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Prediction of silver nanoparticles' diameter in montmorillonite/chitosan bionanocomposites by using artificial neural networks.
- Source :
-
Research on Chemical Intermediates . May2015, Vol. 41 Issue 5, p3275-3287. 13p. 3 Diagrams, 3 Charts, 2 Graphs. - Publication Year :
- 2015
-
Abstract
- Artificial neural networks (ANNs) are computational tools that have found comprehensive utilization in solving many complex real world problems. Major benefits in using ANNs are their remarkable information-processing characteristics pertinent mainly to high parallelism, nonlinearity, fault and noise tolerance, and learning and generalization capabilities. An ANN approach is used to model the size of silver nanoparticles (Ag-NPs) in montmorillonite/chitosan bionanocomposites layers as a function of the silver nitrate concentration, reaction of temperature, chitosan percentage, and d-spacing of clay layers. The best ANN model is found and this final model is capable of predicting the size of nanosilver for a wide range of conditions with a mean absolute error of less than 0.004 and a regression error of about 1. Results obtained showed good ability predictive of neural network model for the prediction of the size of Ag-NPs in chemical reduction methods. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09226168
- Volume :
- 41
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Research on Chemical Intermediates
- Publication Type :
- Academic Journal
- Accession number :
- 101947863
- Full Text :
- https://doi.org/10.1007/s11164-013-1431-6