Phase correction of fourier transform ion cyclotron resonance mass spectra using MatLab

FT-ICR mass spectrometry has been limited to magnitude mode for almost 40 years due to the data processing methods used. However, it is well known that phase correction of the data can theoretically produce an absorption-mode spectrum with a mass-resolving power that is as much as twice as high as conventional magnitude mode, and that it also improves the quality of the peak shape. Temporally dispersed frequency sweep excitation followed by a time delay before detection results in a steep quadratic variation in the signal phase with frequency. Viewing this, it is possible to find the correct phase function by performing a quadratic least squares fit, modified by iterating through phase cycles until the correct quadratic function is found. Here, we present a robust manual method to rotate these signals mathematically and generate a “phased” absorption-mode spectrum. The method can, in principle, be automated. Baseline correction is also included to eliminate the accompanying baseline drift. The resulting experimental FT-ICR absorption-mode spectra exhibit a resolving power that is at least 50% higher than that of the magnitude mode

Variation of the Fourier transform mass spectra phase function with experimental parameters

It has been known for almost 40 years that phase correction of Fourier transform ion cyclotron resonance (FTICR) data can generate an absorption-mode spectrum with much improved peak shape compared to the conventional magnitude-mode. However, research on phasing has been slow due to the complexity of the phase-wrapping problem. Recently, the method for phasing a broadband FTICR spectrum has been solved in the MS community which will surely resurrect this old topic. This paper provides a discussion on the data processing procedure of phase correction and features of the phase function based on both a mathematical treatment and experimental data. Finally, it is shown that the same phase function can be optimized by adding correction factors and can be applied from one experiment to another with different instrument parameters, regardless of the sample measured. Thus, in the vast majority of cases, the phase function needs to be calculated just once, whenever the instrument is calibrated