Towards predicting the piezoelectricity and physiochemical properties of the electrospun P(VDF-TrFE) nanogenrators using an artificial neural network

Electrospun P(VDF-TrFE) nanogenrators with a wide range of piezoelectricity performance and physiochemical properties is fabricated through modification of the processing parameters such as polymer concentration, applied voltage, feed rate and electrospinning time/fibres mat thickness. In order to estimate and predict the relationships of the process parameters with the piezoelectricity performance and fibres morphology, an Artificial Neural Networks (ANN) model is developed. Results of the developed ANN model is found to be in a good agreement with experimental results with less than 5% error and shows the good potential to model physiochemical properties of the nanogenrators to predict untested conditions.