Online Monitoring of Biotransformations in High Viscous Multiphase Systems by Means of FT-IR and Chemometrics

In unstable emulsion systems, the determination of concentrations is a challenge. The use of standard methods like GC, HPLC, or titration is highly inaccurate and makes the acquisition of precise data for these systems complex. In addition, the handicap of high viscosity often comes into play. To ov...

Full description

Saved in:
Bibliographic Details
Published inAnalytical chemistry (Washington) Vol. 82; no. 14; pp. 6008 - 6014
Main Authors Müller, Jakob J, Neumann, Markus, Scholl, Paul, Hilterhaus, Lutz, Eckstein, Marrit, Thum, Oliver, Liese, Andreas
Format Journal Article
LanguageEnglish
Published Washington, DC American Chemical Society 15.07.2010
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:In unstable emulsion systems, the determination of concentrations is a challenge. The use of standard methods like GC, HPLC, or titration is highly inaccurate and makes the acquisition of precise data for these systems complex. In addition, the handicap of high viscosity often comes into play. To overcome these fundamental limitations, the online FT-IR technique was identified in combination with chemometric modeling in order to improve accuracy. The reactor type used in this study is a bubble column reactor with up to four dispersed phases (solid catalyst, two liquid immiscible substrates, and a gaseous phase). The investigated reactions are solvent free enzymatic esterifications yielding myristyl myristate (10 mPa s) and high viscous polyglycerol-3-laurate (300−1500 mPa s), representative industrial products for cosmetic applications. For both reactions, chemometric models were successfully set up and reproducibly applied in the prediction of progress curves of a new set of experiments. This allows the automated determination of sensitive kinetic and thermodynamic data as well as reaction velocities in high viscous multiphase (bio)chemical systems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0003-2700
1520-6882
DOI:10.1021/ac100469t