Volume 3 Number 1 (Jan. 2013)
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IJBBB 2013 Vol.3(1): 56-58 ISSN: 2010-3638
DOI: 10.7763/IJBBB.2013.V3.163

Neural Network Based Modeling for Polycaprolactone Synthesis by Bio-Polymerization of ε-caprolactone

Senthil Kumar Arumugasamy, M. H. Uzir, and Z. Ahmad

Abstract—Extensive study of ring-opening polymerization ε-caprolactone (ε-CL) using lipase Novozym 435 (immobilized form of lipase B from Candida antarctica) as biocatalyst using ring-opening polymerization (ROP) of ε-caprolactone was carried out at impeller speeds of 250, 500, 750, 1000 rpm and temperature of the reactor of 60°C, 70°C and 80°C. The maximum molecular weight out of all the experiments carried out is 310000 Kilo Daltons (weight average molecular weight, Mw) which was obtained at a temperature of 70°C and 3 hours for an impeller speed of 500 rpm. In order to develop a predictive model a multilayer feed-forward neural network (FANN) trained with an error back-propagation algorithm was incorporated. The results showed that a 3-7-1 for FANN1 with the inclusion of the Reactor impeller speed and 2-6-1 FANN2 arrangement with exclusion of the Reactor impeller gave the best performance.

Index Terms—Biopolymers, enzymatic polymerization, molecular weight distribution, polycaprolactone synthesis, ring opening polymerization (ROP)

Senthil Kumar Arumugasamy, M. H. Uzir, and Z. Ahmad are with Universiti Sains Malaysia (e-mail: senthilkumar9999@gmail.com).

Cite: Senthil Kumar Arumugasamy, M. H. Uzir, and Z. Ahmad, "Neural Network Based Modeling for Polycaprolactone Synthesis by Bio-Polymerization of ε-caprolactone," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 3, no. 1, pp. 56-58, 2013.

General Information

ISSN: 2010-3638
Frequency: Bimonthly (2011-2015); Quarterly (Since 2016)
DOI: 10.17706/IJBBB
Editor-in-Chief: Prof. Ebtisam Heikal 
Abstracting/ Indexing: Electronic Journals Library, Chemical Abstracts Services (CAS), Engineering & Technology Digital Library, Google Scholar, and ProQuest.
E-mail: ijbbb@iap.org
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