Abstract
This paper focused on using response surface methodology (RSM) and artificial neural network (ANN) to analyze polyurethane (PU) nanofibers morphology synthesized by electrospinning. The process was characterized in detail by using experimental design to determine the parameters that may affect the nanofibers morphology such as polymer concentration, a tip to collector distance and applied voltage. It was concluded that solution concentration plays an important role (relative importance of 79.85 %) against nanofibers diameter and its standard deviation. Based on the results, applied voltage has a different effect on the nanofiber diameter at low and high solution concentrations. Moreover, the tip to collector distance parameter has no significant impact on the average nanofiber diameter. The finest PU nanofiber (201 nm) was obtained from experimental under conditions of: 9 w/v% polymer concentrations, 12 cm tip to collector distance and 16 kV applied voltage. The results show a very good agreement between the experimental and modeled data. It was demonstrated that both models (specially, in case of neural network) are excellent for predicting diameter of PU nanofibers. Furthermore, numerical optimization has been performed by considering desirability function to access the region in design space that introduces minimum average diameter.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
J. H. He, Y. Liu, L. F. Mo, Y. Q. Wan, and L. Xu, “Electrospun Nanofibres and Their Applications”, pp.6–10, Smithers Rapra Technology, Shawbury, united kingdom 2008.
D. Bjorge, N. Daels, and S. D. Vrieze, Desalination, 249, 942 (2009).
E. R. Kenawy, F. Abdel-Haya, M. El-Newehya, and G. E. Wnek, Mater. Chem. Phys., 113, 296 (2009).
S. Chakraborty, C. Liao, A. Adler, and K. W. Leong, Adv. Drug. Deliver. Rev., 61, 1043 (2009).
B. Yoon and S. Lee, Fiber. Polym., 12, 57 (2011).
F. Nanni, P. Travaglia, and M. Valentii, Compos. Sci. Technol., 69, 485 (2009).
J. Jang and J. Bae, Sensor Actuat. B-Chem., 122, 7 (2007).
J. Stanger, N. Tucker, and M. Staiger, “Electrospinning”, Vol. 16, pp.10–11, Smithers Rapra Technology, United Kingdom, 2005
J. H. He, Y. Q. Wan, and J. Y. Yu, Fiber. Polym., 9, 140 (2008).
M. M. Demir, I. Yilgor, E. Yilgor, and B. Erman, Polymer, 43, 3303 (2002).
S. A. Therona, E. Zussmana, and A. L. Yarin, Polymer, 45, 2017 (2004).
M. Szycher, “Handbook of Polyurethanes”, CRC Press, New York, 1999
F. Cengiz and O. Jirsak, Fiber. Polym., 10, 177 (2009).
N. Amiraliyan, M. Nouri, and M. Haghighat Kish, Fiber. Polym., 10, 167 (2009).
S. Ray and J. A. Lalman, Chem. Eng. J., 169, 116 (2011).
S. Y. Gu, J. Ren, and G. J. Vancso, Eur. Polym. J., 41, 2559 (2005).
K. Sarkar, M. B. Ghalia, Z. Wu, and S. C. Bose, J. Mater. Process Tech., 209, 3156 (2009).
A. S. Nateri and M. Hasanzadeh, J. Comput. Theor. Nanos, 6, 1542 (2009).
A. I. Galushkin, “Neural Networks Theory”, Springer Verlag, New York, 2007
T. L. Fine, “Feedforward Neural Network Methodology”, Springer Verlag, New York, 1999
R. Chattopadhyay and A. Guha, Text. Prog., 35, 1 (2004).
M. J. Anderson and P. J. Whitcomb, “RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments”, Productivity Press, New York, 2005
M. Kasiri, H. Aleboyeh, and A. Aleboyeh, Environ. Sci. Technol., 42, 7970 (2008).
M. J. Anderson and P. J. Whitcomb, “DOE Simplified: Practical Tools for Effective Experimentation”, 2nd Ed., Productivity Press, New York, 2000
H. Fong, I. Chun, and D. H. Reneker, Polymer, 40, 4585 (1999).
Y. Liu, J. H. He, J. Y. Yu, and H. Zeng, Polym. Int., 57, 632 (2008).
S. H. Tan, R. Inaia, M. Kotakib, and S. Ramakrishna, Polymer, 46, 6128 (2005).
Y. J. Ryu, H. Y. Kim, K. H. Lee, H. C. Park, and D. R. Lee, Eur. Polym. J., 39, 1883 (2003).
D. H. Reneker, A. L. Yarin, H. Fong, and S. Koombhongse, J. Appl. Phys., 87, 4531 (2000).
J. S. Lee, K. H. Choi, H. D. Ghim, S. S. Kim, D. H. Chun, H. Y. Kim, and W. S. Lyoo, J. Appl. Polym. Sci., 93, 1638 (2004).
X. M. Mo, C. Y. Xu, M. Kotaki, and S. Ramakrishna, Biomaterials, 25, 1883 (2004).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rabbi, A., Nasouri, K., Bahrambeygi, H. et al. RSM and ANN approaches for modeling and optimizing of electrospun polyurethane nanofibers morphology. Fibers Polym 13, 1007–1014 (2012). https://doi.org/10.1007/s12221-012-1007-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12221-012-1007-x