Optimizing mass spectrometric detection for ion chromatographic analysis. I. Common anions and selected organic acids

We describe a systematic method of optimizing mass spectrometric (MS) detection for ion chromatographic (IC) analysis of common anions and three selected organic acids using response surface methodology (RSM). RSM was utilized in this study because it minimized the number of experiments required to achieve the optimum MS response and included the interactions between individual parameters for multivariable optimization. Five MS parameters, including probe temperature, nebulizer gas, assistant makeup flow, needle voltage and cone voltage, were screened and systematically optimized by two steps. Central composite design (CCD) was used to design the experiment points and a quadratic model was applied to fit the experimental data. Analysis of variance (ANOVA) was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for MS response. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by applying desirability function. Our observation showed good agreements between statistically predicted optimum response and the responses collected at the predicted optimum condition. Operable range of each parameter (with normalized MS response greater than 0.8 for each analyte) was provided for general anionic IC/MS applications.