This installment of "Atomic Perspectives" demonstrates the ability of inductively coupled plasma–optical emission spectrometry to perform high-throughput analysis of digested soil samples. It also provides assistance in setting up an EPA 200.7 soil analysis method.  

Growing populations and the subsequent increased demand for housing have resulted in the need to reclaim land previously designated for industrial development. Because of the nature of industrial activity on this land, some sites are potentially contaminated with substances that are hazardous to human health. Therefore, before housing construction can begin, the soil needs to be tested against environmental regulations and any harmful substances removed. Due to the expense and difficulty in clearing these sites and making them safe to build on, it is vital that the analytical data acquired is robust and rigorously controlled. 

Sample preparation usually involves acid extractions using hotplates and open-tube or microwave digestion systems. These extractions are commonly analyzed using inductively coupled plasma–optical emission spectrometry (ICP-OES) because of its tolerance of complex sample matrices and its rapid, multielement analysis capabilities. Typical analysis times for this application are 2.5–3 min per sample, largely due to the long rinse times required. The ICP-OES system used here typically requires 16 L/min of argon while performing analyses (3 L/min optical purge, 0.5 L/min nebulizer gas, 0.5 L/m auxiliary gas, and 12 L/min coolant gas). Using a typical analysis time of 2.5 min per sample, 11.25 h are required to analyze 200 unknown samples (and the quality control [QC] samples required by EPA method 200.7). This equates to 10,800 L of argon used. 

The regulation of this type of analysis is performed by different environmental bodies in different territories. In the United States, it falls to the Environmental Protection Agency (EPA), and the approved method for the determination of metallic compounds using ICP-OES is EPA method 200.7 (1). This method has become the basis for method development in many other countries. The methodology described within this installment of "Atomic Perspectives" is fully compliant with EPA method 200.7 and would be a good procedural basis for this type of analysis anywhere in the world. The samples are prepared by microwave digestion, in accordance with EPA Method 3051 (2). 

Four dried and ground soil samples were acquired from a brownfield site in the UK. In the UK, a brownfield site is defined as "previously developed land" that has the potential for being redeveloped. The samples were classified as sands, loams, or clays. (See Figure 1 for a photo of the brownfield site excavation.) 

 Figure 1: Brownfield site excavation.			

A 1 ± 0.01 g amount of each sample was weighed, and the weight recorded, before digestion using nitric acid. To stabilize the mercury, the concentrated nitric acid used for sample digestion and preparation of standards was spiked to a gold concentration of 50 mg/L. A 2-mL volume of the concentrated nitric acid (specific gravity [SG] 1.42) reagent was added to each sample and left to stand for 10 min to allow any reaction gasses to escape. Next, 6 mL of concentrated hydrochloric acid (SG 1.18) was added and the samples were left for another 10 min. Both acids were trace metal grade (Fisher Scientific). If mercury, lead, or silver analysis is required, the nitric acid must be added first to prevent the formation of chloride salts, which are highly insoluble.  

The samples were then heated in a microwave digestion system (MARS 5, CEM Corporation) in accordance with EPA method 3051 (2). The samples must be heated to 175 °C within 10 min, and then continue to remain between 170 °C and 180 °C for another 10 min. After the microwave digestion program was complete, the sample containers were left in the microwave digestion system for 5 min to cool down and then were moved to a fume cupboard to reach room temperature. 

The sample digests were quantitatively transferred to 100-mL volumetric flasks, made up to volume with ultrapure deionized water (18.2 MΩ), and then shaken vigorously to produce a homogenous sample. The samples were left overnight to settle out any suspended solids. Alternatively, an aliquot could be transferred to an appropriate container and centrifuged. If suspended solids remained in the samples, they were passed through a 0.45-µm filter. The sample digests were then ready for analysis. 

A series of calibration standards were prepared using 1000-mg/L solutions (assurance grade, Fisher Scientific). These were made up in 500-mL volumetric flasks and were acid-matched to the samples with 10 mL of concentrated nitric acid and 30 mL of concentrated hydrochloric acid. The final concentrations of each standard, and the elements they contain, can be seen in Table I. If stored as required by the EAP method in fluorinated ethylene propylene (FEP) bottles, these solutions will remain stable for 6 months. 

A spiking solution was prepared using an independent batch of 10,000-mg/L element solutions (assurance grade, SPEX CertiPrep) for use in the quality control samples described below. Volumes of 25 mL of Ca and Fe, 0.25 mL of each remaining element solution, 2 mL of concentrated nitric acid, and 6 mL of concentrated hydrochloric acid were made up to volume in a 100-mL volumetric flask with ultrapure deionized water. This solution contained 2500 mg/L of Ca and Fe and 25 mg/L of all other elements. It will remain stable for 6 months if stored in a FEP bottle. 

For use as an on-line internal standard, a 10-mg/L yttrium solution was prepared using a 1000-mg/L yttrium solution (assurance grade, Fisher Scientific, supplied by Fisher Chemicals). A 10-mL volume of the 1000-mg/L solution was added to a 1000-mL volumetric flask, along with 10 mL of concentrated nitric acid to improve stability, and was made up to volume with ultrapure deionized water. This solution remains stable for 6 months if stored in an FEP bottle. 

A rinse solution was prepared by adding 20 mL of concentrated nitric acid and 60 mL of concentrated hydrochloric acid to 700 mL of ultrapure deionized water. The rinse solution was made up to 1 L with ultrapure deionized water. 

Each laboratory using this method is required to operate a formal QC program. The minimum requirements of this program consist of an initial demonstration of laboratory capability, and the periodic analysis of laboratory reagent blanks, fortified blanks, and other laboratory prepared solutions as a continuing performance check. The laboratory is required to maintain performance records that define the quality of the data generated. 

An initial demonstration of performance, also known as a method validation, is required to characterize instrument and laboratory performance before the analysis of unknown samples using this method can take place. It consists of the following three parts: 

 The calibration standards and acceptable instrument performance must be verified by analyses of a quality control sample (QCS) when beginning to use the method, on a quarterly basis, and after the preparation of new stock or calibration standard solutions. The solution is made by adding 2 mL of spiking solution into a 100-mL volumetric flask along with 2 mL of concentrated nitric acid and 6 mL of concentrated hydrochloric acid, and the solution was then made to volume with ultrapure deionized water. This solution will have an equivalent concentration of 5000 mg/kg Ca and Fe, and 50 mg/kg of all other elements (present in the sample). It must be stored in an FEP bottle and will remain stable for 6 months. To verify the calibration standards, the determined mean concentrations derived from three analyses of the QCS must be within ±5% of the stated values. 

Before sample analysis, method detection limits (MDLs) must be established for all wavelengths utilized. A blank should be fortified with a concentration 2 to 3 times the estimated MDL for each element. This with seven repeats. The MDL for each element can be calculated using the following equation:  

MDL = 3.14 × s                               [1] 

-value for 99% confidence, and s is the standard deviation for seven replicates measured at the estimated MDL. This test should be run on three consecutive days and the average taken. 

 Before analysis, the linear dynamic range (LDR) must be established for all wavelengths used. To establish the LDR, a series of loaded blanks with increasing concentrations are analyzed until the observed analyte concentration is no more than 10% outside of the stated concentration of the standard. If a determined sample analyte concentration is greater than 90% of the determined upper LDR limit for that analyte, then the sample must be diluted appropriately and reanalyzed.  

The LDR limits must be recalculated annually or whenever the instrument hardware or method parameters change.  

Continuous Assessment of Laboratory Performance

As described below, EPA Method 200.7 defines several quality control samples that must be analyzed along with the unknown samples after the method validation is complete.  

The instrument performance check (IPC) is a continuing check of the calibration accuracy and drift. The solution used for the QCS is used for the IPC, and it must be analyzed following every calibration, after every 10 samples, and at the end of every sequence. The initial IPC must be within ±5% of the expected value, and subsequent IPCs must be within ±10% of the expected value. 

 The laboratory reagent blank (LRB) checks the laboratory reagents and sample preparation technique for contamination. A digestion tube that includes only the analytical reagents is prepared and processed in the same manner as the samples. The analysis results must be below 2.2x the MDL. An LRB must be analyzed for every batch of 20 or fewer samples. 

 The laboratory fortified blank (LFB) checks the recovery of analytes by spiking a known quantity into a blank sample. A 1-mL volume of the spiking solution is added to a digestion tube and treated in the same manner as the samples. The result is compared to that of the LRB. The spike recovery should be the equivalent of 2500 mg/kg for Ca and Fe, and 25 mg/kg for all other elements, and the recovery must be ±15% to pass. An LFB must be analyzed for every batch of 20 or fewer samples. 

Table II: Suggested concentrations of SIC element solutions 			

The laboratory fortified matrix (LFM) is used to check analyte recoveries from the matrix by spiking a known quantity into a sample. A 0.1-mL volume of the spiking solution is added to 10 mL of sample and the result is compared to that of the unspiked sample. The spike recovery should be the equivalent of 2500 mg/kg for Ca and Fe, and 25 mg/kg for all other elements, and the recovery must be ±30% to pass. An LFM spike must be performed on 10% of all samples. 

EPA Method 200.7 suggests using certified reference materials (CRMs) as an additional mechanism to diagnose problems with the analysis. For this work, a soil CRM was purchased (SQC001, lot 017309, RTC) and treated as a sample. A CRM was run with every batch of 20 samples or fewer. After 20–30 CRM samples have been analyzed, control limits can be developed from the mean concentration (

) and the standard deviation (s) of the mean concentration. This data is used to establish the upper and lower control limits as follows: 

 A series of single-element solutions should be prepared to test for any direct spectral overlap and to make any necessary corrections. There are 17 potential interferences for the ICP-OES analysis. However, because of the resolution and wide wavelength range of the ICP-OES system used here, only three spectral interference checks are required. The required element concentrations for the spectral interference check (SIC) solutions are shown in Table II. These solutions should be analyzed weekly, or when the affected elements produce QC failures. The interelement correction (IEC) factors should be updated as necessary. 			

A Thermo Scientific iCAP 6500 Duo ICP-OES system was used for the analysis because of its ability to view the plasma both axially and radially, while allowing rapid analyses. An ASXpress Plus sample introduction system and an ASX-520 autosampler (both from CETAC Technologies) were coupled to the instrument to minimize the sample pathlength, thus reducing sample uptake and flush times. 

Figure 2: Solution flow paths in both valve positions in the sample introduction accessory. 			

The sample introduction accessory is designed to reduce the sample uptake and wash-out time. Using this accessory, analysis times can be reduced by up to a factor of three. During sample analysis, the system loads sample onto the loop before injecting it in to the nebulizer. Its operation is shown in Figure 2. When the valve is in the "load" position, the vacuum pump rapidly fills the sample loop (green path), while the instrument's peristaltic pump transports carrier solution to the nebulizer, thus maintaining plasma stability (red path). When the valve is in the "inject" position, the instrument's peristaltic pump delivers carrier solution onto the sample loop, driving the sample to the nebulizer for analysis while washing out the sample loop (red/green path). Simultaneously, the autosampler probe is moved to the rinse station and the vacuum pump is used to flush the sample uptake path. 

The method was set up using Thermo Scientific iTEVA Software. Where possible, five emission lines were selected for each element of interest, along with several lines for yttrium fused as an internal standard. The method parameters are shown in Table III. 

Table IV: Emission lines and plasma views chosen, MDLs, suitable reporting limits, and LDRs			

The element emission lines were analyzed in three groups — axial-high, axial-low, and radial-high — to allow optimized light transmission of ultraviolet and visible light wavelengths for highest analytical performance. A single-element internal standard (yttrium, 10 mg/L) was introduced on-line, and then measured simultaneously with the axial-high, axial-low, and radial-high groups as follows: Y 360.073 nm (axial-high), Y 224.306 nm (axial-low), and Y 371.030 nm (radial-high). 			

The autosampler rinse time was set to zero because the rinse is performed during the analysis. To supply a steady flow of carrier solution, the per-pump speed was set the same for the sample flush and analysis.  

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Atomic Perspectives

ICP-OES can provide assistance in setting up an EPA 200.7 soil analysis method.

High-Throughput Soil Analysis Using Inductively Coupled Plasma-Optical Emission Spectrometry

The ionization process in mass spectrometry (MS) creates ions from neutral molecules or extracts preformed ions from the sample. Additionally, the ionization source must facilitate the efficient transport of ions into the mass analyzer of the instrument for mass analysis. In the nearly 100 years of MS, and in 75 years of MS as a method of instrumental analysis, a great breadth and variety of ionization methods have been developed. The applications of these methods reflect the nature of the sample molecule (its volatility and thermal stability), the complexity of its environment (solid, liquid, or gas, and whether it is a mixture or purified), and the requisite flux and persistence of the ions created from the sample. The final four ionization methods in modern MS are electron ionization (EI) and chemical ionization (CI) for volatile samples, and electrospray ionization (ESI) and matrix-assisted laser desorption–ionization (MALDI) for nonvolatile samples. Of the many other distinct ionization methods available (as contrasted with commercial variants of the final four), some are no longer used, a few remain useful in specialized research, and several are used in successful commercial implementations of modern MS. In this installment, we describe the basics of a few "less often seen" ionization methods. 

In the last two installments of this column, we discussed the basics of models that relate the extent of dissociations of isolated ions to their internal energies. The validity of these models is tested by comparison of the predicted results with experimental measurements. For example, an ionization method could create a molecular ion with different amounts of known internal energy, and then the extent of dissociation to fragment ions could be assessed as a function of the internal energy. 

One method used to create molecular ions of known internal energy is charge-exchange ionization. Tedder and Vidaud (1) provide an overview of this method. The basic charge-exchange reaction is 

                                                    [1] 

where X represents the ionizing agent and M represents the sample molecule to be ionized. In the collision between these two species, the charge is transferred from the agent X to the molecule M. The collision should be at a low relative kinetic energy so that none of the kinetic energy is transformed into internal energy of the ion M

. The center-of-mass collision energy is usually held to less than 10 eV. The ionization potential of X is known. If it exceeds the ionization potential of M, then M

 is created with an internal energy that equals the difference between the ionization potentials. 

Charge-exchange ionization can be used to create mass spectra that resemble electron ionization (EI) mass spectra (2) when the source conditions preclude the usual EI process. The selectivity inherent in charge exchange can be used as an advantage when only certain components of a mixture should be ionized. In these applications, the agent X is chosen so that some components are ionized and others are not, and therefore no separation is necessary. Praun and Villinger (3) describe such an application in the analysis of exhaled breath. An off-line analysis is most often used, but the system is simple enough that it also could be used on-line, although the cost of this dedicated analysis would be high. Because no separation is necessary, analysis is rapid, even when 114 different volatile compounds (distinguished by their mass) were monitored (samples included acetaldehyde, acetone, acetonitrile, ammonia, benzene, ethanol, methane, acetic acid, isoprene, and compounds directly related to administered drugs). Why would one want to monitor so many different compounds? Individual organ function in humans has been linked to approximately 60 different compounds found in varying concentrations in exhaled breath (4,5). The comprehensive and quantitative analysis provided by charge-exchange mass spectrometry (MS) may be useful for diagnostic and evaluation purposes. 

Selection of the charge-exchange agent X provides the specificity described in the application described above. Theoretically, the choices are limitless, but in practice, simple species are used so there are not multiple ions that can react in a charge-exchange collision. Positive ions of the noble gases are often used, along with other diatomic and triatomic species. A few of these ionizing agents are listed in Table I along with their ionization potentials. If a given sample molecule M is ionized by a series of charge-exchange ionization agents, the appearance potentials of each of the fragment ions formed by dissociation of the molecule M can be determined. A plot of the intensities of these fragment ions as a function of the internal energy of M

 Table I: Ionizing agents used in charge-exchange ionization and their ionization potentials. The agent will ionize sample molecules M with lower ionization potentials in low energy collisions; the difference in ionization potentials becomes the internal energy of M+. These data are drawn from reference 1, reprinting ionization potentials from a standard compilation. 			

Lindholm (6) described the creation of breakdown curves using charge-exchange MS and a two-stage mass spectrometer. The first mass spectrometer selects the ionization agent ion formed in the source, and is set to pass only this ion into a collision chamber where the charge-exchange ionization occurs. The second mass analyzer (set at 90° to the incident beam) measures the mass spectrum consisting of the fragment ions formed by dissociation of M

Chan and colleagues (7) recently described an ambient MS technique that they termed "desorption ionization by charge exchange." This method is related to desorption electrospray ionization (DESI) and several related methods that involve adding a dopant to the nebulized spray directed at the surface. Chan provides evidence that molecular ions formed in their procedure by a charge-exchange reaction between toluene ions (formed by oxidation that occurs in the electrospray itself, or present in the solution) and the neutral molecules M of the sample. The method was shown to produce ions successfully for samples that proved intractable with other ambient ionization methods. Research showed that charge exchange was probably only one of several ionization processes that were simultaneously occurring, and this is not surprising. Charge exchange should always be considered as a possibility in ion sources and elsewhere. We close this section with a quotation from a paper presented by Wade Fite (8) to the 

Perhaps a little less obvious are the consequences of charge transfer research to more conventional mass spectrometry, however. It would seem clear that the analytical chemist should concern himself with charge transfer in the tube of his analyzer. Resonant charge transfer cross sections become large at typical mass spectrometer ion energies, and the danger of losing certain ions between the source and the detector is a very real one in some analytical mass spectrometers. Since the charge transfer cross section will depend strongly on the ion species in any given residual gas, the ion populations arriving at the detector may not be the same as those leaving the source, particularly if the vacuum in the analyzer is not the best. 

Frans Michel Penning (1894–1953) was a Dutch physicist whose name is often encountered by mass spectrometrists. For example, the pressure inside the mass spectrometer may be measured with a type of cold cathode ionization gauge known as a Penning gauge (also a Phillips gauge). Later researchers used some of the concepts exemplified in the design of the gauge to develop the Penning trap, which uses electric potentials and a static magnetic field to trap ions in stable orbits for extended periods of time. Penning has a long list of U.S. patents, and his name is also attached to the "Penning mixture" used in neon signs. Penning's classic book 

 was published in 1957 and showcased his expertise in the field. He was known as a talented and careful experimenter (9). 

Penning ionization in MS often involves a metastable atom formed from a gas. For example, metastable gas atoms He*, Ne*, Ar*, and Kr* can be generated within the corona discharge at atmospheric pressure of these gases. As in charge exchange, a collision between the metastable ions and the gaseous sample molecule M results in ionization to form M

. The equation illustrates the ionization reaction for metastable He. The molecular ion formed is a radical cation, and the electron shown in the equation is that removed from the molecule; both masses and charges balance in the equation as shown. 

 + electron                             [2] 

The ionization process occurs as written because the ionization potential of the molecule M is lower than internal energy of the metastable ion. The rare gases are often used in Penning ionization for organic analysis because their excited states are of sufficient energy to ionize the sample molecules. Penning first described this process in 1927 (10), in a half-page journal article. In contrast to the precision with which molecular ions with various internal energies can be produced in charge-exchange ionization, Penning ionization can be a more complicated process energetically because there are many metastable states for the rare gas ions, and these states have different lifetimes. Additionally, different sources produce different populations of these various metastable states. Table II lists the most abundant metastable states for various gases commonly used in Penning ionization. Conveniently, the energy levels of these metastable species are grouped. Helium, neon, and argon should be able to ionize almost all organic molecules. The use of krypton or xenon may provide some selectivity. Depending on the metastable atom used, the M

 formed may have little to no internal energy, minimizing dissociation. However, the exact amount of internal energy in the molecular ion is not determined.  

Table II: Energies of selected metastable ion states for some gases			

We leave behind, for now, the wide breadth of Penning ionization processes in science, which includes surface analysis and modification, fundamental studies in spectroscopy, as well as molecular collision and dissociation dynamics (11). Instead, we describe how Penning ionization has provided yet another powerful method for the ionization of organic molecules. In 1993, metastable ion bombardment (MAB) was introduced (12) as a tunable source for organic analysis, designed with the intention of controlling the extent of ionization and the degree of dissociation of the ions formed by changing the identity of the metastable atom. Metastable ions could be created in a variety of sources; the first generation MAB source design uses a low-voltage corona discharge in a chamber filled with the chosen gas at a pressure of 10–100 mbar. Expansion through a skimmer nozzle creates a jet of ions, metastable atoms, and unreacted gas. Electrodes remove the charged species and what passes into the sampling region of the mass spectrometer are the gas and metastable atoms, with the latter involved in the Penning ionization process with gas-phase sample molecules M. The corona discharge produces a flux of metastable atoms of about 10

, depending on the exact source design (13). The metastable ions can be transported into other parts of a mass spectrometer source without regard to source potential or the presence of external magnetic fields. 

Several intriguing applications of the MAB source have appeared in the literature. The MAB source has been fitted to a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer (14), and the tunability of the source demonstrated both with respect to selective ionization of one component of a mixture but not the other, and a variable degree of dissociation in the ionized samples. Dissociation of singly charged peptide ions stored in a radio frequency linear ion trap can be induced by collisions with metastable atoms (15); the neutral atoms are easily introduced into the trap because they are unaffected by the electric fields. Thermally vaporized aerosol particles have been analyzed by MS using metastable atom ionization, with the reduced dissociation thought to provide superior classification information for broad groups of compounds present in the aerosol (16). One of the challenging environmental applications of high resolution gas chromatography–electron ionization high resolution mass spectrometry (HRGC-EIHRMS) is the quantitative analysis of polychlorinated dioxins and furans (PCDDs and PCDFs), which are highly toxic contaminants usually found at trace levels. Common interferences in this analysis are the polychlorinated diphenyl ethers (PCDEs). Because the interference is caused by the isobaric fragment ions, MAB was used to produce only the molecular ions of the compounds, resulting in more-assured quantitative results (17).   

In the examples provided above, Penning ionization is used to analyze samples that are in the gas phase at pressures concordant with the vacuum in the mass spectrometer. However, the samples can also be at atmospheric pressure. Samples and sample solutions are placed on a needle tip positioned near an aperture leading to the analyzer of the mass spectrometer. The needle is heated and a high voltage is applied to aid in the desorption of ions. The initial Penning ionization at the surface begins a cascade of subsequent ionization reactions, including protonation when the sample is dissolved in a matrix that can act as an acid. Tsuchiya and Kuwabara described this method in 1982 and developed it further over the next few years for the analysis of nonvolatile organic compounds (18,19). Recent developments use a similar source to create a sniffer to detect gases at atmospheric pressure (20). 

In 2005, researchers described the direct analysis in real time (DART) ionization source (21). The basic source is well-known to scientists familiar with Penning ionization. Nitrogen or helium is introduced into a chamber, and a high voltage between cathode and anode creates ions and metastable atoms of the gas. The ions are removed from the effusive stream, and the metastable atoms are directed toward the mass spectrometer sampling orifice. Simplistically, sampling occurs when the liquid or solid sample is placed nearby, and the gas flow bounces off the surface into the mass spectrometer. The exact positioning of the sample is not critical; ions are collected from a large solid angle by virtue of the directed conductance through the aperture into the mass analyzer. The total distance from discharge chamber exit to mass spectrometer entrance is a few millimeters.   

In a few situations, a classic Penning ionization mechanism is proposed to explain the ions formed in DART. Usually, a combination of ionization mechanisms is thought to occur, depending on the Penning gas used, and the presence of dopants and solvents. Positive ions include the radical molecular ions M

, as formed in classic Penning ionization, as well as protonated molecules thought to form from the reactions of protonated water clusters with the sample molecule (the source of water is the air itself). Negative ions can be formed by electron attachment, with the population of thermal electrons produced by surface Penning ionization. All of these reactions are well-known and have been studied extensively. The key to the now extensive applications of DART has been in the ease of sampling, since materials can be analyzed directly on surfaces such as glass, paper, pills, skin, or foods, as well as liquids. It is, in retrospect, amazingly easy and direct to create the ions from such samples and capture at least some of them in the gas stream sucked into the mass spectrometer. The sensitivity, dynamic range, and accurate mass measurement capabilities of the instrument then support the identification of the sample (22). After 85 years, Penning ionization is alive and well, and it can be combined with other ionization methods to provide a flexible ionization probe for ambient MS.  

 (2) E.D. Lee, S.-H. Hsu, and J.D. Henion, 

http://www.alpha-mos.co.jp/separation/documents/airsense/vf_non-invasive.pdf

 (5) M. Phillips, J. Herrera, S. Krishnan, M. Zain, J. Greenberg, and R.C. Cataneo, 

 J.L. Franklin, Ed. (Butterworths, London, 1970), p. 457. 

 (7) C.-C. Chan, M.S. Bolgar, S.A. Miller, and A.B. Attygalle, 

 (8) W.L. Fite, "Charge Exchange Reactions," Presented at the 1963 Annual Conference of the American Society for Mass Spectrometry. 

http://www.dtic.mil/dtic/tr/fulltext/u2/409878.pdf

 (9) Penning's translated obituary is found here: 

(12) D. Faubert, J.G.C. Paul, J. Giroux, and M.J. Bertrand, 

(13) A.J. Palmer, M. Baker, and R.T. Sang, 

(14) C. Le Vot, C. Afonso, C. Beaugrand, and J.-C. Tabet,

(16) C.B. Robinson, J.R. Kimmel, D.E. David, J.T. Jayne, A. Trimborn, D.R. Worsnop, and J.L. Jimenez, 

(20) T. Iwama, M. Hirose, I. Yazaw, H. Okoda, and K. Hiraoka, 

(21) R.B. Cody, J.A. Laramée, and H.D. Durst, 

(22) L. Nyadong, A.S. Galhena, and F.M. Fernández, 

  vaguely recalls something about "no new stories, but always new audiences." The reappearance of Penning ionization in MAB and DART applications is a reminder that maintaining a firm and broad foundation in science is fundamental to progress. We have forgotten more than we understand, and this is just as true for Sheldon as it is for Leonard. This column is the sole responsibility of the author, who can be reached at 

MS Forum

The basics of a few "less often seen" ionization methods are described.

More Ways to Make Ions

The Exemplar LS and Exemplar Plus miniature spectrometers from B&W Tek are designed with a low-stray-light "unfolded" Czerny-Turner spectrograph. The LS reportedly is suitable for integration into compact UV or UV–vis spectrophotometer systems. According to the company, the Plus has a thermoelectric-cooled back-thinned CCD detector with 2048 effective pixels. 

www.bwtek.com/technology/ccd-spectrometers

The LabRAM HR Evolution spectrometer from Horiba Scientific is designed with an automated, extended wavelength range capability. According to the company, the product's wavelength range is from 200 nm to 2000 nm, with access to frequencies as low as 10 cm

Specac's Quest ATR is a single-reflection attenuated total reflectance accessory designed for laboratory spectroscopic sample analysis. According to the company, the optical design is based on all reflective gold-coated optics and features the company's Synopti-Focal Array technology with precision-molded aspheric mirrors. The accessory's wavelength capability reportedly ranges from 10,000 cm

Thermo Fisher Scientific's iCAP Q ICP-MS system is designed to provide increased throughput to enable laboratories to cut analysis times by up to 50%. According to the company, the system features an interface that enables one-click setup and allows users to go from standby to performance-qualified analysis with the push of a button.  

The Agilent 8800 triple-quadrupole ICP-MS system is designed to provide improved performance compared with single-quadrupole ICP-MS and to provide MS-MS operation for interference removal in reaction mode. According to the company, the system can be used to analyze elements in life-science, soil, rock, and plant materials. The system reportedly also can be set up to operate like a single-quadrupole ICP-MS system. 

The Maya2000 Pro-NIR spectrometer from Ocean Optics is designed for Raman and low-light-level shortwave NIR applications. According to the company, the spectrometer is optimized for the 780–1180 nm region and includes a 760-nm longpass filter, a 50-μm slit, and gold mirrors.  

Milestone's DMA-80 mercury analyzer is designed to enable an operator to analyze for mercury in matrixes that include solids, liquids, and gases. According to the company, the system can be used in laboratories serving industries that include toxicology, environmental, energy, chemical, quality control, and gases. 

Two demountable ICP torches from Glass Expansion are designed with an alumina inner tube and an optional ceramic outer tube. According to the company, the torches accommodate the PerkinElmer 8300 DV and Agilent 700 Series Axial ICP spectrometers. The D-Torch reportedly can be used for analyzing organic solvents or samples with high levels of dissolved solids. 

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It is common for overlapping spectral lines to occur in Raman spectra. To the extent that analytical bands can provide physical or chemical meaning relevant to the material being studied, it becomes necessary to follow these spectral lines separately as sample parameters change. Anyone who has band-fitted spectra knows that the results are fraught with pitfalls. The most common one is to add a spectral component in order to improve the overall fit. The problem with this approach is that there may not be physical or chemical meaning to this extra component. Another problem is that the fits typically are not unique. That is, the final fit may depend on the starting parameters and how well the algorithm converges. In this installment, we will use real spectra to illustrate how one can be his or her own critic in performing this valuable operation. 

Analytical Raman spectra provide bonding information for chemical species. As such it can be sensitive to anything that changes the chemical bonding — for example, solvation, pH, temperature, applied stress, and crystallinity. Because the spectra are sensitive to such chemical or physical changes, the spectra can be used to infer how the sample of interest is affected by these environmental parameters. However, when the spectra are complex, there are overlapping bands that make the identification of cause and effect difficult. In principle, band-fitting enables separation of the multiple components, which aids in this task.   

The complexity of a vibrational spectrum is determined by the number of degrees of freedom, which, in turn, is directly related to the number of moving atoms. Larger molecules have more degrees of freedom, and therefore more vibrational bands. In a certain sense, polymers offer one of the most challenging systems for band-fitting. The molecules are "infinitely" long, they can orient in particular directions, there can be many conformations — especially around single bonds — and the polymer can be (partially) crystalline. In fact, all of this variability is used to engineer-in particular physical and chemical properties. So vibrational spectra, especially Raman spectra, can be an asset in engineering a material or determining failure mode (especially mechanical failure).   

For a model system I will use the spectra of spin-oriented fibers of polyethylene terephthalate that I worked on many years ago as a collaboration with Herman Noether (1), who had retired from Hoechst Celanese. He had a set of fibers that had been spin-oriented from the melt at 1500, 2500, 3500, 4500, and 5500 m/min. In addition, we had samples from this same set of fibers that we had drawn at room temperature (RT, which is below the glass transition temperature, 

). From birefringence measurements it was known that the orientation in the fibers increased with take-up speed; the birefringence also increased after the RT-draw, with the slowest spun fiber responding the most to the drawing operation. From X-ray diffraction (XRD) it was known that there was crystallinity in only the two most rapidly spun materials. Our goal at the time was to follow the orientation of the molecules in the fibers by recording polarized Raman spectra as a function of take-up speed. In addition to intensity changes, what we found was that changes in band positions of vibrations of the glycol atoms correlated with the increasing orientation which was consistent with the early band assignments (2–5). We also confirmed that the width of the carbonyl band correlated with the degree of crystallinity, which was also consistent with previous studies (6). What we want to show here is how some of the bands' positions or intensities correlate with orientation and therefore enable prediction of the conformation distribution. But because of the complexity of the spectrum, this can only be done by band-fitting the spectra and following the separated bands. Ultimately, this detailed information can be combined with the assignments of Stokr and colleagues (7), thereby aiding in the description of the conformation of the polymer at the molecular level. The goal of this column installment is not to make these detailed assignments; the reader is directed to the more recent literature (8–10). 			

Spectra of single fibers (<10 µm in diameter) were measured on a Raman microscope. The fibers were taped to a slide with minimum tension. Spectra were measured with the laser and Raman polarization either parallel to the fiber axis or perpendicular to it. The spectra were baseline corrected (using a third order polynomial) and then the bands were manually selected based on knowledge of the spectroscopic behavior of these materials. After the bands were selected, the algorithm in LabSpec Raman spectroscopy software (Horiba) optimized the fit, reporting χ

 and standard error, peak position, peak amplitude, peak width, percent Gaussian in the fit, and integrated area of the bands. These parameters can be exported into an Excel (Microsoft) spreadsheet for further manipulation.    

Figure 1 shows the ZZ spectra (laser and Raman polarization parallel to the fiber) between 750 and 1220 cm

 of these fibers, which is the region of the spectrum that has been shown, for the most part, to be sensitive to the conformation of the bonds of the glycol region. The spectra have been band-fit and stacked to evaluate the changes due to the increasing orientation and possible crystallization. The left part of the figure shows spectra of the as-spun fibers, and the right part of the figure shows spectra of the same fibers after drawing at room temperature. Systematic spectral changes are seen; exporting the band-fit parameters enables correlation of these changes to the polymer behavior in terms of molecular orientation and crystallization. Referring to the literature assignments one can then understand the morphological state of a sample in light of the history of that sample (2–4,7–10).   

Figure 1: ZZ band-fitted spectra of PET fibers spin-oriented (from top to bottom) at 5500, 4500, 3500, 2500, and 1500 m/min. The figure on the left shows spectra recorded from as-spun fibers, and the figure on the right shows spectra from fibers that had been subsequently drawn to the break point at room temperature. Each set of spectra was scaled so that the intensity of the band close to 1120 cm-1 was set to the same value. Table I summarizes the observed changes.

What we want to focus on now is the region between 750 and 950 cm

 . Figure 2 shows the spectra of the fiber spin-oriented at 4500 m/min before and after the room-temperature draw. The reason for focus on this region is that the residual in the fit exhibits systematic evidence for a less than perfect fit. The residuals, shown in red in the bottom two traces of the top of Figure 2, have wiggles that are seen in the other fibers as well (not shown). When additional bands were added to the fits, the residuals, seen in the top of the figure, went flat. The top two traces show the same spectra fit with the additional peaks. The strong peak near 860 cm

 is now fit by a sharp and a broader band. And near 890 cm

 a second small, but sharp peak has been added. The overall fit in this region is much improved. As an alternative to this fit, we also tried replacing the two broad peaks near 825 and 886 cm

 by one very broad band that would span the entire range, but found the fit to be poor, and in fact, the algorithm did not converge to anything reasonable. The bottom figure in Figure 2 shows the second fits expanded to emphasize what is happening to the residual and the small bands. The residual is quite flat (except for the noise) and the "extra" band at 886 cm

 is diminished in the spectrum of the drawn fiber, which brings us to the next point.  

Table I: Changes of the glycol vibrations as a function of sample orientation 			

Unlike Fourier transform infrared (FT-IR) spectroscopy, which is an absorption technique where the intensity axis has real physical meaning, Raman is a scattering phenomenon, and there can be many, many variables affecting the measured intensities. To evaluate the spectra in Figure 2, we set the intensity at 860 cm

 the same in the two spectra. But we see that there are two components at 860 cm

 plus a significant baseline (actually the overlap of the two broad bands), so this operation cannot be rigorously accurate. However, others have observed that the intensity of the band at 796 cm

 is relatively constant and independent of polarization (5). The ratio of the intensity of the small band at 886 cm

 band shows that the sharper band at 886 cm

 is diminished in the drawn sample. This is consistent with the assignment to the gauche conformer, which would tend to convert to trans in the drawing operation. The results of the band-fitting are shown in Table II. The top of the table shows the band-fit parameters using four bands, the bottom using six bands. The differences include extra bands near 860 and 886 cm

Table II: Band-fitted parameters of spectra of fiber spun at 4500 m/min before and after drawing at room temperature			

So why would one go to all this trouble? In this case, the underlying presumption is that the history of the polymer determines its morphology that is, the conformer of the chains in these fibers. By relying on the band assignments, one can say what the melt-spinning and drawing has done to the chains, from which one can account for the physical and chemical properties of the fibers. It is interesting that the best fits seem to require two bands in the region of 860 cm

 . This band is assigned to a ring stretch. Usually one assumes that because of the rigidity of the aromatic ring, its vibration is not significantly affected by morphology. But these results show that this is not necessarily true. What would be the origin of this is beyond the scope of this column installment. Our purpose is to show the information that potentially can be extracted from these measurements.  

Figure 2: Band-fitted spectra of fiber spun at 4500 m/min before and after drawing at room temperature. In the top figure, the spectra from bottom to top represent the as-spun fiber fit to four bands, the drawn fiber fit to four bands, the as-spun fiber fit to six bands, and the drawn fiber fit to six bands. The bottom figure shows the spectra fit to six bands expanded to emphasize the quality of the fits. 			

Until now we have not directly addressed the issue of how to decide when to introduce additional bands into the band-fitting operation. My colleague, Dr. Sergey Mamedov, has worked extensively with glasses. In these systems, the Raman bands are broad, and the fit of a spectrum could be done with numerous combinations of bands. I have heard him say recently that rational fitting of this type of spectra requires the spectra of a series of related materials to be recorded. One can then follow analogous bands and show that sample variations correlate with band behavior systematically.  

Raman spectra of spin-oriented and drawn fibers were band-fitted to illustrate how this spectral treatment can unravel correlations between molecular conformers and sample history. Care must be taken to avoid over-fitting spectra; there should be chemical or physical reasons for introducing bands to improve the overall fit.   

 (2) S.K. Bahl, D.D. Cornell, F.J. Boerio, and G.E. McGraw, 

 (5) J.C. Rodriguez-Cabello, L. Quintanilla, and J.M. Pastor, 

 (7) J. Stokr, B. Schneider, D. Doskocilova, J. Lovy, and P. Sedlacek, 

 (8) N. Everall, P.G. Taylor, J.M. Chalmers, D. MacKerron, R. Ferwerda, and J.H. van der Maas, 

 (9) C.C.C. Lesko, J.F. Rabolt, R.M. Ikeda, B. Chase, and A. Kennedy, 

(10) M. Richard-Lacroix and C. Pellerin, 

 is the Worldwide Raman Applications Manager for Horiba Jobin Yvon (Edison, New Jersey). She can be reached by e-mail at 

Molecular Spectroscopy Workbench

Here, real spectra illustrate how to be your own critic when evaluating band-fitted spectra.

Band-fitting Raman Spectra to Extract Chemical and Physical Information

Raman spectroscopy is a sensitive method for monitoring the self-assembly of biological macromolecules. Amyloidogenic peptides have been shown to form peptide nanotubes often with a central diphenylalanine core. In this article, we show that UV resonance Raman spectroscopy (UVRR) can be used to characterize nanotubes formed with diphenylalanine (FF) peptides and graphene by tuning the excitation wavelengths to match the electronic transitions of the individual components (FF and graphene) and probe their properties during assembly. Raman spectra of graphene consist of spectral bands indicative of sp

  hybridized content. Deep UVRR spectra of graphene show a distinct "G" tangential stretching mode, which is split into a doublet at 1477 cm

. Scanning electron microscopy is used to confirm formation of diphenylalanine–graphene nanotube assembly. 

Molecular self-assembly has attracted considerable attention for the design and fabrication of nanostructures. Self-assembly is ubiquitous in biological systems and plays a key pathogenic role in amyloidosis, which is the underlying cause of diseases like Alzheimer's disease, type II diabetes, and prion diseases. Diphenylalanine (FF) peptides, a core structural motif of the Alzheimer's β-amyloid polypeptide, spontaneously self-assemble into nanostructures and can act as a template in the self-assembly process, facilitating the formation of both peptide nanocomposites and conductive nanowires. Reduced graphene sheets and FF dipeptides form nanocomposites through simple mixing, in which the electrostatic and aromatic properties of both species, particularly π-π stacking interactions and hydrophobicity, drive the association (1).  

Graphene, a two-dimensional sheet of one-atom-layer-thick sp

-bonded carbon atoms (2), possesses unique electronic transport properties (3,4) and is also an interesting candidate for composite materials because of its mechanical flexibility (5,6), large surface area (7), thermal and chemical stability (8), and ease of functionalization of the graphene edges (5,7,9,10). Graphene is often chemically modified at the periphery to facilitate its dispersion into monolayers under aqueous conditions (11).  

UV resonance Raman (UVRR) spectroscopy, a powerful and convenient tool for protein structural characterization and studying molecular self-assembly in peptides and proteins (12–16), has also been shown to be particularly useful for characterizing the properties of highly insoluble and fibril precipitations (14,17,18). Previously, visible Raman spectroscopy had been used for characterization of carbon-based materials (19–22), but recently deep UVRR spectroscopy has emerged as a convenient technique for characterizing such materials (22–24). Advantages of UVRR spectroscopy arise from the resonance-enhanced signal, which allows it to overcome the strong scattering and fluorescence effects of the sp

-bonded carbon in the visible region. The present study uses UVRR spectroscopy in combination with scanning electron microscopy (SEM) to probe the interaction of diphenylalanine with functionalized graphene nanoplatelets and their self-assembly into nanostructures. 

Peptides were purchased from Sigma-Aldrich, and stock solutions were prepared by dissolving the lyophilized powder in 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) (Sigma-Aldrich) to a concentration of 100 mg/mL. This concentrated stock was diluted into aqueous media to a final concentration of 2 mg/mL for nanotube preparation. The functionalized graphene dispersions were prepared by adding 1 mg of single-layer graphene nanoplatelets (Cheaptubes Inc.) to 7XTE buffer and sonicating for at least 2 h to uniformly disperse the graphene. 7XTE buffer contained 7 mL of Tris (TEKnova 1 M, pH 7.5) and 1.4 mL of EDTA (Promega Inc., 0.5 M, pH 8.0) in water to a final volume of 100 mL and pH of 7.4. For circular dichroism (CD) measurements, a stock 2-mg/mL peptide solution was immediately diluted to 0.04 mg/mL and spectra were recorded on a Jasco spectropolarimeter J-180 with a Peltier controller unit and a quartz cuvette with a 2-mm optical pathlength. SEM images were prepared using a JEOL JSM-6390 LV SEM system (JEOL). For SEM, an aliquot (10 μL) of the peptide nanotubes (2 mg/mL) was deposited on aluminum stubs and sputter coated with 50-Å Au-Pd. For the UVRR experiments a Nd:YLF pumped Ti:sapphire laser system (Quantronix) was used to generate the excitation wavelengths of 210 nm and 262 nm as previously described (25,26). Raman spectra at 229 nm were acquired with a continuous wave ion laser (Innova 300C MotoFreD Argon; Coherent) in which the 457.9-nm laser line was intracavity frequency-doubled with a barium borate (BBO) crystal to yield 229 nm. The lasers were operated at an average power of 1.0 mW. Raman spectra were acquired with the monochromator-CCD system previously described (25). A 170-μm spectral slit width was used for all excitation wavelengths, and data were calibrated with acetone, ethanol, and pentane and were accurate to 1 cm

. Spectra were collected for an acquisition time of 90 s to prevent sample damage. Data manipulation and analysis were performed using GramsAI spectral analysis software (ThermoGalactic). 

To verify the formation of peptide-graphene nanotubes, we visualized the nanotubes using SEM and examined them relative to each species of the solution (Figure 1). Specifically, the functionalized graphene dispersion in the absence of any peptide appears as flakes in SEM (Figure 1a). FF stock dilution into 7XTE leads to the formation of a nanotube mesh with tube diameters reaching 1–1.5 μm (Figures 1b and 2). The SEM images clearly show evidence of tubes associating into larger assemblies. Dilution of the FF stock into the aqueous graphene dispersion led to immediate peptide–graphene assembly, and nanotubes are observed by SEM, with diameters of 500–1000 nm (Figures 1c and 1d). As shown in Figure 2, more tubes with a smaller diameter are visible in the peptide–graphene mixture than with peptide alone. Disappearance of the graphene flakes after the addition of FF is consistent with peptide–graphene assembly. As controls, we performed the same steps with the Ala-Ala dipeptide and separately with the FF peptide in HFIP. In both cases, nanotube assembly was not observed by SEM (Figures 1e and 1f).  

Figure 1: SEM images of (a): GR and 7XTE; (b): FF and 7XTE (c) and (d): FF and graphene in 7XTE; (e): Ala-Ala and 7XTE; (f): FF and HFIP. Grapheneâpeptide ratios were 1:1 with final concentrations of 0.67 mg/mL. The FF and Ala-Ala solutions had a concentration of 2 mg/mL.			

We used CD spectroscopy to further confirm the formation of FF peptide nanotubes (Figure 3) where the CD curve obtained for the FF nanotubes is similar to that of the β-turn peptides with a minimum around ~190 nm and two maxima at ~200 nm and ~220 nm (27,28). The Ala-Ala control yields a spectrum that is indicative of random coil (29), with a characteristic minimum at 200 nm. The CD spectrum of the Ala-Ala peptide also indicates that it does not form any nanotubes (Figure 3).  

Figure 2: Distribution of nanotube diameters observed in SEM for the (a) FF and (b) FFâgraphene solutions.			

We exploited the capabilities of UVRR spectroscopy, a nondestructive vibrational technique, to selectively examine the FF and graphene nanotubes by using an excitation wavelength that corresponds to an electronic transition. In our study, the FF and graphene nanotubes have two components with vibrational transitions that can be resonantly enhanced by tuning the excitation wavelength to match the electronic transition of each component. This selectivity allows us to probe the properties of FF and graphene while in assembly and thereby infer the intermolecular effects on self-assembly.  

Figure 3: CD spectra of FF and Ala-Ala under aqueous conditions. Peptide concentrations are 0.04 mg/mL.			

An excitation wavelength of 210 nm primarily enhances the phenylalanine residues, which gives rise to two strong modes at 1602 and 1583 cm

  in the UVRR spectra of the FF–graphene and FF nanotubes (Figure 4). These bands result from ring C-C stretching vibrations (30). A total of six phenylalanine modes are observed and are consistent with those observed in the L-Phe spectrum. Substantial shifts in frequency and intensity are not observed when the FF nanotubes are formed or when the FF–graphene composite tubes are formed. In the FF–graphene spectrum, only modes from the Phe residues are observed and graphene modes are not detectable.  

Figure 4: The UVRR spectra of the (a) FFâgraphene nanotubes, (b) FF nanotubes, and (c) L-phenylalanine monomer obtained at Î»exc = 210 nm. Peptide concentrations are ~1 mg/mL.			

When an excitation wavelength of ~229 nm is used, we observe that modes from both the FF peptide and the graphene can be observed (Figure 5). As shown, at this excitation wavelength the vibrational modes in the 1000–1035 cm

  region of the FF nanotubes are enhanced and dominate the FF spectrum. The UV Raman spectrum of the functionalized graphene nanoplatelet suspension exhibits two very distinct bands at 1691 cm

. Graphitic materials have typically been characterized by a highly dispersive band in the 1200–1400 cm

  region, called the disorder-induced D band, and the graphitic mode (G) at higher frequencies (~1590 cm

), which is because of the stretching of sp

  atoms in the rings and chains (19,31). These modes are observed in the spectrum of the FF–graphene nanotubes, but they are small in intensity relative to the 1002 cm

  band detected for the FF peptide. Nevertheless, they are distinct and occur at the same frequency as in the spectrum of the graphene suspension. The pronounced intensities of the FF modes arise from the resonance enhancement of that species at 229 nm.  

Figure 5: The UVRR spectra of the (a) FFâgraphene nanotubes, (b) graphene suspension, and (c) FF nanotubes obtained at Î»exc = 228.8 nm. Apart from the FF vibrational modes, the graphitic modes (1691 cm-1 and 1736 cm-1) can also be observed in the spectrum of FFâgraphene nanotubes.			

When using an excitation wavelength of ~262 nm, we obtained spectra of the graphene suspension and the FF–graphene assemblies (Figure 6). At this wavelength, fluorescence from the FF peptide dominates the signal from the FF nanotubes, preventing us from collecting a UVRR spectrum with sufficient signal to discern the vibrational bands. Interestingly, the fluorescence does not obscure the signal in the FF–graphene nanotubes; however, in both spectra (FF–graphene nanotubes and graphene suspension) only two relatively sharp modes associated with graphene are observed at 1477 and 1516 cm

. This demonstrates the selectivity of the UV excitation in enhancing the graphitic modes. The G modes observed with the 262-nm excitation are shifted to lower frequency relative to what was observed with 229-nm excitation and suggests that the functionalized graphene suspensions exhibit vibrational modes whose frequencies are dependent on the excitation wavelength.  

Figure 6: The UVRR spectrum of the (a) FFâgraphene nanotubes and (b) graphene suspension obtained at Î»exc = 262 nm showing the presence of G band splitting at 1477 cm-1 and 1516 cm-1.			

In this study, we show the utility of UVRR spectroscopy for characterizing FF–graphene assemblies and demonstrate that the components can be selectively investigated using different excitation wavelengths. The presence of nanotubes was verified visually using SEM and spectroscopically with CD spectroscopy. We further verified that these structures are unique to the FF-graphene mixtures as no nanotubes were observed in either the Ala-Ala-graphene mixture or in the mixture of FF peptides in HFIP (Figures 1e and 1f). We find that an excitation wavelength of 210 nm mainly yields features from the FF peptides (Figure 4), and longer wavelengths selectively (229 and 262 nm) enhance the graphene moiety. Both components are observed with an excitation of 229 nm and this might be the preferred wavelength if only one excitation line is available.  

In the UVRR spectra obtained with excitation wavelengths of 229 and 262 nm (Figures 5 and 6), we mainly detect the graphitic G mode, consistent with previous UV Raman spectra of graphitic materials (32,33). The graphitic modes observed in our samples are higher in frequency compared to the typical graphitic peak at ~1600 cm

  (21). Vibrational modes in the high frequency region, above 1600 cm

  sites (21,22,34) and can vary greatly with the sp

  character (20–22,31). In materials containing sp

  chains, typical of diamond-like carbons (DLCs), the G peak occurs at frequencies greater than 1600 cm

  with 229 nm excitation, similar to what is observed in this study (31,34). The presence of distinct and intense vibrational modes in this high-frequency region that are dispersive and the absence of graphene modes around 1060 cm

  content of the graphene samples. The signal-to-noise ratio was not sufficient to observe the broad D band. Thus, UVRR spectroscopy can effectively characterize the nature of the graphene in these suspensions. 

The frequency of the G mode can be affected by the addition of substituents, functionalization, and the number of layers making up the graphene sheets (21,22,32,35,36). Inclusion of disorder in nanocrystalline graphite decreases the frequency of the G peak from 1600 cm

. Large shifts in the graphitic modes with variations in excitation energy, as seen in this study, are indicative of disorder, with the degree of dispersion related to the amount of disorder. Thus, the UVRR data collected using different excitation wavelengths also provides information on the relative order of these materials. 

Tangential G band splitting has been noted for single-walled nanotubes because of their curvature (23,37). Such splitting leads to the observance of two very sharp bands of almost equal intensities, separated by 26–56 cm

  (37). The sharp bands noted in the UV Raman spectra of our graphene suspension (Figures 5 and 6) are separated by 45 cm

  at 262 nm. The splitting observed suggests that the graphene flakes have some curvature and are not unilamellar graphene sheets. The presence of split graphitic modes in the peptide–graphene assembly further supports the finding that the splitting is curvature-induced. Interestingly, the frequency of the bands remains constant upon formation of the nanotubes, but the ratio of the intensities changes.  

The present study demonstrates the utility of deep UVRR spectroscopy for the study and characterization of hybrid biomolecule–graphene nanotubular structures. In particular, we show that selective resonance enhancement of the components is achieved through variation of the laser excitation energy. This behavior could be useful in studying the properties of the individual components during assembly. Further applications of deep UVRR spectroscopy could be accomplished by extending such work to amyloidogenic peptides and their assemblies with graphene-based materials. 

We would like to thank Jeff Gilarde of Wesleyan University for his assistance with the SEM, the National Science Foundation for funding (MCB-0843656), and Wesleyan University for research support. 

(5) G. Eda, G. Fanchini, and M. Chhowalla, 

(6) C. Gomez-Navarro, M. Burghard, and K. Kern, 

UVRR spectroscopy can be used to characterize nanotubes formed with diphenylalanine peptides and graphene by tuning the excitation wavelengths to match the electronic transitions of the individual components.

UV Resonance Raman Characterization of Diphenylalanine–Graphene Nanotubes

When an application is referred to as commercial off the shelf (COTS) software, what does this really mean? Do you appreciate what you are buying and can you manage the risks involved? Here, we look at how the term COTS can be used and abused. 

Have you read the marketing literature of some companies selling laboratory software for spectrometers, electronic laboratory notebooks (ELN), and laboratory information management systems (LIMS)? Delve into the detail and the chances are that you will see the term "COTS" used in several places to justify that you buy the application. However, the chances are even higher that when you do, the term COTS will not be defined. The assumption being that you, dear reader, are a sophisticated, intelligent, erudite individual for whom the definition of this term is self evident and it is not worth the writer wasting brochure space to undertake such a lowly task. In reality, are you being taken for a ride? 

The problem is that the term COTS is commonly used but there is no commonly accepted definition of what this really encompasses, certainly not when you read marketing literature. So, for the uninformed COTS stands for commercial off the shelf. We will start our discussion with the debate of do you make or buy software? 

Let us start from the beginning with a simple question: Are you going to write your own software application for controlling a spectrometer and also acquiring and manipulating the data? Of course you won't. You'll purchase the instrument together with the controlling application as a complete package. One advantage is that the development, support, and enhancement costs of the software will be spread across the whole user base and it's a lot easier than doing it yourself. This means that some of the risk around the software is removed from the project. In addition, rather than having to specify and wait for the software to be written and tested and then rewritten and retested; you can start the roll-out process much sooner after being trained on the application. Ideally, this should give you the confidence that the application will do what it is supposed to do.  

Today, there is little justification for writing your own software for use in an analytical laboratory unless there is nothing on the market that meets your specific needs and it is cost-justified to do so. If the case for a custom solution arises, it may be resolved by changing the way you work and using a more robust commercial solution. However, this topic is not the subject of today's column, which focuses on commercial software and the term COTS. 

Figure 1: Options for the modification and use of commercial software. 			

Therefore, the first stage of the process is the decision to have a custom solution or a commercial one as we can see from the first part of Figure 1. Hence the rationale for the "C" in COTS is "commercial". This is the easy part of the discussion, but now we have to consider what is meant by "off the shelf" or the "OTS" in COTS. 

What does the phrase "off the shelf" mean to you? Taken literally, this is the purchase of an item — for instance let's say food in a supermarket or clothing in a retail outlet — that can be eaten or worn immediately. It is something that can be used as is with no modification.   

So let us look at some dictionary definitions for "off the shelf":									

Available from merchandise in stock; not custom-made (American Heritage Dictionary).

Made in standard sizes and available from merchandise in stock; (especially of clothing) for example, "a ready-made jacket"; "ready-to-wear clothes" (

In the world outside the laboratory, therefore, "off the shelf" is something that can be used as is, eaten, or worn straight way without any changes.  

However, what is the situation with software? 					

A look at how the term commercial off-the-shelf can be abused in marketing literature.

Spectroscopy-11-01-2012

High-Throughput Soil Analysis Using Inductively Coupled Plasma-Optical Emission Spectrometry

More Ways to Make Ions

Products

Band-fitting Raman Spectra to Extract Chemical and Physical Information

UV Resonance Raman Characterization of Diphenylalanine–Graphene Nanotubes

Software Out of the Box?

Departments: Market Profile: Laboratory and Portable IR and NIR in Environmental Analyses

Vol 27 No 11 Spectroscopy November 2012 Regular Issue PDF