Objective:

Review the development, applications, strengths, and remaining challenges of comprehensive two-dimensional gas chromatography (GC×GC), as presented in The Analytical Scientist’s GC×GC Detective Stories series.

Approach:

• Development across generations: The series describes progress from early instrument and proof-of-concept development to broader applications and current priorities in study design, data processing, and interpretation.
• Applications and analytical value: It considers GC×GC use across fields including fuels, environmental monitoring, food, forensics, metabolomics, exposomics, and breath analysis.
• Remaining challenges: It identifies training, data handling, and standardization as current bottlenecks, and emphasizes selecting the method according to the analytical question.

Key Findings:

• GC×GC can reveal minor compounds that co-elute with more abundant compounds in one-dimensional separations.
• Structured two-dimensional plots can help interpret complex samples, including in process monitoring, clinical research, and regulatory settings.
• The article describes commercial systems as robust and identifies operator training, time-consuming and operator-dependent data processing, and inconsistent formats and procedures as current obstacles.
• The article identifies hands-on courses, shared tutorials and open data sets, vendor-independent processing tools, and agreed file formats as ways to address these obstacles.

Interpretation:

The article presents GC×GC’s ability to reveal compounds hidden by co-elution as its central strength, and identifies operator training, data handling, and standardization as remaining challenges.

Limitations:

• The supplied context is a narrative overview of The Analytical Scientist’s GC×GC Detective Stories series, rather than a report of a single study with methods or quantitative results.

Conclusion:

The article describes GC×GC as a mature technique with applications across multiple fields. Its future development is framed around improving user skills, data workflows, and standardization, while applying the technique selectively when a second dimension is needed.

Sources:

• Article context supplied by the user