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An Artificial Neural Network (ANN) Model for Predicting Water Absorption of Nanoclay-Epoxy Composites
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作者 Guillermina Capiel Arrosio Florencia +2 位作者 Vera A. Alvarez pablo e. montemartini Juan Morán 《Journal of Materials Science and Chemical Engineering》 2019年第8期87-97,共11页
Glass fiber reinforced epoxy (GFRE) composite materials are prone to suffer from water absorption due to their heterogeneous structure. The main process governing water absorption is diffusion of water molecules throu... Glass fiber reinforced epoxy (GFRE) composite materials are prone to suffer from water absorption due to their heterogeneous structure. The main process governing water absorption is diffusion of water molecules through the epoxy matrix. However, hydrolytic degradation may also take place during components service life specially due high temperatures. In order to mitigate the effects of the water diffusive processes in the deterioration of in-service behavior of epoxy matrix composites, the use of chemically modified nanoclays as an additive has been proposed and studied in previous works [1]. In this work, an Artificial Neural Network (ANN) model was developed for better understanding and predicting the influence of modified and unmodified bentonite addition on the water absorption behavior of epoxy-anhydride systems. An excellent correlation between model and experimental data was found. The ANN model allowed the identification of critical points like the precise temperature at which a particular system’s water uptake goes beyond a predefined threshold, or which system will resist an immersion longer than a particular time. 展开更多
关键词 Artificial Neural Networks Epoxy-Anhydride CLAY NANOCOMPOSITES Water Absorption
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Chemical and Morphological Surface Modification of Epoxy Based Thermosets
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作者 Marcela e. Penoff Patricia A. Oyanguren +1 位作者 Wido Schreiner pablo e. montemartini 《Materials Sciences and Applications》 2013年第7期1-9,共9页
Recently developed low fluorine containing polymers are advanced materials which confer advantageous properties to surfaces at a lower cost than conventional fluoropolymers (like PTFE), and are also more easily proces... Recently developed low fluorine containing polymers are advanced materials which confer advantageous properties to surfaces at a lower cost than conventional fluoropolymers (like PTFE), and are also more easily processable. Fluoropolymer surfaces are characterized by a low surface energy, high oleo and hydrophobicity, low coefficients of friction, among many other properties. This makes them desired materials in microelectronics, antifogging, antifouling and medical applications, to name a few. Fluorinated compounds are not easily coupled with macromolecules or common organic systems, and great efforts are made to compatibilize fluorinated species with hydrocarbon polymers. In this work, two chemical routes were explored in order to incorporate perfluorinated alkyl chains in an epoxy-amine based thermoset. On one side, a perfluoroalkyl thiolated molecule was used as a stabilizing ligand for silver nanoparticles, which were incorporated in the matrix polymer. On the other hand, fluorinated chains containing epoxy functionalities, were used as the matrix modifier. In the first case, fluorinated chains covering the nanoparticles, were mixed with the matrix, while in the second case, the fluoroalkyl chains were chemically linked to the network. Fluorine migration to the air—polymer interface was confirmed by X-Ray photoelectron spectroscopy (XPS). The materials hydrophobicity was then studied in terms of their contact angle with water (CA), as a function of the surface composition and the topography. Scanning electron microscopy (SEM) and atomic force microscopy (AFM), operated in moderate and light tapping modes, were used to morphologically describe the surfaces. An exhaustive surface analysis was made in order to explain the different hydrophobicity grades found. 展开更多
关键词 FLUOROPOLYMER Nanoparticles THERMOSET Surface HYDROPHOBIC
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