بررسي ارتباط ريزساختار با خواص مكانيكي و حرارتي چسب‌هاي بر پايه اپوكسي/فنوليك حاوي نانوذرات آلومينا و نانولوله‌هاي‌كربني‌چندجداره و چقرمه‌كننده‌ي پلي‌آميد6

Investigating the relationship between microstructure an‎d mechanical an‎d thermal properties of epoxy/phenolic-based adhesives containing alumina nanoparticles an‎d carbon nanotubes an‎d polyamide 6 toughener

مهندسي شيمي

In this study, an Epoxy/Phenolic-based adhesive incorporating Polyamide 6 as a toughening agent, along with alumina nanoparticles an‎d multi-walled carbon nanotubes as reinforcing agents, was utilized to investigate microstructure, behavior, an‎d mechanical an‎d thermal properties, with the aim of enhancing the single-lap shear strength of bonded aluminum plates. The silane agent 3-aminopropyltriethoxysilane is also used to modify the surface of alumina nanoparticles an‎d multi-walled carbon nanotubes. In first section, The results show that the highest improvement in tensile strength, tensile modulus, an‎d shear strength is related to the optimal epoxy/alumina/MWCNT ternary sample, an‎d the highest improvement in toughness is related to the optimal epoxy/polyamide 6/MWCNT ternary sample which showed increases of 49%, 44%, 150%, an‎d 176%, respectively, compared to pure epoxy. Effective interactions between the nanoparticles an‎d the epoxy matrix, including hydrogen bonding between the nanoparticlesʹ functional groups an‎d the epoxy, as well as with the surface groups of the anodized aluminum sheets, along with the superior intrinsic mechanical properties of the nanoparticles, are among the key factors contributing to the improved properties compared to neat epoxy. Also, other important points in the results of the mechanical properties an‎d adhesion strength tests are the presence of a negative interaction between polyamide 6 an‎d alumina nanoparticles an‎d the synergistic effect between alumina nanoparticles an‎d MWCNT. Data obtained from tensile an‎d shear strength tests were modeled an‎d analyzed using Artificial Neural Networks (ANN). In the present study, two feed-forward multilayer perceptron networks were designed an‎d implemented to predict the mechanical an‎d physical properties of epoxy adhesives. Thermogravimetric analysis (TGA) results indicate that the ternary sample containing epoxy, alumina, an‎d multi-walled carbon nanotubes exhibited the best performance, showing increases of 30°C an‎d 9°C in the onset degradation temperature an‎d the maximum degradation temperature, respectively. Furthermore, differential scanning calorimetry (DSC) results revealed that the sample containing the optimal percentage of alumina nanoparticles led to a 9.5°C reduction in the onset curing temperature. In second section, Based on the tensile test results, the highest improvement in tensile strength, tensile modulus, an‎d fracture toughness was for the nanoparticle-modified hybrid sample (41.8 MPa, 3.48 GPa, an‎d 353 kJ/m3, respectively), which was 55, 13, an‎d 113 percent higher than pure epoxy, respectively. The single-lap shear strength results also showed that the highest improvement in shear strength was for the nanoparticle-modified hybrid sample (6 MPa), which was 140 percent higher than pure epoxy, indicating a significant synergistic effect. TGA an‎d DSC test results show that the sample containing the modified nanoparticle composition had the best performance with a 37°C improvement in the degradation onset temperature an‎d an 8°C decrease in the curing onset temperature. The fracture surfaces of the optimized samples were examined using FESEM an‎d were in good agreement with the results of mechanical tests. The main toughness mechanisms in these samples included crack deflection, crack tip blunting, an‎d shear ban‎ding. In addition, the surface modification of the nanoparticles resulted in a more uniform distribution of the nanoparticles in the epoxy substrate

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