Person: ÖMEROĞULLARI BAŞYİĞİT, ZEYNEP
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
ÖMEROĞULLARI BAŞYİĞİT
First Name
ZEYNEP
Name
3 results
Search Results
Now showing 1 - 3 of 3
Publication Investigation and feed-forward neural network-based estimation of dyeing properties of air plasma treated wool fabric dyed with natural dye obtained from hibiscus sabdariffa(Wiley, 2023-01-01) Eyüpoğlu, Can; Eyüpoğlu, Seyda; Merdan, Nigar; Ömerogulları Başyigit, Zeynep; ÖMEROĞULLARI BAŞYİĞİT, ZEYNEP; Bursa Uludağ Üniversitesi/İnegöl Meslek Yüksekokulu/Tekstil, Giyim, Ayakkabı ve Deri, Tekstil Teknolojisi Bölümü.; HJY-8602-2023In the colouring processes of textile products, more environmentally friendly chemicals and finishing methods should be used instead of conventional ones that harm the environment every day, so that alternative realistic ways to protect nature, both academically and industrially, could be possible. Due to some inconveniences caused by synthetic dyes that are widely used today, in this study, ultrasonic dyeing of wool fabric with Hibiscus sabdariffa was carried out after environmental-friendly air vacuum plasma application which increased the absorption of the dyes into the textile material. According to the performance results, colour strengths of the wool fabrics were increased significantly. Surface morphology analysis was carried out and etching effects of air vacuum plasma treatment were clearly seen on the micrographs of the treated wool fabrics. An environmental-friendly green process was achieved through this study and it was concluded that vacuum air plasma treatment could be an alternative green-process as a pretreatment to increase the dye up-take of natural dyeing treatment. Moreover, in this study, a feed-forward neural network (FFNN) model was presented and used for predicting the dyeing properties (L, a, b and K/S) of samples. The experimental results showed that the presented model achieves the regression values greater than 0.9 for all dyeing properties. Consequently, it was considered that the proposed FFNN was successfully modelled and could be efficiently utilised for dyeing characteristics of wool fabrics dyed with natural dye extracted from Hibiscus sabdariffa.Publication Production and characterization of magnetic textiles(Taylor & Francis Ltd, 2022-11-22) Başyiğit, Zeynep Ömeroğulları; Beden, Ali Rıza; Coşkun, Hatice; ÖMEROĞULLARI BAŞYİĞİT, ZEYNEP; Bursa Uludağ Üniversitesi/İnegöl Meslek Yüksekokulu/Tekstil, Giyim, Ayakkabı ve Deri Bölümü/Tekstil Teknolojisi Programı.; HJY-8602-2023In this study, 100% cotton fabrics were imparted with magnetic field properties using a conventional screen printing method to obtain magnetic fabrics in the context of smart textiles. The magnetism in the fabrics was generated by using a Fe3O4 compound. In order to make this compound adhere more strongly to the fabric sample, printing method was used as a finishing application. The Fe3O4 compound was added to the printing paste without using any dyestuff since the Fe3O4 compound had a unique color itself. The washing durability of the printed functional textiles were investigated. The washing fastness, acidic sweat fastness, alkaline sweat fastness, water fastness, dry rubbing fastness, wet rubbing fastness, tear strength, pilling and degree of external magnetic induction of the fabrics were analyzed. In addition, the morphological analyzes of the fabrics were performed by scanning electron microscopy (SEM-EDX) and X-ray crystallography (XRD) to determine the crystallographic properties of the materials and the phases they contained. According to the result of quantitative evaluation of magnetic fields on textile surfaces, Fe3O4 microparticles were in the range of 25 mT when they constituted 50% of the weight.Thus, it was found that a magnetic field was successfully generated in the textiles. Moreover, the magnetic property of the fabric was durable after the washing process as the mT values were maintained even after 20 washing cycles, and the fastness and performance tests were also at the highest level. Increasing the Fe3O4 content in the formulations used in the study improved the tensile strength by 2-7%. Comparing the test results of the fabric sample with the optimum formulation with the untreated fabric sample, it was also determined that the tensile strength increased by 8-10% on average after 20 washes.Publication Natural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network(Wiley, 2023-06-09) Eyüpoğlu, Can; Eyüpoğlu, Şeyda; Merdan, Nigar; Başyiğit, Zeynep Ömeroğulları; ÖMEROĞULLARI BAŞYİĞİT, ZEYNEP; Bursa Uludağ Üniversitesi/İnegöl Meslek Yüksekokulu/Tekstil, Giyim, Ayakkabı ve Deri, Tekstil Teknolojisi Bölümü.; HJY-8602-2023In this study, the ecological dyeing process of wool fabrics was investigated. Wool fabric samples were treated with atmospheric pressure plasma-jet and corona discharge plasma to modify the surface to make the process sustainable and greener. The samples were dyed with the aqueous extract procured from the powdered roots of Rubia tinctorum L. (madder) using the ultrasonic-assisted method. Scanning electron microscopy and Fourier Transform-infrared analysis were performed to investigate the effect of plasma treatment on the physical and chemical properties of wool fibres. The effects of plasma treatment type, plasma treatment parameters and the duration of dyeing on colorimetric and fastness properties were investigated. The etching of the wool fibre surface and roughness after plasma treatment were proven with scanning electron microscopy images. The Fourier Transform-infrared spectra showed that no significant differences in the functional groups of wool fibre occurred after plasma treatment. The experimental results proved that plasma treatment parameters and dyeing time had an effect on the colorimetric and fastness properties of the samples. Furthermore, an artificial neural network model was proposed for estimating the dyeing properties of wool fabrics, namely, L, a, b, K/S, colour change, rubbing fastness (dry) and rubbing fastness (wet). The experimental results show that the proposed model achieves regression values greater than 0.97 for all dyeing properties. The proposed model is successful and can be efficiently used for estimating the dyeing characteristics of wool fabrics.