Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology
The present research aimed to investigate the effect of working parameters on the electrospinning of niobium–tungsten oxide nanofibers and optimize the process using central composite design (CCD) based on the response surface methodology (RSM). An experiment was designed to assess the effects of fi...
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doaj-6da57fdb11864701bd4cec157aa6def42021-07-23T13:57:12ZengMDPI AGNanomaterials2079-49912021-06-01111644164410.3390/nano11071644Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface MethodologyBabajide Oluwagbenga Fatile0Martin Pugh1Mamoun Medraj2Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaDepartment of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaDepartment of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaThe present research aimed to investigate the effect of working parameters on the electrospinning of niobium–tungsten oxide nanofibers and optimize the process using central composite design (CCD) based on the response surface methodology (RSM). An experiment was designed to assess the effects of five variables including the applied voltage (V), spinning distance (D), polymer concentration (P), flow rate (F), and addition of NaCl (N) on the resulting diameter of the nanofibers. Meanwhile, a second-order prediction model of nanofibers diameter was fitted and verified using analysis of variance (ANOVA). The results show that the diameter of the nanofibers was significantly influenced by all the variables except the flow rate. Some second-order and cross factor interactions such as VD, DP, PF, PN, and P<sup>2</sup> also have significant effects on the diameter of the nanofibers. The results of the ANOVA yielded <i>R</i><sup>2</sup> and adjusted <i>R</i><sup>2</sup> values of 0.96 and 0.93 respectively, this affirmed that the predictive model fitted well with the experimental data. Furthermore, the process parameters were optimized using the CCD method and a maximum desirability function of 226 nm was achieved for the diameter of the nanofibers. This is very close to the 233 nm diameter obtained from a confirmatory experiment using the optimum conditions. Therefore, the model is representative of the process, and it could be used for future studies for the reduction of the diameter of electrospun nanofibers.https://www.mdpi.com/2079-4991/11/7/1644niobium–tungsten oxidenanofiberselectrospinningoptimizationresponse surface methodology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Babajide Oluwagbenga Fatile Martin Pugh Mamoun Medraj |
spellingShingle |
Babajide Oluwagbenga Fatile Martin Pugh Mamoun Medraj Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology Nanomaterials niobium–tungsten oxide nanofibers electrospinning optimization response surface methodology |
author_facet |
Babajide Oluwagbenga Fatile Martin Pugh Mamoun Medraj |
author_sort |
Babajide Oluwagbenga Fatile |
title |
Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology |
title_short |
Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology |
title_full |
Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology |
title_fullStr |
Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology |
title_full_unstemmed |
Optimization of the Electrospun Niobium–Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology |
title_sort |
optimization of the electrospun niobium–tungsten oxide nanofibers diameter using response surface methodology |
publisher |
MDPI AG |
series |
Nanomaterials |
issn |
2079-4991 |
publishDate |
2021-06-01 |
description |
The present research aimed to investigate the effect of working parameters on the electrospinning of niobium–tungsten oxide nanofibers and optimize the process using central composite design (CCD) based on the response surface methodology (RSM). An experiment was designed to assess the effects of five variables including the applied voltage (V), spinning distance (D), polymer concentration (P), flow rate (F), and addition of NaCl (N) on the resulting diameter of the nanofibers. Meanwhile, a second-order prediction model of nanofibers diameter was fitted and verified using analysis of variance (ANOVA). The results show that the diameter of the nanofibers was significantly influenced by all the variables except the flow rate. Some second-order and cross factor interactions such as VD, DP, PF, PN, and P<sup>2</sup> also have significant effects on the diameter of the nanofibers. The results of the ANOVA yielded <i>R</i><sup>2</sup> and adjusted <i>R</i><sup>2</sup> values of 0.96 and 0.93 respectively, this affirmed that the predictive model fitted well with the experimental data. Furthermore, the process parameters were optimized using the CCD method and a maximum desirability function of 226 nm was achieved for the diameter of the nanofibers. This is very close to the 233 nm diameter obtained from a confirmatory experiment using the optimum conditions. Therefore, the model is representative of the process, and it could be used for future studies for the reduction of the diameter of electrospun nanofibers. |
topic |
niobium–tungsten oxide nanofibers electrospinning optimization response surface methodology |
url |
https://www.mdpi.com/2079-4991/11/7/1644 |
work_keys_str_mv |
AT babajideoluwagbengafatile optimizationoftheelectrospunniobiumtungstenoxidenanofibersdiameterusingresponsesurfacemethodology AT martinpugh optimizationoftheelectrospunniobiumtungstenoxidenanofibersdiameterusingresponsesurfacemethodology AT mamounmedraj optimizationoftheelectrospunniobiumtungstenoxidenanofibersdiameterusingresponsesurfacemethodology |
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