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

Importance of the Topic

In modern analytical environments, accurate identification of unknown compounds by GC-MS and LC-MS is crucial for research, manufacturing, environmental monitoring, and quality control. The NIST Search software combined with comprehensive commercial and user-generated libraries provides a robust platform to rapidly recognize contaminants, process upsets, and novel molecules.

Objectives and Overview

This work presents Eastman Chemical Company’s strategy for routine unknown identification using NIST Search across distributed laboratories. It describes the spectrum libraries in use, user training initiatives, and the introduction of a hybrid search approach that extends identification capabilities beyond standard spectral matching.

Methodology and Instrumentation

Eastman operates approximately fifty GC-MS and LC-MS systems, primarily Agilent GC-MSDs, networked worldwide. Spectra are processed with NIST Search software accessing commercial EI and MS/MS libraries (NIST20, Wiley), the crowd-sourced MoNA database, and a proprietary Eastman corporate library updated daily. For challenging samples, the central mass spectrometry laboratory provides accurate mass measurements, chemical ionization, multiple derivatizations (Me, TFA, TMS, TBDMS), advanced sample preparation, micro-synthesis, and infusion MS/MS at varied collision energies to enrich the spectral database.

Main Results and Discussion

The hybrid search algorithm integrates conventional spectrum matching with neutral-loss comparisons, producing a hybrid score and DeltaMass to pinpoint molecular modifications. In over thirty thousand EI and five hundred MS/MS searches, this approach delivered significantly improved hit rates and uncovered relevant structural analogs. A dedicated pipeline for targeted acquisition and quality control ensures continuous growth of high-priority spectra, validated by multi-evaluator review and accurate-mass correlation tools.

Benefits and Practical Applications

• Rapid source identification of spills and contaminants in manufacturing and water monitoring using TOC-GC-MS workflows.
• Daily distribution of an up-to-date corporate library guarantees consistent access to new spectral entries across all facilities.
• Free web-based training and detailed handouts lower the barrier for non-expert users to leverage advanced search functions effectively.
• Hybrid search supports discovery of novel analogs, aids in fragmentation mechanism studies, and enhances routine QA/QC and R&D screening.

Future Trends and Potential Applications

Ongoing expansion of spectral libraries, incorporation of machine learning for pattern recognition, and increased community contributions will drive further enhancements. Advanced hybrid algorithms and accurate-mass structural interpretations promise deeper insights in fields such as metabolomics, petrochemical analysis, and untargeted screening.

Conclusion

NIST Search, reinforced by a blend of commercial and user-generated libraries, stands as an essential tool for unknown identification by GC-MS and LC-MS. The hybrid search methodology and continuous library curation markedly improve identification confidence and broaden analytical reach for diverse industrial and research challenges.

References

• Importance of NIST Search at Eastman
• Eastman General Approach for Unknown Identification
• Free Training Courses GC-MS and LC-MS Unknown Identification with NIST Search
• EI Hybrid Video
• EI Hybrid Handout
• Tandem Hybrid Video
• Tandem Hybrid Handout
• NIST Pipeline for Improving EI and Tandem Libraries
• MS Interpreter Correlating Structure to EI Spectrum Video
• MS Interpreter Correlating Structure to EI Spectrum Handout
• MS Interpreter Correlating Structure to MSMS Spectrum Video
• MS Interpreter Correlating Structure to MSMS Spectrum Handout
• Delta Mass Table of Values
• MoNA (MassBank of North America)
• Handout Describing MoNA