Katherine A. Bakeev

The Raman technique is gaining widespread acceptance as an investigative tool for forensic applications. This article focuses on the use of portable and handheld Raman spectroscopy in the field of forensic science and illustrates it with real-world examples.

	The benefits of Raman spectroscopy are well recognized for the molecular identification of unknown molecular compounds and as a result the technique is being used routinely in applications areas such as pharmaceutical manufacturing (1), raw material verification (2), detection of counterfeit drugs (3), medical diagnostics (4), characterization of polymers (5), and the quality control of food products (6). However, more recently the technique is gaining widespread acceptance as an investigative tool in the areas of forensic science and homeland security (7,8). On-board spectral libraries and intelligent decision-making software make Raman spectroscopy ideally suited to help law enforcement agencies better understand the source and nature of illicit materials. Today's Raman instrumentation is faster, more rugged, and less expensive, and the advances in component miniaturization have led to the design of portable devices with extremely high performance that can be taken out and used for field-based investigations. Therefore, this study focuses on the use of handheld Raman spectroscopy for the characterization and identification of samples encountered in various application areas related to forensic science.

	Law enforcement agencies responsible for reducing the level of serious crime are being faced with more challenges than ever before. For example, new designer drugs are appearing on street corners around the world almost every day. Additionally, terrorism attacks using various explosive devices are being reported by the media around the globe on a regular basis. Also, a topic of international importance is the increase in production of counterfeit cancer, malaria, prescription, and over-the-counter (OTC) drugs, particularly in parts of the world that do not have the skill and expertise to detect them (9). As a result, there is clearly a need to investigate these events in a speedy and timely manner.

	This fact is supported by investigations into the illegal use of both social and performance-enhancing drugs, where an identification needs to be made on the type and source of the material used as quickly as possible. Traditionally, test kits are used to obtain a positive indication of a particular drug for presumptive evidence purposes. Unfortunately, for some of the newer, more exotic, and designer drugs of abuse, specific test kits may not be available. Since limited testing can be carried out in the field, seized samples are subsequently sent to a state or federal laboratory for confirmatory analysis. Overburdened laboratories may require weeks or even months before test results reach the prosecutor's hands and, as a result, the pressure placed on analytical chemists to process samples as quickly as possible can be quite significant.

	Forensic laboratories that provide evidence for the positive identification of these kinds of samples frequently use gas chromatography–mass spectrometry (GC–MS), which is considered the gold standard for the analysis of volatile organic compounds. However, even though GC–MS provides definitive results, it is a costly, destructive, laboratory-based technique that is extremely time-consuming and contributes to the backlog of samples, subsequently delaying the reporting of results back to law enforcement agencies waiting to prosecute cases.

	For that reason, state-of-the-art analytical techniques being used for rapid screening and confirmatory identification are now being miniaturized and making their way into field instrumentation. The transition from laboratory-based to field-based analyzers allows law enforcement agencies to conduct reliable measurements at the point of use, lessening the burden on crime laboratories, reducing their sample backlog, and accelerating the prosecution process. One of the most exciting analytical techniques that is moving analysis away from the laboratory and into the field is portable Raman spectroscopy. Before we take a look at how this new technique is revolutionizing the forensic analysis landscape, let's take a brief look at its fundamental principles of operation.

	Similar to infrared (IR) absorption techniques, Raman spectroscopy measures vibrational, rotational, and other low-frequency modes of a molecule. Whereas IR spectroscopy is based on focusing a broad range of IR wavelengths of light on to the sample and measuring which ones are absorbed, a Raman spectrum is obtained by directing a single wavelength of light and collecting the resulting scattered light. The frequencies of the scattered light depend on the bond strength of the molecules, the mass of the bound atoms, and other factors such as intermolecular interactions. The pattern of vibrational and rotational frequencies from a molecule is highly characteristic of a given molecular species or the structural arrangement of those molecules and, as a result, can be used for the positive identification of that species or compound (10). Because of variations in Raman band intensities and overlapping bands, robust library searching algorithms are needed for reliable identification of samples. Unfortunately, with many sample types, baseline changes caused by fluorescence, scattering effects, and changes in the signal intensity with different power settings can interfere with the Raman measurements. For this reason it is very important that any portable or handheld Raman spectrometer is designed with an understanding that these kinds of potential interferences need to be addressed to handle real-world applications.

	This study examines the use of a handheld Raman spectrometer (TacticID, B&W Tek) to carry out the real-world testing of a group of forensic and homeland security–related samples. The fundamental principles of the device have been described in the open literature, but it is basically a field-ready, spectral analysis instrument specifically designed to enable the forensic analysis of unknown chemicals and narcotics. It is a compact spectrometer and integrated computing system weighing approximately 2 lb, and it allows for the confirmation of a sample in less than 30 s.

	The system includes a 785-nm, 300-mW laser excitation source with a crossed Czerny-Turner spectrograph and a charge-coupled device (CCD) array detector. The system provides a stable signal with low background noise, which is very important when testing materials of a similar molecular structure such as narcotics, pharmaceuticals, or hazardous and explosive mixtures because of the potential for other components in the sample to increase the background noise and elevate the baseline through fluorescence or other photon scattering effects.

The system can be customized for specific forensic applications, but the standard configuration contains a library of spectral information generated from more than 4500 chemicals, toxic or hazardous materials, explosives, precursors, narcotics, pharmaceutical drugs, and cutting agents. For example, the hazardous or explosive materials in the spectral library include polynitro aromatics such as trinitrotoluene (TNT) and trinitrobenzene (TNB); nitrate esters or nitroamines such as RDX, Semtex, and nitroglycerin; and a number of different inorganic nitrates and chlorates. Examples of Raman spectra of three explosives in the database are displayed in Figure 1, which shows two nitroamines (HMX and RDX) in red and green, respectively, and 2,4,6-trinitrophenylmethylnitroamine (tetryl) in blue. The spectra have been offset for clarity purposes.

	A system specifically designed for pharmaceutical and narcotics identification is available (TacticID-N, B&W Tek) that contains nearly 1000 spectra, including Class A drugs such as ecstasy, cocaine, methadone, and phencyclidine (PCP); Class B drugs like amphetamines and methylphenidate (Ritalin); and Class C drugs such as tranquilizers together with many OTC and prescription painkillers. Examples of Raman spectra of three narcotics are demonstrated in Figure 2, which shows a barbiturate (butabarbital) in red, a psychedelic drug (3-C bromo-dragonfly) in blue, and cocaine in green. Once again, all spectra are offset for clarity purposes.

The testing procedure for real-world samples involves either using the supplied spectral libraries for reference and identification purposes or calibrating the device using pure forms of each of the chemical or drug compounds to develop user-defined libraries to test all the unknown materials under investigation. A proprietary software algorithm is included in the handheld unit in which the Raman spectrum is compared and matched with that in the library to generate a numerical hit quality index (HQI) value from which the result is determined. Analyzing samples in this way with spectral libraries ensures the identification of samples based on the Raman signature that can be related to the unique characteristics of the chemical materials, and provides a reliable testing procedure for unskilled operators required for the unambiguous identification of unknown materials. In routine use, the total scan time and decision making process takes approximately 30 s to make an assessment of a material and whether a match has been found. This is exemplified in Figure 3, which shows a Raman spectrum of pure acetaminophen in red (reference) and Tylenol (McNeil-PPC, Inc.), an OTC pain medication containing acetaminophen, as the active ingredient in blue (sample). The spectra have been offset slightly for clarity purposes, but it can be clearly seen that both spectra are almost identical, indicating a positive match.

	Figure 4 shows a positive match for a sample of cocaine (blue) compared to a reference standard (red). This spectrum was actually supplied by a major metropolitan law enforcement agency in the United States, whose police officers were using it for the identification of street drugs.

Figure 5 shows the identification of the explosive TNT. The Raman spectrum of reference TNT standard is shown in red, and the unknown sample is shown in blue. Once again it can be seen that both spectra are almost identical, indicating a positive match.

	If a positive identification cannot be found because of a weak Raman signal or high fluorescence, or there is just no match in the spectral library, "no match" will be displayed on the screen. Figure 6 shows a Raman spectrum for which no reference match was found in the library. When this happens, the user can submit the spectrum for further analysis and after positive identification is made, the library can be updated. 

	There will always be a need for law-enforcement and homeland security agencies to characterize and identify narcotics and chemicals that have been used for illegal purposes. Whether they are drugs of abuse, performance-enhancing drugs, counterfeit prescriptions, OTC medications, or hazardous and explosive materials used in acts of terrorism, the source, nature, and classification of these materials is critical to unravel the crimes committed behind their use. Handheld Raman spectroscopy is proving that it is ideally suited for this task.

, is the director of analytical services and support at B&W Tek in Newark, Delaware. 

is the principal consultant at Scientific Solutions Inc., in Gaithersburg, Maryland. Direct correspondence to: katherineb@bwtek.com

http://www.pharmamanufacturing.com/articles/2013/006/?page=full

http://www.americanpharmaceuticalreview.com/Featured-Articles/126738-The-Benefits-of-a-High-Performance-Handheld-Raman-Spectrometer-for-the-Rapid-Identification-of-Pharmaceutical-Raw-Materials/

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

, "Non-destructive Materials Identification Supplement," 

	(4) R. Thomas, K. Bakeev, M. Claybourn, and R. Chimenti, 

Vibrational Spectroscopy of Polymers: Principles and Practice

, N.J. Everall, J. Chalmers, and P.R. Griffiths, Eds. (John Wiley and Sons, Chichester, UK, 2007).

	(6) B. Diehl, C.S. Chen, B. Grout, J. Hernandez, S. O'Neill, C. McSweeney, J.M. Alvarado, and M. Smith, 

	(8) J.F. Kelly, T.A. Blake, B.E. Bernacki, and T.J. Johnson, 

	(9) "Arrest in Cancer Drug Sales in Turkey," 

http://online.wsj.com/news/articles/SB1000142405270230470380457938	3271726960510

, I.R. Lewis and H.G.M. Edwards, Eds. (Practical Spectroscopy Series 28, Marcel Dekker, New York, 2001).

Articles

The Raman technique is gaining widespread acceptance as an investigative tool for forensic applications.

The Use of Portable and Handheld Raman Spectroscopy for Forensic Investigations

Both Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are proving to be invaluable tools in the field of biomedical research and clinical diagnostics. The robust, compact, fit-for-purpose Raman spectrometer designs are appropriate for use in surgical procedures to help surgeons assess tumors and allow rapid decisions to be made. Raman systems are also being developed for molecular diagnostic testing to detect and measure human cancer biomarkers. Based on the SERS technique, this approach potentially could change the way bioassays are performed to improve both the sensitivity and reliability of testing. The two applications highlighted in this review, together with other examples of the use of Raman spectrometry in biomedical research areas such as the identification of bacterial infections, are clearly going to make the technique an important part of the medical toolbox, as we continually strive to improve diagnostic techniques and bring a better health care system to patients.

In recent years, Raman spectroscopy has gained widespread acceptance in applications that span from the rapid identification of unknown components to detailed characterization of materials and biological samples. The technique's breadth of application is too wide to reference here, but examples include quality control (QC) testing and verification of high purity chemicals and raw materials in the pharmaceuticals and food industries (1–3), investigation of counterfeit drugs (4), classification of polymers and plastics (5), characterization of tumors, and the detection of molecular biomarkers in disease diagnostics (6–8) and theranostics (9).  

One of the most exciting application areas is in the biomedical sciences. The major reason behind this surge of interest is that Raman spectroscopy is an ideal technique for molecular fingerprinting and is sensitive to the chemical changes associated with disease. Furthermore, components in the tissue matrix, principally those associated with water and bodily fluids, give a weak Raman response, thereby improving sensitivity for those changes associated with a diseased state (10). The growing body of knowledge in our understanding of the science of disease diagnostics and improvements in the technology has led to the development of fit-for-purpose Raman systems designed for use in surgical theaters and doctors' surgeries, without the need for sending samples to the pathology laboratory (8).  

Surface-enhanced Raman spectroscopy (SERS) is a more sensitive version of Raman spectroscopy, relying on the principle that Raman scattering is enhanced by several orders of magnitude when the sample is deposited onto a roughened metallic surface. The benefit of SERS for these types of applications is that it provides well-defined, distinct spectral information, enabling characterization of various states of a disease to be detected at much lower levels. Some of the many applications of Raman and SERS for biomedical monitoring include   					

Cytology investigations at the cellular level

Direct investigation of cancerous tissues

Surgical targets and treatment monitoring 

The basics of Raman spectroscopy are well covered elsewhere in the literature (11). However, before we present some typical examples of both Raman and SERS applications in the field of cancer diagnostics, let's take a closer look at the fundamental principles and advantages of SERS. 

Principles of Surface-Enhanced Raman Spectroscopy

The principles of SERS are based on amplifying the Raman scattering using metal surfaces (usually Ag, Au, or Cu), which have a nanoscale roughness with features of dimensions 20–300 nm. The observed enhancement of up to 10

-fold can be attributed to both chemical and electromagnetic effects. The chemical component is based on the formation of a charge-transfer state between the metal and the adsorbed scattering component in the sample and contributes about three orders of magnitude to the overall enhancement. The remainder of the signal improvement is generated by an electromagnetic effect from the collective oscillation of excited electrons that results when a metal is irradiated with light. This process, known as the surface plasmon resonance (SPR) effect, has a wavelength dependence related to the roughness and atomic structure of the metallic surfaces and the size and shape of the nanoparticles. For a more detailed discussion of SERS and its applications, see reference 12.    

Detection by SERS has several benefits. Firstly, fluorescence is inherently quenched for an adsorbate analyte on a SERS surface resulting in fluorescence-free SERS spectra. This is primarily because the Raman signal is enhanced by the metal surface, and the fluorescence signal is not. As a result, the relative intensity of the fluorescence is significantly lower than the Raman signal and in many occasions is not observable. Secondly, signal averaging can be extended to increase sensitivity and lower detection levels. Finally, SERS spectral bands are very sharp and well-defined, which improves data quality, interpretability, and masking by interferents. Recent work using silver nanoparticles as the enhancing substrate has shown that SERS can be applied to single-molecule detection, rivaling the performance of fluorescence measurements (13). 

Although SERS has many advantages it also has several disadvantages that are worth noting. The first is that unlike traditional Raman spectroscopy, SERS requires sample preparation. The ability to measure samples in vivo without the need for sample pretreatment is one of the major advantages of traditional Raman spectroscopy. For that reason, it is important to understand the signal enhancement benefits of SERS compared to the ease of sampling of traditional Raman spectroscopy when deciding which technique to use (14). Second, high performance SERS substrates are difficult to manufacture and, as a result, there is typically a high degree of spatial nonuniformity with respect to the signal intensity (15). For example, the SERS substrates used in the research being carried out by the University of Utah (described later in this article) tend to have much higher concentrations of analyte on the edges of the sampling area than in the center. Lastly, it is important to note that when the sample is deposited onto the surface, the molecular structure (the nature of the analyte) can be altered slightly resulting in differences between traditional Raman spectra and SERS spectra (16). However, it should be emphasized that there have been improvements in the quality of substrates being manufactured today and new materials such as Klarite (Renishaw Diagnostics) are showing a great deal of promise in terms of consistency and performance (17). 

Raman Spectroscopy Applied to Biomedical Studies

There are several important functional groups related to biomedical testing that have characteristic Raman frequencies. Tissue samples include components such as lipids, fatty acids, and protein, all of which have vibrations in the Raman spectrum. The most significant spectral regions include 					

X-H bonds (for example, C-H stretches): 4000–2500 cm

Multiple bonds (such as N≡C): 2500–2000 cm

Double bonds (for example, C=C, N=C): 2000–1500 cm

Complex patterns (such as C-O, C-N, and bands in the fingerprint region): 1500–600 cm

The identification and measurement of Raman scattering in these spectral regions can be applied to the following biomedical applications: 					

Measurement of biological macromolecules such as nucleic acids, proteins, lipids, and fats

Investigation of blood disorders such as anemia, leukemia, and thalassemias (inherited blood disorder)

Detection and diagnosis of various cancers including brain, breast, pancreatic, cervical, and colon 

Assaying of biomarkers in studying human diseases

Understanding cell growth in bacteria, phytoplankton, viruses, and other microorganisms

Analysis of abnormalities in tissue samples such as brain, arteries, breast, bone, cervix, embryo media, esophagus, gastrointestinal tract, and the prostate gland

Some typical examples of Raman spectra of biological molecules are shown in Figure 1. Figure 2 gives a summary of some common biochemical functional groups with their molecular vibrational modes and frequency ranges, which are observed in compounds such as proteins, carbohydrates, fats, lipids, and amino acids (6,8,10,18–20). Identification of these functional groups can be used as a qualitative or quantitative assessment of a change or anomaly in a sample under investigation. 

Figure 1: Raman spectra of various biological compounds. Adapted from reference 21.			

Let's take a look at two examples of the use of both conventional Raman spectroscopy and SERS, specifically for cancer diagnostic purposes. The first example uses traditional Raman spectroscopy for the assessment of breast cancer and the second example takes a look at SERS for the screening of pancreatic cancer biomarkers. 

Figure 2: Some common functional groups with their molecular vibrational modes and frequency ranges observed in various biochemical compounds. Adapted from reference 18.			

Detection and Diagnosis of Breast Cancer 

The surgical management of breast cancer for some patients involves two or more operations before a surgeon can be assured of removing all cancerous tissue. The first operation removes the visible breast cancer and samples the lymph nodes for signs of the disease spreading. Intraoperative methods for testing the health of the lymph nodes involve classical tissue mapping techniques such as touch imprint cytology and histopathological, frozen section microscopy. The problem with both of these methods is that they have poor sensitivity and require an experienced pathologist to interpret the data and relay the "benign" or "malignant" diagnostic report to the surgeon. For that reason, these intraoperative methods have not been widely adopted by the medical community and, as a result, most procedures still require samples to be sent to a laboratory for further testing. If tests confirm that the cancer has spread, then the patient must undergo an additional surgery to remove all the nodes in the affected area.  

A preferable approach would be for an intraoperative assessment, which would allow for the immediate excision of all of the axillary lymph nodes, if required. Studies by researchers at Cranfield University and Gloucestershire Royal Hospital in the United Kingdom have shown that Raman spectroscopy can detect differences in tissue composition, particularly a wide range of cancer pathologies (22). This group used a portable Raman spectrometer with a 785-nm excitation laser wavelength and a fiber-optic probe (MiniRam, B&W Tek) and principal component analysis (PCA) along with linear discriminant analysis (LDA) data processing to evaluate the Raman spectra of lymph nodes. They confirmed that the technique can match the sensitivities and specificities of histopathological techniques that are currently being used.  

The initial work in this study involved taking Raman spectra of the same samples that were being evaluated by the traditional intraoperative techniques. The study, which assessed 38 (25 negative and 13 positive) axillary lymph nodes from 20 patients undergoing surgery for newly diagnosed breast cancer, compared the results with a standard histopathological assessment of each node. The results showed a specificity of 100% and sensitivity of 92% when differentiating between normal and metastatic nodes. These results are an improvement on alternative intraoperative approaches and reduce the likelihood of false positive or false negative assessment (20). Typical Raman spectra of lymph nodes from benign breast tissue and malignant tumors are shown in Figure 3. It can be seen that while there are very subtle differences between the two spectra, the data classes can be discriminated using multivariate classification tools such as PCA-LDA and support vector machine (SVM) classification applied over the 800–1800 cm

 spectral range. By using such supervised classification tools, Raman spectroscopy is sensitive enough to pick up the differences in the chemistry of the diseased state compared to that of the healthy tissue. For example, in Figure 3, subtle differences in the fatty acid peaks at 1300 and 1435 cm

, are highlighted from the loadings plots from PCA analysis of the data (19). 

Figure 3: Raman spectral peaks of lymph nodes of benign breast tissue (blue), together with a malignant breast tumor (red). Adapted from reference 21.			

More work is currently being done to support these findings at the University of Exeter and other research facilities. If confirmed, the next stage is to introduce the probe-based Raman spectrometer into an operating theater, where it can be used to assess the node as soon as it is removed from the patient.  

Additionally, many other groups are working on different approaches to cancer screening using Raman spectroscopy. Recent studies at the Massachusetts Institute of Technology (MIT) have shown that this technique has the potential to be built in to a biopsy needle, allowing doctors to instantaneously identify malignant or benign growths before an operation (23). Recent studies have indicated that the efficacy of these techniques can be enhanced by including a wider spectral region beyond 1800 cm

  in the model to increase specificity (24). Finally, for the characterization of highly fluorescent biological tissues, such as liver and kidney samples, researchers have shown evidence to suggest that shifting the excitation laser wavelength to 1064 nm provides a cleaner Raman response with reduced fluorescence compared to excitation at 785 nm (25). Dispersive Raman technology at 1064 nm is relatively new and is slowly gaining traction. Most biological tissues produce fluorescence to a greater or lesser extent, so reducing this effect will improve the Raman signal and potentially improve the analysis and the quality or accuracy of the diagnostic outcome. 

SERS Immunoassay for Pancreatic Cancer Biomarker Screening

Pancreatic adenocarcinoma is the fourth most common cause of cancer deaths in the United States, with a 5 year survival rate of ~6% and an average survival rate of <6 months. The reason for this high ranking is that the disease can only be detected and diagnosed by conventional radiological and histopathological detection methods when it has progressed to an advanced stage. After it has been diagnosed, resection (partial removal) of the pancreas is the normal treatment (26).  

There are potentially more than 150 biomarkers found in serum for the detection of pancreatic and other cancers. One of the most prevalent is carbohydrate antigen 19-9 (CA 19-9), a mucin type glycoprotein sialosyl Lewis antigen (SLA), which shows elevated levels in ~75% of patients with pancreatic adenocarcinoma (27). The most common diagnostic test for these biomolecular compounds is enzyme-linked immunosorbent assay (ELISA), which is a well-established bioassay that uses a solid-phase enzyme immunoassay to detect the presence of an antigen in serum samples. It works by attaching the sample antigen to the surface of the sorbent. Then a specific monoclonal antibody, which is linked to the enzyme, is applied over the surface so it can bind to the antigen. In the final step, a substance containing the enzyme's substrate is added, which generates a reaction to produce a color change in the substrate (28). Even though this technique is widely used for bioassays, it does have some limitations with regard to the detection of cancer biomarkers. For example, early stage markers are present at levels well below current detection capabilities. In addition, 100–200 μL of sample is typically required to achieve a low enough limit of detection. Moreover, CA 19-9 is unlikely to be detected in patients with tumors smaller than 2 cm. It is further complicated by the fact that an estimated 15% of the population cannot even synthesize CA 19-9. The limitations in the ELISA approach (29) have led to the investigation of alternative methods, including an immunoassay based on SERS. This offers the exciting possibility of an alternative, faster way of detecting many different biomarkers in the same assay.  

A portable Raman spectrometer (MiniRam, B&W Tek) was used in a recent study at the University of Utah's Nano Institute to detect and quantify the CA 19-9 antigen in human serum samples (30). It showed the advantages of generating a SERS-derived signal from a Raman reporter molecule attached to the biomolecule marker analyte using gold nanoparticles. This process is carried out using an analyte sandwich immunoassay in which monoclonal antibodies are covalently bound to a solid gold substrate to specifically capture the antigen from the sample. The captured antigen is in turn bound to the corresponding detection antibody. This complex is joined together with gold nanoparticles that are labeled with different reporter molecules, which serve as extrinsic Raman labels (ERLs) for each type of antibody. The presence of specific antigens is confirmed by detecting and measuring the characteristic SERS spectrum of the reporter molecule. Let's take a closer look at how this works in practice for these biomarkers and how the sample is prepared and read-out, in particular.   

The first step is the preparation of the ERLs. This is done by coating a 60-nm gold nanoparticle with the Raman reporter molecule, which in this case is 5,5'-dithiobis(succinimidyl-2- nitrobenzoate (DSNB). This complex is then coated with a target or tracer antibody using 

-hydroxysuccinimide (NHS) coupling chemistry. The DSNB serves two purposes: The nitrobenzoate group is the reporter molecule and the NHS group enables the protein to be coupled to the nanoparticle surface. 

The second step is to prepare the substrate for capture. This is done by resistively evaporating solid gold under vacuum using thin film deposition on a glass microscope slide and then growing a monolayer of dithiobis(succinimidyl propionate) (DSP) on the surface of the slide to link the capture antibody to the gold surface. Next, the appropriate antibody is attached to the substrate, based on the biomarker of interest. 

The third step is to make the immunoassay sandwich. This step involves incubating the slide with serum containing the CA 19-9 or MMP-7 antigens, which are then captured by surface-bound monoclonal antibodies and labeled with the ERLs. 

The fourth and final step is to read out the Raman signal of the functional group of interest, using a spot size of ~85 μm with a laser excitation wavelength of 785 nm. In the study, the symmetric nitro stretch band of the DNSB molecule at 1336 cm

  was used for quantitation by measuring the peak height to construct a calibration curve for various concentrations of the antigens spiked into serum. Real-world serum samples are then quantified using this calibration curve.  

Both Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are proving to be invaluable tools in the field of biomedical research and clinical diagnostics.

The Use of Raman Spectroscopy in Cancer Diagnostics

This second installment in the pair looks at NIR applications performed at-line and on-line, as well as some points to be considered in implementing NIR as a process analytical tool.

Molecular Spectroscopy Workbench Near-Infrared Spectroscopy as a Process Analytical Tool, Part II: At-line and On-line Applications and Implementation Strategies (PDF)

Rapid near-infrared spectroscopy measurement near the process line of lab applications may speed up the process.

Katherine A. Bakeev

Articles

The Use of Portable and Handheld Raman Spectroscopy for Forensic Investigations

The Use of Raman Spectroscopy in Cancer Diagnostics

Molecular Spectroscopy Workbench Near-Infrared Spectroscopy as a Process Analytical Tool, Part II: At-line and On-line Applications and Implementation Strategies (PDF)

Molecular Spectroscopy Workbench: Near-Infrared Spectroscopy as a Process Analytical Tool, Part I: Laboratory Applications (PDF)