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Experimental study demonstrates optimized green synthesis of gold nanoparticles using catechin, indicating a reliable predictive model for sustainable nanomaterial production.
Gold nanoparticles have become increasingly important because of their broad range of applications, especially in healthcare and life sciences. Hence, there is a growing need for greener synthesis methods that are both accessible and robust. Syntheses of gold nanoparticles remain nonetheless challenging. The formation mechanism(s) are often complex, requiring careful control of multiple variables to reliably produce nanoparticles with the desired properties. In this study, we explore a green bottom-up synthesis approach for the formation of gold nanoparticles using the flavonoid catechin as both the reducing and stabilizing agent. To systematically investigate the synthesis conditions, a design of experiments (DOE) framework was employed. A full factorial screening design was first used to assess the effect of three, two-level experimental variables on the experimental outcomes, followed by central composite optimization design to assess the effect of the remaining two, three-level experimental variables on experimental outcomes. Multivariate statistical analysis allowed for the identification of experimental variables with a statistically significant impact and provided mechanistic insight into the role of catechin as a reducing and stabilizing agent, facilitating synthesis optimization. The optimization model demonstrated predictive capability within the range of conditions tested.
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Subuloye et al. (2026) studied this question.
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