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Shafaei, Amineh, Khayati, Gholam. (1400). Gene Expression Programming for Green Synthesis of Silver Nanoparticles: Size Evolution. , 54(2), 180-191. doi: 10.22059/jufgnsm.2021.02.07
Amineh Shafaei; Gholam Reza Khayati. "Gene Expression Programming for Green Synthesis of Silver Nanoparticles: Size Evolution". , 54, 2, 1400, 180-191. doi: 10.22059/jufgnsm.2021.02.07
Shafaei, Amineh, Khayati, Gholam. (1400). 'Gene Expression Programming for Green Synthesis of Silver Nanoparticles: Size Evolution', , 54(2), pp. 180-191. doi: 10.22059/jufgnsm.2021.02.07
Shafaei, Amineh, Khayati, Gholam. Gene Expression Programming for Green Synthesis of Silver Nanoparticles: Size Evolution. , 1400; 54(2): 180-191. doi: 10.22059/jufgnsm.2021.02.07

Gene Expression Programming for Green Synthesis of Silver Nanoparticles: Size Evolution

Journal of Ultrafine Grained and Nanostructured Materials
دوره 54، شماره 2، اسفند 2021، صفحه 180-191    اصل مقاله (2.43 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jufgnsm.2021.02.07
نویسندگان
Amineh Shafaei1؛ Gholam Reza Khayati* 2
1Department of Materials Science and Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, 7618868366 Kerman, Iran
2Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
چکیده
In this study, gene expression programming (GEP) was used as a new method for the formulation of the size of Ag nanoparticles (AgNPs) as functions of the AgNO3-to-opium syrup (OS) ratio, pH, temperature (T), agitation speed (AS) and feed rate (Fr) of reducing agent in green synthesis. The models differ from each other concerning their genes number, chromosomes, interconnected function, and head size. A total of 63 samples were selected at different practical parameter products to generate databases for the new particle size formulations, testing, and training sets. The training and testing sets included 47 and 16 randomly selected mixtures for the proposed models. The best GEP model is found, and this final model can predict the size of AgNPs with an R squared of 0.828, a root means square error (RMSE) of 5.894, a root-relative squared error (RRSE) of 0.44. All results in the models indicated an applicable performance for predicting the minimum particle size of the AgNPs and found it reliable. The predicted model showed that all of the input parameters affect the resulting particle size. GEP modeling results denoted that the selected GEP successfully predicts the behavior of the size of nanoparticles as functions of operating variables.
کلیدواژه‌ها
Gene expression programming؛ Green synthesis؛ Ag nanoparticles؛ Modeling
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