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Acidic Dyes Analysis by HPLC

Brochures and specifications | 2022 | SIELCInstrumentation
HPLC, Consumables, LC columns
Industries
Energy & Chemicals
Manufacturer
SIELC

Summary

Significance of Dye Analysis

The analysis of dyes is a critical step in both industrial production and quality control, particularly when dyes are used as food additives.

Ensuring high purity levels is essential for consumer safety and regulatory compliance, and it enables the detection of counterfeit or substandard dye mixtures.

Reliable separation of structurally similar and multi-charged dye isomers presents a longstanding challenge in analytical chemistry.

Goals and Study Overview

This study reports on the application of Bridge Ion Separation Technology (BIST) for the rapid and efficient separation of acidic azo dyes.

Using a reputed sample of Brilliant Black BN, the analysis revealed that the material contained four different dyes—Sunset Yellow, Tartrazine, Brilliant Blue FCF, and Amaranth—instead of the claimed compound.

These findings underscore the need for robust analytical methods to verify dye composition in food and industrial products.

Methodology

BIST relies on a doubly charged ionic modifier in the mobile phase to form an electrostatic bridge between analytes and a like-charged stationary phase surface.

Key requirements for effective BIST separation:
  • Presence of a double-charged ionic modifier in the mobile phase
  • Modifier ions of opposite charge to the stationary phase surface
  • Reduced water content to minimize ion solvation

Under these conditions, multi-charged acidic dyes can be retained and separated with high selectivity, as demonstrated by the increased retention of Tartrazine using TMDAP versus a single-charged modifier (TEA).

Used Instrumentation

Column: BIST™ A+ (4.6 × 150 mm, 5 µm)
Mobile phase: Acetonitrile/water gradient (80/20 to 60/40 over 20 min)
Buffer: 5 mM TMDAP formate (pH 5.0)
Flow rate: 1.0 mL/min
Detection: UV–Vis at 430, 520, 600 nm (additional wavelengths and MS detection employed in application studies)

Additional stationary phases and buffer systems (e.g., magnesium or calcium acetate) were evaluated to extend the technique to a variety of charged analytes.

Main Results and Discussion

BIST enabled complete separation of counterfeit Brilliant Black BN into four individual dyes, demonstrating its power for quality control in dye analysis.

Application examples include:
  • Analysis of Allura Red and Chicago Sky Blue in mixtures
  • Verification of dye components in sports drink and food-coloring formulations
  • Assessment of ionic modifier effects on retention of mono- versus multi-charged dyes

Results highlight BIST’s ability to resolve complex mixtures of charged species within minutes and its compatibility with multiple detection modes.

Benefits and Practical Applications

  • High selectivity for multi-charged acidic dyes and other ionic compounds
  • Improved purity assessment and counterfeit detection in food additives and industrial dyes
  • Flexibility in buffer composition and detection techniques, including UV–Vis, MS, and conductivity
  • Potential integration into routine QA/QC workflows for rapid, reliable analysis

Future Trends and Potential Applications

Anticipated developments for BIST include:
  • Expansion to pharmaceutical and biological analytes with multiple charge states
  • Design of novel bridge ions tailored for specific analyte classes
  • Coupling with high-resolution mass spectrometry for structural elucidation
  • Automation and incorporation into standardized protocols for industrial laboratories

Conclusion

Bridge Ion Separation Technology represents a versatile and powerful HPLC mode for the selective separation of charged species. Its unique mechanism, based on electrostatic bridging, offers superior retention control and resolves complex dye mixtures rapidly. BIST addresses critical needs in food safety, counterfeit detection, and broader analytical applications.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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