Modelling and Optimization of Polycaprolactone Ultrafine-Fibres Electrospinning Process Using Response Surface Methodology

被引:18
作者
Anindyajati, Adhi [1 ]
Boughton, Philip [1 ]
Ruys, Andrew J. [1 ]
机构
[1] Univ Sydney, Sch Aerosp Mech & Mechatron Engn, Sydney, NSW 2006, Australia
来源
MATERIALS | 2018年 / 11卷 / 03期
关键词
electrospinning; polycaprolactone; response surface methodology; fibre diameter; elastic modulus; TISSUE ENGINEERING APPLICATIONS; MECHANICAL-PROPERTIES; FIBROUS SCAFFOLDS; NANOFIBROUS SCAFFOLDS; EXTRACELLULAR-MATRIX; ACETABULAR LABRUM; DIAMETER; PARAMETERS; MORPHOLOGY; CRYSTALLINITY;
D O I
10.3390/ma11030441
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Electrospun fibres have gained broad interest in biomedical applications, including tissue engineering scaffolds, due to their potential in mimicking extracellular matrix and producing structures favourable for cell and tissue growth. The development of scaffolds often involves multivariate production parameters and multiple output characteristics to define product quality. In this study on electrospinning of polycaprolactone (PCL), response surface methodology (RSM) was applied to investigate the determining parameters and find optimal settings to achieve the desired properties of fibrous scaffold for acetabular labrum implant. The results showed that solution concentration influenced fibre diameter, while elastic modulus was determined by solution concentration, flow rate, temperature, collector rotation speed, and interaction between concentration and temperature. Relationships between these variables and outputs were modelled, followed by an optimization procedure. Using the optimized setting (solution concentration of 10% w/v, flow rate of 4.5 mL/h, temperature of 45 degrees C, and collector rotation speed of 1500 RPM), a target elastic modulus of 25 MPa could be achieved at a minimum possible fibre diameter (1.39 +/- 0.20 mu m). This work demonstrated that multivariate factors of production parameters and multiple responses can be investigated, modelled, and optimized using RSM.
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页数:23
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