ABSTRACT
The solution of ion mobility's nonlinear function coefficients α2 and α4 is the basis for achieving substance identification of High Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS). Currently, nonlinear function coefficients α2 and α4 lack priors, meanwhile, existed solving results about α2 and α4 are deficient in error evaluation standard. In this article, acetone, isopropanol and 1, 2-dichlorobenzene were detected under different dispersion voltage by homemade FAIMS. In general, the spectrum peak of same sample at different dispersion voltage value is unique. Different dispersion voltage and corresponding compensation voltage value determines the value of α2 and α4. According to sample spectra at different dispersion voltage value, groups of spectral characteristics were obtained. Affirmatory number of data which were selected from multiple sets of compensation voltage value and dispersion voltage value, so that they were utilized to solved out lots of α2 and α4. Lots of factor have an effect on the accuracy of the solving results of α2 and α4, for instance, value of compensation voltage and dispersion voltage, style of fetching points of dispersion voltage, and so on. Comparing to other factors, style and amount of dispersion voltage is likely to control. By data analyzing huge amounts of α2 and α4 data, this paper explored their characteristic of distribution and correlation about them, research influence of number and method to fetch dispersion voltage detected points for error of solving results. After fitting frequency of α2 and α4, it was found that they conform to normal distribution, goodness of fitting exceed 0. 96, thus standard deviation of their distribution are able to evaluate error of solving results. In addition, a strong correlation exists between them, relevance of sample is -0. 977, -0. 968, -0. 992 respectively. With increasing of computing selected points, the corresponding error of solving results decrease. By comparing the standard deviation of method to fetch dispersion voltage detected points, found that detecting frequency in case of detecting maximum and the 70% of maximum of dispersion voltage value is lower at approximately same standard deviation, solving effect was optimized in unique fetching points style. Based on the premise of ensuring the accuracy of solving results of α2 and α4, it is obvious that reducing the frequency of detections for FAIMS effectively. It created favorable conditions for rapid field detection and precise spectral analysis.
ABSTRACT
FAIMS's ion separation mechanism is based on analyte's characteristic nonlinear relationship between its ion mobility and applied electric field strength. Present characterization methods for this nonlinear relationship are based on precarious assumptions which incur substantial errors under many circumstances. A rigorous method for solving the second and fourth taylor series coefficient of this relationship based on dispersion voltage value (assuming half-sinusoidal waveform) and associated compensation voltage value of spectrum peak is presented, alongside with rigorous analytical functions. FAIMS spectrums were obtained for ethanol, metaxylene and n-butanol using custom-built FAIMS spectrometer, and corresponding second and fourth taylor series coefficients were obtained with the proposed method. Evaluation shows that this method substantially reduces the RMS error between interpolated and measured peak compensation voltage values under different dispersion voltages, confirming its superiority over present methods. This rigorous method would help improve spectral resolutions of FAIMS spectrometer, facilitating high precision FAIMS spectrum database construction and accurate analyte discrimination.
ABSTRACT
FAIMS is a fast and high sensitive technique for detecting trace volatile organic compounds. Spectra of acetone, benzene and toluene were obtained on a homemade high-field asymmetric waveform ion mobility spectrometer and they can be easily separated in the spectra. Three xylene isomeric compounds were also successfully separated in FAIMS. Effect of carrier gas flow rate on the ion intensity was analyzed, and the optimal flow rate of carrier gas was 220 L x h(-1) which can be used for the optimization of FAIMS instrument. The detection limit for acetone is 100 ng x L(-1) that is an order of magnitude lower than the foreign traditional IMS.
