Identification of Nitro Explosives by Direct Analysis in Real-Time Time-of-Flight Mass Spectrometry

Influence of ZnO morphology on the capability of portable paper-based electrospray ionization mass spectrometry to determine therapeutic drugs in complex matrices

Adsorbents play a significant role in enhancing the analytical sensitivity of target analytes in complex samples by mitigating matrix effects. In our recent report, ZnO stood out among various adsorbents to determine target therapeutic drugs in complex biological matrices when applied for portable paper-based electrospray ionization mass spectrometry (PPESI-MS). However, the influence of the morphology of ZnO on the performance of PPESI-MS is elusive. Herein, different morphologies of ZnO particles were prepared via co-precipitation or ultrasonic methods, and their capability to determine different therapeutic drugs in serum were systemically investigated. The results demonstrated that flower-shaped ZnO gave a superior capacity, and its analysis sensitivity was 2.9-12.8-fold higher than those achieved with other ZnO morphologies. Further characterization revealed that the unique performance of flower-shaped ZnO was closely associated with its favorable desorption behavior to drugs, small spray plume, and few spray emitters at the tip of coated paper substrate. To illustrate the potential of flower-shaped ZnO, its coated paper was used as a substrate for the determination of various drugs in complex matrices such as serum, and a limit of detection as low as 2 pg mL-1 was achieved. The corresponding recoveries ranged from 93.2% to 107.2%. The developed protocol is promising in high-sensitivity analysis of target drugs in complex sample matrices.

Selectivity of Explosives Analysis with Ambient Ionization Single Quadrupole Mass Spectrometry: Implications for Trace Detection

Ambient ionization (AI) is a rapidly growing field in mass spectrometry (MS). It allows for the direct analysis of samples without any sample preparation, making it a promising technique for the detection of explosives. Previous studies have shown that AI can be used to detect a variety of explosives, but the exact gas-phase reactions that occur during ionization are not fully understood. This is further complicated by differences in mass spectrometers and individual experimental set ups between researchers. This study investigated the gas-phase ion reactions of five different explosives using a variety of AI techniques coupled to a Waters QDa mass spectrometer to identify selective ions for explosive detection and identification based on the applied ambient ionization technique. The results showed that the choice of the ion source can have a significant impact on the number of ions observed. This can affect the sensitivity and selectivity of the data produced. The findings of this study provide new insights into the gas-phase ion reactions of explosives and could lead to the development of more sensitive and selective AI-based methods for their detection.

Plasma-based ambient mass spectrometry: Recent progress and applications

Ambient mass spectrometry (AMS) has grown as a group of advanced analytical techniques that allow for the direct sampling and ionization of the analytes in different statuses from their native environment without or with minimum sample pretreatments. As a significant category of AMS, plasma-based AMS has gained a lot of attention due to its features that allow rapid, real-time, high-throughput, in vivo, and in situ analysis in various fields, including bioanalysis, pharmaceuticals, forensics, food safety, and mass spectrometry imaging. Tens of new methods have been developed since the introduction of the first plasma-based AMS technique direct analysis in real-time. This review first provides a comprehensive overview of the established plasma-based AMS techniques from their ion source configurations, mechanisms, and developments. Then, the progress of the representative applications in various scientific fields in the past 4 years (January 2017 to January 2021) has been summarized. Finally, we discuss the current challenges and propose the future directions of plasma-based AMS from our perspective.

Interpol review of detection and characterization of explosives and explosives residues 2016-2019

This review paper covers the forensic-relevant literature for the analysis and detection of explosives and explosives residues from 2016-2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/Resources/Documents#Publications.

Diaminocyclohexane-Functionalized/Thioglycolic Acid-Modified Gold Nanoparticle-Based Colorimetric Sensing of Trinitrotoluene and Tetryl

Detection of explosive residues in soil and postblast debris is an important issue in sensor design for environmental and criminological purposes. An easy-to-use and low-cost gold nanoparticle (AuNP)-based colorimetric sensor was developed for the determination of nitroaromatic explosives, i.e., trinitrotoluene (TNT) and tetryl, capable of analyte detection at picomolar (pM) levels. The sensor nanoparticles were synthesized by functionalizing the negatively charged thioglycolic acid (TGA)-modified AuNPs with positively charged (±)- trans-1,2-diaminocyclohexane (DACH) at a carefully calculated pH. The working principle of the sensor is charge-transfer (CT) interaction between the electron-rich free amino (-NH₂) group of DACH and the electron-deficient -NO₂ groups of TNT/tetryl, added to possible nanoparticle agglomerization via electrostatic interaction of TNT-Meisenheimer anions with more than one cationic DACH-modified AuNP. The limit of detection (LOD) and limit of quantification (LOQ) of the sensor were 1.76 pM and 5.87 pM for TNT and 1.74 pM and 5.80 pM for tetryl, respectively. TNT, tetryl, and tetrytol, extracted from a nitroaromatic explosive-contaminated soil sample, were determined with the proposed sensor, yielding good recoveries. The sensor could be selectively applied to various mixtures of TNT with common energetic materials such as RDX, HMX, and PETN. Additionally, common soil ions (Cl^-, NO₃^-, SO₄^2-, K⁺, Mg²⁺, Ca²⁺, Cu²⁺, Fe²⁺, Fe³⁺, and Al³⁺) as well as detergents, sugar, sweeteners, acetylsalicylic acid (aspirin), caffeine, and paracetamol-based painkiller drugs, which may be used as camouflage materials for explosives, either had no adverse effects or removable interferences on the detection method. The developed method was statistically validated against a GC-MS literature method.