Please use this identifier to cite or link to this item:
|Title:||Spectral pattern recognition of in situ FT-IR spectroscopic reaction data using minimization of entropy and spectral similarity (MESS): Application to the homogeneous rhodium catalyzed hydroformylation of isoprene||Authors:||Chen, L.
Pure component spectra
Spectral pattern recognition
|Issue Date:||May-2003||Citation:||Chen, L., Chew, W., Garland, M. (2003-05). Spectral pattern recognition of in situ FT-IR spectroscopic reaction data using minimization of entropy and spectral similarity (MESS): Application to the homogeneous rhodium catalyzed hydroformylation of isoprene. Applied Spectroscopy 57 (5) : 491-498. ScholarBank@NUS Repository. https://doi.org/10.1366/000370203321666489||Abstract:||An improved algorithm using minimization of entropy and spectral similarity (MESS) was tested to recover pure component spectra from in situ experimental Fourier transform infrared (FT-IR) reaction spectral data, which were collected from a homogeneous rhodium catalyzed hydroformylation of isoprene. The experimental spectra are complicated and highly overlapping because of the presence of multiple intermediate products in this reaction system. The traditional entropy minimization method fails to resolve real reaction mixture spectra, but MESS can successfully reconstruct pure component spectra of unknown intermediate products for real reaction systems by the addition of minimization of spectral similarity. The quantitative measure of spectral similarity between two spectra was given by their inner products. The results indicate that MESS is a stable and useful algorithm for spectral pattern recognition of highly overlapped experimental reaction spectra. Comparison is also made between MESS, entropy minimization, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), interactive principle component analysis (IPCA), and orthogonal projection approach-alternating least squares (OPA-ALS).||Source Title:||Applied Spectroscopy||URI:||http://scholarbank.nus.edu.sg/handle/10635/52676||ISSN:||00037028||DOI:||10.1366/000370203321666489|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jun 8, 2021
WEB OF SCIENCETM
checked on May 31, 2021
checked on Jun 11, 2021
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.