Real-time wavelet compression and self-modeling curve resolution for ion mobility spectrometry

Chemometrics has proven useful for solving chemistry problems. Most of the chemometric methods are applied in post-run analyses, for which data are processed after being collected and archived. However, in many applications, real-time processing is required to obtain knowledge underlying complex chemical systems instantly. Moreover, real-time chemometrics can eliminate the storage burden for large amounts of raw data that occurs in post-run analyses. These attributes are important for the construction of portable intelligent instruments.; Ion mobility spectrometry (IMS) furnishes inexpensive, sensitive, fast, and portable sensors that afford a wide variety of potential applications. SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) is a self-modeling curve resolution method that has been demonstrated as an effective tool for enhancing IMS measurements. However, all of the previously reported studies have applied SIMPLISMA as a post-run tool.; A modified SIMPLISMA algorithm, referred to as RTSIMPLISMA, was developed for modeling IMS data in real-time. The real-time algorithm can determine the number of components in the IMS data automatically. Resolved concentration and spectral profiles are simultaneously displayed on a virtual instrument while the data is collected from an ion mobility spectrometer.; The computational burden for real-time SIMPLISMA increases when the collected number of spectra grows in size. A spectrum will not be acquired when the data processing consumes too large a share of computer resources. To alleviate this problem, a two-dimensional wavelet compression (WC2) was applied prior to RTSIMPLISMA modeling. The optimal settings of WC2 -RTSIMPLISMA for processing IMS data were obtained, by which satisfactory models could be resolved when the data was compressed to 1/256.; A novel real-time WC2 has been developed to compress data as it is acquired from IMS sensors. RTSIMPLISMA was applied to the WC 2 processed data in real-time, by which the real-time modeling could be significantly accelerated. An integrated software package was developed to implement the real-time WC2-RTSIMPLISMA algorithm and used for the rapid processing of the IMS data of drugs and explosives. The real-time algorithm was able to disclose the very small features in the IMS data and rapidly model the dynamic changes during an IMS measurement course.