Comprehensive Characterization of E-Cigarette Liquids

Significance of the topic

Electronic-cigarette liquids (e-liquids) compose a chemically complex matrix that directly determines the composition of the inhaled aerosol and therefore influences product quality, consumer exposure and regulatory classification. Comprehensive chemical characterization is essential for product development, quality control, regulatory compliance (for example nicotine monitoring), and safety assessments. Analytical approaches that combine broad, untargeted screening with confident confirmation of specific analytes from a single measurement increase laboratory efficiency and the information yield from limited samples.

Objectives and study overview

This application note demonstrates a single-injection workflow that integrates automated non-target discovery with targeted confirmation using full-scan gas chromatography/mass spectrometry (GC/MS). Commercial e-liquids obtained in Japan were diluted and analyzed on an Agilent 5977C GC/MSD. Data processing combined Agilent MassHunter Unknowns Analysis for automated component detection and spectral deconvolution with MassHunter Quantitative Analysis Target Deconvolution for targeted confirmation. Menthol and nicotine standards were spiked to evaluate confirmation performance in a realistic, complex matrix.

Experimental methodology

Sample preparation

- Two commercial e-cigarette liquids were diluted 1:10 (v/v) with dichloromethane.
- Menthol and nicotine were spiked to the samples at approximately 10 µg/mL prior to analysis.

Analytical approach and data processing

- Single GC/MS full-scan acquisition (m/z 30–400) was used to capture the entire volatile/semivolatile profile.
- Unknowns Analysis performed automated peak detection, spectral deconvolution and library searching (NIST23) for non-targeted component discovery.
- Target Deconvolution evaluated compound-specific spectral patterns from the same full-scan dataset to confirm menthol and nicotine against target library entries.

Used instrumentation

- GC/MS platform: Agilent 8890 GC coupled to Agilent 5977C GC/MSD.
- Column: Agilent J&W DB-624 UI, 30 m × 0.32 mm, 1.8 μm.
- Carrier gas: Helium, constant flow ~1.8 mL/min.
- Injection: 1 μL, split 20:1, inlet 250 °C.
- Oven program: 50 °C (2 min), ramp 10 °C/min to 240 °C, hold 10 min.
- Transfer line / ion source temperature: 250 °C; quadrupole 150 °C.
- Mass scan range: m/z 30–400 (full-scan).

Results and discussion

Overview of chromatographic profile

- Full-scan total ion chromatograms (TICs) revealed broad distributions of peaks across the run, reflecting major carrier solvents (propylene glycol and glycerin) together with numerous flavoring agents and additives. One sample showed clear menthol and synthetic cooling agents (WS-23, WS-3) as dominant flavor components.

Non-targeted discovery with Unknowns Analysis

- Automated component detection and spectral deconvolution extracted deconvoluted spectra across crowded regions that are difficult to resolve from the TIC alone.
- Library matching (NIST23) produced tentative identifications with generally high match factors for both major and minor constituents.

Representative identified compounds (summary)

- Major carriers: propylene glycol, glycerin.
- Mint/cooling and terpene-related flavorants: DL-menthol, D-carvone, eucalyptol, DL-isopulegol, menthol-related alcohols, methyl salicylate, trans-linalool oxide, D-limonene, vanillin.
- Other formulation additives/fixatives: triacetin, benzyl benzoate.

Resolving coelutions through deconvolution

- Spectral deconvolution separated overlapping signals (for example nicotine and triacetin in a congested region), reconstructing individual mass spectra for improved library matching and component recognition.
- The deconvolution approach improves detection sensitivity for trace components masked by dominant matrix peaks and reduces false negatives that arise from TIC-based review.

Target confirmation using Target Deconvolution

- Menthol and nicotine, spiked into the sample, were successfully confirmed from the same full-scan dataset using Target Deconvolution. The reported match scores were high (menthol ≈ 99.8; nicotine ≈ 94.6), demonstrating robust spectral agreement against reference library entries despite matrix complexity and potential coelution.
- This targeted confirmation used full-scan spectral pattern recognition rather than simple extracted-ion chromatograms or SIM, enabling reliable identification without additional targeted acquisitions.

Integrated workflow advantages and practical considerations

- A single full-scan acquisition supported both comprehensive discovery and confident confirmation, simplifying laboratory workflows and reducing sample consumption and instrument time.
- Tentative library identifications from Unknowns Analysis still benefit from orthogonal confirmation (authentic standards, retention-index checks, or alternate techniques) for regulatory reporting or absolute identification in forensic contexts.
- Limitations to consider include the dependence on library coverage and quality, matrix-driven ion suppression for low-level analytes, and the finite sensitivity of unit-resolution MS compared with high-resolution alternatives.

Benefits and practical applications

- Quality control and formulation verification: rapid profiling of carriers, flavorants and additives to confirm label claims or batch consistency.
- Regulatory and compliance testing: screening for presence/absence of controlled compounds such as nicotine in markets with restrictions.
- Product safety and toxicology screening: identification of unexpected reaction or degradation products and potential impurities.
- Research and development: flavor-profile characterization and candidate screening during formulation development.

Future trends and potential applications

- Integration with high-resolution mass spectrometry (HRMS) and accurate-mass libraries to improve elemental composition assignment and identification confidence for unknowns.
- Increased automation and machine-learning assisted spectral interpretation to accelerate deconvolution, reduce reviewer workload and improve identification of novel flavoring compounds.
- Expanded target libraries (including retention indices and in-house spectra) to increase confirmation reliability across diverse product matrices.
- Combined workflows where full-scan discovery guides follow-up targeted quantitation (SIM or MS/MS) for regulatory compliance or toxicant quantitation.

Conclusion

A single GC/MS full-scan acquisition processed with Agilent MassHunter Unknowns Analysis and Target Deconvolution can deliver both broad, non-targeted chemical discovery and confident targeted confirmation in complex e-cigarette liquid matrices. Spectral deconvolution improves detection and identification in crowded chromatographic regions, while target-focused spectral matching verifies analytically important compounds such as menthol and nicotine without requiring separate SIM or reanalysis. The integrated approach increases analytical throughput, reduces sample handling, and provides a practical strategy for QC, regulatory screening and product-safety investigations of vaping liquids.

References

• NIST23 Mass Spectral Library (used for library searching).
• Agilent 8890 GC and 5977C GC/MSD instrumentation and MassHunter software (Unknowns Analysis and Target Deconvolution) described within the application note.