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|Title:||Weighted two-band target entropy minimization for the reconstruction of pure component mass spectra: Simulation studies and the application to real systems||Authors:||Zhang, H.
|Issue Date:||Nov-2003||Citation:||Zhang, H., Garland, M., Zeng, Y., Wu, P. (2003-11). Weighted two-band target entropy minimization for the reconstruction of pure component mass spectra: Simulation studies and the application to real systems. Journal of the American Society for Mass Spectrometry 14 (11) : 1295-1305. ScholarBank@NUS Repository. https://doi.org/10.1016/S1044-0305(03)00540-3||Abstract:||A method is proposed, on the basis of a recently developed algorithm - Band Target Entropy Minimization (BTEM) - to reconstruct mass spectra of pure components from mixture spectra. This method is particular useful in dealing with spectral data with discrete features (like mass spectra). Compared to the original BTEM, which has been applied to differentiable spectroscopies such as Fourier-transfer infrared spectroscopy (FTIR), ultraviolet (UV), Raman, and nuclear magnetic resonance (NMR), the latest modifications were obtained through: (1) Reformulating the objective function using the peak heights instead of their derivatives; (2) weighting the abstract vector VT to reduce the effect of noise; (3) using a two-peak targeting strategy (tBTEM) to deal with strongly overlapping peaks; and (4) using exhaustive search to locate all the component spectra. A set of 50 multi-component mass spectra was generated from ten reference experimental pure component spectra. Many of the compounds chosen have common MS fragments and therefore, many of the pure component spectra have considerable intensity in same data channels. In addition, a set of MS spectra from a real system with four components was used to examine the newly developed algorithm. Successful reconstruction of the ten component spectra of the simulated system and the four component spectra of the real system was rapidly achieved using the new tBTEM algorithm. The advantages of the new algorithm and its implication for rapid system identification of unknown mixtures are readily apparent. © 2003 American Society for Mass Spectrometry.||Source Title:||Journal of the American Society for Mass Spectrometry||URI:||http://scholarbank.nus.edu.sg/handle/10635/92469||ISSN:||10440305||DOI:||10.1016/S1044-0305(03)00540-3|
|Appears in Collections:||Staff Publications|
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