A high-performance field asymmetric waveform ion mobility spectrometry (FAIMS)-IMS-MS platform was developed and applied to explore the conformational diversity of the singly and doubly charged bradykinin (BK + H+)+ and (BK + 2H+)2+ ions. With pure N2 as the FAIMS carrier gas, more than ten conformers of (BK + H+)+ can be resolved using FAIMS-IMS, as compared to only four conformers resolved using either FAIMS or IMS alone. Interestingly, multiple conformers of (BK + H+)+ were found to have completely different values of FAIMS compensation voltage (CV), while their IMS drift times were essentially the same, which were also proven experimentally to not result from the structural annealing by the collisional heating in the ion funnel. The separations in the FAIMS and IMS dimensions are substantially orthogonal, and the overall resolving power of two-dimensional FAIMS-IMS separation is largely proportional to the product of the separation resolving powers of FAIMS and IMS. Using a gas mixture of N2/He to further improve the resolving power of the FAIMS separation, the total resolving powers of the combined FAIMS and IMS separation were estimated to be about 1020 and 1400 for (BK + H+)+ and (BK + 2H+)2+ ions, respectively, which are significantly higher than the resolving power of any ion mobility-based separation techniques demonstrated so far. The combined FAIMS-IMS can thus be a much more powerful technique to explore the structural diversity of biomolecules.

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Rationale Field asymmetric waveform ion mobility spectrometry (FAIMS) has a great potential to become a portable technology for rapid detection of chemical and biological agents. However, the ion current signals, measured at the exit of the planar FAIMS directly, may contain different types of noises. The peak information in the FAIMS spectrum, such as the compensation voltage (CV) value at the maximum peak intensity (CVP) and the peak width at half maximum (Wh), could not be accurately determined under the weak signal condition, which significantly limits the achievable instrument sensitivity, and there are no existing solutions to the problem. Methods This study analyzed the noise type of FAIMS signal in detail, and three different signal processing algorithms, such as median filtering (MF), discrete wavelet transform (DWT), and zero‐phase digital filtering (ZDF), were evaluated for their performance in denoising the FAIMS signal. Results The results show that the standard deviation of CVp obtained from the signal denoised using ZDF algorithm is at least 31.82% smaller as compared to using MF and DWT algorithms. The standard deviation of Wh is at least 45.45% smaller using ZDF algorithm. Moreover, only ZDF algorithm can keep the percentage error for the CV value of the denoised signal to be within 0.50 ± 0.47% of the true CV value, implying the effectiveness of ZDF algorithm in denoising while retaining the integrity of the signal. Conclusions The ZDF algorithm greatly reduces the analyte peak extraction error and improves the limit of detection in FAIMS measurements.

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