, aluminum, and copper together make up about 80% of this total. The remaining applications concern alloys of nickel, cobalt, zinc, titanium, magnesium, and the lead/tin/solder group. Refractories, precious metals, steel-making slags and geological materials, and other exotic materials account for the remaining 1% (2,3). 

Electrical discharge excitation sources were developed in the latter part of the 19th entury. The first two decades of the 20th century saw considerable development in direct current, alternating current, and high voltage excitation sources. 

In the arc/spark spectrometer, the excitation is produced by the energy of the electrical discharge between the sample and the electrode. The resulting plasma temperatures effectively remove sample material (called "ablation") and excite the constituent atoms. Today, this electrical discharge typically is carried out in an argon atmosphere, although all early instruments were run in air. For this type of spectrometer using electrical excitation, the sample must be electrically conductive. Therefore, this instrumentation is very popular in the metals industry. 

 A diagram of a typical spark stand (electrode and sample geometry) is shown in Figure 1. It illustrates the conventional "point-to-plane" configuration (electrode to sample). The electrode typically is made of tungsten, although graphite electrodes have been used in the past with nonferrous materials. 

 Figure 1: Basic sample stand configuration for arc/spark excitation.			

The spark stand in modern instrumentation is flushed with argon to prevent oxidation effects and allow transmission of UV wavelengths absorbed by oxygen.  

A very basic electrical circuit diagram used to provide the discharge is shown in Figure 2, where 

 is a resistor. When the switch is closed the capacitor is charged to the voltage 

 When the switch is opened, the electrical energy stored in the capacitor is released through the inductor and resistor, producing a discharge across the spark gap. 

Figure 2: Simple electrical circuit diagram for arc/spark excitation.

Several comments must be made concerning the basic electrical circuit of Figure 2: 									

The voltage in the circuit is generally between about 400 and 1000 V. This is not enough to cross ("breakdown") the 3–4 mm spark gap. A much higher voltage, on the order of 10,000 V, is required. This is provided by an ignitor circuit (similar to the ignition coil of an automobile), whose sole function is to bridge the gap. Once this short path has been ionized, the lower voltage is sufficient for a continued discharge.

In modern spark excitation sources, the discharge is unidirectional, from the electrode to the sample. To prevent an oscillating discharge as would occur normally in the circuit of Figure 2, a diode D is included across the capacitor. (A diode is an electrical circuit component that only permits a current to flow in only one direction.)

The switch S is opened and closed electronically many times per second. This is referred to as the "frequency" of the discharge.

The "spark gap" generally is referred to as the "analytical gap" in arc/spark spectrometry. The 5000–15,000 K plasma temperatures generated in this region is where the analytical processes important for spectrochemical analysis occur. The sample is the cathode (negative) and the electrode is the anode (positive).

The nature of the electrical discharge between the sample and electrode is dependent on the electrical parameters of the source, specifically, the values of 

. These parameters determine the way the current varies with time in the analytical gap. The electrical discharges fall into three categories: spark-like, arc-like, and high-energy prespark (HEPS) discharges. The latter is not really an excitation at all, but rather a sample homogenization discharge.  

 Spark-like refers to high-current discharges that come in short bursts, like "gunshots." For a "spark-like" discharge, some typical electrical parameters are as follows: 					

Note: FWHM is "full width at half maximum," in this case a measure of the duration of the electrical discharge. 

Arc-like refers to a lower current, drawn-out, almost continuous discharge. Arc-like discharges can be either direct current (DC), or alternating current (AC) with a frequency like the spark-like discharges discussed earlier. The DC arc is a low-current discharge, on the order of perhaps 3–10 A. The AC arc can provide currents as high as 20–30 A with a frequency of 100–200 Hz and a total duration for each cycle of 500–1000 µs. 

Analytically, the differences between the arc and spark excitations can be summarized as in Table I, which compares precision and limits of detection (LODs). The precision numbers listed are at concentrations well above the limit of detection. 

Table I: Analytical comparison of arc and spark excitations			

 The primary function of the excitation source is to generate spark- or arc-like electrical discharges. These will vaporize sample material and produce excitation of the electrons of the atoms for the measurement of spectral line light intensities. 

 The excitation source has, however, a second very important function: The sample surface is first subjected to a HEPS. This is a high-current spark discharge designed to homogenize the sample surface in preparation for the actual measurement of light intensities which follows. 

The action of HEPS can be compared to that of a remelt furnace, in the sense that the sample surface subjected to the electrical discharge is effectively "re-melted." This technique is important in removing any effects of the metallurgical history or structure of the sample (for example, cast versus wrought, heat treatment, and so forth). Typical prespark currents can be from about 120 to 150 A with durations from about 10 to 20 s. Depending upon the electrical parameters used, the crater produced in the sample surface during the high-energy prespark is about 10 mm in diameter with a maximum depth (penetration at the center) on the order of 50 μm. 

 After the prespark period the sample is ready for the actual measurement or integration of the light intensity signals. This is generally carried out with a spark-like discharge for about a 5-s time period. Arc-like discharges are used primarily where very small amounts of the elements present must be detected (see Table I). If this were the case, however, we would include a second integration or measurement period of 5 s using an arc-like discharge. Therefore, the complete source cycle during the sparking of a sample would look like the following: 					

 There is spectral background radiation across the electromagnetic spectrum and this is crucial to an understanding of detection limits. The spectral background radiation determines the limit of detection attainable at any particular analytical spectral line for a given optical system (4,5). If this background could somehow be reduced, then better detection limits would result. 

Figure 3 shows a rough sketch of the time evolution of the light intensities in a spark-like discharge. It shows the background radiation along with light from both ionic and atomic spectral lines. By eliminating the initial spectral background and ionic line radiation, a significant reduction in the spectral "noise" could be achieved for atomic spectral lines. We must delay the integration of the light intensity by about 100–150 µs after initiation of the spark. The actual integration should take place in the "afterglow" period, that is, after the actual spark discharge shuts down. 

Figure 3: Time evolution of light intensities from a spark discharge.			

Note that the idea of time resolving the measured light intensities is not new. Spectroscopists have researched this technique since the early part of the 20th century. Early work used a rotating disk with only a small opening to allow light to pass. The rotation of the disk could be timed so that any particular time period of the discharge could be viewed. Today, the procedure is much easier through the use of electronics. 

An electronic gate is inserted between the output of the photomultiplier tube and the integrator. After the preset time delay, the light signal from the photomultiplier is integrated for a short time, on the order of 50 µs. Because of the low signal level, an amplifier is necessary.  

				Time-resolved spectroscopy (TRS) provides several benefits for the analyst (3):									

Improved detection limits: The limits of detection improve by a factor of 10–100 for the aluminum and copper alloys. For ferrous alloys, the improvement in LODs is less, generally on the order of 2–10 times. This might be attributed to the magnitude of spectral lines for iron.

Reduced interelement effects: Another result of the time-resolved spectroscopy technique is the reduction of line overlap problems from ionic spectral lines. The majority of the light from the ionic lines is no longer integrated by using a time delay.

Improved calibration: The calibration curve fits for trace elements in aluminum and copper also show improvement using TRS. The quality of the curve fit improves by about a factor of about four using this technique.

In conventional spark OES, the emission intensities of the individual sparks generally is integrated over a suitable measurement interval, usually about 5 s. However, instead of integrating, with suitable readout electronics it is possible to evaluate the intensity of each individual spark.  

For the matrix element and elements in solid solution, this produces a random (Gaussian) distribution of spark intensities. Things become more interesting, however, when one evaluates the single sparks of inclusions. Figure 4 shows the pulse height distribution of 1500 single sparks as measured at the Al I 396.1 nm spectral line in a low alloy steel sample (6). 

Figure 4: Single-spark evaluation spectrum of Al in steel.			

The aluminum in this certified reference material is present in both insoluble and acid soluble components. The baseline intensities (around 500 counts) are representative of the soluble fraction, whereas the spikes up to several thousand counts are due to the spark discharge encountering an inclusion (Al

This technique has important applications for steelmakers as it allows a quick determination of the "cleanliness" of the steel, a function of the number of inclusions. 

  a physicist by training, has some 30 years of experience in elemental spectrochemical analysis (OES and XRF). He is currently a consultant in this area from his home in Atibaia, São Paulo, Brazil. His other interests include mineralogy and history of science. Occasionally, he still plays the blues harmonica. He can be reached at 

, 2d ed. (Bruehlische Univ. Press, Germany, 1993). 

Modern Spectrochemical Analysis of Metals: An Introduction for Users of Arc/Spark Instrumentation 

(ASM International, Materials Park, Ohio, 1996). 

Articles

Following a discussion of the basic modules of spectrometer systems in Part I, the author continues his series on spectrochemical analysis with a discussion of ark/spark optical emission spectrometers.

Spectrometers for Elemental Spectrochemical Analysis, Part III: Arc/Spark Optical Emission Spectrometers

The Evolution 200 UV–vis spectrophotometers from Thermo Fisher Scientific feature the company's INSIGHT software with customized scripting capabilities. Three models are available for applications ranging from standard quantitative analysis to research life science assays. According to the company, the instruments are designed for routine QA/QC analyses in the life science, food and beverage, and material science industries and for fast data collection rates for kinetics measurements (up to 100 data points/s). The instruments are available in both local and computer-controlled configurations. 

The McPherson Commander f/4.8 triple spectrometer is designed for UV and wide-wavelength-range Raman applications. The spectrometer has continuously tunable wavelength positioning for use with tunable lasers, to seek resonance, or at deep UV wavelengths where filters are not available. Purge fittings are provided for experiments that approach the oxygen absorption envelope. According to the company, the configuration of slit width, apertures, and gratings are user-controlled. A single-stage bypass reportedly allows dedicated use of the spectrograph. 

The Sol2.2A NIR spectrometer from B&W Tek provides a spectral range out to 2.2 µm. The spectrometer reportedly features a built-in autozero function. The instrument is designed with four levels of gain for use in low light level NIR detection. According to the company, the spectrometer is equipped with a built-in three-stage cooler that allows for integration by providing +5 V DC power. 

SPEX SamplePrep's model 6970 Enclosed Freezer/Mill includes a totally enclosed liquid nitrogen autofill system with external loading of sample vials. The instrument's dual grinding chambers, which are positioned in the liquid nitrogen reservoir, are accessed through external gates. The grinder is designed with magnetically powered impactors and is controlled by a color touch screen interface that can store as many as 10 programs. Users reportedly can control both grinding chambers for independent operation with different protocols. 

A 2010–2011 mini-catalog from International Crystal Laboratories shows products using in IR, UV, and visible spectroscopy. Products listed include optics, IR cards, liquid cells, gas cells, solid sampling accessories, film makers, laboratory grinding mills, KBr and XRF dies, NIST-traceable calibration films, and cuvettes. A PDF version of the catalog is also available at the company's website. 

A full-color brochure from Shimadzu Scientific Instruments describes the company's UV–vis–NIR spectrophotometers. The brochure, titled "Measurement of Transmission and Reflectance of PV Materials and Cells," explains the role of the company's SolidSpec-3700 and UV-3600 instruments in the manufacture of solar cell materials, cells, and modules. According to the brochure, the instruments reduce measurement workload and achieve more efficient nondestructive analysis of PV materials. 

Moxtek's XPIN detectors are designed for use in benchtop and handheld energy dispersive X-ray fluorescence (EDXRF) instrumentation. The detectors reportedly are optimized to provide maximized resolution, count rate, energy absorption, and peak-to-peak background for various industrial and scientific applications. 

The amaZon Powerpack LC–MS system from Bruker Daltonics is designed for laboratories involved with detailed structural analysis of various molecules. The system combines the company's amaZon SL ion-trap mass spectrometer and a Dionex Ultimate 3000 UHPLC system. According to the company, features include automated, intuitive software; data acquisition at isotopic resolution in MS and MS-MS modes for use with UHPLC; on-the-fly polarity switching; reproducible fragmentation for unknown compound identification; and low maintenance requirements. 

Thermo Fisher Scientific's Nicolet iS5 FT-IR spectrometer is designed for product assurance testing, basic troubleshooting, and chemistry teaching. The small-footprint spectrometer reportedly provides performance comparable to full-size spectrometers. The instrument reportedly is powered by the company's OMNIC software and includes an open-architecture sample compartment that accepts various sampling accessories. According to the company, the spectrometer can be used for raw materials, impurities, and mixtures identification. 

The CC-UV/VIS/NIR-8MM and CC-UV/VIS/NIR-5.0 cosine correctors from Avantes are designed for solar measurement applications. The former instrument has an 8-mm active area. The latter instrument has a 5° angular field of view and is normally affixed to a sun tracker system. Solar monitoring can be achieved using the company's pyranometer, pyrheliometer, or spectroradiometer instruments.  

The model 8453 UV–vis spectrophotometer from Agilent Technologies uses a photodiode-array detector to make measurements throughout the 190–1100 nm wavelength range. According to the company, measurements are made in less than 1 s. The system reportedly is coupled with the company's UV-Visible ChemStation software for data analysis, data archival, and compliance with pharmacopoeia requirements and good laboratory practices. 

StellarNet's DUAL-DSR spectrometer systems integrate two detector arrays to cover the 200–1700 nm wavelength range simultaneously. The fiber-optically coupled instruments provide absolute measurements in units of watts/m

, radiant or luminous flux, and others. Each system is configured with a BLACK-Comet spectrometer that covers the 200–1080 nm range, and the remainder of the spectrum is continued with a RED-Wave NIR spectrometer that includes a TEC cooled InGaAs detector. The NIR spectrometer is available with 512 or 1024 pixels. The systems can be battery powered for field use. Applications include direct solar monitoring, solar simulator classification and analysis, crop reflectometry, and biological and environmental studies. 

The VS7000 UV–vis–NIR miniature spectrometer from HORIBA Jobin Yvon is a preconfigured, low stray light system that includes an uncooled back-illuminated CCD and USB-2 integrated electronics. The spectrometer is designed for OEM low light, high SNR requirement applications. The instrument also includes a selection of slit widths, integrated OSF, and three spectral range selections: 200–860, 380–750, and 200–1050 nm. 

SPEX CertiPrep's website is designed to enable users to purchase organic and inorganic certified reference materials. The site includes a search function, a custom standard request form, and live chat for access to the company's support staff. Products include certified reference materials for AA, ICP, ICP-MS, and IC analytical instrumentation. 

Departments

Products

Raleigh, North Carolina is a city steeped in rich history and natural beauty, so it should come as no surprise that the Federation of Analytical Chemistry and Spectroscopy Societies chose it as the site for the 37th FACSS Conference. The conference will be held October 17–21, 2010, at the Raleigh Convention Center.  

(VISIONSOFAMERICA/JOE SOHM/PHOTODISC/GETTY IMAGES)			

As this year's slogan states, the 2010 FACSS Conference will deliver on the latest breakthroughs paving the way for future analytical scientists. The conference will begin on Sunday evening with the "What's Hot Presentations," from 4:40 p.m to 7:00 p.m.  

Monday, and each day after, will begin and finish with plenary sessions by internationally recognized speakers and FACSS award winners. Kicking off the lectures on Monday will be the Arthur F. Findeis Award for Achievement by a Young Analytical Scientist winner Christy L. Haynes, University of Minnesota (Minneapolis, Minnesota). Haynes' presentation is titled "Electroanalytical Eavesdropping on Cellular Communications." After the first lecture, attendees will have a vast pick of poster and oral presentations to attend. Finally, Uli Hacksell of ACADIA Pharmaceuticals will end the first day's events with his plenary lecture, "The Role of Analytical Chemistry and Spectroscopy in Drug Discovery and Development: Challenges and Opportunities." 

The remaining days of the conference will follow the same format, covering a variety of interesting topics and break-through presentations. Prizes will be awarded daily for outstanding poster presentations. 

A highlight at any conference is always seeing who wins the accolades of his or her peers and what these award winners are bringing to the forefront of analytical science. FACSS 2010 is just such a conference, boasting both student and professional awards. 

This year's student awards include the Tomas A. Hirschfeld Award and the FACSS Student Award. The Tomas A. Hirschfeld Award will be presented to Anil Kodali, University of Illinois Urbana-Champaign (Urbana, Illinois) and Ishan Barman Massachusetts Institute of Technology (MIT) (Cambridge, Massachusetts). The FACSS Student Award will be presented to Jacob Shelley, Indiana University (Bloomington, Indiana).  

There are a number of professional awards to be presented at this year's conference, as well. The Charles Mann Award for Applied Raman Spectroscopy is presented to an individual who has demonstrated advancements presented at FACSS in the field of applied Raman spectroscopy or demonstrated dedication to the advancement of the FACSS Raman spectroscopy program or the ASTM Raman subcommittee. This year's recipient will be Richard L. McCreery, who is currently Professor of Chemistry at the University of Alberta (Alberta, Canada), with a joint appointment as a Senior Research Officer at the National Institute for Nanotechnology (Edmonton, Canada). 

Another award being presented is the Ellis R. Lippincott Award, which is given to someone who has made significant contributions to vibrational spectroscopy. These contributions may be theoretical, experimental, or both, as well as basic or applied. This year's recipient is Martin Moskovits, Professor of Chemistry at the University of California, Santa Barbara (Santa Barbara, California).  

Additional award listings and recipient biographies can be found at 

. There will be official presentations of these awards made at the conference. 

More than 50 companies will showcase their products in the exhibit hall during the week. The exhibit hall will open on Monday evening with a reception. 

For more information and to register online, please visit the FACSS website at 

. FACSS International Office, P.O. Box 24379, Sante Fe, NM 87502, Phone: (505) 820-1648, Fax: (505) 989-1073, Email: 

Spectroscopy offers a sneak peak into the 37th FACSS Conference taking place October 17-21, 2010, in Raleigh, North Carolina.

FACSS 2010 Preview: Tomorrow's Analytical Sciences Today

What I see as being really interesting is how the applications and instrumentation developments are driving each other. Raman, of course, is mainly a spectroscopy of vibrational  transitions, and as such, is loaded with information-content. For a variety of reasons, IR absorption, in particular FT-IR, is more mature as an analytical technique than Raman, but with the introduction of the holographic notch filters in 1990 (1), air-cooled lasers, and low-noise CCD detectors, Raman instrumentation has become smaller, less expensive, and easier to use, so its successful implementation in many disciplines has created new applications. This in turn is pushing the instrumentation to do more. 

Microscopy is an area where Raman has had a potential impact since its introduction in 1973 (2). I say potential because as long as the instrumentation was large with utility-intensive lasers and little computational power, its use was limited. But now that proof-of-principle has been shown for many applications, and the instrumentation is more user friendly, people want higher sensitivity and higher spatial resolution, and these are two of the areas that I want to discuss.  

We see a lot of activity in the study of carbon nanomaterials such as nanotubes and graphene (single hexagonal carbon sheets). There is no space to review all the carbon talks and posters, but we want to mention at least, the plenary talk by Andrea C. Ferrari (3) as well as talks by Mildred Dresselhaus (4), Marcos Pimenta (5), and Janina Maultzsch (6). These materials have fascinating resonance. Raman properties following from their unique electronic properties and because of their high electronic mobility are of interest in integrating into electronic circuitry. Raman studies will aid in selecting the particular species and engineering their use.  

I discussed surfaced-enhanced Raman scattering (SERS) in a column almost two years ago. The topic was selected because of its potential to provide sensitivity to things that cannot be detected or studied presently. Because I want to discuss the sensitivity issue in this column, I will start with a review of some of the SERS work reported at ICORS 2010. John Lombardi (7) reviewed the various theories of SERS, and discussed how the mechanisms determining these effects can be differentiated. In one of the plenary talks, Martin Moskovits (8) reviewed the status of robust SERS platforms that can enable reliable application of this technology to reproducible analysis. In his opinion, this technology is robust enough for reliable commercial application of Raman. If he is correct, specialized Raman products will be used for routine analytical chemistry that can be applied to clinical chemistry, industrial analysis, homeland security, and so forth.  

Using a "lab-on-a-chip" to study chemical reactions, separations, analysis, and bio-organisms has always seemed to have potential. For example, Anne Marz (9), working with Juergen Popp, demonstrated sensitivity and robustness for detecting specific molecules in blood assays. In one case, they looked for an antibiotic, and in the second case, they looked for a metabolite of an immunosuppressant agent that is myelotoxic. They used a sum vector machine (SVM) to evaluate the accuracy of their enzyme activity test. The goal was to provide a means to adjust the drug dosage within a range where it would be active, but not generate the toxic side product. Mischa Bonn (10)and Marcus Motzkus (11) have been developing micro-CARS for the lab-on-a-chip application, as well as some other applications, and their innovations will be discussed in the instrumentation section of this column.  

For me, the greatest excitement lies in the developments in the biological and clinical sciences. My postgraduate career started in the Johnson Foundation at the University of Pennsylvania, which was the Department of Biochemistry and Biophysics. When I left academia for the commercial life, the hope was that Raman could play a role in these areas. But, at the time (1978), I looked at the complexity of these systems and felt that even the microscope offered little hope of being able to unravel complex biochemical and physiological states. I am glad that 30 years has changed this. Let me try to select some areas in which Raman is having an impact. There is a lot to choose from, as many researchers who have been active in these areas gave talks during the conference. In addition, I should report that there was a tribute to Michael Feld, a pioneer in this field, who passed away a few months ago.  

Paul Carey (12) gave a talk whose title ("Raman Revolution in Structural Biology") in a way describes the Raman potential for impact. He makes the point that Raman bridges the gap between structure, as determined by X-ray diffraction, and functionality at the molecular level. He used the study of RNA polymerase as an example. For this enzyme, Murakami had already developed a method to capture three-enzyme intermediates. Making use of spectra of microcrystals, Raman difference methods, as developed by Bob Callendar, and isotopically labeled nucleotides, he was able to characterize the enzymatic process and then, using that information, follow Mg binding to aspartate.  

Juergen Popp (13) showed that spectra of single cells and micro-organisms can be recorded, and noted that microfluidics can be used for cell sorting (it takes 10 s to collect a spectrum), and he has produced an 85% correct recognition rate. In the case of bacteria, quickly identifying an infectious strain means that the correct antibiotic can be administered, avoiding sepsis. This is a good example illustrating how Raman can have payoff. People have been measuring and classifying bacteria with their spectra for more than 10 years. Combining these measurements with lab-on-a-chip cell separation and sorting can make this a clinically applicable technology.  

James Chan (14) delivered another talk on the analysis of single cells. Using a laser to trap the cell and suspend it in solution ("laser tweezers"), the signal from the glass support or container is eliminated by confocal optics. This, of course, can be combined with microfluidics. He mentioned many interesting uses of the measurement. At the end, he discussed a method to scan the laser beam to produce multiple optical traps that could then be multiplexed onto the spectrograph slit. His goals are to produce 50 traps in a line and to make a two-dimensional microwell device for a cellular array.  

Tatyana Chernenko (15), working with Max Diem, discussed their analysis of cells, tissues, and drug delivery devices. She discussed two multivariate analysis techniques used to analyze their spectra. Hierarchal cluster analysis (HCA) searches for similarities, producing a dendogram and a pseudocolor map, and reveals biochemical components that cannot otherwise be detected. Vertex component analysis (VCA) searches for dissimilarities in the data set, identifying pure component spectra, and has been successful in localizing drug nanoparticles in cells. Application examples included characterizing an embryonic colony to determine when an embryo can be implanted, and characterizing phospholipid-based nanoparticles used for drug delivery of insoluble molecules that are engineered to bypass lysosomal  degradation so that the drug can be delivered to the target tissue or organelle.  

Rick Mendelsohn (16) currently is studying skin pharmacology. Principle component analysis of a depth profile of the skin has revealed five factor loadings that are identified with the stratum corneum, the epidermis, the dermis, a lipid inclusion composed of ordered lipids with cholesterol, and nuclei. He studied the penetration of a drug that has to be delivered in the form of a "pro-drug" and its conversion to the active form. He detected the drug in the solvated state and in the crystalline form, a piece of information that the drug company would probably be interested to know.  

Mike Morris (17) has been studying bone structure and bone disorders in vitro for quite a while. Using spectral interpretation, he is able to characterize the molecular origins of disease states, and with polarization analysis, proposes the most likely orientation of the structures in bone and tissue. A major hurdle to such work is the inherent light scattering of tissue, which, one would think, would degrade the spatial resolution of the measurement. To work around this limitation, he has collaborated with Pavel Matousek (18) on spatially offset Raman spectroscopy (SORS). The essential point here is that if you want to probe below the surface of a turbid material, you can collect the light at a distance from the point of illumination, and this distance is related to the depth from which the signal is generated.  

Michel Pezolet (19) has spent years studying spider silk. There are seven types of glands that deliver seven types of silk, each with different mechanical properties as determined by stress/strain curves. Some fibers are highly extensible, some are not. Orientation is documented clearly in the polarization behavior of the spectra. These properties can be correlated with the amino acid composition and the Amide I band which provides information on the conformation of the amide linkage ( β sheet versus helical structures versus amorphous phase). Understanding the structure of this unique material can have commercial ramifications, but it also is useful to note that Mike Morris cited Pezolet's methodology in developing the protocol for interpretation of his collagen and mineral spectra.  

Developments of New Raman Methods and Instrumental Innovations

The Raman microscope, as conceived and developed in the early 1970s (2), took advantage of the potential spatial resolution, with the diffraction limit expected to be, and then confirmed, at approximately a half wavelength of the laser light. During the ensuing 25 years, the equipment was used to study polymers, ceramics, semiconductors, catalysts, glasses, works of art, and on and on. Even though performing analysis with 0.5-µm spatial resolution was of interest, there was always the nagging question as to whether a smaller spot could be achieved to study smaller features. In the case of polymers, there is the issue of the size of the particles of one polymer dispersed in a second continuous phase, in the case of semiconductors, there is the issue of lithographic feature size become smaller as the scale of integration became larger, in the case of oxides (ceramics, catalysts, works of art) identification of interfaces and surfaces that could be of different phase compared to the major phase.  

Today we know that "near field" optics can provide spatial resolution better than the diffraction limit. In this case, the light is presented to a sample through an aperture, and because the sample is in close proximity, the aperture size defines the spatial resolution. One way to create such an aperture is with a fiber-optic whose tip is tapered to a submicrometer-sized aperture. These fibers typically were coated with metal to prevent photon leakage because the tapering destroys the confinement properties of the fiber. Raman was attempted through such fibers, but the transmission was so low that the technology proved to be impractical.  

As an alternative a technique called tip-enhanced Raman scattering (TERS) has been developed. This is an apertureless technique in which a gold or silver coating or particle is deposited on an atomic force microscopy (AFM) tip. When the tip is in close proximity to a sample, it functions as a SERS particle to enhance the signal. The AFM system is integrated with a Raman microscope, and the difference between the signal with the tip in close proximity to the sample, and then withdrawn, is calculated and is equal to an enhanced signal from the small volume around the particle, whose size determines the spatial resolution.  

One of the Tuesday afternoon sessions was entitled "Tip-Enhanced and Near Field Raman I." The opening talk was by Aaron Lewis (20) of the Hebrew University in Jerusalem, who, having been involved in the field since the 1970s, was able to review the history. His implementation on current instruments is to use a tapered glass fiber with a gold particle on the tip. The tip approaches the sample at something like a 60° angle so that the standard optical scheme of a Raman microscope can be used. This configuration has the additional advantages of enabling the electric vector of the laser to have a component along the particle axis, further enhancing the Raman effect, and also avoiding generation of a signal from silicon in AFM tips manufactured from this material. 

There are other ways to implement TERS. The easiest is to use an inverted microscope for those cases in which the sample is transparent. The AFM system can be mounted on top of the microscope, with optical access to the sample from below. But for opaque samples, an upright microscope usually is used, and it is  the axis of the laser and Raman light that is diverted. Talks applying this technology to the fields mentioned at the beginning of this column were given by well known leaders in the field: Lukas Novotny (21), Satoshi Kawata (22), Francois Lagugne-Labarthet (23), Volker Deckert (24), and Bruno Pettinger (25), and illustrate the goal to probe semiconductors and biomedical systems well below the diffraction limit. As an example of the importance of these developments, Pettinger discusses single-molecule detection using TERS and Novotny showed images of carbon nanotubes recorded with 15-nm resolution and 50 ms/pixel. 

While TERS addresses the goal for higher spatial resolution, it does not achieve high sensitivity for rapid measurements. The sensitivity to vibrational spectroscopy is being addressed by developments in microcoherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS). Hideako Kano (26) discussed a new CARS method that uses a white light laser for broadband Stokes to enable the simultaneous detection of the spectrum out to 3500 cm

. The white laser is produced in a photonic crystal fiber. But CARS usually is subject to distortions due to the nonresonant background that Kano and his group have been able to suppress using a maximum entropy method (MEMS). Mischa Bonn (10) is also applying CARS to study chemistry in confined regions: microfluidic devices, heterogeneous catalysts, and small lipid droplets. He has applied the MEMS algorithm after isolating the resonant CARS signal by using phase separation; the algorithm is discussed at amolf.memcars.nl. Marcus Motzkus (11) is using picosecond and femtosecond lasers to produce CARS and nonlinear Raman spectra. In his multiplexed CARS experiment, he uses one femtosecond laser to eliminate the requirement for synchronization and thus enables "single-beam CARS." The width of the laser pulse determines the spectral coverage of the CARS output. He uses coherent control to restore spectral resolution, and a liquid crystal mask at the Fourier plane of the laser pulse to recover the spectral information. His goal is to study lipids in the CH region which will require 10-fs pulses and will be implemented on the next generation of his equipment. He uses polarization to reduce the nonresonant background, and heterodyne detection for low concentration species. At the end of the conference Sunney Xie (27), another well-known pioneer of micro CARS, delivered a plenary talk on stimulated Raman microscopy that also offers label-free imaging of biological cells and organisms. He actually commented that he now believes that micro SRM has more potential than micro CARS, and this idea was explored more fully at the satellite meeting mentioned earlier. And on the opening day, Richard Mathies (28) described his use of femtosecond lasers to excite stimulated Raman spectra and study the underlying physics and physical chemistry of the photochemical processes.  

Pavel Matousek has developed techniques for examining highly turbid materials (18), in which microscopy runs into the largest difficulties. Originally, he did time-resolved measurements (picosecond time scale) to determine from how deep in the sample the light was coming, but later realized that time could be converted to spatial separation, resulting in the acronym SORS. He is now using an Axicon component to excite the sample in an annulus and collect on axis. This scheme has the advantage of diffusing the light on a laser-sensitive material. He has also demonstrated the advantage of transmission Raman (TR) to provide spectra that can quantify bulk compositions. This already has been commercialized for QA and QC of pharmaceutical tablets.  

One more instrumentation development deserves reporting. A new type of filter based on a volume Bragg grating has been engineered as a notch filter and demonstrated to enable the acquisition of spectra to better than 5 cm

  from the exciting line (29). These filters are available for lasers at 632.8, 532, 514.5, and 488.0 nm. The capability is of interest for recording longitudinal acoustic modes (LAMs) in polymers and folded acoustic modes in layered semiconductors. Their performance rivals that of the best triple spectrographs, except that they of course are not tunable.  

My final remarks deal with the use of chemometrics for the processing of Raman data. Because of the complexity of the Raman spectra (which is why they are so information-rich) it would be impossible to produce images of most materials without the ability to include information from the entire spectrum. This requires sophisticated software based upon statistics (collect enough data to average out the noise) and matrix algebra (one axis for the spectrum and a second axis for the varying quantity, be it spatial position, time, concentration, and so forth). Discussion of multivariate analysis is far beyond what can be done here, but I do want to say how important it will be for many of the developing Raman fields to reach their potential. There are some commercial software packages available, or you can write your own using a mathematics package. Be forewarned, learning this field is not for the faint-hearted.  

Being a Raman spectroscopist used to be for people who had patience and didn't mind tending their instruments in the dark. With the simplification of the equipment has come new capabilities that match the applications that were always potentially of interest. It's exciting for me to witness these changes, and to participate in the evolution in some small way.  

 is the Worldwide Raman  Applications Manager for Horiba Jobin Yvon (Edison, NJ). She can be reached by email at 

(1) M Carrabba, K.M. Spencer, C. Rich, D. Rauh, 

(3) Raman Spectroscopy of Graphene: State of the Art, ICORS 2010, Boston, Massachusetts. 

(4) Raman Spectroscopy of Carbon Nanotubes, ICORS 2010, Boston, Massachusetts. 

(5) Resonance Raman Spectroscopy in Carbon Nanostructures, ICORS 2010, Boston, Massachusetts. 

(6) Raman Spectroscopy of Carbon Nanostructures, ICORS 2010, Boston, Massachusetts. 

(7) A Unified Theory of Surface Enhanced Raman Scattering, ICORS 2010, Boston, Massachusetts. 

(8) Transforming SERS into a Dependable Platform for Ultra-Sensitive Molecular Sensing, ICORS 2010, Boston, Massachusetts. 

(9) Towards an Analytical Tool Based on Lab-on-a-Chip-SERS (LOC-SERS) for Detection of Drugs in Complex Matrices, ICORS 2010, Boston, Massachusetts. 

(10) Quantitative CARS – Chemistry  in Confinement, ICORS 2010, Boston, Massachusetts. 

(11) Nonlinear Raman Spectroscopy with Shaped Femtosecond Laser Pulses, ICORS 2010, Boston, Massachusetts. 

(12) Raman Revolution in Structural Biology, ICORS 2010, Boston, Massachusetts. 

(13) Raman Spectroscopic Characterization of Single Cells, ICORS 2010, Boston, Massachusetts. 

(14) Laser Tweezers – Raman Spectroscopic Analysis of Single Cells and Their Dynamics, ICORS 2010, Boston, Massachusetts. 

(15) Non-Invasive Raman Spectroscopic Imaging in Biology and Pharmaceutical Sciences (title modified from the published title Non-Invasive Imaging of Modified Liposomal Pharmaceuticla nanocarriers by Raman Microscopy), ICORS 2010, Boston. 

(16) Vibrational Spectroscopy and Micro Spectroscopic Imaging – Applications to Skin Pharmacology and Wound Healing, ICORS 2010, Boston, Massachusetts. 

(17) Non-Invasive and Minimally Invasive Raman Spectroscopic Diagnostics for MusculoSkeletal Tissue Disorders, ICORS 2010, Boston, MA. 

Molecular Spectroscopy Workbench

Fran Adar examines the program at ICORS 2010, providing a sense of how applications and instrumentation are driving each other in the field of Raman research.

Thoughts About ICORS 2010 and Where Raman Spectroscopy Is Headed

In our two previous columns in this (sub)series (1,2), we examined the mathematics behind the classical least squares (CLS) approach to analysis. This approach is based upon the fact that when Beer's law applies, as in clear liquids, the spectrum of a mixture is the sum of the spectra of the individual pure components, each weighted by its concentration. 

What we saw in those actual spectra was that while the mathematics describing the spectra is exact, the synthesis of the mixture spectra, and the recovery of the pure component spectra from a set of mixtures, was approximately correct, but not exactly correct.  

There are two reasons for the discrepancies we found. One reason was the nature of the optical measurement used for obtaining those spectra. While the samples were measured in a temperature-controlled cell, the optical measurements were made by transflectance. Thus, while the incident beam from the spectrometer was fully directed and specular, the beam was returned to the spectrometer for measurement by diffuse reflectance. A consequence of this measurement technique is that the returning rays, after diffuse reflection, are spread out through a wide range of angles. 

We have demonstrated previously an effect on rays passing through a sample at a high angle to the normal (3) (or see chapter 29 in [4]). We summarize the effect here by noting that because those rays at high angles have a longer pathlength through the sample than rays that pass through the sample perpendicular to the faces, they are more strongly absorbed. The net effect is to introduce a nonlinearity in the spectroscopic response, and the nonlinearity is greater at high absorbances, an effect we have also previously demonstrated (see reference 3 or chapter 27 in reference 4).  

The second reason for the discrepancies is the interactions between water, methanol, and acetic acid. All three of these materials contain the  OH functional group. This functional group can dissociate or form hydrogen bonds. Furthermore, there is a very delicate equilibrium between undissociated –OH, and varying amounts of hydrogen bonding between the three materials. The wavelength at which hydrogen absorbs depends strongly upon its environment, and the change from undissociated –OH and hydrogen bonded –OH causes changes in the absorbance properties of the species, both in strength and wavelength. Thus, mixing these materials together created conditions whereby the absorbances change as the proportions of materials in the mixture change. An example is shown in Figure 1, where spectra of water–methanol mixtures are shown. In these mixtures, the amount of water varies between 0% and 100% in uniform 25% steps. It is clear, especially in the spectral region around 2270 nm, that the spectra are compressed at the higher absorbances. 

Figure 1: Spectra of waterâmethanol mixtures varying from 0% water to 100% water in equal steps of concentration.  

The equations for the CLS computations assume that all the spectra respond in a strictly linear fashion to concentration, and add together in exact proportion to their concentrations. As we have seen, however, there are at least two physical causes of nonlinearity in the spectra of the mixtures of these three materials that we were working with, an optical effect and a perturbation of the spectra when the environment is changed. It should come as no surprise, therefore, to find that the equations that depend upon strict linearity in the behavior of the analytes don't properly describe the system formed, when applied to the mixtures where strict linearity is not present. It is the lack of linearity, resulting from distortions of the spectra of the components (due to interactions with the other components) that caused the differences between the spectra of mixtures calculated from the pure materials and the actual mixture spectra, as well as the imperfect recreation of the spectra of the pure materials from the spectra of the mixtures. 

To demonstrate that the CLS approach can, in fact, actually work as described, we will need to start over again, and use materials that will not interact the way water, methanol, and acetic acid do. Before doing that, however, we also will describe the CLS method in a way that (we hope) will be more meaningful to a spectroscopist than the descriptions we used previously (1,2), which were intended for more mathematically and chemometrically oriented practitioners. Then we'll examine the results of using toluene, n-heptane, and dichloromethane as the three liquids, these being all hydrocarbons with no –OH or other functional groups. We also will see that the measurements are made in transmission, so that the nonlinearities attendant upon the use of transflection are not operative. So now we'll begin approaching this by presenting the same algebraic equations we saw before, but we will look at them as a spectroscopist would, not as a statistician or chemometricians would. Because we are still talking about Beer's law, we again begin with the equation for Beer's law: 

As we described previously, equation 1 applies wavelength-by-wavelength, and tells us that at any given wavelength, the absorbance (

) of a material at the chosen wavelength, the pathlength of the light through the material (

) and the concentration of the material (

), of course, is the implicit property of a molecule that varies with wavelength, and thereby constitutes the "spectrum" of that molecule. Because the pathlength is often, in practice, a quantity fixed by the cell that contains the sample, and is certainly the same for all components of a sample being measured, it is convenient to combine it with 

Equation 1 applies to a single component in a sample. When there are multiple absorbing components, the total absorbance is the sum of the absorbances of all the absorbing materials, at the wavelength of interest. Because this happens at every wavelength, we also speak of the spectrum of a mixture, that is, the absorbance at every wavelength, as being the sum of the spectra of the components of the mixture, each one weighted by its concentration. 

Equation 1 was derived for, and therefore applies to, measurements made in transmission when the sample is a clear (that is, nonscattering) liquid. The presence of scattering enormously complicates the situation, to the point where it is still considered an unsolved problem despite the extensive efforts of many scientists over the years (5–9) and the more recent work of Don Dahm (10) for typical examples. 

The "inverse" Beer's law case, as it is sometimes called, is derived from equation 1 by the simple expedient of dividing both sides of equation 1 by the

 product, thereby solving the equation for 

In this form, we have previously described how the relationship between the absorbance and analyte concentration can be found using least squares calculations (11). 

Anyone reading the previous explanations will be (or at least should be) asking themselves, "So what's the difference between the "inverse" least squares and the "classical" (or "direct" least squares) methods? They're both least squares, aren't they? 

The answer is "Yes, but . . . ." We continue by presenting some matrix equations, without attempting to understand them, at this point.  

 Table I: Matrix equations comparing CLS and ILS calibration algorithms 

In Table I, the symbols have the following meanings: 

 = coefficients of absorbances at the given wavelengths ***

 = Absorbance spectra of pure materials ***

] represents the concentration of the analyte for which a model is being developed; in CLS, [

] represents the concentrations of all the pure materials comprising the sample. 

] represents the absorbance of the samples comprising the calibration mixtures, while in CLS, [

] represents the absorbance spectrum of the sample being analyzed. 

 (the coefficients of selected wavelengths) and 

 (spectra of pure materials) do not have exact counterparts in the other calibration algorithm, although in a loose way, the spectrum of a pure material could be viewed as "coefficients" representing the absorbance that material at the various wavelengths. 

A casual inspection of the two equations in Table I probably would elicit the reaction "But except for the positions of the labels 

, those two equations look practically the same!"

Yes, indeed they do. There are corresponding parts to the two equations, [

] on the ILS side. These correspondences are due to the fact that both equations represent a "least squares" calculation of the data. So what's the difference? The equations seem to do the same things. Because they both specify the computation of least squares, they are doing the same things. In fact, without going into all the gory details, the two equations are, in reality, the inverse case of each other. But then, don't they say to do the same things, regardless of the label used to represent the variables?  

The answer is "not exactly." The difference between the two equations becomes more apparent when you realize that, first of all, those equations in Table I are matrix equations (as we stated initially, just before we presented the equations) and that while matrix operations sometimes appear to reflect algebraic equations, there are differences between matrix operations and similar-looking algebraic equations.  

In the case of the equations in Table I, the pertinent rule for matrix operations is that matrix multiplication does not commute, that is, given two matrices [

] does not, except under very special conditions, equal [

]. Therefore, it's not just a matter of the labeling. Even if 

 were to represent the same quantities (which they don't despite the fact that they both represent absorbances), the product 

We have previously examined the case of ILS in earlier columns (11,12), so let us now concentrate on the "classical" least squares methodology, to see how it differs. Again, we come back to the fact that "classically," chemists learned to do chemical analysis using spectroscopy by thinking about spectra the way they were taught to do. 

So how do chemists think about spectra? To answer this question, let's look at Figures 2a and 2b. Figure 2a shows the absorbance spectra of some pure liquids: dichloromethane, toluene, and 

-heptane. The reasons for the choice of these materials were mentioned briefly earlier, and also will be discussed further, in due course.

 Figure 2: (a) Absorbance spectra of pure dichloromethane, n-heptane, and toluene (x-scale in wavenumbers) and (b) absorbance spectra of pure dichloromethane, n-heptane, and toluene, and of a ternary mixture of the three (x-scale in wavenumbers). Note that the baselines of the spectra are offset for clarity. 

When chemists get their first exposure to spectroscopy, it is normally explained in terms of transmission measurements through clear liquids, and they start by learning a few basic "ground rules" about those measurements: 

I. The presence of absorbance bands in the material, and their wavelengths, is characteristic of the nature of the material. 

II. The strength of a given absorbance band depends on three factors:  

The absorptivity of the material at that wavelength, which is an inherent property of the material.

The pathlength of the light through the sample.

The concentration of the analyte in the sample.

III. The total absorbance of a sample, at a given wavelength, equals the sum of the absorbances, at that wavelength, of all the materials in the sample. 

Let us make the point now that in the discussion to follow, all references to samples, spectra, and every other aspect of the discussion is based upon the paradigm of transmission measurements through clear liquid samples. 

Figure 3: Spectra of two mixtures. Mixture 1 (blue): toluene = 50%, dichloromethane = 25%, n-heptane = 25%. Mixture 2 (black): toluene = 25%, dichloromethane = 50%, n-heptane = 25%. 

For clear liquid samples, these properties of spectral measurements are universals, that is, they are valid for any sample and any wavelength, regardless of the underlying physics creating the absorbance properties of the material. Thus, for example, the same considerations apply whether the measurement is made in the UV range, where the underlying absorptions are due to the interactions of photons with the electronic atomic and molecular orbitals, or in the infrared range, where the underlying absorptions are due to interactions of light with the vibrations of the nuclei of the atoms comprising the sample. 

Figure 4: Absorbance spectra of pure dichloromethane, n-heptane, and toluene, and of a ternary mixture of the three (x-scale in wavenumbers). Note that this graph is identical to the graphs in Figure 1b except that it has been turned on its side by rotating it 90Â°. 

Later, when we have become more sophisticated about these matters, we learn some new rules, such as the need to avoid interactions between different species present in the sample, and so forth. But for now, let's keep things simple and basic, and just consider the basic rules we stated earlier. 

From rule 2 earlier, we learn about Beer's law. Without going into detail, we learn that there is a quantity call the absorbance (abbreviated 

) that, at every wavelength, is the product of the three quantities listed: the absorptivity, the pathlength, and the concentration of the analyte. A way to see a convenient mnemonic is again to rewrite equation 1, as we do here: 

 is the absorbance of the analyte at a specified wavelength, 

Chemometrics in Spectroscopy

The authors continue their ongoing discussion of classical least squares with a look at spectroscopic theory.

Classical Least Squares, Part III: Spectroscopic Theory

The microscope and infrared spectrometer are two of the most useful tools for the study of biological materials, and their combined analytical power far exceeds the sum of the two. Performing molecular spectroscopy through a microscope superimposes chemical information onto the physical microstructure obtained from the optical microscope when visible and infrared information are collected under the same conditions. The instrument developments that enable current infrared microspectroscopic studies began with the introduction of the first research-grade infrared microscope, patented in 1989 (1). By 1993, published reports using this method to determine macroalgae (seaweed) cell-wall composition appeared (2-4). Since these initial reports, the use of infrared microspectroscopy (IMS) in microalgal (single cells or groups of cells) research has grown. Primarily, cultured algae have been used to hone IMS methodology and evaluate its capabilities in algal research (5–8). Studies involving natural, mixed species assemblages, which can utilize the spatial resolution potential of this technique fully are rare (9–11). For instance, in a recent review of IMS microalgal ecological research (12), only 3 of the 29 peer-reviewed publications investigated natural algal assemblages. Both thermal and synchrotron infrared sources provide a resolution capable of measuring individual algae in mixed species assemblages, and each has its advantages. For example, thermal source IMS is more accessible, allowing more samples to be analyzed than synchrotron IMS. However, synchrotron IMS with confocal masking provides superior resolution, which can be critical in isolating small or contiguous cells.  

Algal ecology is the study of the interaction between algae and their environment. Infrared microspectroscopy addresses a major logistical problem in this field, obtaining species-specific cellular biochemical information from natural, mixed-species assemblages (11,12). Benthic (bottom-dwelling) algae, for example, grow in a three-dimensional matrix (biofilm) composed of different cell sizes, shapes, and configurations. The optical and ecological challenge of studying algae is apparent from Figure 1, which shows a photomicrograph of algal chlorophyll fluorescence on a rock. Several issues make it difficult to obtain single species measurements with standard techniques: cell sizes can vary over an order of magnitude; species can occur as single cells, long filaments, or globular colonies; a number of different species can be found within a few square millimeters; and fluorescence can vary across cells (that is, the physiological state varies across cells). 

 Figure 1:  Micrograph of algal chlorophyll fluorescence (red) on a rock (white) collected with confocal laser scanning microscopy. Note the variety of cell shape configurations and sizes among the benthic algal species. Larger species and colonies are routinely analyzed by conventional IMS. The small size of many species (

The authors use synchrotron confocal IMS to measure the response of two dominant algal species from a stream of biofilm to a reduction in nutrient availability.

Measuring Cellular-Scale Nutrient Distribution in Algal Biofilms with Synchrotron Confocal Infrared Microspectroscopy

Issue PDF

Click the title above to open the Spectroscopy October 2010 regular issue, Vol 25 No 10, in an interactive PDF format.