Discrimination of phenethylamine regioisomers and structural analogues by Raman spectroscopy

In this study, the Raman spectra of 21 phenethylamines were obtained using far‐red excitation (785 nm). The distinguishing ability of Raman for phenethylamines, especially for phenethylamine regioisomers and structural analogues, was investigated. Here, the evaluation of a cross section of Raman spectra demonstrated that all types of phenethylamines were distinguishable, even for certain structural analogues with high spectrum similarity. Raman exhibited high distinguishing ability for phenethylamine regioisomers that differ in the substitution position of halogen, methoxy, alkyl, or other substituted groups; as well as for structural analogues containing different groups, such as furanyl, 2,3‐dihydrofuranyl, halogen, and alkyl substituted at the same position. The Raman spectra for homologues with differences in only a methyl group were found to be highly similar; however, their spectra demonstrated small but detectable differences. Four analogue mixtures and 59 seized samples were also analyzed to study the practical use of the Raman method in forensic field. 95% of the seized samples were correctly identified, which significantly validated the ability of Raman method in identifying the correct isomers. Accordingly, this study provides a non‐destructive, high‐throughput and minimal sample preparation technique for the discrimination of phenethylamines.     

Identification of Different Forms of Cocaine and Substances Used in Adulteration Using Near‐infrared Raman Spectroscopy and Infrared Absorption Spectroscopy

Identification of cocaine and subsequent quantification immediately after seizure are problems for the police in developing countries such as Brazil. This work proposes a comparison between the Raman and FT‐IR techniques as methods to identify cocaine, the adulterants used to increase volume, and possible degradation products in samples seized by the police. Near‐infrared Raman spectra (785 nm excitation, 10 sec exposure time) and FT‐IR‐ATR spectra were obtained from different samples of street cocaine and some substances commonly used as adulterants. Freebase powder, hydrochloride powder, and crack rock can be distinguished by both Raman and FT‐IR spectroscopies, revealing differences in their chemical structure. Most of the samples showed characteristic peaks of degradation products such as benzoylecgonine and benzoic acid, and some presented evidence of adulteration with aluminum sulfate and sodium carbonate. Raman spectroscopy is better than FT‐IR for identifying benzoic acid and inorganic adulterants in cocaine.     

Application of Raman Spectroscopy and Surface‐Enhanced Raman Scattering to the Analysis of Synthetic Dyes Found in Ballpoint Pen Inks*

Abstract: The applicability of Raman spectroscopy and surface‐enhanced Raman scattering (SERS) to the analysis of synthetic dyes commonly found in ballpoint inks was investigated in a comparative study. Spectra of 10 dyes were obtained using a dispersive system (633 nm, 785 nm lasers) and a Fourier transform system (1064 nm laser) under different analytical conditions (e.g., powdered pigments, solutions, thin layer chromatography [TLC] spots). While high fluorescence background and poor spectral quality often characterized the normal Raman spectra of the dyes studied, SERS was found to be generally helpful. Additionally, dye standards and a single ballpoint ink were developed on a TLC plate following a typical ink analysis procedure. SERS spectra were successfully collected directly from the TLC plate, thus demonstrating a possible forensic application for the technique.     

Evaluation and classification of fentanyl-related compounds using EC-SERS and machine learning

Multiple analytical techniques for the screening of fentanyl-related compounds exist. High discriminatory methods such as GC–MS and LC–MS are expensive, time-consuming, and less amenable to onsite analysis. Raman spectroscopy provides a rapid, inexpensive alternative. Raman variants such as electrochemical surface-enhanced Raman scattering (EC-SERS) can provide signal enhancements with 10¹⁰ magnitudes, allowing for the detection of low-concentration analytes, otherwise undetected using conventional Raman. Library search algorithms embedded in instruments utilizing SERS may suffer from accuracy when multicomponent mixtures involving fentanyl derivatives are analyzed. The complexing of machine learning techniques to Raman spectra demonstrates an improvement in the discrimination of drugs even when present in multicomponent mixtures of various ratios. Additionally, these algorithms are capable of identifying spectral features difficult to detect by manual comparisons. Therefore, the goal of this study was to evaluate fentanyl-related compounds and other drugs of abuse using EC-SERS and to process the acquired data using machine learning—convolutional neural networks (CNN). The CNN was created using Keras v 2.4.0 with Tensorflow v 2.9.1 backend. In-house binary mixtures and authentic adjudicated case samples were used to evaluate the created machine-learning models. The overall accuracy of the model was 98.4 ± 0.1% after 10-fold cross-validation. The correct identification for the in-house binary mixtures was 92%, while the authentic case samples were 85%. The high accuracies achieved in this study demonstrate the advantage of using machine learning to process spectral data when screening seized drug materials comprised of multiple components.     

Advanced statistical analysis of Raman spectroscopic data for the identification of body fluid traces: Semen and blood mixtures

Conventional confirmatory biochemical tests used in the forensic analysis of body fluid traces found at a crime scene are destructive and not universal. Recently, we reported on the application of near-infrared (NIR) Raman microspectroscopy for non-destructive confirmatory identification of pure blood, saliva, semen, vaginal fluid and sweat. Here we expand the method to include dry mixtures of semen and blood. A classification algorithm was developed for differentiating pure body fluids and their mixtures. The classification methodology is based on an effective combination of Support Vector Machine (SVM) regression (data selection) and SVM Discriminant Analysis of preprocessed experimental Raman spectra collected using an automatic mapping of the sample. This extensive cross-validation of the obtained results demonstrated that the detection limit of the minor contributor is as low as a few percent. The developed methodology can be further expanded to any binary mixture of complex solutions, including but not limited to mixtures of other body fluids.     

Blind field test evaluation of Raman spectroscopy as a forensic tool

Analytical instrumentation for Raman spectroscopy has advanced rapidly in recent years to the point where commercial field-portable instruments are available. Raman analysis with portable instrumentation is a new capability that can provide emergency response teams with on-site evaluation of hazardous materials. Before Raman analysis is accepted and implemented in the field, realistic studies applied to unknown samples need to be performed to define the reliability of this technique. Studies described herein provide a rigorous blind field test that utilizes two instruments and two operators to analyze a matrix that consists of 58 unknown samples. Samples were searched against a custom hazardous materials reference library (Hazardous Material Response Unit (HMRU) Spectral Library Database). Experimental design included a number of intentionally difficult situations including binary solvent mixtures and a variety of compounds that yield medium-quality spectra that were not contained in the HMRU library. Results showed that over 97% of the samples were correctly identified with no occurrences of false positive identifications (compounds that were not in the library were never identified as library constituents). Statistical analysis indicated equivalent performance for both the operators and instruments. These results indicate a high level of performance that should extrapolate to actual field situations. Implementation of Raman techniques to emergency field situations should proceed with a corresponding level of confidence.     

Raman spectroscopy and microspectrophotometry of reactive dyes on cotton fibres: Analysis and detection limits

A collaborative study on Raman spectroscopy and microspectrophotometry (MSP) was carried out by members of the ENFSI (European Network of Forensic Science Institutes) European Fibres Group (EFG) on different dyed cotton fabrics. The detection limits of the two methods were tested on two cotton sets with a dye concentration ranging from 0.5 to 0.005% (w/w). This survey shows that it is possible to detect the presence of dye in fibres with concentrations below that detectable by the traditional methods of light microscopy and microspectrophotometry (MSP). The MSP detection limit for the dyes used in this study was found to be a concentration of 0.5% (w/w). At this concentration, the fibres appear colourless with light microscopy. Raman spectroscopy clearly shows a higher potential to detect concentrations of dyes as low as 0.05% for the yellow dye RY145 and 0.005% for the blue dye RB221. This detection limit was found to depend both on the chemical composition of the dye itself and on the analytical conditions, particularly the laser wavelength. Furthermore, analysis of binary mixtures of dyes showed that while the minor dye was detected at 1.5% (w/w) (30% of the total dye concentration) using microspectrophotometry, it was detected at a level as low as 0.05% (w/w) (10% of the total dye concentration) using Raman spectroscopy. This work also highlights the importance of a flexible Raman instrument equipped with several lasers at different wavelengths for the analysis of dyed fibres. The operator and the set up of the analytical conditions are also of prime importance in order to obtain high quality spectra. Changing the laser wavelength is important to detect different dyes in a mixture.     

Application of Infrared and Raman Spectroscopy in Paint Trace Examination

Raman spectroscopy has proved to be a promising technique in forensic examinations, where optical microscopy, micro‐infrared spectroscopy, and microspectrophotometry in the visible and UV range are used for identification and differentiation between paint traces. Often no organic pigments are detected using Fourier transform infrared spectroscopy, because their content in a trace is usually undetectable. Application of a micro‐Raman spectrometer equipped with several excitation lasers helps forensic experts in paint analysis enabling identification of main pigments. Three cases concerning comparative examination of car paint are discussed in detail. The comparison of Raman spectra of paint chips found on clothing of a victim or smears found on body of a damaged car to these of paint chips originated from the suspected car enabled us to identify the car involved in the accident. When no comparative material is available, the method can be useful in establishing the color and make of the car.     

In situ identification and analysis of automotive paint pigments using line segment excitation Raman spectroscopy: I. Inorganic topcoat pigments

Several applications of Raman spectroscopy in the forensic sciences have recently been demonstrated, but few have involved the analysis of paints. Undoubtedly, this is a reflection of the sample degradation problems often encountered when a visible or near-infrared laser is focused on a light-absorbing matrix. In this study, a dispersive CCD Raman spectrometer (785 nm) was used in a configuration which collected scattered light from an excitation region 3 mm long and 80 microm wide, instead of from a focused spot. Sample degradation was not observed, and Raman spectra of automotive paints of all colors were readily obtained. Most of the paints analyzed were U.S. automobile original finishes (1974 to 1989) from the Reference Collection of Automotive Paints, and the inorganic pigments examined were those which had been identified previously by infrared spectroscopy in finishes from this collection. Prominent peaks of rutile were observed in Raman spectra of light-colored nonmetallic finishes for both monocoats and basecoat/clearcoat systems, and the rutile peaks are readily distinguished from those of anatase. The lead chromates (Chrome Yellow, Molybdate Orange, and silica-encapsulated versions of the two) are the strongest Raman scatterers among the pigments examined, and Chrome Yellow was identified by Raman spectroscopy in several yellow and orange nonmetallic monocoats for which infrared absorptions of this pigment were not observed. Raman spectroscopy also provides an unequivocal means to distinguish Chrome Yellow from Molybdate Orange. This is particularly helpful for the analysis of paints containing light pigment loads or encapsulated pigments since the two formulations cannot be differentiated by infrared spectroscopy in such cases. The iron-containing pigments, ferric oxide, hydrous ferric oxide, and Prussian Blue, are relatively weak Raman scatterers, but peaks of hydrous ferric oxide and Prussian Blue were observed in spectra of paints containing heavy pigment loads. Because no sample preparation is required. Raman spectroscopy provides an excellent means to rapidly screen reference panels for the presence of certain pigments, and some examples of the differences in Raman spectra which occur for paints having similar colors are presented.     

拉曼光谱快速定性分析合成毒品

目的快速定性检测合成毒品;方法利用激光拉曼光谱仪对合成毒品进行检验;结果合成毒品苯丙胺、甲基苯丙胺、氯胺酮、麻黄碱、甲基麻黄碱均能被拉曼准确检出;结论激光拉曼光谱能对合成毒品快速定性分析。     

Raman Spectroscopic Differences between Ephedrine and Pseudoephedrine

Ephedrine (EPH) and pseudoephedrine (PSE) were studied by micro‐Raman spectroscopy and UV resonance Raman spectroscopy excited at 785 and 360 nm, respectively. Raman bands at approximately 245 and 410 cm^?1 for ephedrine have apparent differences from the same bands at approximately 215, 265, 350, 450, and 555 cm^?1 for pseudoephedrine, and these differences can be applied to distinguish between EPH and PSE. Additionally, density functional theory was used for the Raman calculations to obtain results identical to the experimental spectra. This work is expected to expand the applications of Raman spectroscopy in forensic science.     

TrueAllele® Genotype Identification on DNA Mixtures Containing up to Five Unknown Contributors

Computer methods have been developed for mathematically interpreting mixed and low‐template DNA. The genotype modeling approach computationally separates out the contributors to a mixture, with uncertainty represented through probability. Comparison of inferred genotypes calculates a likelihood ratio (LR), which measures identification information. This study statistically examined the genotype modeling performance of Cybergenetics TrueAllele^® computer system. High‐ and low‐template DNA mixtures of known randomized composition containing 2, 3, 4, and 5 contributors were tested. Sensitivity, specificity, and reproducibility were established through LR quantification in each of these eight groups. Covariance analysis found LR behavior to be relatively invariant to DNA amount or contributor number. Analysis of variance found that consistent solutions were produced, once a sufficient number of contributors were considered. This study demonstrates the reliability of TrueAllele interpretation on complex DNA mixtures of representative casework composition. The results can help predict an information outcome for a DNA mixture analysis.     

Principal component analysis and analysis of variance on the effects of Entellan New on the Raman spectra of fibers

During the forensic examination of textile fibers, fibers are usually mounted on glass slides for visual inspection and identification under the microscope. One method that has the capability to accurately identify single textile fibers without subsequent demounting is Raman microspectroscopy. The effect of the mountant Entellan New on the Raman spectra of fibers was investigated to determine if it is suitable for fiber analysis. Raman spectra of synthetic fibers mounted in three different ways were collected and subjected to multivariate analysis. Principal component analysis score plots revealed that while spectra from different fiber classes formed distinct groups, fibers of the same class formed a single group regardless of the mounting method. The spectra of bare fibers and those mounted in Entellan New were found to be statistically indistinguishable by analysis of variance calculations. These results demonstrate that fibers mounted in Entellan New may be identified directly by Raman microspectroscopy without further sample preparation.     

激光拉曼光谱对苯骈杂氮（堇）类药物的定性检测

目的 建立用拉曼光谱检测苯骈杂氮革类药物的定性方法.方法 利用激光拉曼光谱仪对10种苯骈杂氮革类药物进行检验.结果 10种苯骈杂氮（萆）类药物的主成分均能被拉曼准确检出.结论 该法能较好地对苯骈杂氮革类药物固体样品快速定性分析.     

Raman Spectroscopy as a Simple,Rapid, Nondestructive Screening Test for Methamphetamine in Clandestine Laboratory Liquids

Raman spectroscopy has found increased use in the forensic controlled substances laboratory in recent years due to its rapid and nondestructive analysis capabilities. Here, Raman spectroscopy as a screening test for methamphetamine in clandestine laboratory liquid samples is discussed as a way to improve the efficiency of a laboratory by identifying the most probative samples for further workup among multiple samples submitted for analysis. Solutions of methamphetamine in ethanol, diethyl ether, and Coleman fuel were prepared in concentrations ranging from 0.5% to 10% w/v, and Raman spectra of each were collected. A concentration‐dependant Raman peak was observed at 1003 per cm in each solution in 4% w/v and greater solutions. Case samples were analyzed and also found to reliably contain this diagnostic peak when methamphetamine was present. The use of this diagnostic indicator can save the forensic controlled substances laboratory time and materials when analyzing clandestine laboratory liquid submissions.     

激光共聚焦拉曼光谱技术在烟火药检验中的应用

目的建立微量烟火药的无损检验方法。方法利用激光共聚焦拉曼光谱技术对烟火药进行检验。结果烟火药的不同组分具有不同的拉曼特征散射峰。结论利用激光共聚焦拉曼光谱技术可以对烟火药中的不同组分进行检验,通过成像技术可得到不同组分的分布信息,该方法具有检验灵敏度高、无需样品制备、无损检材等优点。     

Highly Sensitive Detection of Blood by Surface Enhanced Raman Scattering,,

Raman spectroscopy for forensic body fluid analysis has received some attention due to the nondestructive nature and potential application for identification at the crime scene; however, its usage has been limited by low detection sensitivity. Surface enhanced Raman scattering (SERS) was evaluated for blood identification for forensic applications. Specifically, a SERS‐active substrate was fabricated, composed of nickel nanotips coated with Ag nanoparticles. Compared with a conventional substrate, the SERS substrate enhanced Raman scattering by more than two orders of magnitude and allowed blood to be identified to a dilution of 1:100,000. Blood was also successfully detected by swabbing the SERS substrate directly on mock evidence. Most importantly, Raman spectra obtained by swabbing the SERS substrate on blood stains were free of luminescence even when blood was deposited on luminescent fabrics. The nondestructive character, simplicity of sample preparation, and high sensitivity make SERS a prime candidate for field and laboratory‐based blood identification.     

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.     

Applications of a transportable Raman spectrometer for the in situ detection of controlled substances at border controls

A transportable Raman spectrometer was tested for the detection of illicit drugs seized during border controls. In a first step, the analysis methodology was optimized using reference substances such as diacetylmorphine (heroin), cocaine and amphetamine (as powder or liquid forms). Adequate focalisation distance and times of analysis, influence of daylight and artificial light sources, repeatability and limits of detection were studied. In a second step, the applications and limitations of the technique to detect the illicit substances in different mixtures and containers were evaluated. Transportable Raman spectroscopy was found to be adequate for a rapid screen of liquids and powders for the detection and identification of controlled substances. Additionally, it had the advantage over other portable techniques, such as ion mobility spectrometry, of being non-destructive and capable of rapid analysis of large quantities of substances through containers such as plastic bags and glass bottles.