Design of Electrospinning-made Materials Using 3D Computational Simulation

The importance of computational simulation to develop and optimize materials obtained by electrospinning is linked to the prediction and evaluation of the performance of materials and the influence of key input parameters. The methodology presented combines experimental information and the implementation of a computational tailor-made simulation tool to predict properties and trends. To simulate fibrous materials obtained by electrospinning, the input key factors are the filament 3D dimensions, and the outputs are the key network properties of porosity and pore dimensions, that play an important role in the retention and release of active molecules. The inclusion of the fibre at the nano and micro scale and the formation of the network structure step-wise is a plus from the optimization point of view, transforming a multi-input–multi-output problem into useful information to predict and design electrospun materials. Here, the simulation of a 3D network is presented, using a Polyamide-6 network obtained by electrospinning. The model inputs include the fibre morphology and flexibility to build the network. The simulation outputs are the structural properties such as coverage, thickness, porosity, and relative bonded area. The simulated networks appeared qualitatively similar to the experimental ones. Pore dimension measurements showed that the model can reproduce the network structures. A Latin hypercube computer experimental design was implemented for 1000 simulations and the resulting structures were organized using regression trees. The simulation results indicate that the maximum and minimum porosity can be identified and this approach can be used to manufacture optimized structures.