%0 Journal Article
%T Neural Network Based Modeling for Polycaprolactone Synthesis by Bio-Polymerization of ¦Å-caprolactone
%A Senthil Kumar Arumugasamy
%A M. H. Uzir
%A Z. Ahmad
%J International Journal of Bioscience, Biochemistry and Bioinformatics
%D 2013
%I IACSIT Press
%R 10.7763/ijbbb.2013.v3.163
%X Extensive study of ring-opening polymerization¦Å-caprolactone (¦Å-CL) using lipase Novozym 435 (immobilizedform of lipase B from Candida antarctica) as biocatalyst usingring-opening polymerization (ROP) of ¦Å-caprolactone wascarried out at impeller speeds of 250, 500, 750, 1000 rpm andtemperature of the reactor of 60¡ãC, 70¡ãC and 80¡ãC. Themaximum molecular weight out of all the experiments carriedout is 310000 Kilo Daltons (weight average molecular weight,Mw) which was obtained at a temperature of 70¡ãC and 3 hoursfor an impeller speed of 500 rpm. In order to develop apredictive model a multilayer feed-forward neural network(FANN) trained with an error back-propagation algorithm wasincorporated. The results showed that a 3-7-1 for FANN1 withthe inclusion of the Reactor impeller speed and 2-6-1 FANN2arrangement with exclusion of the Reactor impeller gave thebest performance.
%K Biopolymers
%K enzymatic polymerization
%K molecular weight distribution
%K polycaprolactone synthesis
%K ringopening polymerization (ROP)
%U http://www.ijbbb.org/papers/163-W003.pdf