Trilinear decomposition method applied to removal of three-dimensional background drift in comprehensive...

Area of Science:

• Analytical Chemistry
• Chromatography

Background:

• Comprehensive two-dimensional liquid chromatography (LCxLC) is a powerful separation technique.
• Three-dimensional background drift can significantly impact data quality and analysis in LCxLC-DAD.
• Existing methods for drift correction may require blank runs or prior sample knowledge.

Purpose of the Study:

• To propose a novel technique for the accurate removal of three-dimensional background drift in LCxLC-DAD data.
• To improve the quality and reliability of analytical data obtained from LCxLC-DAD.

Main Methods:

• The study employs trilinear decomposition, specifically the alternating trilinear decomposition (ATLD) algorithm.
• Background drift is modeled as a distinct component alongside analytes within the trilinear model.
• The method involves extracting the background component and subtracting it from the raw instrumental response data.

Main Results:

• The proposed technique successfully determines and removes three-dimensional background drift from both simulated and experimental LCxLC-DAD data.
• Analyte signals are effectively isolated on a flat baseline after background subtraction.
• The method demonstrates good background drift removal without requiring blank chromatographic runs or prior sample composition information.

Conclusions:

• Trilinear decomposition offers an effective approach for addressing 3D background drift in LCxLC-DAD.
• This novel technique enhances data quality by providing a flat baseline for accurate analyte signal evaluation.
• The method's independence from blank runs and prior knowledge makes it a versatile tool for LCxLC-DAD data processing.