Chemical Sensing and Analytical Methods for Forensic Applications

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Analytical Methods, Instrumentation and Miniaturization".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 3694

Special Issue Editor


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Guest Editor
Department of Forensic Science, Sam Houston State University, Huntsville, TX, USA
Interests: forensic sciences; analytical chemistry; forensic chemistry; trace chemical detection; solid phase microextraction; trace evidence; crime scene management

Special Issue Information

Dear Colleagues,

In forensic science, there is a high demand for rapid, easy-to-use, inexpensive, and non-destructive analytical methods with selective capabilities that could be efficiently used in presumptive or confirmatory testing of forensic evidence. With the paradigm shift in the chemical analysis of trace evidence, integrating chemical characteristics of physical evidence for intelligent investigation of crimes is one of the major focuses of this discipline.

This Special Issue aims to focus on the development of novel sensing or analytical systems that can accurately and reliably promote the use of trace evidence for high-quality crime scene investigation. Papers that address the various emerging technologies such as 3D printing, 3D scanning, and artificial intelligence (AI)-powered field chemical sensing systems are highly encouraged.

The topics of this Special Issue include, but are not limited to, the following:

  • Chemical sensing and analysis in forensic science;
  • Trace evidence detection;
  • Crime scene management;
  • Separation science for forensic chemistry;
  • Emerging technologies in trace chemical detection;
  • Artificial intelligence-powered field chemical sensors.

Prof. Dr. Jorn Yu
Guest Editor

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Published Papers (2 papers)

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Research

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11 pages, 488 KiB  
Article
A Deep Learning Approach to Investigating Clandestine Laboratories Using a GC-QEPAS Sensor
by Giorgio Felizzato, Nicola Liberatore, Sandro Mengali, Roberto Viola, Vittorio Moriggia and Francesco Saverio Romolo
Chemosensors 2024, 12(8), 152; https://doi.org/10.3390/chemosensors12080152 - 5 Aug 2024
Cited by 4 | Viewed by 1712
Abstract
Illicit drug production in clandestine laboratories involves the use of large quantities of different chemicals that can be obtained for legitimate purposes. The identification of these chemicals, including reagents, catalyzers and solvents, is crucial for forensic investigations. From a legal point of view, [...] Read more.
Illicit drug production in clandestine laboratories involves the use of large quantities of different chemicals that can be obtained for legitimate purposes. The identification of these chemicals, including reagents, catalyzers and solvents, is crucial for forensic investigations. From a legal point of view, a drug precursor is a material that is specific and critical to the production of a finished chemical and that constitutes a significant portion of the final molecular structure of the drug. In this study, a gas chromatography quartz-enhanced photoacoustic spectroscopy (GC-QEPAS) sensor—in conjunction with a deep learning model—was evaluated for its effectiveness in the detection and identification of interesting compounds for the production of amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA), phenylcyclohexyl piperidine (PCP), and cocaine. The GC-QEPAS sensor includes a gas sampler, a fast GC for separation, and a QEPAS detector, which excites molecules exiting the GC column using a quantum cascade laser to provide the infra-red (IR) spectrum. The on-site capability of the GC-QEPAS system offers significant advantages over the current instruments employed in this field, including rapid analysis, which is crucial in field operations. This allows law enforcement to quickly identify specimens of interest on site. The system’s performance was validated by taking into account the limit of detection, repeatability, and within-laboratory reproducibility. The results showed excellent repeatability and reproducibility for both the GC and QEPAS modules. The deep learning model, a multilayer perceptron neural network, was trained using IR spectra and retention times, achieving very high classification accuracy in the testing conditions. This study demonstrated the efficacy of the GC-QEPAS sensor combined with a deep learning model for the reliable identification of drug precursors, providing a robust tool for law enforcement during criminal investigations in clandestine laboratories. Full article
(This article belongs to the Special Issue Chemical Sensing and Analytical Methods for Forensic Applications)
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Review

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13 pages, 992 KiB  
Review
The Application of Molecularly Imprinted Polymers in Forensic Toxicology: Issues and Perspectives
by Susan Mohamed, Simone Santelli, Arianna Giorgetti, Guido Pelletti, Filippo Pirani, Paolo Fais and Jennifer P. Pascali
Chemosensors 2024, 12(12), 279; https://doi.org/10.3390/chemosensors12120279 - 23 Dec 2024
Cited by 1 | Viewed by 1207
Abstract
Molecularly imprinted polymers (MIPs) are synthetic receptors designed to selectively bind specific molecules, mimicking natural antibody–antigen interactions. Produced through polymerization around a target molecule (template), MIPs create imprints that confer high specificity and binding affinity upon template removal. Initially developed in the 1970s [...] Read more.
Molecularly imprinted polymers (MIPs) are synthetic receptors designed to selectively bind specific molecules, mimicking natural antibody–antigen interactions. Produced through polymerization around a target molecule (template), MIPs create imprints that confer high specificity and binding affinity upon template removal. Initially developed in the 1970s with organic polymers, MIPs now play critical roles in separation sciences, catalysis, drug delivery, and sensor technology. In forensic science, MIPs offer potential for sample preparation, pre-concentration, and analyte detection, especially with complex biological and non-biological matrices. They exhibit superior stability under extreme conditions, enabling their use in challenging forensic contexts such as detecting new psychoactive substances or trace explosives. Despite advantages like reusability and high selectivity, MIPs face limitations in forensic analysis due to their complex synthesis, potential template leakage, and non-specific binding. Moreover, the lack of standardized protocols limits their mainstream adoption, as forensic applications require validated, reproducible methods. This review systematically assesses MIPs in forensic toxicology, focusing on their current capabilities, limitations, and potential for broader integration into forensic workflows. Future research should address standardization and evaluate MIPs’ effectiveness in diverse forensic applications to realize their full potential. Full article
(This article belongs to the Special Issue Chemical Sensing and Analytical Methods for Forensic Applications)
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