In this work we report the results of analysis of the acoustic signal generated by the interaction of a nanosecond laser pulse (30 mJ, 1064 nm) with various residues placed on a silica wafer. The signal was captured by a unidirectional microphone placed 30 mm from the laser-generated plasma. The examined sample classes, other than the clean wafer, included particles from soils and rocks, carbonates, nitro precursors, ash, coal, smeared diesel, and particles of explosives. We tested three types of explosives, namely PETN, RDX, and HMX, having different origins. For the explosives, the acoustic signal showed a faster rise, larger amplitude, different width, and attenuation compared with the other sample classes. By subtracting the acoustic signal from the wafer at the same position, obtained after four cleaning laser pulses, the contribution of echoes was eliminated and true differences between the residue and substrate became evident. Through four different features in the subtracted signal, it was possible to classify explosives without the presence of false positives; the estimated limit of detection was 15 ng, 9.6 ng, and 18 ng for PETN, RDX, and HMX, respectively, where the mass was extrapolated from nano-printed samples and LIBS spectra acquired simultaneously. Furthermore, HMX was distinguished from the other two explosives in 90% of the cases; diesel and coal were also recognized. We also found that explosives deposited through wet transfer behaved as inert substances for the tested masses up to 30 ng.

Lazic, V., Stankov, B., Andreoli, F., Pistilli, M., Menicucci, I., Ulrich, C., et al. (2026). Acoustic signatures in laser-induced plasmas for detection of explosives in traces. SENSORS, 26(2) [10.3390/s26020672].

Acoustic signatures in laser-induced plasmas for detection of explosives in traces

Gaudio, Pasqualino
2026-01-01

Abstract

In this work we report the results of analysis of the acoustic signal generated by the interaction of a nanosecond laser pulse (30 mJ, 1064 nm) with various residues placed on a silica wafer. The signal was captured by a unidirectional microphone placed 30 mm from the laser-generated plasma. The examined sample classes, other than the clean wafer, included particles from soils and rocks, carbonates, nitro precursors, ash, coal, smeared diesel, and particles of explosives. We tested three types of explosives, namely PETN, RDX, and HMX, having different origins. For the explosives, the acoustic signal showed a faster rise, larger amplitude, different width, and attenuation compared with the other sample classes. By subtracting the acoustic signal from the wafer at the same position, obtained after four cleaning laser pulses, the contribution of echoes was eliminated and true differences between the residue and substrate became evident. Through four different features in the subtracted signal, it was possible to classify explosives without the presence of false positives; the estimated limit of detection was 15 ng, 9.6 ng, and 18 ng for PETN, RDX, and HMX, respectively, where the mass was extrapolated from nano-printed samples and LIBS spectra acquired simultaneously. Furthermore, HMX was distinguished from the other two explosives in 90% of the cases; diesel and coal were also recognized. We also found that explosives deposited through wet transfer behaved as inert substances for the tested masses up to 30 ng.
2026
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore FIS/01
Settore PHYS-02/A - Fisica teorica delle interazioni fondamentali, modelli, metodi matematici e applicazioni
English
Acoustic; Detection; Explosives; Forensic; Laser; LIBS; Limit of detection; Sensitive; Traces
Lazic, V., Stankov, B., Andreoli, F., Pistilli, M., Menicucci, I., Ulrich, C., et al. (2026). Acoustic signatures in laser-induced plasmas for detection of explosives in traces. SENSORS, 26(2) [10.3390/s26020672].
Lazic, V; Stankov, B; Andreoli, F; Pistilli, M; Menicucci, I; Ulrich, C; Schnürer, F; Chirico, R; Gaudio, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/463737
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