Optimising PVDF microfibers using electrospinning
Chin, Zheng Yee
Date of Issue2017
School of Mechanical and Aerospace Engineering
Electrospinning has gather a great amount of attention for researchers to explore the potential of this technology. Electrospinning offers a great amount of advantages such as low startup cost, low learning curve. Polymer solution mixed with other solvent will be used in electrospinning and to produce fiber. Fiber comes in micro/nano meter and this will depends on the various parameters used that will affect the fiber diameter and morphology. Electrospun fibers had good track record and wide usage for sensor applications. Sensors are found in many areas such as chemical sensors for the environment, security sensors for detection of any form of lapses, sensors for rehabilitative purposes and many more. Due to the nature of sensors being small in size, micro/nano fibers fits in the criteria coupling with its benefits of high strength, flexibility, electroactive properties. Other research articles had shown the success of producing nanofibers with electrospinning, hence the focus of this paper would be to use polymer suitable for sensor application to electrospin microfiber. Polyvinylidene Fluoride (PVDF) is selected to investigate the feasibility of obtaining microfiber. In order to achieve micron range fiber, there are many working parameters to consider in achieving larger fiber diameter. Only certain parameters such as polymer concentration, working distance, applied voltage and flowrate are being investigated and experimented. Poly (vinyl alcohol) (PVA) and Polycaprolactone (PCL) are used for the initial stage of experimenting the parameters and familiarization of the electrospinning process. For PVDF, design of experiment (DOE) approach was adopted. A 3 level 3 factor full factorial design with diameter as the output response is required to be carried out under the DOE approach to determine the significance of the factors. Through the usage of Minitabs software, the optimal parameters can be obtained using the multiple regression model in terms of various terms such as P-Value, R-Squared that is closely associated with the X-Y relationship.
Final Year Project (FYP)
Nanyang Technological University