Direct Identification of Packaged Substances using the Agilent Resolve Handheld Raman Analyzer
Applications | 2023 | Agilent TechnologiesInstrumentation
Rapid, non-destructive identification of concealed substances is essential for law enforcement, border security, and industrial quality control. Handheld Raman analyzers capable of probing materials through barriers enable on-site screening of illicit drugs, hazardous chemicals, and controlled substances without opening or sampling packaging.
This study evaluated the Agilent Resolve handheld Raman analyzer in two modes: conventional surface Raman and spatially offset Raman spectroscopy (SORS) through-barrier. White granulated sugar served as a model substance to simulate weak Raman scatterers such as illicit drugs. Key goals included:
The Agilent Resolve handheld Raman analyzer employs an 830 nm Class 3B laser, a protective nose cap doubling as calibration standard, and on-board spectral libraries with user customization. Operators select “surface” or “through-barrier” scan modes via the software interface. Samples tested included sugar in:
Layer thickness was measured with a digital micrometer (0.001 mm resolution). Conventional scans used the orthogonal laser only, while SORS scans combined orthogonal and offset laser delivery.
In surface mode, sugar was correctly identified through up to 11 LDPE layers (460 µm). Beyond this, the algorithm began matching barrier polymers or waxes as primary components. In SORS mode, accurate identification extended to 67 layers (2.7 mm) of LDPE with match rates above 75%. Opaque paper sachets yielded 98% correct matches with SORS versus 93.5% in surface mode due to cellulose interference.
The Resolve analyzer’s SORS capability enables:
Advances may include integration with AI-driven spectral interpretation, expanded deep library coverage for novel psychoactive substances, hybrid multimodal imaging combining Raman with IR or fluorescence, and further miniaturization for drone-based inspections. Real-time data sharing and cloud-based analytics will enhance remote support and rapid decision making.
The Agilent Resolve handheld Raman analyzer demonstrates robust through-barrier identification of weak Raman scatterers. SORS mode outperforms conventional Raman by a factor of six in penetration depth, making it a valuable tool for field detection of concealed substances. Its speed, portability, and ease of use support a wide range of security, regulatory, and industrial applications.
1. Nicolson F. et al. J. Raman Spectrosc. 2017, 48(12), 1828–1838.
2. Jordan J. L. et al. J. Dynamic Behavior Mater. 2016, 2, 411–420.
3. Poh L. et al. Rheol. Acta 2022, 61, 701–720.
4. Omnexus. Definition of Haze, 2023.
5. Tang L. Agilent Technologies Application Note 5994-6693EN, 2023.
RAMAN Spectroscopy
IndustriesForensics
ManufacturerAgilent Technologies
Summary
Significance of the Topic
Rapid, non-destructive identification of concealed substances is essential for law enforcement, border security, and industrial quality control. Handheld Raman analyzers capable of probing materials through barriers enable on-site screening of illicit drugs, hazardous chemicals, and controlled substances without opening or sampling packaging.
Objectives and Study Overview
This study evaluated the Agilent Resolve handheld Raman analyzer in two modes: conventional surface Raman and spatially offset Raman spectroscopy (SORS) through-barrier. White granulated sugar served as a model substance to simulate weak Raman scatterers such as illicit drugs. Key goals included:
- Comparing detection depths of surface and through-barrier modes
- Assessing identification accuracy through plastic and opaque wrappers
- Determining the maximum barrier thickness for reliable detection
Methodology and Used Instrumentation
The Agilent Resolve handheld Raman analyzer employs an 830 nm Class 3B laser, a protective nose cap doubling as calibration standard, and on-board spectral libraries with user customization. Operators select “surface” or “through-barrier” scan modes via the software interface. Samples tested included sugar in:
- Single LDPE zip bag (40–60 µm thick)
- Cellophane wrap
- Paper sachet (130 µm thick)
- Stacked LDPE layers (up to 69 plies)
Layer thickness was measured with a digital micrometer (0.001 mm resolution). Conventional scans used the orthogonal laser only, while SORS scans combined orthogonal and offset laser delivery.
Results and Discussion
In surface mode, sugar was correctly identified through up to 11 LDPE layers (460 µm). Beyond this, the algorithm began matching barrier polymers or waxes as primary components. In SORS mode, accurate identification extended to 67 layers (2.7 mm) of LDPE with match rates above 75%. Opaque paper sachets yielded 98% correct matches with SORS versus 93.5% in surface mode due to cellulose interference.
Benefits and Practical Applications
The Resolve analyzer’s SORS capability enables:
- Rapid (<2 min) screening of concealed drugs in sealed plastic, tape, or paper wrappers
- Minimal operator training through on-screen guidance
- Library updates and custom entries for emerging threats
- Non-contact or vial-based analysis for hazardous samples
Future Trends and Possibilities
Advances may include integration with AI-driven spectral interpretation, expanded deep library coverage for novel psychoactive substances, hybrid multimodal imaging combining Raman with IR or fluorescence, and further miniaturization for drone-based inspections. Real-time data sharing and cloud-based analytics will enhance remote support and rapid decision making.
Conclusion
The Agilent Resolve handheld Raman analyzer demonstrates robust through-barrier identification of weak Raman scatterers. SORS mode outperforms conventional Raman by a factor of six in penetration depth, making it a valuable tool for field detection of concealed substances. Its speed, portability, and ease of use support a wide range of security, regulatory, and industrial applications.
Reference
1. Nicolson F. et al. J. Raman Spectrosc. 2017, 48(12), 1828–1838.
2. Jordan J. L. et al. J. Dynamic Behavior Mater. 2016, 2, 411–420.
3. Poh L. et al. Rheol. Acta 2022, 61, 701–720.
4. Omnexus. Definition of Haze, 2023.
5. Tang L. Agilent Technologies Application Note 5994-6693EN, 2023.
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