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Yazar "Unal, Merve" seçeneğine göre listele

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    Development and characterization of self-healing microcapsules, and optimization of production parameters for microcapsule diameter and core content
    (Emerald Group Publishing Ltd, 2022) Ozada, Cagatay; Unal, Merve; Sahin, Eslem Kuzu; Ozer, Hakki; Motorcu, Ali Rıza; Yazici, Murat
    Purpose This study produced epoxy-filled urea-formaldehyde (UF) microcapsules (MCs) and T-403 amine MCs using the in situ technique. The Taguchi method was used to determine the effects of the control factors (temperature, stirring speed, core-shell ratio and surfactant concentration) affecting MCs' core diameter and core content and optimizing their optimum levels with a single criterion. Optimum control factor levels, which simultaneously provide maximum core diameter and core content of MCs, were determined by the PROMETHEE-GAIA multi-criteria optimization method. In addition, the optimized MC yield was analyzed by thermal camera images and compression test. Design/methodology/approach Microcracks in materials used for aerospace vehicles and automotive parts cause serious problems, so research on self-healing in materials science becomes critical. The damages caused by micro-cracks need to heal themselves quickly. The study has three aims: (1) production of self-healing MCs, mechanical and chemical characterization of produced MCs, (2) single-criteria and multi-criteria optimization of parameters providing maximum MC core diameter and core content, (3) investigation of self-healing property of produced MCs and evaluation. Firstly, MCs were produced to achieve these goals. Findings The optimized micro cures are buried in the epoxy matrix at different concentrations. Thermal camera images after damage indicate the presence of healing. An epoxy-amine MC consisting of a 10% by weight filled aluminum sandwich panel was prepared and subjected to a quasi-static compression test. It was determined that there is a strong bond between the UF shell and the epoxy resin. Originality/value The optimization of production factors has been realized to produce the most efficient MCs that heal using less expensive and more accessible methods.

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