The effectiveness of nanocomposite materials depends on the accuracy of the binder selection process. This process is crucial for ensuring compatibility, better adhesive behaviour, and stability during the synthesis of polymer composites with metal nanoparticles. An investigation was conducted to analyze the accuracy and efficiency of binder materials on metal nanoparticle (oxide) featured polymer composites. The investigation utilized Advanced Spectroscopic Computational Optimization Analysis (ASCOA) and high-throughput experimental methods to identify and optimize binders using computational modelling (ACM). The processes driving binder-nanoparticle interactions were unravelled by combining advanced characterization methods such as Transition Metal Oxide-based Materials (TMO-M), non-hydrolyzable sialic acid (N-HSIA), and oxygen reduction reaction process (ORR) investigations. In-depth simulation analyses were performed to verify the effectiveness of the proposed methods and gain further understanding. These simulations investigated alternative binding arrangements to maximize material performance while considering sustainability and economic factors. The results demonstrated how binder choice affects material properties, which can be valuable for designing better nanocomposite materials for specific purposes. Additionally, the ASCOA and ACM analyses revealed an accuracy ratio of more than 90% and efficiency ratios of 86% and 84% for ASCOA and ACM, respectively.
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