Response surface methodology (RSM) based on a three-level, three-variable Box-Benkhen design (BBD), and artificial neural network (ANN) techniques were compared for modeling the average diameter of electrospun polyacrylonitrile (PAN) nanofibers. The multilayer perceptron (MLP) neural networks were trained by the sets of input-output patterns using a scaled conjugate gradient backpropagation algorithm. The three important electrospinning factors were studied including polymer concentration (w/v%), applied voltage (kV) and the nozzle-collector distance (cm). The predicted fiber diameters were in agreement with the experimental results in both ANN and RSM techniques. High-regression coefficient between the variables and the response (R 2 ¼ 0.998) indicates excellent evaluation of experimental data by second-order polynomial regression model. The R 2 value was 0.990, which indicates that the ANN model was shows good fitting with experimental data.Moreover, the RSM model shows much lower absolute percentage error than the ANN model. Therefore, the obtained results indicate that the performance of RSM was better than ANN. The RSM model predicted the 118 nm value of the finest nanofiber diameter at conditions of 10 w/v% polymer concentration, 12 cm of nozzle-collector distance, and 12 kV of the applied voltage. The predicted value (118 nm) showed only 2.5%, difference with experimental results in which 121 nm at the same setting were observed.

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The dispersion behavior of single‐walled carbon nanotube (SWCNT) has important effects on morphological and mechanical properties of SWCNT composite nanofibers. The relationship of the dispersion conditions with morphological and mechanical characteristics for SWCNT / polyacrylonitrile (PAN) / polyvinylpyrrolidone (PVP) composite nanofibers have been examined. The SEM and TEM analyses of the nanofibers revealed that the deformation in the nanofiber structures increases with increasing concentration of SWCNTs. Tensile results showed that only 2 wt% SWCNT loading to the electrospun composite nanofibers gave rise to 10‐fold and 3‐fold increase in the tensile modulus and tenacity of nanofiber layers, respectively. Essentially, high mechanical properties and uniform morphology of the composite nanofibers were found at SWCNT concentration of ∼2 wt% due to their stable and individual dispersion. POLYM. COMPOS., 33:1951–1959, 2012. © 2012 Society of Plastics Engineers

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