Combined Raman and LIBS Detection System for Threat Agents
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current threat detection methods are inefficient and labor-intensive, relying on separate instrumentation for detection and identification of threat agents, with limitations in sensitivity and specificity, particularly in the use of Raman and LIBS spectroscopy for airborne and biological threats.
Innovation Solution
A combined Raman and LIBS system optimized for threat detection, utilizing structured illumination and chemometric spectral processing to enhance sensitivity and specificity, allowing for simultaneous Raman and LIBS data analysis without reagents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If separate instrumentation is used for detection and identification of threat agents, then detection coverage is broad, but detection efficiency and productivity are low
Solution Approach 1:
The patent combines Raman spectroscopy and LIBS techniques into a single integrated system that performs both detection and identification functions simultaneously. The system uses a shared optical path, detector, and processing unit to acquire both molecular fingerprint data (Raman) and elemental composition data (LIBS) from the same sample, thereby improving productivity while managing device complexity through unified architecture
2Measurement precision
If Raman spectroscopy is used for threat agent identification, then molecular specificity is high, but sensitivity to certain threats is insufficient
Solution Approach 1:
The patent creates a composite analytical approach by fusing Raman spectroscopy data with LIBS data. The Raman component provides molecular specificity through vibrational fingerprinting, while the LIBS component contributes elemental sensitivity through atomic emission spectroscopy. The chemometric fusion of these two complementary data types produces a combined detection system with both high specificity and high sensitivity, overcoming the limitations of either technique alone
3Reliability
If LIBS is used for threat agent detection, then elemental sensitivity is high, but molecular specificity is reduced
Solution Approach 1:
The patent creates a composite analytical approach by fusing Raman spectroscopy data with LIBS data. The Raman component provides molecular specificity through vibrational fingerprinting, while the LIBS component contributes elemental sensitivity through atomic emission spectroscopy. The chemometric fusion of these two complementary data types produces a combined detection system with both high specificity and high sensitivity, overcoming the limitations of either technique alone
4Ease of operation
If conventional spectroscopic methods are used for identification, then reagent-free detection is achieved, but false positives occur due to background interference
Solution Approach 1:
The patent introduces chemometric spectral processing algorithms as an intermediary between the raw spectral data and the final identification result. These algorithms process and analyze the fused Raman and LIBS spectral data, applying pattern recognition and statistical methods to distinguish true threat signals from background interference. This intermediary processing layer maintains the simplicity of reagent-free detection while significantly reducing false positives through intelligent data analysis
Data Source
AI summary
In one embodiment, the disclosure relates to a method for interrogating a sample by: illuminating a first region of the sample with a first illumination pattern to obtain a plurality of first sample photons; illuminating a second region of the sample with a second illumination pattern to obtain a plurality of second sample photons; processing the plurality of first sample photons to obtain a characteristic atomic emission of the first region and processing the plurality of second sample photons to obtain a Raman spectrum; and identifying the sample through at least one of the characteristic atomic emission of the first region or the Raman spectrum of the second region of the sample.