Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Tanoglu, MetinDepartment: search.filters.department.İzmir Institute of Technology

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  • Article
    Investigating the Effects of Functionalized Single Wall Carbon Nanotubes on the Cure Behavior of a Carbon/Epoxy Prepreg System by an Optimized Parameter Approach
    (Wiley, 2025) Oz, Murat; Uz, Yusuf Can; Tanoglu, Gamze; Tanoglu, Metin; Barisik, Murat
    Carbon/Epoxy composite materials are used in a wide range of applications due to their superior performance. However, their properties are strongly related to cross-linking reactions occurring during the curing process, and a prior estimation of curing parameters is the key to manufacturing the desired material. This study builds a mathematical model to solve the inverse kinetic problem based on differential scanning calorimetry data and later presents its use in curing experiments. The method derived (Gamze-Murat-Neslisah (GMN) approach) determines the pre-exponential and activation energy of the curing process. Later, an extended experimental study was performed. Functionalized single-wall carbon nanotubes (F-SWCNTs) were prepared by oxidizing their surface with carboxyl to enhance the dispersion of the nanoparticulates. The epoxy resin systems were modified with 0.05%, 0.1%, and 0.2% wt. F-SWCNTs, which were impregnated on carbon fibers (CFs). The curing behavior was studied, cure kinetic parameters were determined, and the thermal behavior was characterized. Differential scanning calorimetry (DSC) data sets for CF/epoxy prepregs containing F-SWCNTs were used for the verification of the proposed method. It was found that the GMN approach is in good agreement with the experimentally measured data for all kinetic parameters. The addition of F-SWCNTs increased the material's curing efficiency as the CNTs enhanced heat transport in composites, reducing the activation energy. The results obtained from the GMN algorithm were also found in good agreement with the well-known Kissinger-Akahira-Sunose (KAS) and Kissinger methods, while the current GMN method revealed itself as an accurate algorithm to obtain the activation energy.