Direct Determination of the Concentration of Nitric Acid Using Spatially Offset Raman Spectroscopy

Significance of the Topic

Nitric acid is a widely used strong mineral acid and oxidizing agent involved in industrial, laboratory, and commercial processes.
Its hazard level correlates directly with concentration, making rapid in situ identification critical for safety and risk management.

Objectives and Study Overview

This study aimed to develop and validate a library for concentration determination of nitric acid using Spatially Offset Raman Spectroscopy (SORS) with a handheld Raman analyzer.
Eight standard nitric acid samples ranging from 28% to 98% by volume were used to build a spectral reference library and test unknown samples at 32.5%, 65%, and 95%.

Methodology

Samples of nitric acid were prepared by diluting a 98% stock solution to defined concentrations and stored in clear and amber glass vials.
The Agilent Resolve handheld Raman analyzer was operated in SORS through-barrier mode, using default acquisition settings and full laser power.

Instrumentation

• Agilent Resolve handheld Raman analyzer
• Agilent Resolve Command fleet management software for library creation and deployment

Main Results and Discussion

Spectral features changed systematically with acid concentration due to varying water content and species distribution.
The custom library enabled clear discrimination of reference samples across the full concentration range.
Validation of the library against three verification samples produced match scores above 90%, demonstrating reliable identification at 32.5%, 65%, and 95%.

Benefits and Practical Applications

• Fast, direct, non-destructive analysis of hazardous acids within sealed containers for operator safety.
• Accurate concentration assessment to support hazard classification and handling protocols.
• Portable solution suitable for field and laboratory environments.

Future Trends and Opportunities

Advances in handheld Raman sensitivity may extend this approach to other corrosive or volatile chemicals.
Integration with automated fleet management systems could enable large scale screening in industrial or security settings.
Machine learning algorithms may enhance quantification accuracy and broaden library adaptability.

Conclusion

The SORS-based method with a handheld Raman analyzer and custom spectral library provides a rapid and reliable tool for determining nitric acid concentration in situ.
High match quality for unknown samples demonstrates its effectiveness for hazard assessment and process control.

References

1. Greenwood NN, Earnshaw A. Chemistry of the Elements. 2nd ed. Butterworth-Heinemann; 1997:465-471. ISBN 9780080379418.