Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method

The artificial neural network (ANN) models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the casting methods. Determination of particle size is one of the critical parameters in nanotechnology.TheAg-NPs have at...

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Main Authors: Shabanzadeh, Parvaneh, Senu, Norazak, Shameli, Kamyar, Ismail, Fudziah, Mohagheghtabar, Maryam
Format: Article
Language:English
English
Published: National Institute R and D of Materials Physics 2013
Online Access:http://psasir.upm.edu.my/id/eprint/30164/1/Application%20of%20Artificial%20Neural%20Network.pdf
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author Shabanzadeh, Parvaneh
Senu, Norazak
Shameli, Kamyar
Ismail, Fudziah
Mohagheghtabar, Maryam
author_facet Shabanzadeh, Parvaneh
Senu, Norazak
Shameli, Kamyar
Ismail, Fudziah
Mohagheghtabar, Maryam
author_sort Shabanzadeh, Parvaneh
collection UPM
description The artificial neural network (ANN) models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the casting methods. Determination of particle size is one of the critical parameters in nanotechnology.TheAg-NPs have attracted significant attention for chemical, physical and clinical applications due to their exceptional properties.The nanosilver crystals were prepared in the biopolymer mediated without any aggregation by using green chemical reduction method. The method has an advantage of size control which is essential in nano-metal synthesis. The resulting of silver nanoparticles (Ag-NPs) characterized by using of X-ray diffraction (XRD) and transmission electron microscopy (TEM) technique.XRD patterns confirmed that Ag-NPs crystallographic planes were face centered cubic (fcc) type. TEM results showed that mean diameters of Ag-NPs for four different amounts of variables were less than 40 nm. This method with comparison to other methods is green, high yield, speedy and easy to use.This paper presents an ANN model for the predictionsize of Ag-NPs by green method. Themodel accounts for the effect of NaOH volumes, temperature, stabilizer, and AgNO3 concentration on the size of nanoparticle.The best model presented a trustworthy agreement in predicting experimental data. The characteristic parameters of the presented ANN models are fully reported in the paper.
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spelling upm.eprints-301642016-02-03T01:38:09Z http://psasir.upm.edu.my/id/eprint/30164/ Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method Shabanzadeh, Parvaneh Senu, Norazak Shameli, Kamyar Ismail, Fudziah Mohagheghtabar, Maryam The artificial neural network (ANN) models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the casting methods. Determination of particle size is one of the critical parameters in nanotechnology.TheAg-NPs have attracted significant attention for chemical, physical and clinical applications due to their exceptional properties.The nanosilver crystals were prepared in the biopolymer mediated without any aggregation by using green chemical reduction method. The method has an advantage of size control which is essential in nano-metal synthesis. The resulting of silver nanoparticles (Ag-NPs) characterized by using of X-ray diffraction (XRD) and transmission electron microscopy (TEM) technique.XRD patterns confirmed that Ag-NPs crystallographic planes were face centered cubic (fcc) type. TEM results showed that mean diameters of Ag-NPs for four different amounts of variables were less than 40 nm. This method with comparison to other methods is green, high yield, speedy and easy to use.This paper presents an ANN model for the predictionsize of Ag-NPs by green method. Themodel accounts for the effect of NaOH volumes, temperature, stabilizer, and AgNO3 concentration on the size of nanoparticle.The best model presented a trustworthy agreement in predicting experimental data. The characteristic parameters of the presented ANN models are fully reported in the paper. National Institute R and D of Materials Physics 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30164/1/Application%20of%20Artificial%20Neural%20Network.pdf Shabanzadeh, Parvaneh and Senu, Norazak and Shameli, Kamyar and Ismail, Fudziah and Mohagheghtabar, Maryam (2013) Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method. Digest Journal of Nanomaterials and Biostructures, 8 (2). pp. 541-549. ISSN 1842-3582 http://www.chalcogen.ro/digest.html English
spellingShingle Shabanzadeh, Parvaneh
Senu, Norazak
Shameli, Kamyar
Ismail, Fudziah
Mohagheghtabar, Maryam
Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title_full Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title_fullStr Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title_full_unstemmed Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title_short Application of artificial neural network(ANN) for the prediction of size of silver nanoparticles prepared by green method
title_sort application of artificial neural network ann for the prediction of size of silver nanoparticles prepared by green method
url http://psasir.upm.edu.my/id/eprint/30164/1/Application%20of%20Artificial%20Neural%20Network.pdf
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