Morus alba-Mediated Green Synthesis of ZnO Nanoparticles Coupled with Augmented ANN Modeling for Process Optimization and Predictive Design

Ahmadi, Omid; Javanmardi, Hamid; Mohammadi-Aghdam, Sarvin; Beigzadeh, Reza

doi:10.22059/jchpe.2026.408200.1694

Morus alba-Mediated Green Synthesis of ZnO Nanoparticles Coupled with Augmented ANN Modeling for Process Optimization and Predictive Design

Articles in Press

Document Type : Research Paper

Authors

Omid Ahmadi ¹

Hamid Javanmardi ¹

Sarvin Mohammadi-Aghdam ²

Reza Beigzadeh ¹

¹ Department of Chemical Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

² Department of Chemistry, Payam Noor University, Tehran, Iran

10.22059/jchpe.2026.408200.1694

Abstract

A sustainable and environmentally benign route for the synthesis of zinc oxide (ZnO) nanoparticles was developed using Morus alba leaf extract as a natural reducing and stabilizing agent. Multiple green synthesis approaches were systematically investigated in order to evaluate the influence of processing conditions on the physicochemical properties of the resulting nanoparticles. Key synthesis parameters, including reaction strategy and operating conditions, were analyzed with respect to their effects on crystallinity, particle size, and surface characteristics. The results revealed that the synthesis pathway plays a decisive role in governing the structural quality of ZnO nanoparticles, and an optimal operating window was identified that produces particles with enhanced crystallinity and favorable surface features. To further support process optimization, a data-augmented artificial neural network (ANN) model was developed to establish predictive relationships between synthesis parameters and nanoparticle properties. The ANN exhibited superior generalization capability and predictive accuracy compared with conventional statistical modeling approaches. Overall, this study provides both experimental insight and data-driven tools for the rational design and optimization of green ZnO nanoparticle synthesis, offering a reliable framework for scalable and eco-friendly nanomaterial production.

Keywords

Artificial neural network

Green synthesis

Predictive modeling

Process optimization

Zinc oxide nanoparticles

Subjects