A Green Synthesis of Iron Oxide Nanoparticles Using Full Factorial Experimental Design: Technical and Analytical Impact of FeCl3.6H2O Precursor on Yield
Keywords:
ANOVA, Full factorial, IONPs, Pro-analytical, TechnicalAbstract
Green synthesis has garnered significant interest in producing iron oxide nanoparticles (IONPs) due to its eco-friendliness and sustainability. This method simplifies the process, reduces costs, and minimizes waste by utilizing natural resources, one of which is a natural reducing agent from green tea extract. The green synthesis of IONPs uses different types of FeCl3.6H2O precursors, especially technical and pro-analytical. The method used is a full factorial experimental design to analyze factors such as reaction temperature, precursor concentration, and reducing agent volume. A factorial type linear regression equation was selected, and the factors were evaluated through analysis of variance (ANOVA) with the Design Expert 13.0.5.0 software program. The analysis results reveal that the predicted values are within reasonable consistency based on the experimental data of both IONPs from the technical and pro-analytical precursors. The ANOVA values for both precursor sources show that the reaction temperature factor is negatively correlated, while the precursor concentration and reducing agent volume are positively correlated with the IONPs yield. Regression model variance (ANOVA) can be explained 98.15% for the technical precursor model and 99.83% for the analytical precursor model from data variations.
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