In this study, definitions and explanations of the relationships between selected independent and dependent parameters of roller electrospinning are introduced. We aimed to define and completely analyze new parameters, such as the number of Taylor cones per square meter, the spinning performance for one Taylor cone, total spinning performance, fiber diameter uniformity coefficient and non-fibrous area percentage. Also, new measurement methods were developed and explained to analyze these parameters. According to the experimental results, strong and significant relationships between independent and dependent parameters of roller electrospinning were found. These independent and dependent parameters were affected by varying the concentrations of polyurethane and tetraethylammoniumbromide (TEAB) salt. In particular, the spinnability of the polymer solution, which is the most important factor for the roller electrospinning method, significantly increased with the TEAB concentration. If the spinning performance is positive, a specific solution is spinnable. However, the solution is not spinnable if the spinning performance is zero.

This article proposes prediction approaches for the determination of the breaking strength of the yarn properties by using evaluation programing. Gene expression programing (GEP) and neural networks are the evaluation programings that are used for the prediction of physical properties of yarn. In addition to these methods, multiple linear regression analysis is also used to examine the predictive power of the evaluation programings in comparison to classical statistical approach. The implementation of the genetic programing technique in GEP to the prediction of physical properties of yarn is indicated for the first time in this paper. The results obtained from the computational tests clearly show that GEP is a promising technique in terms of precision and computation time for the prediction of yarn properties (98.88 %).

The aim of this study was to produce advanced nanofiber mats by adding boron nitride to poly (ɛ-caprolactone) polymer using an electrospinning method and to characterize the resultant structures. Pure poly (ɛ-caprolactone) nanofiber mats and boron nitride-doped nanofiber mats prepared at different concentrations were compared. The morphological structures of the nanofiber mats were examined under a scanning electron microscope, spectroscopic analyses were conducted using Fourier transform infrared spectroscopy, and thermal stability was analyzed using a thermogravimetric analysis method. Successful electrospinning of boron nitride-doped nanofibers at lower voltages was achieved. The thermogravimetric analysis test found that the thermal stability of boron nitride-doped nanofiber mats is higher than that of pure nanofibers, which suggests that the produced composite material could be preferable in applications involving insulation and high temperature. On the other hand, the Fourier transform infrared spectroscopy results indicated that no chemical reaction occurred between boron nitride and the poly (ɛ-caprolactone) nanofibers.

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