Complex catalyzed synthesis and prediction of properties of poly(acrylonitrile‐co‐acrylamide)/crab shell powder composites by using artificial neural network

Abstract In a nitrogen atmosphere, a novel composite, Poly(Acrylonitrile‐co‐Acrylamide)/crab shell powder, was synthesized by combining two monomers, acrylonitrile (AN) and acrylamide (Aam), with varying weight percentages of crab shell powder (CSP) as bio‐filler. The synthesized composite Poly (AN‐co‐Aam)/CSP, copolymer Poly (AN‐co‐Aam), and CSP were characterized using Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), thermogravimetric (TGA) analysis, derivative thermogravimetric (DTG) analysis, and a scanning electron microscope (SEM). The mechanical properties, like tensile, flexural, and impact strengths, were studied. The hardness, biodegradability, and water absorbency properties have been studied using appropriate methodologies. The SEM images and FTIR data confirm the appropriate synthesis of the composite material and the uniform distribution of CSP. The mechanical strength increases with the rise in concentration of CSP up to 20 wt. % and then gradually decreases. The thermal analysis reveals that the composite exhibits adequate thermal stability. The artificial neural network (ANN) model is used for the prediction of mechanical properties, which shows adequate results with the experimental results. The training and test datasets use a correlation factor associated with this analysis that is higher than 0.9, which confirms that the expected values of the mechanical performance are an excellent comparison to the experimental value.