Characterization and prediction of some engineering properties of polymer - Clay/Silica hybrid nanocomposites through ANN and regression models

The search from time immemorial for stronger, lighter and more durable materials used in construction and tools continues to this day. This urge to discover, invent and synthesize new materials has resulted in innumerable kinds of alloys, plastics and composites owing to the very exacting demands from different industries like aerospace, automobile, chemical, marine and so on. Glass fibers reinforced in polymers have received considerable attention during the last century. Studies conducted during the last decade reveal that adding small amounts of foreign particles (like clay or silica) of nanosize significantly improves the engineering properties of the polymers. This study presents the effect of reinforcing epoxy polymer with Halloysite nanoclay on mechanical properties. In the present work the clay in terms 1, 2 and 3 percent by weight was surface treated with a suitable silane agent. The hybrid nanocomposite was prepared by the hand lay-up technique. Characterization of the nanoclay was done by X-ray diffraction and Scanning electron microscopy. ASTM standards have been employed for investigating hardness, dynamic mechanical properties, wear, damping and post underwater shock. All the tests were done for both silica and clay as reinforcement materials. Analysis and Results have been presented for impact of nanoclay reinforcement on all the parameters. Radial basis function network, a tool of ANN, is employed to predict the above outcomes. Mathematical regression models have been employed for theoretical prediction. Comparative study reveals that ANN Tool predictions have better agreement with measured values than the other model. Thus, it can be confidently concluded that ANN Tool can be used to predict the properties of hybrid nanocomposites before actual manufacture. This will result in considerable savings in terms of project time, effort and cost.