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The continuing threats of military conflicts and terrorism may involve the misuse of chemical weapons. The present study aims to use environmental samples to find evidence of the release of such agents at an incident scene. A novel approach was developed for identifying protein adducts in plants. Basil (

New psychoactive substances (NPS) are synthetic derivatives of illicit drugs designed to mimic their psychoactive effects. NPS are typically not controlled under drug acts or their legal status depends on their molecular structure. Discriminating isomeric forms of NPS is therefore crucial for forensic laboratories. In this study, a trapped ion mobility spectrometry time-of-flight mass spectrometry (TIMS-TOFMS) approach was developed for the identification of ring-positional isomers of synthetic cathinones, a class of compounds representing two-third of all NPS seized in Europe in 2020. The optimized workflow features narrow ion-trapping regions, mobility calibration by internal reference, and a dedicated data-analysis tool, allowing for accurate relative ion-mobility assessment and high-confidence isomer identification. Ortho-, meta- and para-isomers of methylmethcathinone (MMC) and bicyclic ring isomers of methylone were assigned based on their specific ion mobilities within 5 min, including sample preparation and data analysis. The resolution of two distinct protomers per cathinone isomer added to the confidence in identification. The developed approach was successfully applied to the unambiguous assignment of MMC isomers in confiscated street samples. These findings demonstrate the potential of TIMS-TOFMS for forensic case work requiring fast and highly-confident assignment cathinone-drug isomers in confiscated samples.

There is an ongoing forensic and security need for rapid, on-scene, easy-to-use, non-invasive chemical identification of intact energetic materials at pre-explosion crime scenes. Recent technological advances in instrument miniaturization, wireless transfer and cloud storage of digital data, and multivariate data analysis have created new and very promising options for the use of near-infrared (NIR) spectroscopy in forensic science. This study shows that in addition to drugs of abuse, portable NIR spectroscopy with multivariate data analysis also offers excellent opportunities to identify intact energetic materials and mixtures. NIR is able to characterize a broad range of chemicals of interest in forensic explosive investigations, covering both organic and inorganic compounds. NIR characterization of actual forensic casework samples convincingly shows that this technique can handle the chemical diversity encountered in forensic explosive investigations. The detailed chemical information contained in the 1350–2550 nm NIR reflectance spectrum allows for correct compound identification within a given class of energetic materials, including nitro-aromatics, nitro-amines, nitrate esters, and peroxides. In addition, the detailed characterization of mixtures of energetic materials, such as plastic formulations containing PETN (pentaerythritol tetranitrate) and RDX (trinitro triazinane), is feasible. The results presented illustrate that the NIR spectra of energetic compounds and mixtures are sufficiently selective to prevent false-positive results for a broad range of food-related products, household chemicals, raw materials used for the production of home-made explosives, drugs of abuse, and products that are sometimes used to create hoax improvised explosive devices. However, for frequently encountered pyrotechnic mixtures, such as black powder, flash powder, and smokeless powder, and some basic inorganic raw materials, the application of NIR spectroscopy remains challenging. Another challenge is presented by casework samples of contaminated, aged, and degraded energetic materials or poor-quality HMEs (home-made explosives), for which the spectral signature deviates significantly from the reference spectra, potentially leading to false-negative outcomes.

The large numbers of 3,4-methylenedioxy-N-methylamphetamine (MDMA) formulations encountered by the police and border security necessitates the need for safe, rapid and reliable tests to be performed on-site. Near-infrared (NIR) spectroscopy is a promising technique for on-scene illicit-drug detection because of its rapid analysis, non-invasive nature, broad scope to detect various substances, and small-sized sensors suitable for portable operation. The NIR spectrum of MDMA shows an intriguing, intense peak at ∼2000 nm that was found characteristic for MDMA within a large set of drugs and drug-related substances. Herein, we show that this peak can be attributed to water molecules of crystallization in the MDMA lattice. Drying experiments showed that both an anhydrous and hydrated form of MDMA·HCl exists with significantly different NIR spectra. At ambient conditions, the anhydrous form converted back to the hydrated form within 2 months. Our data analysis model was able to identify MDMA·HCl in mixtures of both forms. Assessment of seized casework materials showed that the majority of MDMA·HCl in The Netherlands is of the hydrated type. This is explained by the use of water-containing concentrated hydrochloric acid in the final conversion step of MDMA-base to the hydrochloride salt in clandestine laboratories. These findings provide insight in the challenges associated with NIR-based identification of drugs that may appear in various crystalline forms. Awareness on the existence of these forms and the consequences of library and data-model design to cope with this phenomenon will increase the robustness of on-site NIR-based drug detection.

The increasing workload for forensic laboratories and the expanding complexity of the drug market necessitates efficient approaches to detect drugs of abuse. Identification directly at the scene of crime enables investigative forces to make rapid decisions. Additionally, on-site identification of the material also leads to considerable efficiency and cost benefits. As such, paperwork, transportation, and time-consuming analysis in a laboratory may be avoided. Near-infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR-based (1300-2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a99% true negative and93% true positive rate for heroin and MDMA. These results show that accurate on-site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory-based techniques to portable equipment operated on scene.

Illicit-drug production, trafficking and seizures are on an all-time high. This consequently raises pressure on investigative authorities to provide rapid forensic results to assist law enforcement and legal processes in drug-related cases. Ideally, every police officer is equipped with a detector to reliably perform drug testing directly at the incident scene. Such a detector should preferably be small, portable, inexpensive and shock-resistant but should also provide sufficient selectivity to prevent erroneous identifications. This study explores the concept of on-site drugs-of-abuse detection using a 1.8 × 2.2 mm2 multipixel near-infrared (NIR) spectral sensor that potentially can be integrated into a smartphone. This integrated sensor, based on an InGaAs-on-silicon technology, exploits an array of resonant-cavity enhanced photodetectors without any moving parts. A 100% correct classification of 11 common illicit drugs, pharmaceuticals and adulterants was achieved by chemometric modelling of the response of 15 wavelength-specific pixels. The performance on actual forensic casework was investigated on 246 cocaine-suspected powders and 39 MDMA-suspected ecstasy tablets yielding an over 90% correct classification in both cases. These findings show that presumptive drug testing by miniaturized spectral sensors is a promising development ultimately paving the way for a fully integrated drug-sensor in mobile communication devices used by law enforcement.

The capability of an ion trap mass spectrometer to store ions for an arbitrary amount of time allows the use of a single infrared (IR) laser to perform two-color double resonance IR–IR spectroscopic experiments on mass-to-charge (m/z) selected ions. In this single-laser IR2MS3 scheme, one IR laser frequency is used to remove a selected set of isomers from the total trapped ion population and the second IR laser frequency, from the same laser, is used to record the IR spectrum of the remaining precursor ions. This yields isomer-specific vibrational spectra of the m/z-selected ions, which can reveal the structure and identity of the initially co-isolated isomeric species. The use of a single laser greatly reduces the experimental complexity of two-color IR2MS3 and enhances its application in fields employing analytical MS. In this work, we demonstrate the methodology by acquiring single-laser IR2MS3 spectra in a forensic context, identifying two previously unidentified isomeric novel psychoactive substances (NPS) from a sample that was confiscated by the Amsterdam Police.

Both the increasing number and diversity of illicit-drug seizures complicate forensic drug identification. Traditionally, colorimetric tests are performed on-site, followed by transport to a laboratory for confirmatory analysis. Higher caseloads increase laboratory workload and associated transport and chain-of-evidence assurance performed by police officers. Colorimetric tests are specific only for a small set of drugs. The rise of new psychoactive substances therefore introduces risks for erroneous results. Near-infrared (NIR)-based analyzers may overcome these encumbrances by their compound-specific spectral selectivity and broad applicability. This work introduces a portable NIR analyzer that combines a broad wavelength range (1300–2600 nm) with a chemometric model developed specifically for forensic samples. The application requires only a limited set of reference spectra for time-efficient model training. This calibration-light approach thus eliminates the need of extensive training sets including mixtures. Performance was demonstrated with 520 casework samples resulting in a 99.6% true negative and 97.6% true positive rate for cocaine. Similar results were obtained for MDMA, methamphetamine, ketamine, and heroin. Additionally, 236 samples were analyzed by scanning directly through their plastic packaging. Also here, a >97% true positive rate was obtained. This allows for non-invasive, operator-safe chemical identification of potentially potent drugs of abuse. Our results demonstrate the applicability for multiple drug-related substances. Ideally, the combination of this NIR approach with other portable techniques, such as Raman and IR spectroscopy and electrochemical tests, may eventually eliminate the need for subsequent laboratory analysis; therefore, saving tremendous resources in the overall forensic process of confirmatory illicit drug identification.

Forensic drug laboratories are confronted with increasing amounts of drugs and a demand for faster results that are directly available on-site. In addition, the drug market is getting more complex with hundreds of new psychoactive substances (NPS) entering the market in recent years. Rapid and on-scene presumptive drug testing therefore faces a shift from manual colorimetric tests towards approaches that can detect a wider range of components and process results automatically. Electrochemical detection offers these desired characteristics, making it a suitable candidate for on-site drug detection. In this study, a two-step electrochemical sensor is introduced for the detection of MDMA and 2C-B. Firstly, a direct electrochemical analysis was performed to detect MDMA. Validation experiments on over 70 substances revealed that 2C-B was the only frequently encountered drug that gave a false positive result for MDMA in this first analysis. A second step using in-situ derivatization was subsequently introduced. To this end, formaldehyde was used for N-methylation of 2C-B thereby enhancing its electrochemical profile. The enriched electrochemical fingerprint in the second step allowed for clear differentiation between MDMA and 2C-B. The applicability of this approach was demonstrated with 71 ecstasy tablets seized by the Amsterdam Police. The MDMA/2C-B sensor correctly identified all 39 MDMA-containing tablets and 10 out of 11 tablets containing 2C-B. Most notably, correct results were also obtained for dark colored tablets in which both spectroscopic analysis and colorimetric tests failed due to obscured signals.

Both the increasing volume and diversity of drugs-of-abuse encountered by investigation services necessitates the need for fast on-scene detectors to detect and identify a broad range of substances. Near-Infrared (NIR) spectroscopy is suitable for presumptive drugs testing by miniaturized sensors implemented in portable devices. Currently, a myriad of different portable NIR spectrometers is available that utilize different wavelength ranges. This study presents a comparison of NIR spectra of frequently occuring drugs analyzed by five different devices. A 350 – 2500 nm range laboratory grade VIS-NIR spectrometer was used to gain insight in spectral ranges diagnostic for substances relevant in forensic science. Obtained spectra were compared to the output of portable spectrometers operating in the 740 – 1070 nm, 950 – 1650 nm, 1550 – 1950 nm and 1300 – 2600 nm range. The results yielded novel insights in the usability of individual spectrometers by visual inspection of NIR spectra as well as comparative statistics with reference substances. For MDMA detection, an instrument capable of detecting a highly abundant and specific peak at 2020 nm is beneficial whereas colored samples are more difficult to detect by lower wavelength range sensors. Relatively pure, lightly colored samples may be correctly characterized by all sensors. These findings may aid NIR spectrometer selection in forensic practice as well as future studies on instrument selectivity or cross-platform calibration transfer.

On‐scene drug detection is an increasingly significant challenge due to the fast‐changing drug market as well as the risk of exposure to potent drug substances. Conventional colorimetric cocaine tests involve handling of the unknown material and are prone to false‐positive reactions on common pharmaceuticals used as cutting agents. This study demonstrates the novel application of 740–1070 nm small‐wavelength‐range near‐infrared (NIR) spectroscopy to confidently detect cocaine in case samples. Multistage machine learning algorithms are used to exploit the limited spectral features and predict not only the presence of cocaine but also the concentration and sample composition. A model based on more than 10,000 spectra from case samples yielded 97% true‐positive and 98% true‐negative results. The practical applicability is shown in more than 100 case samples not included in the model design. One of the most exciting aspects of this on‐scene approach is that the model can almost instantly adapt to changes in the illicit‐drug market by updating metadata with results from subsequent confirmatory laboratory analyses. These results demonstrate that advanced machine learning strategies applied on limited‐range NIR spectra from economic handheld sensors can be a valuable procedure for rapid on‐site detection of illicit substances by investigating officers. In addition to forensics, this interesting approach could be beneficial for screening and classification applications in the pharmaceutical, food‐safety, and environmental domains., The novel application of 740‐1070 nm small wavelength range NIR spectroscopy to confidently detect cocaine in case samples is demonstrated. Multi‐stage machine learning algorithms are applied to exploit the limited spectral features and predict not only the presence of cocaine but also predict a concentration and sample composition. A model based on >10,000 spectra from case samples yielded 97% true positive and 98% true negative results. The practical applicability is shown on over 100 case samples not included in model design.

When considering incident investigations and security checks focused on energetic materials, there is an ongoing need for rapid, on-scene chemical identification. Currently applied methods are not capable of meeting all requirements, and hence, portable mass spectrometry is an interesting alternative although many instrumental challenges still exist. To be able to analyze explosives with mass spectrometry outside the traditional laboratory, suitable ambient ionization methods need to be developed. Ideally such methods are also easily implemented in the field requiring limited to no power sources, gas supplies, flow controllers, and heating devices. For this reason, the potential of SAWN (surface acoustic wave nebulization) for the ambient ionization and subsequent mass spectrometric (MS) analysis of organic explosives was investigated in this study. Excellent sensitivity was observed for nitrate-based organic explosives when operating the MS in negative mode. No dominant adduct peaks were observed for the peroxides TATP and HMTD with SAWN-MS in positive mode. The MS spectra indicate extensive fragmentation of the peroxide explosives even under the mild ionization conditions provided by SAWN. The potential of SAWN-MS was demonstrated with the correct identification of nitrate-based organic explosives in pre- and post-explosion case samples in only a fraction of the time and effort required for the regular laboratory analysis. Results show that SAWN-MS can convincingly identify intact organic energetic compounds and mixtures but that sensitivity is not always sufficient to detect traces of explosives in post-explosion residues. Electronic supplementary material The online version of this article (10.1007/s13361-019-02335-y) contains supplementary material, which is available to authorized users.

Chemical attribution typically aims to establish a link between material found at a crime scene and a person, location or other evidence. In the field of illicit drugs, chemical attribution signatures are usually impurity profiles. Extending these to metabolized samples would create new possibilities in forensic investigations. The present study explores the effect of human metabolism on the impurity profile of fentanyl, as representative of synthetic opioids. Two different methods (Gupta and Siegfried) were used to synthesize fentanyl, after which the samples were incubated with liver microsomes to mimic human metabolism. The impurity profiles have been characterized with gas chromatography-mass spectrometry (GC-MS), gas chromatography with flame ionization detector (GC-FID), liquid chromatography quadrupole-time of flight mass spectrometry (LC-Q-TOF-MS) and liquid chromatography orbitrap mass spectrometry (LC-Orbitrap-MS). It was found that GC-FID and LC-Orbitrap-MS can both be used to discriminate between the Gupta and Siegfried synthesis method. This holds both for the analyses performed before and after metabolism. In addition, principal component analysis (PCA) identified acetyl fentanyl as the most important marker compound. Associated detection limits are in the range of concentrations expected in case work. While acetyl fentanyl is not stable during metabolism, its discriminating potential is transferred to its metabolic product acetyl norfentanyl. In addition, the stable impurities phenylacetamide and 1-phenylethylpiperidin-4-ol were found to be significant classifiers. To implement the results in a forensic framework, linear discriminant analysis (LDA) was applied and used to establish likelihood ratios. To our knowledge, the present work demonstrates for the first time the possibility of chemical attribution of drugs through the analysis of metabolic trace levels in biological samples.

Analysis of isomeric mixtures is a significant analytical challenge. In the forensic field, for example, over 1000 new psychoactive substances (NPSs), comprising of many closely related and often isomeric varieties, entered the drugs-of-abuse market within the last decade. Unambiguous identification of the isomeric form requires advanced spectroscopic techniques, such as GC-Vacuum Ultraviolet Spectroscopy (GC-VUV). The continuous development of NPSs makes the appearance of a novel compound in case samples a realistic scenario. While several analytical solutions have been presented recently to confidently distinguish NPS isomers, the presence of multiple isomers in a single drug sample is typically not considered. Due to their structural similarities it is possible that a novel NPS coelutes with a known isomer and thus remains undetected. This study investigates the capabilities of VUV spectral deconvolution for peak detection and identification in incompletely resolved drug mixtures. To mimic worst case scenarios, severe coelution was deliberately induced at elevated GC temperatures. The deconvolution software was nevertheless able to correctly detect both substances, even in case of near-identical VUV spectra at almost full coelution. As a next step, spectra were subsequently removed from the reference library to simulate the scenario in which a novel substance was encountered for the first time in forensic case work. However, also in this situation the deconvolution software still detected the coelution. This work shows that a VUV library match score below 0.998 may serve as a warning that a novel substance may be present in a street sample.

Smokeless powders (SPs) are one of the most commonly used propellants for ammunition but can also be abused as energetic material in improvised explosive devices (IEDs) such as pipe bombs. After a shooting or explosion, unburnt or partially burnt particulates may be observed which can be used for forensic investigation. SPs comprise mainly nitrocellulose (NC) and additives. Therefore, the characterization of both NC and the additives is of significant forensic importance. Typically, the identification, classification, and chemical profiling of smokeless powders are based exclusively on the analysis of the additives. In this study, information regarding the NC base component was combined with the chemical analysis of the additives using two-dimensional liquid chromatography (2D-LC). The system combines size-exclusion chromatography (SEC) and reversed-phase liquid chromatography (RPLC) in an on-line heart-cut 2D-LC configuration. In the first dimension, the NC is characterized by its molecular-weight distribution (MWD) while being separated from the additives. The additives are then transferred to the second-dimension separation using a novel analyte-transfer system. In the second dimension, the additives are separated to obtain a detailed profile of the low-molecular-mass compounds in the SP. With this approach, the MWD of the NC and the composition of the additives in SP have been obtained within an hour. A discrimination power of 90.53% was obtained when studying exclusively the NC MWD, and 99.47% for the additive profile. This novel combination enables detailed forensic comparison of intact SPs. Additionally, no extensive sample preparation is required, making the developed method less labor intensive.

Handheld Raman spectroscopy is an emerging technique for rapid on‐site detection of drugs of abuse. Most devices are developed for on‐scene operation with a user interface that only shows whether cocaine has been detected. Extensive validation studies are unavailable, and so are typically the insight in raw spectral data and the identification criteria. This work evaluates the performance of a commercial handheld Raman spectrometer for cocaine detection based on (i) its performance on 0–100 wt% binary cocaine mixtures, (ii) retrospective comparison of 3,168 case samples from 2015 to 2020 analyzed by both gas chromatography–mass spectrometry (GC–MS) and Raman, (iii) assessment of spectral selectivity, and (iv) comparison of the instrument's on‐screen results with combined partial least square regression (PLS‐R) and discriminant analysis (PLS‐DA) models. The limit of detection was dependent on sample composition and varied between 10 wt% and 40 wt% cocaine. Because the average cocaine content in street samples is well above this limit, a 97.5% true positive rate was observed in case samples. No cocaine false positives were reported, although 12.5% of the negative samples were initially reported as inconclusive by the built‐in software. The spectral assessment showed high selectivity for Raman peaks at 1,712 (cocaine base) and 1,716 cm−1 (cocaine HCl). Combined PLS‐R and PLS‐DA models using these features confirmed and further improved instrument performance. This study scientifically assessed the performance of a commercial Raman spectrometer, providing useful insight on its applicability for both presumptive detection and legally valid evidence of cocaine presence for law enforcement., The performance of a handled Raman spectrometer for cocaine detection is evaluated by validation samples, spectral assessment, and retrospective comparison. Raman and GC–MS results of 3,168 cases samples from 2015 to 2020 were compared. Limits of detection were dependent of sample composition and varied between 10 and 40 wt% cocaine. A 97.5% true positive rate was observed in case samples. Instrument performance was assessed and further improved by a combined partial least square regression (PLS‐R) and discriminant analysis (PLS‐DA) model.

This study builds on the multicomponent analysis strategy for flash bangers which was previously introduced and where a representative sample set has been collected of a certain type of flash bangers. To expand the forensic strategy, elemental analysis of the plastic caps which are present in these items was performed. Both x-ray fluorescence (XRF) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) analysis was performed to explore the possibilities for differentiation. The inherent inhomogeneity of the plastics resulted in high variations, especially for LA-ICP-MS trace analysis. In addition, due to the lack of suitable reference materials the LA-ICP-MS results can only be used for qualitative comparisons. Although XRF is less sensitive it allows for semi-quantitative analysis and the effect of inhomogeneity is significantly reduced due to the larger sample areas. Therefore, XRF is the method of choice for elemental analysis of intact plastic caps. In this scenario initial differentiation based on visual examination is combined with elemental analysis to obtain the highest degree of discrimination. In post-explosive scenarios, using XRF is not as straightforward due the irregular shapes of the burned plastic cap residues and contamination by explosive residues. For the analysis of these post-explosive caps, LA-ICP-MS proved to be useful for characterization and differentiation. Overall, it was found that blue caps contain a considerable higher amount of elements than the white caps, mainly due to additives related to the coloring process. This limits differentiation for the flash bangers containing white caps. Therefore, isotope ratio mass spectrometry (IRMS) analysis was performed to increase the differentiation potential. Based on carbon and hydrogen isotope ratios additional sets could be distinguished, both for flash bangers containing white and blue caps, that otherwise have similar visual and elemental characteristics. With the elemental and isotopic analysis of the plastic caps, an analysis strategy has been introduced that is not based on the pyrotechnic charge and therefore provides a unique opportunity to perform characterization and differentiation of flash bangers in pre- and post-explosive casework.

List-based approaches for judicial control of synthetic drugs inevitably introduce a group of legal highs that do not fall under the scope of legislation but may exhibit similar effects and associated health risks as illicit substances. Differences between controlled and uncontrolled components may be as minor as a single molecular group rearrangement. This phenomenon complicated forensic drug analysis in recent years due to both the rise of new psychoactive substances (NPS), and selectivity limitations of the workhorse gas chromatography-mass spectrometry (GC−MS) technique, especially with respect to ring-isomers. Our study demonstrates the value of GC-solid deposition-Fourier-transform infrared spectroscopy (FTIR) as a complementary technique for NPS identification in multi-drug mixtures. The instrument design using direct deposition of the GC effluent on a cryogenically cooled ZnSe-disk allows for signal enhancement of minor constituents by collecting eluting peaks of multiple GC injections. Highly diagnostic spectra were obtained for all ortho, meta and para-isomers of fluoroamphetamine (FA), fluoromethamphetamine (FMA), methylmethcathinone (MMC) and methylethcathinone (MEC). Combined results of GC−MS and GC-solid deposition-FTIR revealed the presence of up to 11 individual NPS mixed together in liquid samples sold as research chemicals or room odorizer in The Netherlands. Sample compositions rapidly evolved over time with recently controlled substances such as 4-fluoroamphetamine (4-FA), pentedrone, ethylone and 4-methylethcathinone (4-MEC) being replaced by uncontrolled isomers or analogues as 2-fluoroamphetamine (2-FA), 2- or 4-fluoromethamphetamine (2-FMA, 4-FMA) and dimethylone. In 12 different samples all marketed under two brand names, a total of 9 different compositions were identified in samples from 2018 and 2019.

In this work, we present a novel probabilistic peak detection algorithm based on a Bayesian framework for forensic DNA analysis. The proposed method aims at an exhaustive use of raw electropherogram data from a laser-induced fluorescence multi-CE system. As the raw data are informative up to a single data point, the conventional threshold-based approaches discard relevant forensic information early in the data analysis pipeline. Our proposed method assigns a posterior probability reflecting the data point's relevance with respect to peak detection criteria. Peaks of low intensity generated from a truly existing allele can thus constitute evidential value instead of fully discarding them and contemplating a potential allele drop-out. This way of working utilizes the information available within each individual data point and thus avoids making early (binary) decisions on the data analysis that can lead to error propagation. The proposed method was tested and compared to the application of a set threshold as is current practice in forensic STR DNA profiling. The new method was found to yield a significant improvement in the number of alleles identified, regardless of the peak heights and deviation from Gaussian shape.

Infrared ion spectroscopy (IRIS), a mass-spectrometry-based technique exploiting resonant infrared multiple photon dissociation (IRMPD), has been applied for the identification of novel psychoactive substances (NPS). Identification of the precise isomeric forms of NPS is of significant forensic relevance since legal controls are dependent on even minor molecular differences such as a single ring-substituent position. Using three isomers of fluoroamphetamine and two ring-isomers of both MDA and MDMA, we demonstrate the ability of IRIS to distinguish closely related NPS. Computationally predicted infrared (IR) spectra are shown to correspond with experimental spectra and could explain the molecular origins of their distinctive IR absorption bands. IRIS was then used to investigate a confiscated street sample containing two unknown substances. One substance could easily be identified by comparison to the IR spectra of reference standards. For the other substance, however, this approach proved inconclusive due to incomplete mass spectral databases as well as a lack of available reference compounds, two common analytical limitations resulting from the rapid development of NPS. Most excitingly, the second unknown substance could nevertheless be identified by using computationally predicted IR spectra of several potential candidate structures instead of their experimental reference spectra.

In the Netherlands, the illegal use of powerful flash bangers is popular and as a result these items are frequently encountered in forensic casework. In collaboration with the Dutch police a representative sample set of the most frequently confiscated flash bangers, the Cobra 6 and Cobra 6 2G, has previously been collected also including imitation items. Classification of the different flash bangers was performed by analysing the pyrotechnic charge using capillary electrophoresis (CE) with indirect UV-detection. Two rapid CE methods were used to determine the anions and cations present in the pyrotechnic mixtures. Black and flash powders were easily distinguishable based on their main inorganic compositions,i.e., KNO3and KClO4, respectively. Differentiation of flash powders from the commercial and imitation pyrotechnic items was achieved by the identification of Ca2+and Mg2+cation traces in the imitation flash banger powders. Quantitative CE results were used to explore the possibilities to differentiate seized sets of flash bangers but this proved to be difficult for commercial items due to lack of impurities and uniform production processes. In addition, inherent inhomogeneity of the powders and incomplete sample extraction yielded a relative high measurement uncertainty within a set. For the imitation items potential for set-based differentiation was observed. Although the number of seized imitation sets was limited, a first step has been taken to classify pyrotechnic mixtures to provide additional information and intelligence in forensic casework of flash bangers.

Currently, forensic drug experts are facing chemical identification challenges with the increasing number of new isomeric forms of psychoactive substances occurring in case samples. Very similar mass spectra for these substances could easily result in misidentification using the regular GC-MS screening methods in combination with colorimetric testing in forensic laboratories. Building on recent work from other groups, this study demonstrates that GC-VUV is a powerful technique for drug isomer differentiation, showing reproducible and discriminating spectra for aromatic ring-isomers. MS and VUV show complementary selectivity as VUV spectra are ring-position specific whereas MS spectra are characteristic for the amine moieties of the molecule. VUV spectra are very reproducible showing less than 0.1 parts per thousand deviation in library match scores and therefore small spectral differences suffice to confidently distinguish isomers. In comparison, MS match scores gave over 10 parts per thousand deviation and showed significant overlap in match score ranges for several isomers. This poses a risk for false positive identifications when assigning compounds based on retention time and GC-MS mass spectrum. A strategy was developed, based on Kernel Density Estimations of match scores, to construct Receiver Operating Characteristic (ROC) curves and estimate likelihood ratios (LR values) with respect to the chemical differentiation of drug related isomers. This approach, and the added value of GC-VUV is demonstrated with the chemical analysis of several samples from drug case work from the Amsterdam area involving both compounds listed in Dutch drug legislation (3,4-MDMA; 3,4-MDA; 4-MMC; 4-MEC and 4-FA) as well as their unlisted and thus uncontrolled isomers (2,3-MDMA; 2,3-MDA; 2- and 3-MMC; 2- and 3-MEC and 2- and 3-FA).

Forensic examination of fire debris evidence is a notoriously difficult analytical task due to the complexity and variability of sample composition. The use of comprehensive two-dimensional gas chromatography with mass spectrometry detection (GC × GC–MS) allows the coupling of orthogonal retention mechanisms and therefore a high peak capacity.We demonstrate recent innovations in combining chemometric techniques for data reduction and feature selection, with evaluation of the evidence for forensic questions pertaining to the detection and subsequent classification of ignitable liquid residue (ILR) in fire debris samples. Chromatograms are divided into non-overlapping spatially delimited regions; for each of these regions a Local Ion Signature (LIS) is computed by summing the intensities, per nominal mass/charge over all points contained within each region. This yields a reduced feature space representing the original data as a set of consolidated ion traces. Subsequent feature selection is performed by evaluating the individual efficacy of each feature using a univariate score-based likelihood ratio (LR) approach for discriminating between pairs of same or different type samples. The retained features are used to model each ILR class using linear discriminant analysis (LDA).Results are demonstrated for 155 arson samples containing a diversity of substrate compounds and several known ignitable liquids. ILR detection is performed at 84% accuracy with fewer than 1% false positives followed by subsequent classification. Likelihood ratio distributions are presented referring to both detection and classification tasks.

Drug isomer differentiation has become a relevant problem in forensic drug testing laboratories as new psychoactive substances include many closely related and isomeric forms. Both legislative and public safety requirements demand unambiguous identification of the isomers. A novel approach for ring-isomeric differentiation using GC–MS by means of low energy Electron Ionization (EI) in combination with chemometric data analysis was developed. An ionization energy of 15 eV combined with a high efficiency EI source yields more information rich and thus discriminating mass spectra for ring-isomeric, cathinone-type drugs. Through multivariate statistics using Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) mass spectral data can be exploited to confidently distinguish isomeric classes. Including feature selection of the mass spectra further enhanced the discriminative power of these models. In this way, all examined classes of cathinone and fluoroamphetamine isomers could be robustly identified, even through their conventional 70 eV mass spectrum from a quadrupole-MS instrument. A characteristic Likelihood Ratio (LR) based indicator was developed to quantify the selectivity of the models which proved to be useful for comparison, optimization and identification purposes. The potential of the method was demonstrated with six forensic case samples, providing 100% correct isomer identification. In general, this new approach enables robust classification of drug isomers that is currently not possible with conventional GC–MS methods without the use of additional spectroscopic analyses.

As part of forensic toxicological investigation of cases involving unexpected death of an individual, targeted or untargeted xenobiotic screening of post-mortem samples is normally conducted. To this end, liquid chromatography (LC) coupled to high-resolution mass spectrometry (MS) is typically employed. For data analysis, almost all commonly applied algorithms are threshold-based (frequentist). These algorithms examine the value of a certain measurement (e.g., peak height) to decide whether a certain xenobiotic of interest (XOI) is present/absent, yielding a binary output. Frequentist methods pose a problem when several sources of information [e.g., shape of the chromatographic peak, isotopic distribution, estimated mass-to-charge ratio (m/z), adduct, etc.] need to be combined, requiring the approach to make arbitrary decisions at substep levels of data analysis. We hereby introduce a novel Bayesian probabilistic algorithm for toxicological screening. The method tackles the problem with a different strategy. It is not aimed at reaching a final conclusion regarding the presence of the XOI, but it estimates its probability. The algorithm effectively and efficiently combines all possible pieces of evidence from the chromatogram and calculates the posterior probability of the presence/absence of XOI features. This way, the model can accommodate more information by updating the probability if extra evidence is acquired. The final probabilistic result assists the end user to make a final decision with respect to the presence/absence of the xenobiotic. The Bayesian method was validated and found to perform better (in terms of false positives and false negatives) than the vendor-supplied software package.

Determination of eight drugs of abuse in blood has been performed using paper spray or extraction spray mass spectrometry in under 2 min with minimal sample preparation. A method has been optimized for quantification of amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine (MDA), 3,4-methylenedioxy-N-methylamphetamine (MDMA), 3,4-methylenedioxy-N-ethylamphetamine (MDEA), morphine, cocaine, and Delta 9-tetrahydrocannabinol (THC) from a single blood spot. Sample to sample variations of 1-5% relative standard deviation were achieved using stable isotope-labeled internal standards and tandem mass spectrometry. Limits of detection for all drugs were below typical physiological and toxicological levels. Paper spray and extraction spray each used less than 10 mu L of whole blood. These methods exhibit the potential for performing rapid and high-throughput assays for selective on-site multicompound quantitative screening of illicit drugs.

An important aspect of any crime scene investigation is to detect, secure and analyze trace evidence. Atomic force microscopy (AFM) is a nanotechnology that can be used to generate forensic information. This review aims to briefly explain principles of AFM and review potential forensic applications like age determination of bloodstains, fingermark examination, investigation of textile fibers, document forgery detection, gunshot and explosive residues analysis, and pressure sensitive adhesives investigation. Current techniques are highlighted and the usefulness of AFM is discussed. For the examination of gunshot, explosives and pressure sensitive adhesive residues AFM can determine elastic moduli, adhesion forces, energy dissipation, and dielectric properties of trace material, provide synoptic mapping of these characteristics and identify compositions. Phase imaging and force spectroscopy are important options but cannot unravel chemical identities. Forensic relevance of force spectroscopy for red blood cell age estimation is promising but remains to be fully explored. If not affected by surface roughness AFM height imaging may yield complementary information with respect to fingermark, textile and document examinations. For overlapping, (partially) erased marks or mixtures of biological traces phase imaging could provide composition information. If the chemical identity of trace components is important AFM may be combined with (surface/tip enhanced) Raman spectroscopy. Equipped with high resolution optical microscopy AFM(-Raman) technology may become a valuable forensic tool to characterize and understand trace transfer and persistence and to assess condition and age of evidence material. AFM could thus yield additional options for forensic association and assist in forensic analysis at activity level.

Studying links between triacetone triperoxide (TATP) samples from crime scenes and suspects can assist in criminal investigations. Isotope ratio mass spectrometry (IRMS) and gas chromatography (GC)-IRMS were used to measure the isotopic compositions of TATP and its precursors acetone and hydrogen peroxide. In total, 31 TATP samples were synthesized with different raw material combinations and reaction conditions. For carbon, a good differentiation and a linear relationship were observed for acetone–TATP combinations. The extent of negative (d13C) fractionation depended on the reaction yield. Limited enrichment was observed for the hydrogen isotope (d2H) values of the TATP samples probably due to a constant exchange of hydrogen atoms in aqueous solution. For oxygen (d18O), the small isotopic range and excess of water in hydrogen peroxide resulted in poor differentiation. GC-IRMS and IRMS data were comparable except for one TATP sample prepared with high acid concentration demonstrating the potential of compound-specific isotope analysis. Carbon IRMS has practical use in forensic TATP investigations. © 2016 American Academy of Forensic Sciences

A novel test sample for the spatially resolved quantification of illicit drugs on the surface of a fingerprint using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and desorption electrospray ionization mass spectrometry (DESI-MS) was demonstrated. Calibration curves relating the signal intensity to the amount of drug deposited on the surface were generated from inkjet-printed arrays of cocaine, methamphetamine, and heroin with a deposited-mass ranging nominally from 10 pg to 50 ng per spot. These curves were used to construct concentration maps that visualized the spatial distribution of the drugs on top of a fingerprint, as well as being able to quantify the amount of drugs in a given area within the map. For the drugs on the fingerprint on silicon, ToF-SIMS showed great success, as it was able to generate concentration maps of all three drugs. On the fingerprint on paper, only the concentration map of cocaine could be constructed using ToF-SIMS and DESI-MS, as the signals of methamphetamine and heroin were completely suppressed by matrix and substrate effects. Spatially resolved quantification of illicit drugs using imaging mass spectrometry is possible, but the choice of substrates could significantly affect the results.

Quantitative analysis using comprehensive two-dimensional (2D) gas chromatography (GC) is still rarely reported. This is largely due to a lack of suitable software. The objective of the present study is to generate quantitative results from a large GC x GC data set, consisting of 32 chromatograms. In this data set, six target components need to be quantified. We compare the results of conventional integration with those obtained using so-called "multiway analysis methods". With regard to accuracy and precision, integration performs slightly better than Parallel Factor (PARAFAC) analysis. In terms of speed and possibilities for automation, multiway methods in general are far superior to traditional integration. © 2003 Elsevier B.V. All rights reserved.

Ammonium nitrate (AN) is frequently encountered in explosives in forensic casework. It is widely available as fertilizer and easy to implement in explosive devices, for example by mixing it with a fuel. Forensic profiling methods to determine whether material found on a crime scene and material retrieved from a suspect arise from the same source are becoming increasingly important. In this work, we have explored the possibility of using isotopic and elemental profiling to discriminate between different batches of AN. Variations within a production batch, between different batches from the same manufacturer, and between batches from different manufacturers were studied using a total of 103 samples from 19 different fertilizer manufacturers. Isotope-ratio mass spectrometry (IRMS) was used to analyze AN samples for their (15)N and (18)O isotopic composition. The trace-elemental composition of these samples was studied using inductively coupled plasma-mass spectrometry (ICP-MS). All samples were analyzed for the occurrence of 66 elements. 32 of these elements were useful for the differentiation of AN samples. These include magnesium (Mg), calcium (Ca), iron (Fe) and strontium (Sr). Samples with a similar elemental profile may be differentiated based on their isotopic composition. Linear discriminant analysis (LDA) was used to calculate likelihood ratios and demonstrated the power of combining elemental and isotopic profiling for discrimination between different sources of AN.

Inverse gas chromatography (IGC) was applied for the determination of the surface characteristics of Tenax carbon fibers and Akzo Nobel Twaron fibers. Furthermore, IGC procedures for the determination of dispersive and acid-base interactions were validated. The data show that too high values for the dispersive component of the surface energy are obtained when the adsorption area occupied by a single adsorbed n-alkane molecule is estimated from parameters of the corresponding liquid. Comparable values are obtained when the Doris-Gray methodology (area per methylene unit) or measured probe areas are employed. For the fibers studied in this work meaningful Gibbs energy values of the acid-base interaction were only obtained with the polarizability approach. When the dispersive interaction of the polar probes with the fiber surface was scaled to the n-alkane interaction via surface tension, the boiling point, or the vapor pressure of the probes often negative acid-base interaction energies were found. From the temperature dependence of the Gibbs energy, the enthalpy of the acid-base interactions of various probes with the carbon and Twaron aramid fibers was determined. However, from these enthalpy values no meaningful acid-base surface parameters could be obtained. Generally, the limited accuracy with which these parameters can be obtained make the usefulness of this procedure questionable. Also the Gibbs energy data of acid-base interaction can provide a qualitative basis to classify the acidity-basicity of the fiber surface. This latter approach requires only a limited data set and is sufficiently rapid to enable the use of IGC as a screening tool for fibers at a production site. For several polar probes significant concentration effects on carbon fibers were observed. At very low probe loadings the interaction with the fiber surface suddenly increases. This effect is caused by the heterogeneity of the interaction energy of the active sites at the surface. A simple procedure to measure the adsorption isotherm at infinite dilution was developed. The determination of the concentration dependence of the interaction of an n-alkane, an acidic and a basic probe was incorporated in the IGC screening procedure of carbon fibers to monitor this heterogeneity.

In this work, a reliable and robust vacuum-​outlet gas chromatog.-​mass spectrometry (GC-​MS) method is introduced for the identification and quantification of impurities in trinitrotoluene (TNT)​. Vacuum-​outlet GC-​MS allows for short anal. times; the anal. of impurities in TNT was performed in 4 min. This study shows that impurity profiling of TNT can be used to investigate relations between TNT samples encountered in forensic casework. A wide variety of TNT samples were analyzed with the developed method. Dinitrobenzene, dinitrotoluene, trinitrotoluene and amino-​dinitrotoluene isomers were detected at very low levels (

After an explosion of pentaerythritol tetranitrate (PETN), its degradation products pentaerythritol trinitrate (PETriN), dinitrate (PEDiN) and mononitrate (PEMN) were detected using liquid chromatography-atmospheric-pressure chemical-ionization-mass spectrometry (LC-APCI-MS). Discrimination between post-explosion and naturally degraded PETN could be achieved based on the relative amounts of the degradation products. This information can be used as evidence when investigating a possible relationship between a suspect and a post-explosion crime scene. The present work focuses on accurate quantitation of PETN and its degradation products, using PETriN, PEDiN and PEMN standards specifically synthesized for this purpose. With the use of these standards, the ionization behavior of these compounds was studied, and a quantitative method was developed. Quantitation of PETN and trace levels of its degradation products was shown to be possible with accuracy between 85.7% and 103.7% and a precision ranging from 1.3% to 11.5%. The custom-made standards resulted in a more robust and reliable method to discriminate between post-explosion and naturally-degraded PETN. © 2014 Elsevier B.V.

Theoretical and experimental aspects of indirect UV detection are considered. Based on a mathematical treatment of the transport of ions through the capillary, resulting in an eigenvector-eigenvalue problem, some guidelines are formulated about how to increase efficiency and sensitivity in an indirect (UV) detection system. Also, the existence of system peaks can be explained properly. An experimental system consisting of seven amino acids as sample ions and salicylate at pH 11.0 as the UV-absorbing ion was chosen in order to compare theoretical and experimental results. Constructed electropherograms, produced with a computer program based on the above-mentioned mathematical treatment, are also presented and compared with experimental electropherograms.