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Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodology.
Biopolymers. 2018 Dec; 109(12):e23240.B

Abstract

A statistical approach with D-optimal design was used to optimize the process parameters for polycaprolactone (PCL) synthesis. The variables selected were temperature (50°C-110°C), time (1-7 h), mixing speed (50-500 rpm) and monomer/solvent ratio (1:1-1:6). Molecular weight was chosen as response and was determined using matrix-assisted laser desorption/ionization time of flight (MALDI TOF). Using the D-optimal method in design of experiments, the interactions between parameters and responses were analysed and validated. The results show a good agreement with a minimum error between the actual and predicted values.

Authors+Show Affiliations

Department of Chemical and Environmental Engineering, Faculty of Engineering, University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia.Department of Chemical and Environmental Engineering, Faculty of Engineering, University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia.Department of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.Department of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.Graphene & Advanced 2D Materials Group (GAMRG), School of Science & Technology, Sunway University, Subang Jaya, Selangor, Malaysia.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30489632

Citation

Pakalapati, Harshini, et al. "Parametric Optimization of Polycaprolactone Synthesis Catalysed By Candida Antarctica Lipase B Using Response Surface Methodology." Biopolymers, vol. 109, no. 12, 2018, pp. e23240.
Pakalapati H, Arumugasamy SK, Jewaratnam J, et al. Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodology. Biopolymers. 2018;109(12):e23240.
Pakalapati, H., Arumugasamy, S. K., Jewaratnam, J., Wong, Y. J., & Khalid, M. (2018). Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodology. Biopolymers, 109(12), e23240. https://doi.org/10.1002/bip.23240
Pakalapati H, et al. Parametric Optimization of Polycaprolactone Synthesis Catalysed By Candida Antarctica Lipase B Using Response Surface Methodology. Biopolymers. 2018;109(12):e23240. PubMed PMID: 30489632.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodology. AU - Pakalapati,Harshini, AU - Arumugasamy,Senthil Kumar, AU - Jewaratnam,Jegalakshimi, AU - Wong,Yong Jie, AU - Khalid,Mohammad, Y1 - 2018/11/29/ PY - 2018/04/17/received PY - 2018/10/09/revised PY - 2018/10/15/accepted PY - 2018/11/30/pubmed PY - 2019/3/26/medline PY - 2018/11/30/entrez KW - Candida Antarctica lipase B KW - D-optimal method KW - design of experiment KW - enzymatic polymerization KW - optimization KW - polycaprolactone SP - e23240 EP - e23240 JF - Biopolymers JO - Biopolymers VL - 109 IS - 12 N2 - A statistical approach with D-optimal design was used to optimize the process parameters for polycaprolactone (PCL) synthesis. The variables selected were temperature (50°C-110°C), time (1-7 h), mixing speed (50-500 rpm) and monomer/solvent ratio (1:1-1:6). Molecular weight was chosen as response and was determined using matrix-assisted laser desorption/ionization time of flight (MALDI TOF). Using the D-optimal method in design of experiments, the interactions between parameters and responses were analysed and validated. The results show a good agreement with a minimum error between the actual and predicted values. SN - 1097-0282 UR - https://www.unboundmedicine.com/medline/citation/30489632/Parametric_optimization_of_polycaprolactone_synthesis_catalysed_by_Candida_antarctica_lipase_B_using_response_surface_methodology_ L2 - https://doi.org/10.1002/bip.23240 DB - PRIME DP - Unbound Medicine ER -