Simultaneous identification and quantification of nitro-containing explosives by advanced chemometric data treatment of cyclic voltammetry at screen-printed electrodes

Progress on the Electrochemical Sensing of Illicit Drugs

Illicit drugs are harmful substances, threatening both health and safety of societies in all corners of the world. Several policies have been developed over time to deal with this illicit drug problem, including supply reduction and harm reduction policies. Both policies require on-site detection tools to succeed, i.e. sensors that can identify illicit drugs in samples at the point-of-care. Electrochemical sensors are highly suited for this task, due to their short analysis times, low cost, high accuracy, portability and orthogonality with current technologies. In this chapter, we evaluate the latest trend in electrochemical sensing of illicit drugs, with a focus on detection of illicit drugs in seizures and body fluids. Furthermore, we will also provide an outlook on the potential of electrochemistry in wearable sensors for this purpose.

A simple voltammetric method to evaluate the firing distance through determination of nitrocellulose

Nitrocellulose (NC) is the main component of propellants for small firearm ammunitions. Even though NC particles are ejected from gun barrels together with bullets and they are often recovered on close-to-muzzle targets, quantitative analysis of nitrocellulose for forensic purposes has been neglected so far. Moreover, although the presence of the nitroester groups makes nitrocellulose electroactive, its electrochemical determination has been poorly considered in literature. In this paper, a quantitative differential pulse voltammetric method for the analysis of nitrocellulose in targets is suggested, with the aim of estimating its concentration decay on targets with increasing the shooting distance. The presented method works in acetonitrile/ethanol/lithium perchlorate, has a LOQ of 4 mg L-1 and linearity up to 2000 mg L-1. Ammunitions loaded with a nitrocellulose/nitroglycerine-based gunpowder were discharged to draw a calibration curve for shooting distance determination in the range from 5 cm to 120 cm. The effect of possible interfering substances (water, nitroglycerine, nitroguanidine, nitrites) was evaluated, and results are compared with literature methods.

Unlocking the full potential of voltammetric data analysis: A novel peak recognition approach for (bio)analytical applications

Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Molecularly imprinted polymers - towards electrochemical sensors and electronic tongues

Molecularly imprinted polymers (MIPs) are artificially synthesized materials to mimic the molecular recognition process of biological macromolecules such as substrate-enzyme or antigen-antibody. The combination of these biomimetic materials with electrochemical techniques has allowed the development of advanced sensing devices, which significantly improve the performance of bare or catalyst-modified sensors, being able to unleash new applications. However, despite the high selectivity that MIPs exhibit, those can still show some cross-response towards other compounds, especially with chemically analogous (bio)molecules. Thus, the combination of MIPs with chemometric methods opens the room for the development of what could be considered a new type of electronic tongues, i.e. sensor array systems,  based on its usage. In this direction, this review provides an overview of the more common synthetic approaches, as well as the strategies that can be used to achieve the integration of MIPs and electrochemical sensors, followed by some recent examples over different areas in order to illustrate the potential of such combination in very diverse applications.

Electrochemistry of Intact Versus Degraded Cephalosporin Antibiotics Facilitated by LC-MS Analysis

The electrochemical detection of cephalosporins is a promising approach for the monitoring of cephalosporin levels in process waters. However, this class of antibiotics, like penicillins, is composed of chemically active molecules and susceptible to hydrolysis and aminolysis of the four membered β-lactam ring present. In order to develop a smart monitoring strategy for cephalosporins, the influence of degradation (hydrolysis and aminolysis) on the electrochemical fingerprint has to be taken into account. Therefore, an investigation was carried out to understand the changes of the voltammetric fingerprints upon acidic and alkaline degradation. Changes in fingerprints were correlated to the degradation pathways through the combination of square wave voltammetry and liquid chromatography quadrupole time-of-flight analysis. The characteristic electrochemical signals of the β-lactam ring disappeared upon hydrolysis. Additional oxidation signals that appeared after degradation were elucidated and linked to different degradation products, and therefore, enrich the voltammetric fingerprints with information of the state of the cephalosporins. The applicability of the electrochemical monitoring system was explored by the analysis of the intact and degraded industrial process waters containing the key intermediate 7-aminodeacetoxycephalosporanic acid (7-ADCA). Clearly, the intact process samples exhibited the expected core signals of 7-ADCA and could be quantified, while the degraded samples only showed the newly formed degradation products.

Electroanalysis and Spectroelectrochemistry of Nonaromatic Explosives in Acetonitrile Containing Dissolved Oxygen

In search of a rapid, low-cost, and solution-phase detection technique for explosives, the (spectro-)electrochemistry of compounds from two major nonaromatic classes, namely nitramines (RDX and HMX) and nitrate esters (pentaerythritol tetranitrate (PETN) and the plastic explosive composite Semtex 1A) in acetonitrile (AN) is reported. In electrochemical screening, 5 μg of explosive material was detectable in 10 s by multicomponent cyclic voltammetric (CV) analysis on unmodified glassy carbon under ubiquitous environmental influences (i.e., trace water and dissolved oxygen). The explosives were identified with high recoveries under a battery of proof-of-concept testing scenarios in various matrices. In AN containing naturally dissolved oxygen (approx. 2 mM), the superoxide radical is co-electrogenerated during analyte reduction. Free superoxide yields prominent signals that the explosives attenuate quantitatively. To gain further insight into the electrochemical transformation mechanism, spectroelectrochemistry was employed to monitor changes in ultraviolet (UV) absorbance during CV and identify transient intermediates and product species, which could be targeted by future chemical sensors. Overlapping UV spectra of multiple species are deconvoluted using a new strategy, spectral regional baselining, for time- and potential-resolved spectroelectrochemical (SEC) analysis. This study shows that dissolved oxygen, hitherto an interferent purposefully removed from the solution, can be exploited advantageously in electrochemical sensing. The work expands our understanding of high-explosive solution-phase chemistry and offers a novel route to signal transduction for the sensing of energetic materials.

Machine Learning Techniques for Chemical Identification Using Cyclic Square Wave Voltammetry

Electroanalytical techniques are useful for detection and identification because the instrumentation is simple and can support a wide variety of assays. One example is cyclic square wave voltammetry (CSWV), a practical detection technique for different classes of compounds including explosives, herbicides/pesticides, industrial compounds, and heavy metals. A key barrier to the widespread application of CSWV for chemical identification is the necessity of a high performance, generalizable classification algorithm. Here, machine and deep learning models were developed for classifying samples based on voltammograms alone. The highest performing models were Long Short-Term Memory (LSTM) and Fully Convolutional Networks (FCNs), depending on the dataset against which performance was assessed. When compared to other algorithms, previously used for classification of CSWV and other similar data, our LSTM and FCN-based neural networks achieve higher sensitivity and specificity with the area under the curve values from receiver operating characteristic (ROC) analyses greater than 0.99 for several datasets. Class activation maps were paired with CSWV scans to assist in understanding the decision-making process of the networks, and their ability to utilize this information was examined. The best-performing models were then successfully applied to new or holdout experimental data. An automated method for processing CSWV data, training machine learning models, and evaluating their prediction performance is described, and the tools generated provide support for the identification of compounds using CSWV from samples in the field.

A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures

This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model. In this manner, a set of standards based on a full factorial design, ranging from 0 to 300 mg·L^-1, was prepared to build the model; afterward, the model was validated with a completely independent set of standards. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.030 and 0.076 for the training and test subsets, respectively, and r ≥ 0.948.

Electronic Tongue-A Tool for All Tastes?

Electronic tongue systems are traditionally used to analyse: food products, water samples and taste masking technologies for pharmaceuticals. In principle, their applications are almost limitless, as they are able to almost completely reduce the impact of interferents and can be applied to distinguish samples of extreme complexity as for example broths from different stages of fermentation. Nevertheless, their applications outside the three principal sample types are, in comparison, rather scarce. In this review, we would like to take a closer look on what are real capabilities of electronic tongue systems, what can be achieved using mixed sensor arrays and by introduction of biosensors or molecularly imprinted polymers in the matrix. We will discuss future directions both in the sense of applications as well as system development in the ever-growing trend of low cost analysis.

A Simple and Inexpensive Electrochemical Assay for the Identification of Nitrogen Containing Explosives in the Field

We report a simple and inexpensive electrochemical assay using a custom built hand-held potentiostat for the identification of explosives. The assay is based on a wipe test and is specifically designed for use in the field. The prototype instrument designed to run the assay is capable of performing time-resolved electrochemical measurements including cyclic square wave voltammetry using an embedded microcontroller with parts costing roughly $250 USD. We generated an example library of cyclic square wave voltammograms of 12 compounds including 10 nitroaromatics, a nitramine (RDX), and a nitrate ester (nitroglycine), and designed a simple discrimination algorithm based on this library data for identification.

Surface-enhanced Raman spectroscopy combined with gold nanorods for the simultaneous quantification of nitramine energetic materials

A nanosensing method based on surface-enhanced Raman spectroscopy was proposed for simultaneous quantification of nitramine compounds, HMX and RDX.

Electronic tongue for nitro and peroxide explosive sensing

This work reports the application of a voltammetric electronic tongue (ET) towards the simultaneous determination of both nitro-containing and peroxide-based explosive compounds, two families that represent the vast majority of compounds employed either in commercial mixtures or in improvised explosive devices. The multielectrode array was formed by graphite, gold and platinum electrodes, which exhibited marked mix-responses towards the compounds examined; namely, 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), pentaerythritol tetranitrate (PETN), 2,4,6-trinitrotoluene (TNT), N-methyl-N,2,4,6-tetranitroaniline (Tetryl) and triacetone triperoxide (TATP). Departure information was the set of voltammograms, which were first analyzed by means of principal component analysis (PCA) allowing the discrimination of the different individual compounds, while artificial neural networks (ANNs) were used for the resolution and individual quantification of some of their mixtures (total normalized root mean square error for the external test set of 0.108 and correlation of the obtained vs. expected concentrations comparison graphs r>0.929).

A facile strategy applied to simultaneous qualitative-detection on multiple components of mixture samples: a joint study of infrared spectroscopy and multi-label algorithms on PBX explosives

We combined infrared spectroscopy with multi-label algorithms to propose a facile yet efficient strategy to realize simultaneous qualitative-detection on multiple components of mixture explosives without pre-separation.

Voltammetric classification of ciders with PLS-DA

Voltammograms recorded on the glassy carbon electrode (GCE) may be a chemical fingerprints of food samples, enabled distinguishing the origin of the considered products. In this work the objects of the study was 5 Polish ciders of various brands. For each sample 10 scans were recorded by DPV in the potential range between -0.2 and 1.0 V in Britton-Robinson buffer at pH 2.0. The signals preprocessing realized by baseline correction with 4-th degree polynomial and normalization (in 0 to 1 interval), performed to reduce problems with insufficient signal's repeatability associated with mechanical renovation of the electrode surface before each measurement. The PLS-DA classification models were built using the training set and then validated using the samples absent in the learning process. The final multi-class model with optimized complexity enables classification of the ciders with 100% sensitivity and specificity, with the exception of one cider, where specificity was 95% (for validation set).

Simultaneous determination of multiple components in explosives using ultraviolet spectrophotometry and a partial least squares method

We used UV spectrophotometry and a chemometric method to develop a novel method for the simultaneous determination of multiple components in explosives.

Supersensitive fingerprinting of explosives by chemically modified nanosensors arrays

The capability to detect traces of explosives sensitively, selectively and rapidly could be of great benefit for applications relating to civilian national security and military needs. Here, we show that, when chemically modified in a multiplexed mode, nanoelectrical devices arrays enable the supersensitive discriminative detection of explosive species. The fingerprinting of explosives is achieved by pattern recognizing the inherent kinetics, and thermodynamics, of interaction between the chemically modified nanosensors array and the molecular analytes under test. This platform allows for the rapid detection of explosives, from air collected samples, down to the parts-per-quadrillion concentration range, and represents the first nanotechnology-inspired demonstration on the selective supersensitive detection of explosives, including the nitro- and peroxide-derivatives, on a single electronic platform. Furthermore, the ultrahigh sensitivity displayed by our platform may allow the remote detection of various explosives, a task unachieved by existing detection technologies.

Coupling paper-based microfluidics and lab on a chip technologies for confirmatory analysis of trinitro aromatic explosives

A new microfluidic paper-based analytical device (μPAD) in conjunction with confirmation by a lab on chip analysis was developed for detection of three trinitro aromatic explosives. Potassium hydroxide was deposited on the μPADs (0.5 μL, 1.5 M), creating a color change reaction when explosives are present, with detection limits of approximately 7.5 ± 1.0 ng for TNB, 12.5 ± 2.0 ng for TNT and 15.0 ± 2.0 ng for tetryl. For confirmatory analysis, positive μPADs were sampled using a 5 mm hole-punch, followed by extraction of explosives from the punched chad in 30 s using 20 μL borate/SDS buffer. The extractions had efficiencies of 96.5 ± 1.7%. The extracted explosives were then analyzed with the Agilent 2100 Bioanalyzer lab on a chip device with minimum detectable amounts of 3.8 ± 0.1 ng for TNB, 7.0 ± 0.9 ng for TNT, and 4.7 ± 0.2 ng for tetryl. A simulated in-field scenario demonstrated the feasibility of coupling the μPAD technique with the lab on a chip device to detect and identify 1 μg of explosives distributed on a surface of 100 cm(2).

Cavity transport effects in generator–collector electrochemical analysis of nitrobenzene

Two types of generator–collector electrode systems, (i) a gold–gold interdigitated microband array and (ii) a gold–gold dual-plate microtrench, are compared for nitrobenzene electroanalysis in aerated aqueous 0.1 M NaOH.