Please use this identifier to cite or link to this item: https://doi.org/10.1366/000370203321666489
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dc.titleSpectral 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
dc.contributor.authorChen, L.
dc.contributor.authorChew, W.
dc.contributor.authorGarland, M.
dc.date.accessioned2014-05-16T07:24:44Z
dc.date.available2014-05-16T07:24:44Z
dc.date.issued2003-05
dc.identifier.citationChen, 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
dc.identifier.issn00037028
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/52676
dc.description.abstractAn 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).
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1366/000370203321666489
dc.sourceScopus
dc.subjectEntropy
dc.subjectInfrared spectroscopy
dc.subjectMinimization
dc.subjectPure component spectra
dc.subjectSpectral pattern recognition
dc.subjectSpectral similarity
dc.typeArticle
dc.contributor.departmentCHEMICAL AND PROCESS ENGINEERING CENTRE
dc.contributor.departmentCHEMICAL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1366/000370203321666489
dc.description.sourcetitleApplied Spectroscopy
dc.description.volume57
dc.description.issue5
dc.description.page491-498
dc.description.codenAPSPA
dc.identifier.isiut000184358400003
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