SERS-integrated centrifugal microfluidic platform for the detection and quantification of Chemical Warfare Agents in single-component solution and mixtures

• Published in: Sensors and actuators. B, Chemical Chemical, 2025-01, Vol.422, p.136698, Article 136698
• Main Authors: Zappalà, Giulia, Soufi, Gohar, Dumont, Elodie, Molander, Nora, Slipets, Roman, Thamdrup, Lasse Højlund Eklund, Andersson, Per Ola, Rindzevicius, Tomas, Boisen, Anja
• Format: Article
• Language: English
• Subjects: Automation; Centrifugal microfluidics (CM); Label-free detection; Nerve agents; On-site detection; SERS
• ISSN: 0925-4005
• DOI: 10.1016/j.snb.2024.136698

Chemical Warfare Agents (CWAs) are toxic chemicals. Among CWAs, nerve agents are lethal compounds at low concentrations, and, thus, there is the need to detect and quantify the danger. The combination of Surface-Enhanced Raman Spectroscopy (SERS) with centrifugal microfluidic (CM) systems is a possibility for a safer handling and a fast analysis of nerve agents. In this work, the SERS signal from single-component solutions and mixtures of Tabun (GA) and VX were analyzed with Au-capped silicon nanopillar (NP) SERS substrates integrated on a CM platform and recorded with a custom-built Raman System (RS). Univariate and multivariate analysis methods were applied for the quantification. Both GA and VX were detected and quantified individually with Partial Least Squares regression (PLSR) models, with LoD and LoQ values of 7.39 ppm and 22.17 ppm respectively for GA, and 7.13 ppm and 21.39 ppm for VX. Detection and quantification of GA and VX in mixtures was achieved with Supported Vector Machine (SVM), obtaining R2 of the prediction 0.87 and 0.95, respectively. The results obtained show the potential of the SERS-integrated CM platform combined with machine learning analysis as a reliable method for CWAs on-site detection and quantification and for national security applications in real-case scenarios. •Advancing nerve agent analysis by integration of SERS with centrifugal microfluidic.•Detecting Tabun and VX using innovative SERS substrates.•Accurate nerve agent quantification with machine learning algorithms.•Real-Case Scenario Application: Reliable on-site CWA detection for security.•Automation and Label-Free Detection: efficient analysis with automated processes.