Improved partition equilibrium model for predicting analyte response in electrospray ionization mass spectrometry

Area of Science:

• Analytical Chemistry
• Mass Spectrometry

Background:

• Quantitative prediction of analyte response in electrospray ionization mass spectrometry (ESI-MS) is crucial.
• Existing partition equilibrium models have limitations in accuracy and applicability.

Purpose of the Study:

• To modify a partition equilibrium model for improved quantitative prediction of analyte response in ESI-MS.
• To develop a simplified model for predicting analyte responses in solutions with multiple components.

Main Methods:

• Modification of a previously proposed partition equilibrium model.
• Modeling analyte response as a competition mechanism between analyte and background electrolytes.
• Validation of the model across a wide range of experimental conditions.

Main Results:

• An improved linear relationship was achieved for analyte mass spectrometer response.
• The model accurately predicts analyte behavior in salt solutions, overcoming limitations of the original model.
• Ion suppression effects of 16:0 lysophosphatidylcholine (LPC) were explained by charge competition and surface tension effects.

Conclusions:

• The simplified, modified model provides a more accurate and versatile tool for quantitative analysis in ESI-MS.
• The model facilitates easier prediction of analyte responses in complex, multi-component solutions.
• This advancement aids in understanding and mitigating ion suppression effects in ESI-MS.