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Öğe Characterization of a novel natural plant-based fiber from reddish shell bean as a potential reinforcement in bio-composites(Springer Science and Business Media Deutschland GmbH, 2024) Eyupoglu, Seyda; Eyupoglu, Can; Merdan, NigarThe main aim of this study is to identify a new sustainable plant-based fiber extracted from the reddish shell bean plant to investigate its usage in polymer matrix composites. Natural reddish shell bean fiber was extracted from vegetable shells with a biological degradation method. To determine the fiber characteristic properties, physical, chemical, and instrumental tests were performed on reddish shell bean fiber. The surface of the sample was determined with a scanning electron microscope, and it shows that the fiber has a rough surface along its length. In addition, an image processing approach was devised and implemented to determine the average fiber diameter of the reddish shell bean fiber. The elemental composition of fiber was obtained as 50.67 wt.% oxygen, 47.89 wt.% carbon, and 1.52 wt.% calcium with an energy disperse X-ray analysis device. In addition, fiber diameter was predicted as 785.87 ?m with the image processing technique. The fiber density was measured as 1080 kg/m3. The crystallinity index of reddish shell bean fiber was calculated as 57%, and the fiber stables up to 328.23°C. The ultimate tensile strength of reddish shell bean fiber was obtained as 111 MPa. The elongation at break and estimated values of Young’s modulus of reddish shell bean fiber are 1.83% and 6.11 GPa, respectively. According to the results, reddish shell bean fiber can be utilized as reinforcement in polymer matrix composites.Öğe 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(John Wiley and Sons, 2022) Omerogullari Basyigit, Zeynep; Eyupoglu, Can; Eyupoglu, Seyda; Merdan, NigarIn the colouring processes of textile products, more environmentally friendlychemicals and finishing methods should be used instead of conventional onesthat harm the environment every day, so that alternative realistic ways to pro-tect nature, both academically and industrially, could be possible. Due to someinconveniences caused by synthetic dyes that are widely used today, in thisstudy, ultrasonic dyeing of wool fabric withHibiscus sabdariffawas carried outafter environmental-friendly air vacuum plasma application which increasedthe absorption of the dyes into the textile material. According to the perfor-mance results, colour strengths of the wool fabrics were increased significantly.Surface morphology analysis was carried out and etching effects of air vacuumplasma treatment were clearly seen on the micrographs of the treated woolfabrics. An environmental-friendly green process was achieved through thisstudy and it was concluded that vacuum air plasma treatment could be analternative green-process as a pretreatment to increase the dye up-take of natu-ral dyeing treatment. Moreover, in this study, a feed-forward neural network(FFNN) model was presented and used for predicting the dyeing properties(L,a,bandK/S) of samples. The experimental results showed that the pre-sented model achieves the regression values greater than 0.9 for all dyeingproperties. Consequently, it was considered that the proposed FFNN was suc-cessfully modelled and could be efficiently utilised for dyeing characteristics ofwool fabrics dyed with natural dye extracted fromHibiscus sabdariffaÖğe Investigation of dyeing properties of mohair fiber dyed with natural dyes obtained from candelariella reflexa(Taylor and Francis Ltd., 2022) Eyupoglu, Can; Eyupoglu, Seyda; Merdan, NigarThe current study reports on using ascorbic acid as a possible substitute for improving fastness properties of natural dyes. In the mordanting process, microwave energy, which is a part of the sustainable and ecological production approach, was used. Renewable natural dye source Candelariella reflexa, which is a genus of lichen, was obtained from the trunk of Pinus nigra. Mohair fiber was dyed with natural dye extracted from Candelariella reflexa by using a conventional method. Before dyeing, mohair fiber was subjected to the premordanted process with iron (III) chloride (FeCl3) using microwave energy. In order to determine the effect of mordanting process parameters on dyeing properties, the mordanting process was performed with different concentrations and durations. In the dyeing process, ascorbic acid was added at different concentrations in the dyeing bath to improve the light fastness of samples. After the dyeing process, spectrophotometric features, light, and rubbing and washing fastness of samples were investigated. The color strength, washing, light, and rubbing fastness of dyed mohair fiber improve slightly with the premordanting process and by adding ascorbic acid. The spectrophotometric measurement results show that color coordinates vary from the mordanting time and amount of ascorbic acid. Furthermore, the use of microwave energy in the mordanting process leads to saving of energy and time. Besides, in this study, a machine learning-based model exploiting the artificial neural network (ANN) was developed for prediction of dyeing properties of mohair fiber dyed with natural dyes obtained from Candelariella reflexa. Experimental data obtained through various tests were first used to feed the proposed ANN, and then the trained ANN was validated and tested for the aim of prediction. The study results show that the proposed model can successfully predict most of the dyeing properties of mohair fiber. Therefore, this model can be used as an effective tool to estimate dyeing characteristics of mohair fiber.Öğe Investigation of thermal conductivity, sound absorption, and mechanical properties of Alcea Rosea L. fiber-reinforced epoxy composites(Springer, 2023) Eyupoglu, Seyda; Cetinsoy, Ertugrul; Eyupoglu, Can; Merdan, NigarThe composite production has been commonly researched because of its crucial properties such as low density, light weight, having better mechanical behaviors, and stifness. There are numerous uses in marine, automotive, sporting, and aerospace industries. In this study, fber-reinforced composites were produced with Alcea Rosea L. fber and epoxy resin. Besides, an image processing technique was proposed and put into use to specify the average fber thickness of Alcea Rosea L. fber. The composites were prepared at 5:95, 10:90 fber:epoxy resin weight percentages. Before the composite synthesis, Alcea Rosea L. fbers were treated to alkali surface modifcation with 10% sodium hydroxyl for 30 min. The thermal conductivity coefcient, sound absorption coefcient, and tensile strength of composites were measured. The thermal conductivity coef fcient of samples decreases with increase in Alcea Rosea L. fber weight percentage. The sound absorption coefcient and mechanical properties of samples improve with increase in Alcea Rosea L. fber weight percentage. These results show that Alcea Rosea L. fber-reinforced sustainable composites can be used as a potential thermal and acoustic insulator.Öğe A multilayer perceptron artificial neural network model for estimation of ultraviolet protection properties of polyester microfiber fabric(TAYLOR & FRANCIS LTD, 2020) Eyupoglu, Can; Eyupoglu, Seyda; Merdan, NigarIn this study, the use of a polyester fabric produced from microfibers as a siding material for construction industry was investigated. In this context, an ultraviolet (UV) absorber was applied to the polyester fabric samples with and without dyeing process. These samples were treated with UV absorber at 1-4% concentration and then an accelerated aging test was carried out. The UV absorbance capacity of the samples was investigated before and after the accelerated aging test. Furthermore, the effects of dyeing process on UV absorbance capacity of samples were analyzed. Afterwards, a multilayer perceptron artificial neural network (MLP-ANN) model was proposed and utilized to predict the UV protection properties which are UV protection factor, UV-A and UV-B in polyester microfiber fabric. The MLP-ANN based results demonstrate that the regression (R) values are almost 1 for all UV protection properties. Accordingly, it was seen that the proposed MLP-ANN is correctly modeled and the prediction of UV protection properties is successfully performed.Öğe Natural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network(John Wiley and Sons Inc, 2023) Eyupoglu, Can; Eyupoglu, Seyda; Merdan, Nigar; Omerogullari Basyigit, ZeynepIn 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.Öğe VITAMIN E LOADED FABRICS AS COSMETOTEXTILE PRODUCTS: FORMULATION AND CHARACTERIZATION(Ege Univ, 2018) Basyigit, Zeynep Omerogullari; Kut, Duck; Yenilmez, Evrim; Eyupoglu, Seyda; Hocaoglu, Emel; Yazan, YaseminSkin fights constantly during the day to be saved from free radicals caused by UV rays and pollution. However, skin cells repair damage and restore complexion during sleep. Enhancement of repair and restoration can be achieved more effectively by the cosmetic products such as antioxidants applied during night. In this study, functional fabrics were prepared for single- use which are impregnated with three different delivery systems containing vitamin E, the mostly known antioxidant ingredient. Comparison of vitamin E release from microcapsule, microemulsion and solid lipid nanoparticle systems embedded in polypropylene fabrics (PP) was aimed in this study. Final purpose of preparing a cosmetotextile for ocular area was to obtain prolonged activity of vitamin E. Following particle size measurement and scanning electron microscopic analyses of all delivery systems prepared, systems embedded in polypropylene nonwoven fabrics were tested for vitamin E meant to be released over time. According to the results obtained, vitamin E was found to be successfully incorporated into all three delivery systems and release of vitamin E was determined to be prolonged best by solid lipid nanoparticles.
