Ion Mobility, HPLC, LC/TOF, LC/HRMS, LC/MS, LC/MS/MS, LC/QQQ, SFC, LC/SQ
IndustriesEnvironmental, Food & Agriculture, Forensics , Proteomics , Metabolomics, Clinical Research, Lipidomics
ManufacturerWaters
Importance of the topic
The development of Supercritical Fluid Chromatography (SFC), in particular ultra-performance SFC (UPC2/UHPSFC), has revolutionized separation science by combining the advantages of gas and liquid chromatography with a green mobile phase based on CO2. Its high speed, low solvent consumption, and compatibility with mass spectrometry make SFC a powerful tool across many fields of analytical chemistry, such as pharmaceuticals, food safety, environmental monitoring, natural products, metabolomics, lipidomics, and traditional Chinese medicine quality control.
Aims and overview
This compendium reviews recent advances (2014–2020) in SFC separations and hyphenation with mass spectrometry, covering:
- Chiral and achiral analyses, including pharmaceuticals, agrochemicals, and natural chiral compounds.
- Greener, high-throughput quantification of vitamins, carotenoids, lipids, and other biomolecules in complex matrices (plasma, food, environmental samples).
- Comprehensive method development strategies based on design of experiments and modeling.
- Comparisons of SFC with UHPLC, GC, and direct infusion MS, highlighting SFC’s orthogonality and speed.
- Preparative scale applications for enantiomer purification.
Methodology and instrumentation
Key features include:
- Stationary phases: polysaccharide chiral selectors, 2-ethylpyridine, diol, 1-aminoanthracene, CSH Fluoro-Phenyl, trefoil columns, chiral zwitterionic phases.
- Mobile phases: supercritical CO2 with methanol or other polar modifiers, with additives (amines, acids) tuned for selectivity and peak shape.
- Interface optimization: low-dead-volume connectors, optimal make-up solvents, and high desolvation settings for robust ESI and APCI–MS detection.
- Analytical hyphenation: UPC2-MS/MS, UHPSFC-Q-TOF, and comparison with UHPLC-MS/MS and GC-MS.
Main results and discussion
- SFC achieves baseline separations in seconds to minutes for complex mixtures (e.g., 95 triacylglycerols, 14 fat-soluble vitamins, 40 lignin-derived phenols).
- Chiral separations: sub-2μm CSP columns enable rapid enantiomer resolution of pesticides, drugs, and natural products with high efficiency.
- Method comparisons: SFC often outperforms UHPLC in throughput and orthogonality, with comparable or superior sensitivity after interface optimization.
- Preparative SFC: scale-up strategies maintain resolution while reducing solvent use, enabling kilogram-scale chiral purification.
Benefits and practical applications
- Green chemistry: >90% CO2 mobile phase, minimal organic solvents, lower waste.
- Speed: analysis times reduced 2–10× versus LC methods.
- Throughput: >5000 serum vitamin determinations in months; high-throughput lipidomics; rapid drug impurity profiling.
- Versatility: simultaneous multi-class analyte detection in single runs.
- Enhanced method transfer and robustness using design-space and eQTL approaches.
Future trends and potential applications
- Integration with ion mobility MS and novel detectors for expanded resolution.
- Advanced multidimensional SFC×LC-MS workflows for ultra-complex matrices.
- In-line sample concentration and SFC-NMR coupling for direct structural elucidation.
- Expanded adoption in regulatory environments for impurity and isomeric profiling.
- Automation and digital method development aided by machine learning.
Conclusion
SFC coupled with modern MS detectors offers unmatched speed, selectivity, and greenness for chiral and achiral separations of complex samples. Continued advances in stationary phase chemistry, interface technology, and data-driven method development will further establish SFC as a cornerstone technique in analytical and preparative separations.
Reference
Compiled bibliography of 184 articles covering UPC2, UHPSFC, SFC-MS/MS, method development, and applications in pharmaceuticals, food, environment, and natural products analysis.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.