This work demonstrates a new analytical technique and its quantification capabilities on a set of disparate metal samples. The laser ablation laser ionization time-of-flight mass spectrometer (LALI-TOF-MS) combines a dual-laser ionization system with a TOF mass analyzer for rapid, high-sensitivity elemental characterization of any solid material. To demonstrate the instrument’s quantification capabilities, nine different reference materials were analyzed. One solid and one powder reference material were then treated as “unknowns,” and quantified using calibration curves generated from the remaining reference materials. Despite being generated from reference materials of various matrices, elemental calibration curves are linear with an average 

 value of 0.96, even for elements that span several orders of magnitude in concentration range. For all elements quantified, results match the certified values of the “unknown” within the margins of error.

For most techniques for solid sample analysis, matrix-matched reference materials are a requirement for reliable quantification. Widely known and accepted among the analytical community, this limitation means metal-testing laboratories need to have a large inventory of solid reference materials. If solid reference materials are not available, quantification requires more complicated dissolution (digestion) sample preparation procedures. For developers of new metal alloys, such as those in the additive manufacturing industry, this dependence on matrix-matched reference materials presents a significant challenge. Additive manufacturing, specifically three-dimensional (3D) metal printing, typically involves transforming feedstock metal powders into finished parts. Compared to traditional manufacturing, this process has some significant advantages, and it is being widely adopted across a variety of industries. As a result, new materials are being developed to ensure desirable material properties throughout the printing process. It may prove difficult for traditional techniques to precisely quantify such novel, complex alloy mixtures with elemental compositions differing from those of established reference materials. Additionally, testing elemental constituents before and after the build requires consistent measurements across both a powder and solid matrix.

Traditional techniques, such as inductively coupled plasma–optical emission spectroscopy (ICP-OES) or ICP–mass spectrometry (ICP-MS), typically require acid digestion for the most accurate elemental analyses, which require chemistry expertise to properly execute, correct for signal interferences, and perform calibrations. Because these plasma-ionizing techniques can create high degrees of elemental suppression, spectral interferences, and matrix effects, accurate quantification depends on matrix-matched reference materials. Additionally, ICP-OES and ICP-MS are not easily capable of measuring carbon or nitrogen, especially when acid digestion is performed. To access high performance with less complicated sample preparation techniques, some users combine ICP-MS with laser ablation (LA) to form the LA-ICP-MS technique. Because of the complexity of each part in the combined LA-ICP-MS system and the lack of continuity between different configurations and vendor combinations, there are still numerous challenges in standardization, automation, and data collection and processing. Currently, LA-based techniques require complex and offline data processing because the LA and the ICP-MS systems are not well integrated, and the data are not easily handled in conventional ICP-MS software. Furthermore, LA-ICP-MS as a technique experiences both transport elemental fractionation and elemental suppression from space-charge effects in ion sampling (1).

Other well-known techniques for analyzing solid materials, such as X-ray fluorescence (XRF), also do not excel at light element determinations, particularly for carbon, nitrogen, and oxygen. These important light elements play a critical role in the manufacture of steel materials because their concentrations affect various physical properties, including brittleness, hardness, ductility, and the melting point (2). Therefore, a technique capable of quantifying the metallic, trace, and low-mass constituents in the same analytical session has the potential to accelerate the quality control (QC) process for additive manufacturing powders.

Providing versatility, high-throughput, excellent elemental coverage, and low detection limits, laser ablation laser ionization time-of-flight MS (LALI-TOF-MS) has the capacity to meet the growing analytical needs of the additive manufacturing industry, as well as the needs of traditional materials analyses. For both solids and powders, the innovative LALI method reduces matrix effects and enables quantification even in the absence of matrix-matched reference materials that are exact. Although LALI was discussed in peer-reviewed literature decades ago (3), technological limitations prevented its commercial development. Capitalizing on modern advances in solid-state lasers and computing, a new LALI-TOF-MS instrument was developed. For any solid material, this innovation provides high-throughput, high-sensitivity quantification of nearly the entire periodic table (1).

As shown in Figure 1, the LALI system uses two lasers. The first laser ablates, or releases, material from the surface of the solid sample and the second laser ionizes that ablated material in a discrete step. Directly analyzing solid materials minimizes the sample preparation procedures required by other high-sensitivity techniques. The ablation process creates both a temporal plasma and a neutral particle cloud. Targeting the neutral particles, the second laser fires after a short delay to allow the primary ions from the initial plasma to disperse. Compared to the primary ablation ions, which experience a high degree of matrix-dependent elemental fractionation, the neutral particles are more representative of the constituents of the sample. Creating ions from these particles results in greater stoichiometric accuracy and reduces matrix effects.

After ionization, the ions move through a series of ion optics to the TOF mass analyzer, which measures the difference in time required for ions of different masses to impact a detector. As shown in Figure 2, this results in a full mass spectrum. This entire process is performed under vacuum, greatly improving ion transmission efficiency compared to LA-ICP-MS, which involves an atmospheric-to-vacuum transition. In addition, this system does not require an inert gas, which facilitates the analysis of a wide range of elements without the need to account for interference from the gas composition (the argon gas used with ICP).

Figure 2 shows an example mass spectrum from analyzing a stainless-steel reference material, IARM Fe316L-18. The zoomed inset for the mass range 

 between 10–16 highlights the trace low-mass elements that are difficult for many techniques to quantify, which are boron, carbon, nitrogen, and oxygen. Note the abundance of these isotopes are three to four orders of magnitude smaller than that of the matrix isotope, 

Fe. For boron, with two naturally occurring isotopes, the text boxes compare its theoretical (known) isotope ratios with those quantified from the peak areas of the mass spectrum. The experimentally derived isotope ratios are within 3% of the known values, demonstrating how LALI-TOF-MS results in mass spectra with isotopically correct peak intensities. Compared to other MS techniques, LALI-TOF-MS allows for more reliable (and automated) isotopic verification and quantification.

To test the quantification capabilities of the technique, nine certified reference materials (CRMs) were analyzed: three solid stainless-steel disks, two solid steel alloys, and four pellets pressed from additive manufacturing powders. Of the four powder CRMs, one pellet was pressed from pure stainless-steel powder (IARM Fe316LP-18) and three pellets were pressed from mixtures of the stainless-steel powder doped with various amounts of nickel alloy powder (IARM Ni718P-18), ranging from 0.6–14% by weight. Table I presents details of these reference materials.

LALI-TOF-MS directly analyzes CRMs 1–5 without any sample preparation. Preparing samples from CRMs 6–9 involves pressing the powders into 1.3-cm (0.5-in) solid pellets using a pellet die set and hydraulic press. Figures 3a–c demonstrate the pellet die set and simple sample preparation procedure. Once prepared, each sample is analyzed using three 0.2 mm

 areas, which are rastered twice. The first pass is to remove any surface contaminants, and the second pass is used for quantification.

Figure 3d shows an example pellet sample after LALI-TOF-MS analysis. The three lines on the pellet’s surface demonstrate the raster areas of the quasi-nondestructive process. The sample tray of the instrument can accommodate nine 1.3-cm (0.5-in) samples. After loading the sample tray, the user can set up the instrument to analyze all nine samples within the same session. Once the instrument has brought the sample chamber to vacuum, typically achieved while the user is defining testing conditions, the analysis requires only 3 min per sample. Testing the quantification capabilities of the new technique involves treating one CRM as an “unknown” and quantifying its major and trace elemental constituents with the calibration curves made from the remaining CRMs. To assess quantification on both solid and powder materials, this work presents results from using both the solid and powder forms of IARM Fe316L-18 (CRM #3 and #6) as the unknowns.

As discussed, LALI-TOF-MS generates mass spectra for each laser shot, which are combined, averaged, and baseline subtracted. The instrument’s software can then detect each element by its naturally occurring isotopic pattern, as shown in Figure 2. For each isotopically verified element, the software integrates the mass spectra peak area and normalizes its intensity to that of a major matrix element, which is iron in this case. Plotting the normalized intensities and the known concentrations of the CRMs creates a calibration curve for each element. If an element’s calibration curve has a strong correlation coefficient and sufficient data points, it can be used to quantify an unknown sample’s concentration.

Figure 4 shows example calibration curves of four elements using the isotopes: 

-axis is concentration (wt.%). Displayed in orange, the CRM treated as the “unknown” is quantified using the best-fit line through the known CRMs, each of which are indicated by distinct shapes (as listed in Table I). Despite using reference materials of different matrices, calibration curves are relatively linear, with an average 

 value of 0.96, even for elements that span several orders of magnitude in concentration range. For instance, the calibration curve of nickel includes concentrations ranging from 0.23% for CRM #5 to 19.4% for CRM #7 and has an 

The bar graphs in Figure 5 and Figure 6 compare quantified results to certified values for the 316L stainless-steel disk (CRM #3) and the 316L stainless-steel powder (CRM #6), respectively. Using the solid disk as an “unknown,” it was quantified with calibration curves generated from all remaining CRMs. Alternatively, the powder was quantified from calibration curves created from the doped powder mixtures (CRMs #7–9) only. In each graph, certified values are gray and those quantified by LALI-TOF-MS are blue. Concentrations of major elements are presented in weight percent (wt.%) and those of trace elements are in parts-per-million (ppm). On the known values, the error bars indicate the certified uncertainties. Uncertainties for the quantified values are calculated to a 95% confidence interval using least squares linear regression of the calibration curves’ points and those unknown (all measured in triplicate). Note these expanded uncertainty values include a combination of sampling, measurement, and calibration uncertainty.

The average uncertainty and the average deviation from the known results are slightly larger for the solid disk analysis than the pressed powder, which is expected because the solid disk was quantified using all of the calibration points, while the powder was quantified by standard addition, which resulted in more linear calibration curves that span a narrower concentration range. Nevertheless, both techniques were successful, and results from both “unknowns” match the certified values within the certificate margins of error.

Results demonstrate the quantitative capabilities of LALI-TOF-MS for both solid metal and powder elemental characterization. Both the 316L stainless-steel solid disk and the stainless-steel powder reference materials’ elemental constituents were quantified within the certified values’ margins of error. For quantified elements, the average internal precision for the solid disk is 0.5% and 1.1% for the powder. For the solid reference material, quantified results’ accuracy for major elements are 4% on average, and all major elements are within 10% of the certified values. The 316L stainless-steel powder’s results for major elements also have an average accuracy of 4%, and all major elements quantified in the powder are within 13% of certified values.

For many major elements, ASTM specifications for stainless steels include an acceptable concentration range of ±0.5 to ±2.0 wt.%, depending on the element (4). With LALI-TOF-MS, all major elements were quantified within 0.02–0.21 wt.% of certified values, and uncertainties calculated with a 95% confidence interval were all less than ±0.18 wt.%. The precision and accuracy of these results indicate that LALI-TOF-MS exceeds the precision and accuracy required to meet the needs of the additive manufacturing industry. Typical powder material data sheets specify only an upper limit for trace elements’ concentrations like carbon and nitrogen (4), which LALI-TOF-MS also verified.

In addition to bulk characterization, LALI-TOF-MS can be used for elemental mapping of powder or solid materials. Each map displays the spatial distribution of any element of interest at the resolution of the spot size of the ablation laser. Depending on the application, the user may adjust the laser spot size between 1–200 μm. For additive manufacturing, this capability can identify chemical heterogeneity in the powders or printed parts. Beyond additive manufacturing applications, elemental mapping can also be impactful in failure analysis or diagnosing corrosion.

This work validates LALI-TOF-MS as a promising new and alternative technique for quantifying elemental constituents of metal disks and powders. For all major and trace elements, quantified results match those of certified results within margins of error. Using a disparate set of metal reference materials to generate linear calibration curves demonstrates LALI-TOF-MS does not require exact matrix-matching of reference materials with samples. LALI-TOF-MS is an attractive solution for metals testing, specifically additive manufacturing. Because it can quantify low-mass elements, trace elements, and metallic constituents in the same analytical session, it can directly analyze solid materials and pelletized powders without complicated sample preparation procedures, and it does not depend on matrix-matched reference materials for reliable quantification, which can support new material development. LALI-TOF-MS offers an answer to the analytical needs for new materials being rapidly developed. This exciting, new technique provides a simple, compact, and cost-effective alternative to traditional analytical methods for these types of metallic matrices and a wide range of other solid samples.

This work was performed under the following financial assistance award 70NANB21H066 from US Department of Commerce, National Institute of Standards and Technology.

(2) Powder Metallurgy: Elemental Analysis of Metal Powders and Metal Parts Produced by Additive Manufacturing - Knowledge Base - Applications, https://www.eltra.com/applications-elemental-analysis/knowledge-base/powder-metallurgy-elemental-analysis-of-metal-powders-and-metal-parts/ (accessed Jan 31, 2022). 

(8), 619–626 (1995). https://doi.org/10.1016/1044-0305(95)00262-C.

(4) EOS StainlessSteel 316L Material Data Sheet, https://www. eos.info/03_system-related-assets/material-related-contents/ metal-materials-and-examples/metal-material-datasheet/ stainlesssteel/material_data-sheet_eos_stainlesssteel_316l_ en_web.pdf (accessed Jan 31, 2022).

Articles

Column: Atomic Perspectives

Laser ablation laser ionization time-of-flight mass spectrometry (LALI-TOF-MS) can quantify elemental constituents without the need for matrix-matching, making it attractive for metals testing, particularly for additive manufacturing.

Using an Innovative Mass Spectrometer and Non-Matrix–Matched Reference Materials to Quantify Composition of Metal Disks and Powders

As we begin our survey of the infrared (IR) spectra of polymers containing C–O bonds, we discuss epoxies, perhaps the most economically important functional group in this category. Epoxy resins are widely used as adhesives, and you may have used them yourself to mend broken household items. In this column, the spectra of epoxides and the reaction via which they become useful is examined. The answer to last column’s Infrared Spectral Interpretation workshop will also be given.

As you probably noticed, the organization of this column series has been divided into sections based on specific chemical bonds. In the first five or so years of this column, there were multiple columns devoted to functional groups containing C-H, C-O, and C=O bonds. Now that we are five columns into our examination of polymer spectra, you may have noticed that these articles are structured similarly. The last four installments were devoted to polymers that contain C-H bonds. Here, we begin a series on polymers containing C-O bonds, and after that, we will discuss polymers with C=O bonds.

Compared to the polymer families containing C-H and C=O bonds, the family of C-O containing polymers is small for reasons I do not understand. Probably the most important polymers in this group are epoxies and epoxy resins, which are widely used as adhesives.

Epoxy resins are used so commonly that the word “epoxy” has entered the English language as a word that refers to a large group of glues and adhesives. We bandy about this word a lot, but what is an epoxy anyway? An 

 is a molecule that contains an epoxy ring, which is a three-membered ring containing two carbons and one oxygen atom (1). The structure of the simplest epoxide, ethylene oxide, is seen in Figure 1.

We know that carbon prefers to form single bonds with bond angles of approximately 109.5° (1). The bond angles in an epoxy ring are less than optimal, creating what is called ring strain, which means these rings are unstable and undergo ring opening reactions easily. Epoxides are monomers that react via ring opening reactions to form the sticky stuff we are familiar with.

Figure 1 shows that an epoxy ring contains two C-O single bonds. We have learned previously when we studied the spectra of alcohols and ethers that C-O stretching vibrations have strong peaks from 1300 to 1000 cm

 (going forward all peak positions will be in cm

 even if not noted) (2). However, epoxies are the first ring systems we have studied that have C-O bonds in them, and they follow our 1300–1000 rule. Figure 2 shows three stretching vibrations for the epoxide ring.

The S in Figure 2 means a bond stretches during that vibration, and a C means a bond contracts during a vibration. The left most vibration illustrated in Figure 2 is called the epoxide symmetric ring breathing vibration. As you can see, all three bonds in the ring stretch and contract in phase with each other, as though the ring were exhaling and inhaling. The peak for this vibration falls from 1280–1230, in the range where we normally see C-O stretching vibrations. The vibration illustrated in the center of Figure 2 is called the asymmetric C-O-C stretch, where one C-O bond stretches and the other contracts, similar to the asymmetric C-O-C stretch of ethers (3). The peak from the epoxide asymmetric C-O-C stretch appears from 950–810. The third vibration illustrated in Figure 2 is the symmetric C-O-C stretch, where the two C-O bonds stretch while the C-C bond contracts. The peak from this vibration is found from 880–750. The spectrum of an epoxide is seen in Figure 3.

Peak A at 1261 is the symmetric ring breathing vibration. Note that this falls in the range where C-O stretching peaks traditionally fall. Peak B at 904 is the asymmetric C-O-C stretch, and peak C at 831 is the symmetric C-O-C stretch. Note how intense peaks B and C are, and that they fall at a relatively low wavenumber. Because the ring opening reaction of epoxides is part of how epoxy resins are made, monitoring the size of any of peaks A, B, or C can be used to determine the extent of cure of an epoxy resin.

When epoxy resins are made, they are typically reacted with a diamine to form a three-dimensional (3D) polymer network (Figure 4). A diamine is a molecule with two amine groups in it. If you have ever worked with epoxy resins, this is why they can be pretty smelly. We have already studied the spectra of amines (4,5).

The epoxy ring reacts with the amine in a ring opening reaction that gives a 3D polymer network as illustrated in Figure 4. I would like to show you what the spectrum of this material looks like, but these materials are intractable and hard to analyze. For example, one could place an epoxide and diamine on an attenuated total reflectance (ATR) crystal and follow the course of the reaction that way (6). Once the reaction is over, the epoxy resin sticks to the crystal and cannot be removed, which means an ATR crystal is sacrificed.

Epoxides are molecules that contain a three-membered ring containing two oxygen atoms and one carbon atom. Their spectra exhibit a series of three peaks from the stretching and contracting of the bonds in this ring that fall from 1280–1230, 950–810, and 880–750. The last two of these are particularly intense. The size of these peaks can be used to follow the curing of an epoxy resin.

Fundamentals of Fourier Transform Infrared Spectroscopy 

(CRC Press, Boca Raton, FL, 2nd Ed., 2011). 

Column: IR Spectral Interpretation Workshop

Epoxies are perhaps the most economically important functional group of polymers. We explain how to interpret their spectra.

The Infrared Spectra of Polymers V: Epoxies

What can spectroscopic techniques, such as portable X-ray fluorescence spectrometry (PXRF), reveal about the sarsen megaliths of Stonehenge and where they originated? David Nash, a professor of physical geography at the University of Brighton in Brighton, United Kingdom, is exploring this question. We recently spoke with Professor Nash about his team’s discovery and what it means for the future of archaeology.

Stonehenge is a prehistoric monument that is considered a British cultural icon and one of the most famous landmarks in Europe. The origin of the sarsen megaliths that comprise Stonehenge have interested archaeologists for decades. What can spectroscopic techniques, such as portable X-ray fluorescence spectrometry (PXRF), reveal about the sarsen megaliths and where they originated? David Nash, a professor of physical geography at the University of Brighton in Brighton, United Kingdom, is exploring this question. We recently spoke with Professor Nash about his team’s discovery and what it means for the future of archaeology.

The major conclusion that was drawn from your research is that the sarsen megaliths that form the primary architecture of Stonehenge most likely originated from the West Woods, Wiltshire, approximately 25 km north of the Stonehenge site (1). How did your team arrive at this inference and how certain are you of this result?

We arrived at the inference that West Woods was the likely source for the Stonehenge megaliths in our 

 via two stages of investigation (1). First, we analyzed all the remaining 52 sarsen stones at Stonehenge using PXRF. Statistical analysis of the resulting data set showed that most of the stones share a consistent chemistry—therefore, they can be considered to come from the same source area. Only two stones were different. The second stage of the research involved comparing higher resolution inductively coupled plasma–mass spectrometry (ICP-MS) data from one sarsen stone at the monument (Stone 58) with equivalent data for sarsen stones from 20 areas across the southern United Kingdom. Stone 58 falls in the centre of the statistical cluster from our PXRF analysis and can therefore be considered chemically representative of the sarsens at Stonehenge. The comparison of ICP-MS data for Stone 58 showed a direct match with the chemistry of sarsen stones in West Wood, and with these samples only. We can be 100% confident of the chemical match between Stone 58 and West Woods—all immobile trace elements that we compared overlapped within instrumental uncertainty. We cannot yet, however, state with certainty the precise area of West Woods from which the stones were sourced.

In your study, your team used PXRF to provide an initial chemical characterization of the sarsen uprights and lintel stones. Why was PXRF the best technique to use for this analysis as compared to other field or laboratory methods?

Stonehenge is a highly protected site, and it is not possible to sample stone from the monument today. Therefore, we had to use a portable technique to ascertain the chemical variability at the monument. Personally, I would not use a technique such as PXRF to compare the chemistry of sarsen stones at Stonehenge and those in other areas. However, PXRF works well for intercomparison of stones at Stonehenge because we know that the stones were erected at roughly the same time and have been exposed to the same degree of natural weathering over the last 4500 years.

Numerous studies in the past have explored plausible explanations for where the stones that comprise Stonehenge came from. What did you do in this study that is unique from what other researchers have done?

Previous studies that have sought to identify where the sarsen stones at Stonehenge came from have been largely speculative. Archaeological studies, for example, have tried to identify hollows that could be quarry sites. Our research was the first ever to utilize chemical data to provenance the stones. This kind of work is widespread in other branches of archaeology, particularly those concerned with the analysis of stone tools, but had never been applied in the context of the British Neolithic.

Your research provided an in-depth characterization of the sedimentology, mineralogy, and geochemistry of a known sarsen megalith at Stonehenge (2). What challenges did you face in using ICP-MS and ICP–atomic emission spectrometry (AES) to generate precise whole-rock geochemical data?

 studies make use of ICP-MS analyses of immobile trace element data. The only real issue was obtaining a reliable sample size from Stonehenge. We were given permission to sample a core that had been drilled from Stone 58 as part of restoration work at the monument in the 1950s. Our sample was approximately 7 cm long, and we needed to be able to capture material for ICP-MS, ICP-AES, and isotope analyses and to prepare geological thin sections.

You and your team used a various number of analytical techniques besides PXRF, ICP-MS, and ICP-AES, including X-ray computed tomography (CT) imaging and high-resolution scanning electron microscopy (SEM) with cathodoluminescence (CL) and energy-dispersive (EDS), and automated SEM-EDS mineral analysis (QEMSCAN). Why were so many techniques used and what data were most valuable to infer origin of the samples?

Our 2021 study provides the first detailed characterization of the petrography, mineralogy, and geochemistry of a sarsen at Stonehenge. Given that the core from Stone 58 was of national and international importance, we wanted to make sure that we applied every state-of-the-art analytical technique to it as possible. We had already published the geochemical data linking the Stonehenge sarsens to West Woods. However, the use of other techniques allowed us to obtain much more detail about the stone. For example, CT imaging allowed us to explore the sedimentary structure of the rock, and thin section analysis enabled us to investigate the distribution of different types of minerals and quartz cements within the stone. We also conducted cathodoluminescence analysis under an SEM to explore the different phases of quartz cement development within the rock. This analysis led to one of the most interesting sets of results from the study in my opinion because it showed that the quartz cements had developed over at least 16 cycles of precipitation. Finally, we used isotope analyses to identify the potential sources of the mineral grains within the stone. The legacy of using this battery of different techniques is that we now have a suite of data that we can use, in addition to geochemical analysis, to refine the potential source areas for the sarsen stones.

Are there still further mysteries surrounding Stonehenge that your team is interested in exploring in a future study?

There is still a lot of work to be done. Most obviously, we would like to refine the source area for the sarsen stones and see if we can identify where the two “unknown” stones originated.

What are your next steps in this work? How have your findings impacted archaeological and geographical research going forward?

The main impact of our research is finally putting a dot on the map for the main source of sarsens at Stonehenge. This now allows us to draw more informed inferences about the routes that the stones took on their way to Stonehenge. Before the publication of our results in 2020, all proposed route maps were purely supposition. Now we have a starting point for the journey of the stones. We also have a geochemical technique that we can apply to other monuments made of sarsen within the wider Stonehenge landscape. It would be fascinating to see if the people who constructed the sarsen circle and avenue at Avebury, for example, obtained their stone from the same areas as the Neolithic peoples who built Stonehenge.

(1) D.J. Nash, T.J.R. Ciborowski, J.S. Ullyott, M.P. Pearson, T. Darvill, S. Greaney, G. Maniatis, and K.A. Whitaker, 

(2) D.J. Nash, T.J.R. Ciborowski, T. Darvill, M.P. Pearson, J.S. Ullyott, M. Damaschke, J.A. Evans, S. Goderis, S. Greaney, J.M. Huggett, R.A. Ixer, D. Pirrie, M.R. Power, T. Saige, and N. Wilkinson, 

Spectroscopy Spotlight

What can spectroscopic techniques, such as portable X-ray fluorescence spectrometry (PXRF), reveal about the sarsen megaliths of Stonehenge and where they originated? 

Using Portable X-ray Fluorescence Spectrometry (PXRF) to Explore the Origins of the Sarsen Megaliths at Stonehenge

, we regularly discuss the chemistry and physics of measurements made on a variety of sample types using many spectroscopic techniques. Only occasionally have we covered what’s inside the instruments we use for making our measurements. Many critical components and procedures are required to build and manufacture safe and effective high-performance instrumentation, including energy sources, lasers, detectors, optics, and electronics, as well as the design and safety and performance testing of those parts. In this four-part article, we survey various aspects and component parts of spectroscopy instrumentation to provide a basic “under the hood” look at those instruments we spectroscopists are sometimes all too familiar with or even complacent about—often referring to instrument research, design, engineering, manufacturing, and quality testing teams simply as “vendors.” In today’s fast-paced instrument manufacturing facilities, there is a lot of research and engineering going on that covers a broad range of scientific endeavors, all the way from ideation to shipping. This four-part series follows on from 

The Spectroscopy Instrument Components Terminology Guide

, published in February, which you can download for use as a reference. We are also planning future tutorial articles, so look out for those.

In this part 1 of a four-part spectroscopy components survey article series, we take a closer look at two main topics, covered in Tables I and II, with each table containing four columns of information—the component name, a text description, basic specifications, and references and links (1–8). Table I describes electronic and vibrational spectroscopy sources and lasers, addressing the topics of lasers, light-emitting diodes (LEDs), broadband-light sources, infrared (IR) light sources, emission lamps, and special sources. Table II surveys vibrational spectroscopy detectors, such as infrared (IR), Raman, charge-coupled devices (CCDs), near-infrared (NIR), visible (vis) detectors, and ultraviolet (UV) detectors.

Part 2 of this series will include Table III, listing a variety of aspects associated with electronic and vibrational spectroscopy optics, including IR, Raman, near-infrared (NIR) optics, UV optics, visible optics, CCDs, monochromators, interferometers, diode arrays, digital light processing (DLP) optics, microscopes, and hyperspectral imaging (HSI) systems. Optical filters (high-pass, low-pass, interference, acousto-optic tunable filters [AOTF], tilting, broadband, narrowband, neutral density, custom, and so forth) is a rather large subject and is beyond the scope of this article series (the 

Spectroscopy Instrument Components Terminology Guide

 covers the general terms related to filters [1], and we note that the subject of optical filters would be an excellent topic for a future article).

Part 3 of this component series lists Table IV and includes the main special components and terms used in atomic spectroscopy instrumentation for inductively coupled plasma–optical emission spectroscopy (ICP-OES), ICP–mass spectrometry (ICP-MS), X-ray fluorescence (XRF), energy-dispersive X-ray spectroscopy (EDX), total-reflection XRF (TXRF), and laser-induced breakdown spectroscopy (LIBS).

Part 4 of the series includes Tables V–VIII, with Table V covering spectroscopy electronics, including printed circuit board (PCB) design and manufacturing. Table VI describes spectroscopy design services, specifically outsourced instrument design and manufacturing. Table VII summarizes instrument testing services, most notably, electrical safety testing, electromagnetic compatibility (EMC), and electromagnetic interference (EMI) testing. Finally, Table VIII delves into the firmware and software aspects of instrumentation, which include instrument driver and control firmware, instrument function driver software, data transfer and user interface software, and data analysis software. All components are listed in alphabetical order in each table.

The technology behind spectroscopic instrument energy sources, lasers, and detectors is advancing rapidly due to materials and electronics advances. However, for new technology to be used for routine instrumentation, it must meet multiple criteria, including predictable performance, reliability, cost requirements, availability, compatibility, and safety. These and other criteria generally require several years of experience with new technologies to effectively incorporate them into reliable instrumentation.

The Spectroscopy Instrument Components Terminology Guide 2022

, posted February 14, 2022 at https://www.spectroscopyonline.com 

The Concise Handbook of Analytical Spectroscopy: Physical Foundations, Techniques, Instrumentation and Data Analysis, in five volumes, first edition, UV, Vis, NIR, IR, and Raman

 (World Scientific Publishing-Imperial College Press, New Jersey and Singapore, 2016). ISBN-13: 978-9814508056.

 (John Wiley & Sons, New York, NY, 1st Ed., 2002). ISBN: 978-0-471-98847-2

(4) ASTM (American Society for Testing and Materials) ASTM Volume 03.06, “Molecular Spectroscopy and Separation Science; Surface Analysis” (ASTM International, West Conshohocken, PA, 2017).

(5) N.B. Colthup, L.H. Daly, and S.E. Wiberley, 

Introduction to Infrared and Raman Spectroscopy

 (Academic Press/Elsevier, Boston, MA, 3rd ed., 1990). ISBN: 9780121825546

Introduction to Plasma Spectroscopy (Vol. 56)

 (Springer Science & Business Media, Berlin, Germany, 2000), ISBN-10: 3642022324

Basic Atomic and Molecular Spectroscopy (Vol. 11)

 (Royal Society of Chemistry, Burlington House, United Kingdom, 2002). ISBN-10: 0854046674

(8) J.A. Holcombe, G.M. Hieftje, and V.Majidi (eds), 

Focus on Analytical Spectrometry: A Compendium of Applied Spectroscopy Focal Point Articles

 (1994-1997) (Society for Applied Spectroscopy, Frederick, MD, 1998). ISBN-10: 1891276018

Featured Articles

High-performance instrumentation requires many critical components. We focus here on energy sources, lasers, and detectors.

A Survey of Basic Instrument Components Used in Spectroscopy, Part 1: Sources, Lasers, and Detectors

This past year was a time where many were hoping and dreaming for a new tomorrow—one that would look a lot like the past. A world where masks, social distancing, jabs, and virtual connections to laboratories and conferences could be left to the historical record. Unfortunately, we are still embroiled in these social and economic conundrums. This 2022 

 salary and employment survey takes a look at spectroscopists from around the globe and their impressions, reactions, responses to how their work life unfolded in 2021 and their future outlooks.

In our salary and employment survey, we gather information on average salary trends and report on how these trends compare to previous years, referring all the way back to the survey completed in 2001. But unlike some previous Spectroscopy salary surveys, which focused heavily on the numerical details of the salary data (1,2), these past two years we have looked beyond the numbers to focus more on broader trends of workplace satisfaction and career attitudes. We asked about job security and respondents’ outlook for the future working in this challenging and technically complex field. We inquired about what spectroscopy professionals consider their greatest workplace concerns. We asked how many respondents are searching for new opportunities and why—and we looked at the effects caused by still working in a pandemic-stressed workplace environment. We also asked respondents for their outlook for the remainder of 2022. In sum, we looked into multiple factors of the current and future employment environment.

As we would expect, this year we found that nearly all professionals working in the field of spectroscopy are more concerned than usual about the security of their jobs and incomes, given the pandemic atmosphere. Nevertheless, respondents are optimistic about the coming year. Nearly 52% of respondents reported that their work environment in 2021 was better than in 2020. Nevertheless, four in ten of respondents 44% (35% last year) indicated that they are interested in seeking a new employment opportunity beyond their current situation while an equal number (44%) say they would not want to leave their current position even if a promising new opportunity were presented.

As we all know, the pandemic resulted in dramatic changes in working conditions throughout the world. Since the pandemic was officially declared in March of 2020, nearly one in five, or 19% (15% last year) of respondents were either laid off or furloughed; nearly one quarter, or 26.6% (50.5% last year) have had limited or no access to their laboratories. More alarmingly, 38% (34% last year) report they are still struggling to stay positive during the globally impacting pandemic situation. On a positive note, 38% report that they actually enjoy working from home, and 9% are now actually working full-time and exclusively from home.

Nearly all types and sizes of organizations and their operations have been seriously challenged by the pandemic, as facilities have remained either closed or with somewhat restricted access. As a result, corporate and university classes, meetings, and scientific and business conferences have continued in an online or virtual format—a complex, ever-changing, and often mandated requirement in many situations. According to our respondents, the business downturn caused by the pandemic in 2021 has resulted in nearly 15% (60% last year) of organizations downsizing as a direct result of the pandemic lockdown, with another 11% (25% last year) downsizing for reasons not directly related to the pandemic. It is noteworthy that 4% (10% last year) of respondents say their work functions were offshored during 2021.

In spite of the challenges of the shutdown, 85% (77% last year) of respondents feel they are able to effectively complete their work. And even though half, or 54% (50% last year) of respondents claim an increased workload, two-thirds, or 66% (65% last year) are satisfied with their current working conditions, and 37% (45% last year) say they actually enjoy the continued requirement of working from home. We note that 65% now report being fully back at their office or laboratories. This is a notable inversion of last year, when 59% of respondents reported limited or no access to their offices and laboratories.

Despite the continuous workplace disruptions—or perhaps because of it— our survey results indicate that over half of respondents, or 56% (44% last year) are not interested in seeking a job change. Generally, these respondents want to keep their current positions because of the location of their office and laboratories (16%), or because of their current salary (9%). Other reasons for staying put in current jobs are good work team colleagues (6%), good management (3%), and high competition for job positions (1%). In a vote of job satisfaction, 44% of respondents would not want to leave their current position even if another promising job opportunity were presented. The “great resignation” does not seem to have hit this sector.

On the other hand, four of ten respondents, or 44% (35% last year) would leave their current positions for a new or better opportunity. A full 23% (vs. 26% last year) indicated they were ready for a career change—either major or minor. According to respondents, the main general reasons for seeking new job opportunities are looking for a new challenge (14%) or a higher salary (11%), dissatisfaction with their current employer (4%), workload increases (4%), or job position insecurity (3.5%). Some respondents have expressed that they are seeking new employment for mostly personal reasons. These job trend attitudes are illustrated in Figures 1a–1c.

Of course, thoughts about job change can often be linked to perceptions of both current job security and the perceived strength of the job market. One in seven respondents, or 14% (25% last year) feel their jobs are less secure this year than last year, while one in four, or 25% (24% last year) feel they are more secure. The remaining group (61%) say there has been no change in their job security over the last year. Figure 2 displays the respondent perception of their current job security—which appears to be an essential aspect of long-term job satisfaction.

One significant improvement this year is the overall job market outlook. Two- thirds of survey respondents, or 65% (55% last year) now believe that the current employment market for spectroscopists is either good or excellent, and only 5% (6% last year) think it is poor; the remaining 30% still believe the market to be fair or average. One in three, or 35% (15% last year) assess the job market as one where employers are having to compete for good candidates, while the rest feel that there is either moderate (40% vs. 55% last year) or strong (25% vs. 30% last year) competition from candidates who are pursuing open career positions (Figure 3).

What Factors Are Most Important in a Job?

The vast majority, or 94% (95% last year) of respondents say that salary and bonus structure is the most important factor in their jobs. The survey results indicated that the next most important factors (in rank order) were work–life balance, at 90% (87% last year); the work team, at 89% (88% last year); job security, at 87% (93% last year); a tolerant workplace, at 84% (82% last year); the quality of equipment and laboratory space, at 84% (85% last year); intellectual challenge, at 83% (88% last year), the importance of one’s work, at 83% (87% last year); health insurance (82%), and retirement benefits, at 79% (82% last year). The factors ranking the lowest in importance for job satisfaction were maternity or paternity leave, at 22% (27% last year)—not important to an older demographic—the prestige of the organization, at 39% (39% last year), the ability to work from home, at 40% (48% last year)—not really a competitive factor in the past two years when so many people were working from home— and continued training and education 68% (62% last year).

For 2022, 59% (37% last year) of respondents received raises, so correspondingly 41% did not. This is a positive development; last year only 37% received any pay increase). It was noted that 6% (13% last year) experienced a decrease in pay over this past year (Figure 4). In our 2020 survey (2) we found that 20% of respondents did not receive a raise, but for that year we did not record any salary cuts for full-time professionals.

Our questions about pay scales indicated that one in sixteen, or 6% (5% last year) are very satisfied with their pay and feel their pay is at the high-end of the market value for their jobs. Nearly one-third, or 39% (35% last year) feel they are paid fairly. However, a full 61% (65% last year), still feel that they are paid at the lower end of the scale, including almost one-third (29%) who report they are paid below market value.

For this year’s survey, we recorded salaries between $17,000 and $220,000 USD ($15,000 and $250,000 USD last year). The reported mean and median annual salaries for all respondents were $99,739 and $94,000, respectively, indicating the reported salaries are higher for this year’s group of respondents than those reported over the past few years. We note that there was a larger percentage of managers in this year’s survey, as well as a lesser percentage of students and postdoctoral researchers than in previous years. In fact a full 45% of respondents reported incomes of $100,000 USD or more. Thus, there was reported a 13.3% (1.8% last year) increase in average salary. Table I displays the annual average salary trend since 2001 for all respondents (see also Figure 5). For vacation or paid time off (PTO) use during this past year, we noted that only 44% of respondents used over half of their allotted vacation during 2021. Do our respondents love their jobs too much to take all their vacation time, or are the work pressures too great? We have no answer for that.

Although the reported average salaries were higher this year, the average bonuses disclosed for the 2022 survey were somewhat lower for this year compared to those in recent years. Nearly one-half, or 47% of respondents, reported receiv- ing an annual bonus (the same as last year). The bonus amounts for our 2022 survey ranged from $100 to $52,000. The mean and median bonus values for all respondents receiving bonuses were $9,680 and $5,000 USD ($19,228 and $11,685 last year), respectively, as compared to $14,121 and $11,000, respectively in the 2020 survey report.

New Hire and Job Candidate Skill Set Assessments

This year, we asked respondents several questions regarding the perceived knowledge and skill sets of recent hires. Four percent of respondents felt that new hires had exceptional knowledge and skills; 29% thought they had very good skills; 47% said they had adequate knowledge and skills; and 20% felt they exhibited poor skill sets.

We also asked about the skills sets of the overall pools of candidates available for new hires. Three percent of the candidates in the pool were rated as excellent, 40% were rated as good, 38% as adequate, and 19% as poor. The respondents reported that the skill sets lacking in candidates seeking employment included the major hard skill categories of fundamental or basic science knowledge, laboratory experience, instrumentation troubleshooting and data analysis, materials handling knowledge, problem solving ability, technical computing, and technical writing. Soft skill complaints were for lack of people skills, little patience, poor multitasking capability, limited creativity, low flexibility, unwillingness to travel, inability to work solo, lack of humility, poor project management, and low basic work ethic.

The Question of Discrimination in the Workplace

Of all respondents, 19% feel they have been discriminated against at their place of employment. Thus, 81% reported they are not discriminated against or feel they are not in a group that is likely to be discriminated against. The main issues named for those indicating discrimination, in rank order, were age (9.7%), education level (4.4%), gender (3.5%), nationality (2.6%), race (1.8%), and religion (<1%) or pregnancy leave (<1%). Table II illustrates these results.

The respondents to the survey described how discrimination was outwardly demonstrated in their work situations. In rank order, the results of manifest discrimination included unequal pay for equal work (6%), lack of promotions (4.4%), fewer growth opportunities (4.4%), being passed over for expected raises and bonuses (3.5%), having their opinions ignored (3.5%), and not being hired when interviewed for job (1.8%).

Of all employees, only 7% have ever formally reported or lodged a complaint for discrimination at their place of employment. The reasons given for not filing a formal complaint (in rank order) included the feeling that it would not help the situation (15%); that it was not serious enough (9%); that the respondent had resigned and moved on (9%); or that the respondent was afraid of reprisals from management, including loss of job (7%). Other important factors for not reporting discrimination at work included a sense of shame (2%), and that a lawsuit was too expensive or too problematic (2%). One percent of respondents felt they would not be believed; that they did not know they could formally complain; and that they felt it would jeopardize future opportunities if they complained.

Of those that have gone through a formal complaint process, a range of results were reported. One quarter (25%) of those that formally complained felt that they were treated as the problem and suffered reprisals. Over one-third (38%) reported there was some action was taken, but it was insufficient. One quarter (25%) reported that appropriate action was taken, and the situation had improved. Another 12% reported a different outcome than those reported above.

Of the spectroscopy professionals from around the world that responded to this year’s survey, which was fielded in December 2021 and January 2022, the respondents were 73% male (67% last year) and 27% female (33% last year). Respondents were from industry (55% vs. 59% last year), academic institutions (24% vs. 23% last year), government or nationally funded laboratories (13% vs. 7% last year), the military (0% vs. 2% last year), and from other types of organizations, such as private laboratories, hospitals, and medical facilities (8% vs. 9.4% last year).

The job titles of respondents, in order of occurrence, included principal or senior scientist, at 24% (27% last year), manager, at 22% (14.8% last year), scientist or associate, at 19% (17.6% last year), director, at 12% (7.4% last year), associate or assistant professor, at 4.6% (3.7% last year), technician, at 3.6% (5.6% last year), full professor, at 3.6% (8.3% last year), CEO, CTO, or president at 2.7 % (4.6% last year), laboratory assistant, at 1% (1.9% last year), and other, at 7.3% (8.3% last year). Note that 91% (87% last year) of respondents are full-time employees, while 2% (5% last year) are part-time employees, and nearly 1% (2% last year) are unemployed. Most respondents have a significant number of years of experience with spectroscopic methods: 57.4% have more than 20 years of spectroscopy experience (Table III and Figure 6). As a comparison, the number of years respondents have been with their current organization is shown in Figure 7.

Spectroscopy professionals across all fields working in 2021 through early 2022 have experienced unprecedented challenges and changes during this continued pandemic year. Among our respondents, 6% experienced a pay cut this year—most likely a result of Covid-19 shutdown issues—and 19% were either laid off or furloughed. Almost two-thirds, 65%, report being fully back at their office or laboratories, and 38% (34% last year) say they are struggling to stay positive during this situation. In spite of all that, a full 85% (77% last year) of respondents feel they are able to complete their work despite the unusual challenges of this year, and 37% actually enjoy working from home.

Of course, the ongoing concerns related to any workplace remain, pandemic or not. We found that the greatest workplace concerns of professionals in the spectroscopy field are salary and bonus structure, work–life balance, working colleagues and associates, job security, a tolerant workplace, the quality of equipment and laboratory space, and the job’s intellectual challenge.

Two-thirds, or 66% (65% last year) of spectroscopists reported they are satisfied with their current working conditions—even though 54% of respondents claim an increased workload. And 44% of our respondents indicate they are interested in seeking a better employment op- portunity beyond their current situation.

We noted that over half of respondents, or 59% (37% last year) received raises, while the remaining 41% did not—and 6% (13% last year) experienced a decrease in pay over this past year. Nearly two-thirds (61%) feel that they are either paid at the low end of the scale or are paid below market value. The mean and median annual salaries for the 2022 survey are much higher than those in the recent past, with an increase in those receiving raises and in the average reported salary for this year vs. the past three survey years (2019–2021 [1–3]).

All in all, 2022 will be an economic enigma as we see supply shortages and higher wages with some business sectors suffering and others booming. This past year remained an extremely challenging and confusing year. In spite of it all, professionals working in spectroscopy continue to remain positive, and determined to apply themselves and their skill sets to improve and develop new products, monitor the environment, delve into important health research, and advance the broad world of developmental and analytical chemistry.

Spectroscopists offer their views on the their salaries and working conditions, including how they are faring through the social and economic challenges still gripping the world.

The 2022 Employment and Salary Survey: Looking for a Return to Normalcy

The fingerprint region in mid-infrared (IR) and Raman spectroscopy, typically between 300 to 1900 cm

, is used to characterize molecules by utilizing their vibrational and rotational changes in this region. In this study, a smaller subset of this Raman spectral region was evaluated for its significance in characterizing pharmaceutical products. This narrower region from 1550 to 1900 cm

 in the Raman spectrum will further be defined as the “fingerprint in the fingerprint” region. A spectral evaluation was conducted on active pharmaceutical ingredients (APIs) in prescription drugs, over-the-counter drugs, and pharmaceutical drug products. Qualitative and quantitative analysis was performed on these products to gain an understanding of this spectral region. The qualitative results showed no Raman spectral signals in this region for any of the common excipients. Additionally, all APIs evaluated had unique Raman vibrations and spectral signals in this region. This data indicates that the 1550–1900 cm

 Raman spectral region is ideal for API identity testing. Furthermore, the data indicate the potential of this spectral region for differentiation and classification of API content in different strengths of a given drug product.

The fingerprint region, typically between 300–1900 cm

 in Raman spectroscopy, is often used for identification or authentication testing of raw materials, excipients, and active pharmaceutical ingredients (APIs) in drug products for quality control (QC) release testing. It is also used for forensic applications, such as screening suspect or counterfeit products (1). The “fingerprint in the fingerprint” is a specific spectral region (1550–1900 cm

) in Raman spectroscopy that can be used for the identity testing of pharmaceutical products, especially APIs. This narrower spectral region can strengthen the Raman capabilities of identity testing by providing the enhanced specificity needed to identify APIs in a drug product. In this spectral region, Raman signals from a variety of prescription and over-the-counter APIs are present, whereas many pharmaceutical excipients do not have Raman signals in this region. This observation leads to the conclusion that this spectral region in Raman spectroscopy is a valuable tool that could be utilized for pharmaceutical qualitative and quantitative testing, such as identity, assay, and content uniformity.

Prior to advancements in infrared (IR) and Raman vibrational spectroscopy, identity testing of pharmaceutical products was performed via chromatography. The most widely used technique for quantitative analyses is high performance liquid chromatography (HPLC), but HPLC is typically used to quantify APIs in drug products rather than excipients (2). Monitoring excipients can be beneficial, especially when it affects quality elements like dissolution (2). Chromatography also has limitations like extensive sample preparation and long analysis times. IR spectroscopy is an alternative for chromatography techniques and is commonly used for identity testing, structural elucidation, and quantitation (3). IR spectroscopy is cost efficient, has shorter analysis times, and requires little or no sample preparation when compared to HPLC. Additionally, IR spectroscopy has high spectral resolution and good signal-to-noise (S/N) ratios, which make it an effective technique for identity testing of pharmaceutical ingredients.

Raman spectroscopy is another analytical technique that can be used for identity testing in the pharmaceutical industry. This nondestructive technique requires almost no sample preparation, provides short analysis times, and enables easy operation (4). A variety of materials can be analyzed via Raman spectroscopy such as solid dosage products, bulk products, or aqueous solutions. Solid dosage formulations are more commonly evaluated via Raman spectroscopy as opposed to aqueous solutions. However, water has a weak Raman signal that does allow for analyzing biological products if needed (4). New advancements in portable Raman spectroscopy also allows for bulk products to be tested directly through their respective packaging, such as plastic liners in drums containing raw materials or excipients or blister packs for drug products. The rapid identification of drug products (5), active ingredients, and excipients are all available using Raman spectroscopy and are being accepted more widely in the pharmaceutical industry.

In this article, the “fingerprint in the fingerprint” (1550–1900 cm

) spectral region in Raman spectroscopy is explored for both prescription and over-the-counter solid dosage forms. A solid dosage product is a powder, capsule, or tablet that contains an API and a range of excipients at varying levels (2). This narrow spectral region can be used for identification and may even be used for assay or content uniformity monitoring, which are critical quality attributes for pharmaceutical products (6). The purpose of this study is to show the importance of this spectral fingerprint region in Raman spectroscopy, and how it can be leveraged for pharmaceutical applications.

Raman spectra were collected using a Thermo Nicolet NXR 6700 FT-Raman spectrometer with a microstage attachment. The microstage was replaced with a 180 reflectance attachment for the quantitative analysis experiments. A 1064-nm laser source was focused on each sample and a laser power of approximately 0.5 W and 1.0 W were used for the microstage and 180 reflectance attachments, respectively. The scattered light was transferred through the interferometer and bench optics before being collected by an indium gallium arsenide (InGaAs) detector. The Raman signals were collected at a spectral resolution of 4 cm

. Spectral calibration was performed via the Thermo ValPro qualification system, which qualifies the spectrometer, sampling module, and analysis software for use.

Omnic spectral software (version 9.8) was used to analyze the acquired Raman data. Unscrambler (version 10.4) was used for principal component analysis (PCA) modeling. Preprocessing for the PCA modeling included standard normal variate (SNV) transformation and a first derivative transformation, which was followed by a second order polynomial fit with nine-point smoothing.

Table I lists the 15 reference excipients evaluated in this article along with their common excipient class. All reference excipients were chosen from the Thermo Scientific Pharmaceutical Excipients FT-Raman library database. This library contains 300 Raman spectra collected on materials which have passed the United States Pharmacopoeia (USP) compendium methodology testing for identity and purity (7). Table II lists the 15 reference APIs evaluated in this article along with their respective drug product categories and functions. The APIs selected ranged from prescription to over-the-counter medications, which are used to treat a variety of health concerns. They are all small molecules and are not the drug substances used in protein-based biologics products. The API spectra were collected in our laboratory via the parameters outlined in the Raman instrumentation section of this article.

The following results are classified into two categories: 1) excipients and 2) APIs. The excipients outlined in Table I were chosen based on the most common inactive ingredients listed in the formulations for 30 reviewed drug products. The APIs outlined in Table II were chosen by selecting a variety of both prescription and over-the-counter medications with a range of functions. Raman data for each category are listed; the Raman band assignments are listed in the literature (8,9).

The first group of compounds analyzed were pharmaceutical excipients. These inactive ingredients have a range of functions in drug product formulations including lubricants, coating compounds, emulsifying agents, absorbents, and diluents. Magnesium stearate was the most common excipient observed. Magnesium stearate is used as a lubricant in tablet and capsule formulations and has strong Raman bands at 1061 cm

. These bands can all be assigned to C-C stretching vibrations, both asymmetric and symmetric and CH

 deformation (8). The most common coating excipient observed was titanium dioxide. Titanium dioxide is used as a coating agent, whitener, and pigment in pharmaceutical products. Raman bands are observed at 636 cm

 bending and stretching vibrations, respectively (8). Another used excipient was lactose. Lactose is widely used as a binding agent or diluent in tablet and capsule formulations. Lactose also has a variety of Raman bands that can all be assigned to C-C, C-O, and C-H bond vibrations (8). The Raman spectra (Figure 1) of the 15 common excipients evaluated in this study, and the corresponding Raman band assignments are outlined in Table III. All 15 excipients did not have any Raman signals in the defined 1550–1900 cm

The second group of compounds analyzed were APIs. These active ingredients are used in a variety of drug products, which range from cancer and diabetes treatments to over-the-counter pain relievers and antihistamines. All these drug products have most of the common excipients listed in Table III. The main spectral differences between these compounds and excipients is that the APIs have Raman vibrations located within the 1550–1900 cm

 region. Some functional groups that correlate to API peaks within this narrow region are C=N vibrations (1610–1680 cm

), and N=N vibrations observed at approximately 1580 cm

. These Raman signals are uniquely typical for APIs and are not present in common excipients. Additionally, it was noted that API #4 had a strong Raman signal at approximately 2250 cm

 that correlates to a C≡N stretching vibrational mode. All 15 active ingredients analyzed in this article had unique Raman signals in the defined 1550–1900 cm

 spectral fingerprint region. The Raman spectra (Figure 2) and corresponding Raman band assignments (Table IV) are outlined below.

The following spectra in Figures 3 and 4 compare the Raman signals within the 1550–1900 cm

 region for both excipients and APIs. As previously mentioned, the 15 excipients analyzed did not have Raman signals within this range whereas the 15 APIs analyzed did, which is an important characteristic of the 1550–1900 cm

 spectral region because the only Raman signals residing in this region are from the APIs. There are no interferences from the excipients in this region; therefore, they can be leveraged for API identity testing in a drug product. The differences in Raman signals between the two groups of compounds are because a variety of factors such as structure, functional groups, and types of bond or group vibrations. Most excipients, with the exception of a few, were comprised of carbon, oxygen, and hydrogen. The APIs had more complex structures and comprised of additional elements such as nitrogen, phosphorus, and halogens. Figure 3 shows an overlay of the Raman spectra from the 15 excipients and 15 APIs in 1550–1900 cm

 spectral region can also be used for the identification of drug products. Like Figure 3, an overlay of 15 drug products and excipients in this region show that the primary Raman signals are from the APIs rather than the excipients. Figure 4 shows the drug products and excipients highlighted in this region. The overlays show that there is no additional interference upon formulation of the product and that the Raman spectra can identify the API component in a complex drug product mixture, which can be used for more quantitative analyses such as monitoring content uniformity and assay.

As stated above, the “fingerprint in the fingerprint” region in Raman spectroscopy can also be used for quantitative analyses such as assay or content uniformity for drug products (14). Content uniformity is a standard pharmaceutical test to ensure the API content in solid dosage products have the correct amount of API across a given manufactured drug product batch (10). A similar approach to the excipient and API evaluation was conducted using FT-Raman surface scattering measurements on pharmaceutical drug products. Additionally, PCA mathematical modeling was used in this article to differentiate and classify the API content in different strengths for a given drug product (13).

As shown in Figure 5, Raman data was collected on three different strengths of a pharmaceutical solid dosage drug product (5, 10, and 15 mg) and all three strengths have a total tablet weight of 95 mg. The total API weight (w/w) in these three strengths are 5.2, 10.5, and 15.8%, respectively. The 5 and 10 mg tablets are rectangular in shape, whereas the 15 mg tablet is round. In spite of the differences in shape, it was observed that as the tablet strength increased from 5 mg to 15 mg, the intensity of the API peaks also increased between 1550–1700 cm

. This spectral intensity variability was further studied using PCA. The combination of spectroscopy and discriminate analysis, such as PCA, is a powerful tool that can be leveraged for classifying various types of medication strengths. Multivariate modeling, such as PCA, uses multiple response variables as opposed to a univariate approach, which only uses one variable. The multivariate approach does not follow a specific signal response such as concentration in Beer’s Law. For this work, PCA modeling was conducted on the “fingerprint in the fingerprint” region to determine if the 5, 10, and 15 mg tablet strengths could be differentiated. The PCA results shown in Figure 6 show a clear separation between the three tablet strengths, yielding a definitive classification of tablet strengths in this region. For this study, 90 Raman spectra were collected for the PCA modeling where 30 Raman spectra were collected for each tablet strength (10 scans per tablet). The PCA loadings plot for PC-1 is also shown in Figure 6. The loadings plot indicates that the majority of the spectral variability used to separate the three strengths along PC-1 are from the API peaks at 1580 cm

. These peaks are mainly because of aromatic ring modes, C=O and C=C vibrations.

These results demonstrate the possibility of quantitative classification of pharmaceutical products using the conventional Raman techniques utilized in this work, and the importance of the “fingerprint in the fingerprint” for both qualitative and quantitative classifications. Although the results show definitive promise and potential for broad pharmaceutical utilization, traditional surface scattering Raman techniques do pose some limitations to accurate quantitative analyses such as content uniformity.

Mitigating some of these limitations, transmission Raman is a technique that has typically been used for quantitative analyses as opposed to conventional backscatter Raman. Transmission Raman requires limited or even no sample preparation, is nondestructive, and enables rapid analysis times (11). It can be applied during both the manufacturing and finished product stages. In this technique, a spectrometer measures a larger volume of the sample and the Raman signal is transmitted and diffused throughout the body of the sample (10). The transmittance through the sample results in a representative measurement and high efficiency (12).

Despite some of the limitations, these results clearly indicate that conventional FT-Raman spectroscopy could be utilized as a potential alternative for content uniformity testing typically performed by HPLC. Additionally, mathematical models such as partial least squares (PLS) regression can also be used to increase the accuracy of quantitative analyses like assay and content uniformity. However, PLS modeling is out of the scope of this article.

The aim of this study was to show the significance of a smaller spectral region of the Raman spectrum, defined as the “fingerprint in the fingerprint,” when evaluating pharmaceutical products. A spectral evaluation was conducted on a myriad of common excipients, APIs, and drug products. Qualitative and quantitative analysis was performed on these products to gain understanding of this spectral region. The qualitative results showed no Raman spectral signals in this region for any of the common excipients outlined in this article. Additionally, all APIs as well as drug products evaluated had unique spectral signal in this region. These data indicate that the 1550–1900 cm

 Raman spectral region is ideal and can be leveraged for API identity testing because there are no interferences from common inactive ingredients. Furthermore, the data indicate that this spectral region can also be used to differentiate and classify the content of API in different strengths of a given drug product, which was shown in the mathematical modelling. Holistically, this work has demonstrated the vast potential of Raman spectroscopy to be utilized for both qualitative and quantitative analyses in the pharmaceutical industry, as well as the importance of the ~1550–1900 cm

 spectral region, the “fingerprint in the fingerprint.”

The authors would like to thank Bristol Myers Squibb and their colleagues from the Global Quality Analytical Science & Technology Forensics team for their support.

(1) J. Peters, A. Luczak, V. Ganesh, E. Park, and R. Kalyanaraman, 

(2) J. Griffen, A. Owen, and P. Matousek, 

(3) E. Mojica, J. Zapata, J. Vedad, R. Desamero, and Z. Dai, in 

Raman Spectroscopy in the Undergrad Curriculum

 (ACS Symposium Series, vol. 1305, 2018), pp. 69–91. 

(4) P. Kalantri, R. Somani, and D. Makhija, 

(5) B. Handzo, A. Luczak, S. Huffman, J. Peters, and R. Kalyanaraman, 

(7) “Pharmaceutical Excipients FT-Raman Library”, Thermo Scientific (Waltham, Maryland, 2007).

(8) M. Veij. P. Vandenabeele, and T. Beer, 

(9) “Raman Data & Analysis: Raman Spectroscopy for Analysis and Monitoring Application Note”, Horiba Scientific (Edison, New Jersey, 2021).

(10) K. Frano, J. Maticchio, and D. Yang, 

(12) Y. Li, B. Igne, J. Drennen III, and C. Anderson, 

(13) R. Kalyanaraman, G. Dobler, and M. Ribick, 

 are with the Forensics and Innovative Technology (FIT) department at Bristol Myers Squibb in New Brunswick, New Jersey. Ravi Kalyanaraman will be chairing a session on Pharmaceutical Forensics at the upcoming 2022 SciX Conference in Cincinnati, Ohio (October 2–7). Direct correspondence to: 

Peer-Reviewed Research

The “fingerprint in the fingerprint” region is key for active pharmaceutical ingredient (API) identity testing. We explain why.

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A Fingerprint in a Fingerprint: A Raman Spectral Analysis of Pharmaceutical Ingredients