Forensic Chemistry最新文献

英文中文

Characterizing nitrocellulose by nitration degree and molecular weight: A user-friendly yet powerful forensic comparison method for smokeless powders

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-24 DOI: 10.1016/j.forc.2024.100637

Rick S. van den Hurk , Ids B. Lemmink , Jade R. van Schaik , Annemieke W.C. Hulsbergen , Ron A.H. Peters , Bob W.J. Pirok , Arian C. van Asten

Smokeless powders (SPs) are commonly used as propellant for ammunition but are also used as explosive component in improvised explosive devices. Therefore, its chemical characterization is of high importance when reporting forensic explosives investigations to a court of law. While conventional analytical strategies focus on the characterization of the additives in SPs, only few methods consider the main explosive component in SP, nitrocellulose (NC).

In this study, a user-friendly analytical method was developed for characterizing NC in SPs. The method employs size-exclusion chromatography combined with ultraviolet (UV) and refractive index (RI) detection. Through the size separation, the SP additives are separated from the polymeric NC because of their lower molecular weight. The novel part of the system lies in the simultaneous measurement of the molecular-weight distribution (MWD) and the nitration degree, thus boosting the discriminating power obtained from a single analysis. The combined use of two detectors enables a highly specific analysis, because the ratio between the UV and RI signal intensities is directly correlated with the nitration degree of NC. Characterizing the nitrocellulose demonstrated high discriminating powers of 98.95 % for the MWD and 92.65 % for the nitration degree using a set of 20 SP products. Combined, all sample pairs in our sample set could be distinguished.

The proposed method is not limited to product classification that is obtained from additive profiles, and potentially offers individualization at batch level. This method provides high discriminating power while requiring little financial investment with regards to instrumentation and maintenance.

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引用次数: 0

Evaluation of the incorporation of µ-XRF SDD systems in analytical workflows of black electrical tapes

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-24 DOI: 10.1016/j.forc.2024.100638

Lacey Leatherland , Ruthmara Corzo , Charlotte Vogler , Addio Fiordigigli , Cedric Neumann , Tatiana Trejos

Micro-X-ray Fluorescence Spectrometry (µ-XRF) is a technique widely adopted in forensic laboratories that has recently experienced a significant improvement with silicon drift detectors (SDDs). However, the research lag in this area has not caught up with the emergent instrumental modernization. This study expands the current body of knowledge by addressing this gap and evaluating the optimal workflow to incorporate µ-XRF SDD methods in electrical tape examinations. The experimental design evaluates sample handling and chemical data interpretation when the tape needs to undergo latent fingerprint development. The dataset includes contemporary electrical tape from 45 rolls produced in four countries, seven manufacturers, ten brands, and various quality grades (high, medium, low); ten sections are sampled per roll. Pairwise comparisons (990) evaluate between-source discrimination and false inclusions. Also, the set contains five same-source rolls with 20 sections per roll to evaluate within-source variability and false exclusions (950 pairwise comparisons). Samples are examined by µ-XRF SDDs and three other conventional methods. Performance rates are reported for each technique alone and when used together to evaluate optimal combinations and analytical sequences. Due to high discrimination and classification abilities, it is recommended that µ-XRF analysis moves to the forefront of the analytical scheme after microscopic examination to optimize turnaround times, costs, and resources. Also, the study utilizes elemental ratio comparison intervals and quantitative similarity metrics that offer complementary information to reduce subjectivity in XRF spectral comparisons. The findings of this study are anticipated to assist forensic laboratories with improved protocols.

{"title":"Evaluation of the incorporation of µ-XRF SDD systems in analytical workflows of black electrical tapes","authors":"Lacey Leatherland , Ruthmara Corzo , Charlotte Vogler , Addio Fiordigigli , Cedric Neumann , Tatiana Trejos","doi":"10.1016/j.forc.2024.100638","DOIUrl":"10.1016/j.forc.2024.100638","url":null,"abstract":"<div><div>Micro-X-ray Fluorescence Spectrometry (µ-XRF) is a technique widely adopted in forensic laboratories that has recently experienced a significant improvement with silicon drift detectors (SDDs). However, the research lag in this area has not caught up with the emergent instrumental modernization. This study expands the current body of knowledge by addressing this gap and evaluating the optimal workflow to incorporate µ-XRF SDD methods in electrical tape examinations. The experimental design evaluates sample handling and chemical data interpretation when the tape needs to undergo latent fingerprint development. The dataset includes contemporary electrical tape from 45 rolls produced in four countries, seven manufacturers, ten brands, and various quality grades (high, medium, low); ten sections are sampled per roll. Pairwise comparisons (990) evaluate between-source discrimination and false inclusions. Also, the set contains five same-source rolls with 20 sections per roll to evaluate within-source variability and false exclusions (950 pairwise comparisons). Samples are examined by µ-XRF SDDs and three other conventional methods. Performance rates are reported for each technique alone and when used together to evaluate optimal combinations and analytical sequences. Due to high discrimination and classification abilities, it is recommended that µ-XRF analysis moves to the forefront of the analytical scheme after microscopic examination to optimize turnaround times, costs, and resources. Also, the study utilizes elemental ratio comparison intervals and quantitative similarity metrics that offer complementary information to reduce subjectivity in XRF spectral comparisons. The findings of this study are anticipated to assist forensic laboratories with improved protocols.</div></div>","PeriodicalId":324,"journal":{"name":"Forensic Chemistry","volume":"42 ","pages":"Article 100638"},"PeriodicalIF":2.6,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modification of screen-printed electrodes using gold nanostructures for SERS detection of low explosives

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-21 DOI: 10.1016/j.forc.2024.100636

Thinnapong Wongpakdee , Duangjai Nacapricha , Bruce McCord

This study explores a novel application of surface-enhanced Raman spectroscopy (SERS) as a highly sensitive analytical tool for forensic analysis. We utilized a screen-printed gold electrode (SPGE) as a SERS active material, integrated with a portable Raman instrument for the rapid detection of low explosives. To enhance sensitivity while ensuring ease of handling, we conducted ex situ electrodeposition of gold nanostructures on the SPGE surface prior to analysis. The targeted molecules, comprising potassium nitrate (KNO₃), potassium perchlorate (KClO₄), sodium benzoate (C₆H₅COONa), diphenylamine (DPA) with its nitro derivatives, methyl centralite (MC) and ethyl centralite (EC), were studied using the proposed methodology. The developed system successfully provided distinctive SERS spectra fingerprints for low explosives (black powder, black powder substitutes, and smokeless powder) within seconds of analysis time. This approach holds promise for rapid, efficient, and accurate forensic analysis in real-world scenarios.

引用次数: 0

Naked-eye sensor for rapid methamphetamine screening with analyte recovery

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-12 DOI: 10.1016/j.forc.2024.100634

Seiya Awata , Futoshi Kikuchi , Toru Oba

The feasibility of a simple and rapid test to detect trace amounts of methamphetamine (MA) based on host–guest molecular interactions is demonstrated. The macrocyclic host molecule, cucurbit[7]uril (CB[7]), encapsulates a single guest molecule of the indicator fluorescent dye, acridine orange (AO). Addition of MA to the mixture shifts the equilibrium by replacing the guest molecule, as reflected by the changes in AO fluorescence. Notably, the colors of 0 and 20 µM MA can be distinguished by the naked eye, and the sensitivity is 135 times higher than that of the conventional Simon’s reagent. Similar fluorescence changes have been observed in the AO•CB[7] assay between 15 and 3 °C in the pH range 6–8 in phosphate buffer. The CB[7] system can detect MA while excluding bulky amines and sugars. However, it is also sensitive to other MA-related compounds such as N-isopropylbenzylamine and dimethylsulfone. MA recovery from the host–guest complex solution was greater than 94 %, allowing more accurate analysis of valuable evidence after this rapid screening. These results indicate that the CB[7] supramolecular system for MA detection has the advantages of operational simplicity, rapidity, high sensitivity, and minimal sample consumption and is suitable for initial drug screening during field analysis.

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引用次数: 0

Spectroscopy and chemometrics for differentiation of sex in human head hair fibers

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-10 DOI: 10.1016/j.forc.2024.100632

Drew Mueller , Alexis Hecker , John V. Goodpaster

Human hair is one of the most common pieces of evidence in forensics, however, it lacks a non-destructive, time-efficient, methodology for qualitative information. With the already well-established method for fiber analysis in spectroscopy and the common presence of Fourier Transform Infrared (FTIR) and microspectrophotometry (MSP) instrumentation in forensics, this study proposes chemometric approach to differentiate hair fibers on the sex assigned at birth. The IR and MSP hair sample spectra from different sexes were collected and, following spectral pre-treatment and mid-level data fusion, were used to calibrate a neural network model with 99.6% accuracy and 99.4% validation accuracy through an external validation dataset. This approach provides a robust model with significant qualitative information for forensic investigations that can be easily applied in forensic labs across the world. These results represent a rather small population size which would need to be expanded for real-world forensic applications.

引用次数: 0

Non-targeted detection of cathinones by high-resolution mass spectrometry based on their fragmentation pattern prediction. Application to pyrrolidine analogues in a hair case of PV8

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-09 DOI: 10.1016/j.forc.2024.100630

José Manuel Matey , Luis Manuel Menéndez-Quintanal , Félix Zapata , Gemma Montalvo , Carmen García-Ruiz

Cathinones (i.e., beta-keto phenyl ethyl amines) are one of the most numerous and widespread categories among new psychoactive substances. A selective methodology based on diagnostic fragment criteria using high resolution mass spectrometry, is comprehensively evaluated. Based on the different fragmentation spectra that have been published in public databases such as mzCloud (www.mzcloud.org) and HighResNPS (www.highresnps.com), we have coded and evaluated the different analogues and substituents in the benzyl position (R₁), in the α-alkyl chain (R₃) and N-alkyl analogues (R₄ and R₅) for existing cathinones, especially focusing on tertiary amines containing a pyrrolidine ring. The proposed fragmentation pattern allows the prediction of the expected fragments for each type of cathinone. The detection of selective diagnostic fragments ions supports the identification among different cathinone analogues. In this work, the proposed methodology is extended from the primary data to the generation of peridate, through their conceptualization and proposed SQL searches. A real case of pyrrolidine cathinones not yet present on the illicit market or recently introduced is used as an example. Using this strategy and specific software, we were able to detect cathinones such as α-pyrrolidinoheptaphenone (PV8) in hair.

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引用次数: 0

In silico created fire debris data for Machine learning

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-06 DOI: 10.1016/j.forc.2024.100633

Michael E. Sigman , Mary R. Williams , Larry Tang , Slun Booppasiri , Nikhil Prakash

Attacking complex forensic problems, such as the classification of fire debris data as positive or negative for ignitable liquid residue (ILR), requires large amounts of training data if machine learning approaches are to be successful. This work examines the in-silico preparation of computed fire debris data for training a machine learning method to classify gas chromatography – mass spectrometry (GC–MS) data as positive or negative for ILR, and reports the outcome of validation tests on a set of laboratory-generated fire debris samples with known ground truth. A set of 240,000 total ion chromatograms (TIC) and total ion spectra (TIS) for fire debris (FD) samples were calculated in silico (IS). The IS FD sample set was balanced with 50% of the samples containing ignitable liquid residue (ILR) and substrate pyrolysis (SUB) contributions. The remaining 50% contained only SUB components. The ignitable liquids incorporated into the samples containing ILR were digitally evaporated to simulate weathering observed in experimental fire debris. The IS FD sample TIS were treated by principal component analysis (PCA) with centering and variance scaling and retaining 90% of the variance. A set of 1,117 experimental FD samples were projected into the IS FD PCA model. The recovered experimental FD TIS were compared to the TIS before projection by calculating the residual mean squared error (RMSE) for each sample as a test of the IS FD samples representation of experimental samples. The range of the RMSE was [ 0.012, 0.127] and the median RMSE was 0.029. Experimental FD samples where the recovered TIS had the larger RMSE values were not well-represented by the IS FD samples. The IS FD samples were randomly split into balanced sets for machine learning (ML) training (90%) and validation (10%). An XGBoost ML method, trained on the IS FD training data, was validated on the testing IS FD data, giving a receiver operating curve (ROC) with area under the curve (AUC) of 0.978. Validation of the model against the experimental FD data gave a lower ROC AUC of 0.845. Limiting the experimental data to samples in the lowest quadrant of RMSE values increased the ROC AUC to 0.90.

{"title":"In silico created fire debris data for Machine learning","authors":"Michael E. Sigman , Mary R. Williams , Larry Tang , Slun Booppasiri , Nikhil Prakash","doi":"10.1016/j.forc.2024.100633","DOIUrl":"10.1016/j.forc.2024.100633","url":null,"abstract":"<div><div>Attacking complex forensic problems, such as the classification of fire debris data as positive or negative for ignitable liquid residue (ILR), requires large amounts of training data if machine learning approaches are to be successful. This work examines the in-silico preparation of computed fire debris data for training a machine learning method to classify gas chromatography – mass spectrometry (GC–MS) data as positive or negative for ILR, and reports the outcome of validation tests on a set of laboratory-generated fire debris samples with known ground truth. A set of 240,000 total ion chromatograms (TIC) and total ion spectra (TIS) for fire debris (FD) samples were calculated in silico (IS). The IS FD sample set was balanced with 50% of the samples containing ignitable liquid residue (ILR) and substrate pyrolysis (SUB) contributions. The remaining 50% contained only SUB components. The ignitable liquids incorporated into the samples containing ILR were digitally evaporated to simulate weathering observed in experimental fire debris. The IS FD sample TIS were treated by principal component analysis (PCA) with centering and variance scaling and retaining 90% of the variance. A set of 1,117 experimental FD samples were projected into the IS FD PCA model. The recovered experimental FD TIS were compared to the TIS before projection by calculating the residual mean squared error (RMSE) for each sample as a test of the IS FD samples representation of experimental samples. The range of the RMSE was [ 0.012, 0.127] and the median RMSE was 0.029. Experimental FD samples where the recovered TIS had the larger RMSE values were not well-represented by the IS FD samples. The IS FD samples were randomly split into balanced sets for machine learning (ML) training (90%) and validation (10%). An XGBoost ML method, trained on the IS FD training data, was validated on the testing IS FD data, giving a receiver operating curve (ROC) with area under the curve (AUC) of 0.978. Validation of the model against the experimental FD data gave a lower ROC AUC of 0.845. Limiting the experimental data to samples in the lowest quadrant of RMSE values increased the ROC AUC to 0.90.</div></div>","PeriodicalId":324,"journal":{"name":"Forensic Chemistry","volume":"42 ","pages":"Article 100633"},"PeriodicalIF":2.6,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DART-HRMS analysis as a screening method for hallucinogenic mushrooms

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-05 DOI: 10.1016/j.forc.2024.100629

Vanessa Braga Galhego, Raquel Capilla Loureiro Alves de Santana, Cecília de Andrade Bhering, Ananda da Silva Antonio, Gabriela Vanini

The global drug abuse scene is dynamic. After COVID-19 psilocin-containing mushrooms (PCM) reemerged in the international scenario. To identify illicit drugs, multiple analytical methods must be employed including triage (e.g. colorimetric test) and confirmatory tests (e.g. GC–MS). In addition, in many cases, only samples that give positive results in the triage method are taken to the confirmatory ones. However, colorimetric methods have several drawbacks in the analysis of complex unusual samples, such as the PCM, which can produce false-negative results. This study evaluated the feasibility of the ambient ionization technique direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) as a triage method for the identification of PCM seized samples. A psilocin standard, edible mushrooms, and 5 seized PCM samples were used to establish the DART-HRMS instrumental setup required for psilocin analysis. The developed DART-HRMS method was compared to the triage method recommended for PCM screening analysis (Erlich’s test). While the analysis of psilocin solutions applied 300 V at the DART grid and carrier gas at 150 °C, the analysis of solid samples applied 300 V and 375 °C. All seized PCM samples presented negative results in Erlich’s test, while all of them were positive for psilocin by DART-HRMS. Based on the quality of the HRMS data it was possible to confirm that Erlich’s test results were false-negative for the seized samples. DART-HRMS presents itself as a fast, reliable, and trustworthy triage method for the qualitative identification of raw hallucinogenic mushrooms for criminal investigation.

{"title":"DART-HRMS analysis as a screening method for hallucinogenic mushrooms","authors":"Vanessa Braga Galhego, Raquel Capilla Loureiro Alves de Santana, Cecília de Andrade Bhering, Ananda da Silva Antonio, Gabriela Vanini","doi":"10.1016/j.forc.2024.100629","DOIUrl":"10.1016/j.forc.2024.100629","url":null,"abstract":"<div><div>The global drug abuse scene is dynamic. After COVID-19 psilocin-containing mushrooms (PCM) reemerged in the international scenario. To identify illicit drugs, multiple analytical methods must be employed including triage (e.g. colorimetric test) and confirmatory tests (e.g. GC–MS). In addition, in many cases, only samples that give positive results in the triage method are taken to the confirmatory ones. However, colorimetric methods have several drawbacks in the analysis of complex unusual samples, such as the PCM, which can produce false-negative results. This study evaluated the feasibility of the ambient ionization technique direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) as a triage method for the identification of PCM seized samples. A psilocin standard, edible mushrooms, and 5 seized PCM samples were used to establish the DART-HRMS instrumental setup required for psilocin analysis. The developed DART-HRMS method was compared to the triage method recommended for PCM screening analysis (Erlich’s test). While the analysis of psilocin solutions applied 300 V at the DART grid and carrier gas at 150 °C, the analysis of solid samples applied 300 V and 375 °C. All seized PCM samples presented negative results in Erlich’s test, while all of them were positive for psilocin by DART-HRMS. Based on the quality of the HRMS data it was possible to confirm that Erlich’s test results were false-negative for the seized samples. DART-HRMS presents itself as a fast, reliable, and trustworthy triage method for the qualitative identification of raw hallucinogenic mushrooms for criminal investigation.</div></div>","PeriodicalId":324,"journal":{"name":"Forensic Chemistry","volume":"42 ","pages":"Article 100629"},"PeriodicalIF":2.6,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Determining extent and distribution of methamphetamine in cars: Air vs. surface vs. fabrics

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-05 DOI: 10.1016/j.forc.2024.100628

Gemma L. Kerry , Kirstin E. Ross , G. Stewart Walker , Jackie Wright

Methamphetamine can be manufactured or smoked in vehicles resulting in contamination. In addition, the transportation of drugs between place of manufacture and distribution can lead to contamination. Subsequent passengers or drivers of contaminated vehicles could be exposed to thirdhand drugs. Individuals exposed to thirdhand contamination have shown adverse health symptoms including respiratory problems, headaches, and behavioural and cognitive issues. Therefore, it is important to determine the overall methamphetamine contamination extent of cars to protect public health. This study was undertaken to determine the extent and distribution of contamination on surfaces, in air and from porous materials in two cars that tested positive for methamphetamine. Air sampling was performed in two cars using two sorbent tube types, followed by solvent desorption, and analysis using liquid chromatography tandem mass spectrometry (LC–MS/MS). Additionally, surface wipe sampling and bulk material sampling was performed for one of the contaminated cars that was going to be destroyed. These results demonstrated that methamphetamine can be detected in air, on the surfaces of non-porous and porous materials and from within porous materials. Results also demonstrated that methamphetamine was still detected from a second, third and fourth wipe sampling event of a plastic surface, indicating that there is a necessity for further research on testing and remediation in cars.

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引用次数: 0

Differentiated factor expression by chemical class in the concentration of ignitable liquid residue by dynamic vapor microextraction

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry

Pub Date : 2024-12-05 DOI: 10.1016/j.forc.2024.100631

Mary Gregg , Jennifer Berry , Kavita Jeerage

Ignitable liquids (IL) are complex mixtures whose chromatographic profiles may vary considerably across chemical compound classes. Dynamic vapor microextraction (DVME) is an emerging technique with potential application for extracting and concentrating IL from fire debris. A previous study assessed the effects of 11 instrumental and debris factors on DVME performance by collecting chromatographic data from a designed experiment, but did not investigate whether factor effects had differential expression within individual chemical classes. In this study, that experimental data is reanalyzed to assess factor effects individually in each of five chemical classes relevant to IL identification (alkanes, cycloalkanes & alkenes, aromatic-alkylbenzenes, indanes, and polynuclear aromatics), and effects are compared to the results previously reported from the original analysis. Two new instrument settings (capillary vapor trap coating and temperature) are found to have significant class-specific effects, providing additional avenues of improving DVME performance, while the effect of collection volume is found to be discordant in one class (alkane) compared to all others. Effects from uncontrollable debris factors on DVME performance are also found to be partially mitigated in certain classes through optimal instrument settings, though “optimal” may depend on the sample being analyzed. This analysis offers new insight into DVME optimization and robustness, and provides a discussion on how experimental conclusions drawn from aggregate chromatographic data, without consideration of class-specific effects, may be incomplete.

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