Systematic Multivariate Analysis for Optimizing Active and Selective AuPd-Based-Nanocatalyts towards Benzyl Alcohol Oxidation

Abstract

Supported bimetallic gold-palladium (AuPd) nanomaterials have been extensively studied as highly active and selective nanocatalysts for oxidation reactions. For long-term viability, optimizing synthesis and reaction parameters is essential for utilizing noble-based materials once they are expensive to produce on a large scale. For that reason, using a performance-focused strategy like a multivariate experimental design is an optimal solution for simultaneously investigating the effects of different parameters and implementing such materials in business activities. Therefore, herein, we report a systematic multivariate optimization of model AuPd/SiO2 nanocatalysts for selective benzyl alcohol oxidation in solvent-free sustainable conditions, which allows for the evaluation of the impact of the material synthesis and reaction conditions on the process and optimization of reaction and calcination temperatures. Our multivariate analysis shows that the calcination temperature has considerably impacted the structural properties of gold nanoparticles; still, these changes did not produce a pronounced effect on the material’s catalytic properties. On the other hand, the physical variables of reaction time and temperature had a more significant influence on both conversion and selectivity. An 18% conversion of benzyl alcohol with a benzaldehyde selectivity of 93% was achieved under a 562 ◦C catalyst calcination temperature, 100 ◦C reaction temperature, and 4 h of reaction time.