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Updated: May 15, 2025

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants
Published on: September 23, 2013
Study on precise identification of remote bacterial species using multi-temporal LIBS optimized by plasma electron
Jiahui Liang1, Fei Chen1, Zhihui Tian2
1State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan, China; Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, China.
Background:
Laser-Induced Breakdown Spectroscopy (LIBS) has demonstrated significant potential in microbial detection due to its rapid, non-contact, and multi-element analytical capabilities. However, remote detection is hindered by challenges such as signal attenuation and the high similarity of spectral features, which reduce classification accuracy. To address these issues, this study proposes a multi-temporal LIBS remote identification method optimized based on the plasma electron temperature coefficient of variation (CVT). By analyzing CVT values across different delay ranges, optimal time delays were selected and combined to amplify spectral differentiation, thereby improving classification performance.
Results:
A coaxial-design LIBS telemetry system with adjustable focus was constructed, and multi-substrate telemetry testing was conducted on 10 common pathogenic bacteria at distances of 5 m and 10 m. By optimizing multiple temporal delays within the 100-1000 ns range, the classification performance of single-temporal, dual-temporal, and multi-temporal spectral combinations was evaluated. The results showed that the multi-temporal approach improved the classification performance across all substrates. At a distance of 5 m, a 100 % identification rate was achieved for all substrates, with Precision, Recall, and F1-score all reaching 1.0. At 10 m, the identification rate for the aluminum substrate increased from 76 % to 93 %. In addition, the contribution of the four major elements, Ca, Na, C, and K, was found to account for up to 60 % of the classification results.
Significance And Novelty:
It is demonstrated that the CVT-optimized multi-temporal LIBS technology effectively overcomes the signal attenuation bottleneck at long distances, significantly enhancing the robustness and analytical capability of remote microbial identification. This approach provides a novel method for remote detection in areas such as public safety, medical diagnostics, and military defense.
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