Identification of Unknowns by GC-MS and LC-MS Using NIST Search with Commercial and User Libraries

Importance of the Topic

Identification of unknown organic compounds via gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) is critical in chemical research, manufacturing process monitoring, environmental analysis and quality control.

Objectives and Overview

This summary reviews the implementation of NIST Search software combined with commercial and proprietary spectral libraries at Eastman Chemical Company for reliable identification of unknowns. It describes library development, user training and hybrid search strategies to enhance hit rates across diverse laboratories.

Methodology and Instrumentation

The approach employs networked GC–MS and LC–MS systems across global sites, leveraging:

• Commercial libraries: NIST20, Wiley EI and MS/MS collections
• Crowd-sourced libraries: MoNA
• Proprietary Eastman corporate libraries, updated daily
• Hybrid search algorithms combining standard spectral matching and neutral loss screening
• Derivatization techniques (Me, TFA, TMS, TBDMS) and accurate mass measurements

Trained experts in a central mass spectrometry laboratory provide advanced analyses including chemical ionization, high-resolution MS/MS, micro-synthesis and custom sample preparation.

Main Results and Discussion

Implementation of NIST Search and corporate libraries enabled over 30 000 EI and 500 MS/MS hybrid searches, revealing:

• Significant improvement in identification success, including structurally related analogs
• Efficient identification workflows for users of varying expertise
• Rapid source tracking of contamination and spills via spectral comments
• Automated daily distribution of an expanding proprietary library for global consistency

Benefits and Practical Applications

The combined library and hybrid search strategy delivers:

• Accelerated unknown compound identification in research and production
• Enhanced troubleshooting in environmental and process monitoring
• Support for non-specialist chromatographers through intuitive search results

Future Trends and Opportunities

Ongoing developments include:

• Continual expansion of spectral libraries via targeted acquisition pipelines
• Integration of machine-learning tools for automated spectrum interpretation
• Community contributions to crowd-sourced databases to fill coverage gaps
• Enhanced coupling of accurate mass data with fragmentation algorithms

Conclusion

The NIST Search platform, augmented by commercial and corporate spectral libraries and hybrid search capabilities, represents a powerful solution for unknown identification by GC-MS and LC-MS across diverse industrial and research contexts.

References

1. Importance of NIST Search at Eastman
2. Eastman General Approach for Unknown Identification
3. Free Training Courses for GC-MS and LC-MS Unknown Identification
4. EI Hybrid Search Video and Handout
5. EI Hybrid Handout
6. Tandem Hybrid Search Video and Handout
7. Tandem Hybrid Handout
8. NIST Pipeline for Improving EI and MS/MS Libraries
9. MS Interpreter Correlating Structure to EI Spectrum
10. MS Interpreter Correlating Structure to EI Spectrum Handout
11. MS Interpreter Correlating Structure to MS/MS Spectrum
12. MS Interpreter Correlating Structure to MS/MS Spectrum Handout
13. Delta Mass Table of Values
14. MassBank of North America (MoNA)
15. MoNA Handout