Optimization of ion mobility spectrometry parameters based on experimental design

The Chemometrics technics have been proved as a useful tool for solving chemical problems. Chemometrics technics facilitate chemists to deal with two issues: good data collection (design of experiments and optimization of experimental protocol) and information extraction from data (analysis of variance, pattern recognition, and modeling) [1]. The focus of this article is the optimization of Ion Mobility Spectrometry (IMS) parameters for the detection of narcotics. Ion mobility spectrometry (IMS) is a sensitive, portable, robust, and inexpensive sensor that has a variety of potential applications. IMS has the potential to yield low cost suitable sensors for narcotics detection and identification [2]. However, the low sensitivity of IMS and the presence of memory effect make it difficult for the detection and identification of intrested chemicals. Response surface methodology (RSM) is a kind of mathematical and statistical technique for designing experiments, building models, evaluating the relative significance of several independent variables, and determining the optimum conditions for desirable responses [3]. The common designs broadly used in RSM are the central composite design (CCD) [4]. Simultaneous optimizion of variables affecting the determination narcotics, such as cell tempreture, drift gas flow, carrier gas flow and injector temperature was performed using design of experiments (30 experiments). The optimum conditions include the use of 175 ºC cell tempreture, 427 ml/min drift gas flow, 211 ml/min carrier gas flow and 219 ºC injector tempreture. Statistical evaluation of the results showed that the quadratic model is well fitted to experimental data. A Good agreement was observed between the predicted response functions and the practical ones.