Colby Edward Ott

Dogs are routinely utilized as chemical detectors within law enforcement, disaster response, military, and medical fields. Their excellent olfactory abilities, as well as their mobility, adaptability, and trainability, position them as an invaluable tool for real‐time odor detection. An emerging and specialized discipline in the forensic canine industry is the detection of electronic storage and mass storage devices. They are commonly referred to as electronic storage detection (ESD) canines, electronic device detection canines, digital evidence canines, electronic media detection dogs, and “digi” dogs. Trained in detecting electronic storage devices such as USB drives, SIM cards, and cell phones, ESD canines play an increasingly vital role supporting investigations involving cybercrime, child exploitation, fraud, and contraband detection in correctional facilities. Despite their proven operational success, the field remains limited by gaps in training—standardization, evaluation, and development of accurate training aids—as well as scientific validation of odor profiles emitted from devices of interest. Being deployed as a chemical sensor in forensics, ESD canines should be backed by scientific research that supports their reliability, similar to laboratory‐based detection methods. This perspective reviews the current state of ESD canines in forensic science, highlighting their biology, training, applications, and challenges. Future avenues of research are considered and discussed, with an emphasis on providing a wider breadth of understanding and scientific validity to the use of ESD canines and the science behind electronic device detection.

The realm of analytical chemistry continues to struggle with defining and evaluating the limit of detection in analytical methods in the sense that a multitude of definitions, criteria, caveats, and methods have been proposed, developed, and adopted across disciplines. The last decade has seen a surge in the growth of electrochemical methods and studies in the field of forensic science and forensic chemistry. While many disciplines within forensic science have established method validation guidelines, the historical and current lack of electrochemical methods within forensic laboratories throughout the United States has left a major gap in knowledge, inhibiting the adoption and utilization of electrochemistry, which may serve as a powerful tool in many subdisciplines of forensics. As such, this work begins this discussion by focusing first on the limit of detection (LOD), with application toward both qualitative and quantitative methods. Both inorganic (ferrocyanide and lead) and organic (diphenylamine, naltrexone, and acetaminophen) target analytes were analyzed via two common voltammetry methods: cyclic voltammetry and square-wave voltammetry. The LOD for each analyte was estimated and/or calculated following a variety of literature-described methods and compared. The accuracy and reliability of these LOD characteristics based on the experimental data is described herein along with suggestions and recommendations. This manuscript is intended to compare the resulting LOD values from various methods and provide a starting point for the incorporation of electrochemistry into the forensic science laboratory, beginning a focused discussion on the development of validation guidelines and parameters needed for the adoption of this technology in forensic laboratories in order to meet the standards required by the criminal justice system.

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.

Applications and advances in surface‐enhanced Raman spectroscopy (SERS) have grown over the last several years, demonstrating improvements in sensitivity and selectivity. Applications for SERS‐related techniques have been explored in many analytical disciplines including forensic applications. Drug chemistry and toxicology may benefit from the growth of SERS since many methods have demonstrated high sensitivity, potential for quantitative analysis, and portable instrumentation for onsite testing. SERS techniques have been developed using many substrates including nanoparticles and colloids; microfluidic devices; paper‐based substrates; electrodes; and wearable/flexible devices. These methods take advantage of the SERS phenomenon, providing more potential applications for Raman analysis and overcoming the traditional challenges of the technique. This is desirable for forensic drug chemistry applications which require screening and confirmatory approaches and analysis of mixtures with low weight percent contributions of analytes, as well as forensic toxicology, where matrix interferences, sensitivity requirements, and a growing introduction of novel drug entities pose challenges. Several chemometric approaches have been applied to Raman data to improve identification, classification, and quantification. These advances position SERS for incorporation into forensic chemistry laboratories. While some SERS applications are available commercially, widespread use of SERS in practicing forensic laboratories remains limited. Due to the requirements for use of analytical techniques in the courtroom, future studies for SERS should revolve around the assessment of validation parameters common in other analytical methods. SERS techniques that are rapid, simple, and inexpensive may be more quickly adapted for forensic testing, where use as advanced screening techniques is a clear avenue of research.This article is categorized under: Forensic Chemistry and Trace Evidence > Controlled and Emerging Drug Compounds Toxicology > New Psychoactive Substances Forensic Chemistry and Trace Evidence > Emerging Technologies and Methods

Forensic science relies on the use of multiple techniques in the assessment of evidence to increase the accuracy and reliability of the results. However, with the rapidly changing drug landscape due to the introduction of novel psychoactive substances, many traditional screening methods are no longer sensitive or selective enough for use. Additionally, many screening methods such as chemical color tests are prone to false positive and negative results and are subjective. Therefore, the goal of this dissertation was to develop a novel analytical scheme that can provide a more efficient, rapid, and sensitive method that will facilitate adoption in the laboratory and onsite in the field. To this end, electrochemistry and Raman spectroscopy were assessed independently for their use in orthogonal testing scenarios, and in tandem via spectroelectrochemical methods to improve both the sensitivity and selectivity of seized drug screening. A panel of 15 drug analytes and 15 diluent compounds comprising some of the most encountered analytes was considered. This panel was characterized via electrochemistry for use as the first tier in investigating a seized substance. Then normal Raman spectroscopy was explored as the second tier in an orthogonal analytical scheme. Both 785 nm and 1064 nm Raman systems were tested with the panel of analytes. The pure compounds were characterized prior to analysis of simulated mixture samples with binary mixtures prepared at 1:4, 1:7, 1:10, and 1:20 ratios. Finally, electrochemistry and Raman spectroscopy were combined into a third-tier technique: time-resolved spectroelectrochemistry. Both targeted and nontargeted electrochemical-surface enhanced Raman spectroscopy method (EC-SERS) was developed. The targeted EC-SERS method provided an analysis approach for fentanyl and fentanyl analogs, while also allowing for in situ generation of a SERS substrate with a silver electrode and simultaneous analysis of the sample. This method demonstrated excellent selectivity and sensitivity with a limit of detection for the most sensitive compound (4-ANPP) of 10 ng/mL. Additionally, differentiation of fentanyl analogs was demonstrated to be achievable. Various potentially interfering compounds were assessed including heroin, cocaine, methamphetamine, caffeine, quinine, and others. Quinine was the only compound observed to have significant interference with fentanyl detection. To demonstrate the fit-for-purpose of this method, authentic seized samples were analyzed from a forensic laboratory including both true fentanyl positive and true fentanyl negative samples. Using GC-MS and LC-MS/MS as ground-truth, an overall accuracy of ~88% was achieved for the detection of fentanyl within the seized samples. More importantly, the power of this

Analysis of gunshot residue currently lacks effective screening methods that can be implemented in real time at the crime scene. Historically, SEM‐EDS has been the standard for analysis; however, advances in technology have brought portable instrumentation to the forefront of forensic science disciplines, including the screening of GSR. This study proposes electrochemical methods with disposable screen‐printed carbon electrodes for GSR screening at the laboratory and points of care due to their rapid, cost‐efficient, and compact platform. GSR residues were extracted from typical aluminum/carbon adhesive collection stubs and analyzed via square‐wave anodic stripping voltammetry. Benchtop and portable electrochemical instruments were compared for the assessment and classification of authentic shooter samples by monitoring a panel of inorganic and organic GSR elements and compounds including lead, antimony, copper, 2,4‐dinitrotoluene, diphenylamine, nitroglycerin, and ethyl centralite. The evaluation included the assessment of figures of merit and performance measures from quality controls, nonshooter, and shooter data sets. Samples collected from the hands of 200 background individuals (nonshooters), and shooters who fired leaded ammunition (100) and lead‐free ammunition (50) were analyzed by the benchtop and portable systems with accuracies of 95.7% and 96.5%, respectively. The findings indicate that electrochemical methods are fast, sensitive, and specific for the identification of inorganic and organic gunshot residues. The portable potentiostat provided results comparable with the benchtop system, serving as a proof‐of‐concept to transition this methodology to crime scenes for a practical and inexpensive GSR screening that could reduce backlogs, improve investigative leads, and increase the impact of gunshot residues in forensic science.

The synthetic cathinones mephedrone (4-MMC) and 4-methylethcathinone (4-MEC) are two designer drugs that represent the rise and fall effect of this drug category within the stimulants market and are still available in several countries around the world. As a result, the qualitative and quantitative determination of ‘legal highs’, and their mixtures, are of great interest. This work explores for the first time the spectroelectrochemical response of these substances by coupling cyclic voltammetry (CV) with Raman spectroscopy in a portable instrument. It was found that the stimulants exhibit a voltammetric response on a gold screen-printed electrode while the surface is simultaneously electro-activated to achieve a periodic surface-enhanced Raman spectroscopy (SERS) substrate with high reproducibility. The proposed method enables a rapid and reliable determination in which both substances can be selectively analyzed through the oxidation waves of the molecules and the characteristic bands of the electrochemical SERS (EC-SERS) spectra. The feasibility and applicability of the method were assessed in simulated seized drug samples and spiked synthetic urine. This time-resolved spectroelectrochemical technique provides a cost-effective and user-friendly tool for onsite screening of synthetic stimulants in matrices with low concentration analytes for forensic applications.

LC-MS/MS and guest-host chemistry is a viable approach for the dual detection of organic and inorganic gunshot residue.