Prediction and optimization of process parameters of electrospun polyacrylonitrile based on numerical simulation and response surface method

There is a strong coupling relationship between the process parameters of electrospun polyacrylonitrile (PAN) and its fiber diameter. By examining the mechanism of influence, the quality of electrospun products can be significantly improved and controlled. In this study, a novel idea for predicting...

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Bibliographic Details
Published in:Textile research journal 2021-10, Vol.91 (19-20), p.2332-2344
Main Authors: Chen, Peng, Zhou, Qihong, Chen, Ge, Zhang, Qian, Wang, Shaozong
Format: Article
Language:English
Subjects:
Correlation analysis
Electric fields
Electric potential
Electrospinning
Feed rate
Mathematical models
Optimization
Polyacrylonitrile
Prediction models
Process parameters
Response surface methodology
Surface tension
Velocity
Voltage
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Summary:There is a strong coupling relationship between the process parameters of electrospun polyacrylonitrile (PAN) and its fiber diameter. By examining the mechanism of influence, the quality of electrospun products can be significantly improved and controlled. In this study, a novel idea for predicting and optimizing electrospun PAN process parameters was proposed. First, the control equation of the electrospun PAN was established based on the incompressible Navier–Stokes equation, and the volume force (generated via electric field force, gravity, and surface tension) and jet velocity during electrospinning were solved and analyzed via simulation software. Then, grey correlation analysis was used to calculate the correlation among the three process parameters (applied voltage, feed rate, and distance between the needle and collector) of the electrospun PAN, volume force, jet velocity, and average fiber diameter. Subsequently, the effect of simultaneous changes in multiple process parameters on the average fiber diameter was examined based on the response surface method, and a prediction model was established. Finally, the experimental results indicated that the model can predict the average fiber diameter when multiple process parameters are simultaneously changed. The model predicted the average fiber diameter with an error of only 0.28%, and the optimized minimum fiber average diameter was 235.3 nm (the applied voltage was 12 kV, the distance between the needle and collector was 15.6 cm, the feed rate was 0.37 mL/h). This study provides a theoretical basis for the on-line monitoring of the electrospun PAN.
ISSN:0040-5175
1746-7748
DOI:10.1177/00405175211003986