Rapid and reliable discrimination of authentic nerve agents in complex environments is a critical, unsolved challenge for security and public safety. Current detection technologies are often limited by bulky instrumentation, prolonged analysis times, or validation restricted to simulants, hindering their real-world threat-monitoring capabilities. Here, we demonstrate a machine learning-enhanced colorimetric sensor array that overcomes these limitations. We employed a systematic data-driven approach using hierarchical clustering, analysis of variance, and correlation analysis to optimally select just six commercially available fluorescent dyes from an initial 29-candidate library. This optimized array was rigorously evaluated against five authentic nerve agents (GA, GB, GD, GF, VX) and a key simulant using a novel dual-mode (Visible/UV) illumination strategy. By quantifying colorimetric responses (RGB-to-ΔE₀₀), our linear discriminant analysis classifier achieved 100% classification accuracy. The sensor provides an instantaneous visual response and maintains discrimination capability down to 10 μM, markedly outperforming the 87.5% accuracy of visible-light-only detection. This study establishes a simple, low-cost, and scalable platform for the rapid, accurate discrimination of multiple authentic nerve agents. By integrating data-driven sensor design with robust visual analysis, our system provides a clear pathway toward next-generation portable technologies for real-time chemical threat surveillance.

This study investigates the design and experimental evaluation of Fe–B–Si-based bilayer composites engineered for dual shielding against gamma rays and thermal neutrons. The materials integrate a boron-enriched amorphous Fe matrix with surface coatings of high-Z fillers—lead (Pb) and tungsten (W)—dispersed in an epoxy resin. W or Pb powders (20–40 µm) were dispersed in epoxy resin at a high filler loading (60–70 wt% metal, approximately several tens to one by weight). This ensured a dense and uniform coating structure. The metallic fillers were high-purity (≥99.9%) powders. Gamma-ray attenuation was examined using ¹³⁷Cs and ⁶⁰Co sources at photon energies of 661.7, 1173, and 1332 keV, while thermal neutron shielding was assessed with a moderated Am-Be neutron source. The effects of boron concentration (13–21 at%) in the matrix and coating thickness (80–400 μm) were systematically evaluated. Increasing boron content markedly enhanced thermal neutron attenuation, reaching up to 29%, whereas Pb- and W-filled coatings achieved more than 85% gamma-ray attenuation at 661.7 keV. All measurements were repeated three times; standard deviations were below 2% across conditions, confirming reproducibility and indirectly indicating uniform coating dispersion. At 661.7 keV, the half-value and tenth-value layers (HVL/TVL) were derived from the measured linear attenuation coefficients to benchmark performance. Notably, W coatings delivered shielding efficiency comparable to Pb while offering advantages in environmental safety, mechanical robustness, and regulatory compliance. These results highlight the potential of Fe–B–Si bilayer composites as lightweight, scalable, and lead-free shielding materials for aerospace electronics, portable radiation protection devices, and modular panels for satellites and nuclear facilities.