Influence of curing condition on thermo-mechanical properties of fly ash reinforced epoxy composite

• Published in: Composites. Part B, Engineering Engineering, 2019-11, Vol.176, p.107301, Article 107301
• Main Authors: Pattanaik, A., Mukherjee, M., Mishra, S.B.
• Format: Article
• Language: English
• Subjects: Curing condition; Fly ash epoxy composite; Mechanical behaviour; Process optimization; Thermal behaviour
• ISSN: 1359-8368; 1879-1069
• DOI: 10.1016/j.compositesb.2019.107301

The effect of ambient, oven and microwave curing conditions on the thermo-mechanical properties of fly ash (FA) filled epoxy composites with four different volume fraction of fly ash mixed with five different mixing duration have been investigated. The thermal analysis of the composites was carried out in a differential scanning calorimeter (DSC) to determine the transitions, the amount of curing heat, the degree of cure (α) etc. The mechanical behaviour was evaluated from the tensile, flexural and impact characteristics of the specimens. The obtained results showed that the composite with 10%FA content mixed for 30 min has the minimum void fraction with a homogeneous mixture. DSC analysis clearly showed that the microwave cured specimen requires less heat energy to attain ~99% degree of crosslinking. The oven cured specimen with similar process variables had slightly higher Tg and Tm than the microwave cured specimens. Ambiently cured specimens generally had the lowest thermal properties with an insignificant degree of cure. The maximum tensile, flexural and impact properties were achieved with microwave cured specimen containing 10%FA mixed for 30 min followed by oven cured and ambient cured specimens of similar condition. Several non-linear equations have been developed to predict the responses (i.e. σs, σf and IJ) as a function of FA content and mixing time. The models are able to predict the responses adequately with more than 96% accuracy. The optimum values of FA content and mixing time are 10% and 30 min respectively were achieved by an optimization test in RSM.