Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract
In this study silver nanoparticles (Ag-NPs) are biosynthesized from silver nitrate aqueous solution through a simple and eco-friendly route using Curcuma longa (C. longa) tuber powder extracts which acted as a reductant and stabilizer simultaneously. Characterizations of nanoparticles are done using...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
National Institute R and D of Materials Physics
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30112/1/Application%20of%20Artificial%20Neural%20Network.pdf |
| _version_ | 1825947642992001024 |
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| author | Shabanzadeh, Parvaneh Senu, Norazak Shameli, Kamyar Ismail, Fudziah |
| author_facet | Shabanzadeh, Parvaneh Senu, Norazak Shameli, Kamyar Ismail, Fudziah |
| author_sort | Shabanzadeh, Parvaneh |
| collection | UPM |
| description | In this study silver nanoparticles (Ag-NPs) are biosynthesized from silver nitrate aqueous solution through a simple and eco-friendly route using Curcuma longa (C. longa) tuber powder extracts which acted as a reductant and stabilizer simultaneously. Characterizations of nanoparticles are done using X-ray diffraction (XRD) and
transmission electron microscopy (TEM). We present an artificial neural network (ANN) approach is used to model the size of Ag-NPs as a function of the volume of C. Longa
extraction, temperature of reaction, stirring time and volume of AgNO3. The suitable ANN model is found to be a network with two layers that first layer has 10 neurons and second layer has 1 neuron. This model is capable for predicting the size of Ag-NPs synthesized by green method for a wide range of conditions with a mean absolute error of less than 0.01 and a regression of about 0.99. Based on the presented model it is possible to design an
effective green method for obtain Ag-NPs, while minimum received materials are used and minimum size of Ag-NPs will be obtained. Also simulation of the process is
performed using ANN media. According to the model’s results, the volume of C. Longa extraction, temperature of reaction, and volume of AgNO3 about 18 mL, 30 °C and 2 mL
are chosen as the optimum size of Ag-NPs, respectively. Results obtained reveal the reliability and good predicatively of neural network model for the prediction of the size of Ag-NPs in green method. |
| first_indexed | 2024-03-06T08:16:31Z |
| format | Article |
| id | upm.eprints-30112 |
| institution | Universiti Putra Malaysia |
| language | English English |
| last_indexed | 2024-03-06T08:16:31Z |
| publishDate | 2013 |
| publisher | National Institute R and D of Materials Physics |
| record_format | dspace |
| spelling | upm.eprints-301122016-02-03T01:36:07Z http://psasir.upm.edu.my/id/eprint/30112/ Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract Shabanzadeh, Parvaneh Senu, Norazak Shameli, Kamyar Ismail, Fudziah In this study silver nanoparticles (Ag-NPs) are biosynthesized from silver nitrate aqueous solution through a simple and eco-friendly route using Curcuma longa (C. longa) tuber powder extracts which acted as a reductant and stabilizer simultaneously. Characterizations of nanoparticles are done using X-ray diffraction (XRD) and transmission electron microscopy (TEM). We present an artificial neural network (ANN) approach is used to model the size of Ag-NPs as a function of the volume of C. Longa extraction, temperature of reaction, stirring time and volume of AgNO3. The suitable ANN model is found to be a network with two layers that first layer has 10 neurons and second layer has 1 neuron. This model is capable for predicting the size of Ag-NPs synthesized by green method for a wide range of conditions with a mean absolute error of less than 0.01 and a regression of about 0.99. Based on the presented model it is possible to design an effective green method for obtain Ag-NPs, while minimum received materials are used and minimum size of Ag-NPs will be obtained. Also simulation of the process is performed using ANN media. According to the model’s results, the volume of C. Longa extraction, temperature of reaction, and volume of AgNO3 about 18 mL, 30 °C and 2 mL are chosen as the optimum size of Ag-NPs, respectively. Results obtained reveal the reliability and good predicatively of neural network model for the prediction of the size of Ag-NPs in green method. National Institute R and D of Materials Physics 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30112/1/Application%20of%20Artificial%20Neural%20Network.pdf Shabanzadeh, Parvaneh and Senu, Norazak and Shameli, Kamyar and Ismail, Fudziah (2013) Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract. Digest Journal of Nanomaterials and Biostructures, 8 (3). pp. 1133-1144. ISSN 1842-3582 http://www.chalcogen.ro/digest.html English |
| spellingShingle | Shabanzadeh, Parvaneh Senu, Norazak Shameli, Kamyar Ismail, Fudziah Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title | Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title_full | Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title_fullStr | Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title_full_unstemmed | Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title_short | Application of Artificial Neural Network (ANN) for prediction diameter of silver nanoparticles biosynthesized in Curcuma longa extract |
| title_sort | application of artificial neural network ann for prediction diameter of silver nanoparticles biosynthesized in curcuma longa extract |
| url | http://psasir.upm.edu.my/id/eprint/30112/1/Application%20of%20Artificial%20Neural%20Network.pdf |
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