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Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

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Published on: January 20, 2022

Optimum waveforms for differential ion mobility spectrometry (FAIMS).

Alexandre A Shvartsburg¹, Richard D Smith

¹Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.

Journal of the American Society for Mass Spectrometry

|July 1, 2008

Summary

Optimizing field asymmetric waveform ion mobility spectrometry (FAIMS) waveforms using a full mobility expansion improves ion separation. This refinement enhances resolving power up to 2.2 times, especially for miniaturized devices and targeted analyses.

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Area of Science:

Analytical Chemistry
Physical Chemistry
Spectrometry

Background:

Field asymmetric waveform ion mobility spectrometry (FAIMS) separates gas-phase ions using electric fields.
Optimizing FAIMS waveform profiles is crucial for enhancing separation and identification capabilities, particularly when coupled with mass spectrometry.
Previous optimizations relied on simplified models of ion mobility dependence on electric fields.

Purpose of the Study:

To investigate the impact of a more complete description of ion mobility (K) as a function of electric field (E) on FAIMS performance.
To determine optimal FAIMS waveform profiles beyond the conventional E(2) scaling assumption.
To assess the potential for improved resolving power in FAIMS, especially for miniaturized systems and targeted analyses.

Main Methods:

Developed theoretical models incorporating higher-order terms in the electric field expansion of ion mobility (K(E)).
Simulated FAIMS performance using these advanced models with realistic K(E) dependencies.
Analyzed the effect of waveform amplitude and profile on ion separation and resolving power.

Main Results:

The optimum FAIMS waveform profiles are determined by the full series expansion of K(E), not just the E(2) term.
For many ion/gas pairs, including those in miniaturized FAIMS devices, the first two terms of K(E) have opposing signs, necessitating revised optimal profiles.
Improved resolving power of up to 2.2 times was demonstrated with the new optimization approach.
Reducing maximum waveform amplitude by 20-30% can be beneficial under realistic K(E) conditions.

Conclusions:

The study reveals that simplified models of ion mobility in FAIMS lead to suboptimal waveform designs.
Accurate K(E) dependence is critical for optimizing FAIMS, particularly in high-field or miniaturized systems.
The findings offer a pathway to significantly enhance FAIMS resolving power for advanced analytical applications, especially targeted analyses.