Prediction and optimization of stability parameters for titanium dioxide nanofluid using response surface methodology and artificial neural networks
The effect of various process parameters on the stability of TiO2 nanofluid, which can mostly be defined as zeta potential and particle size, was studied using response surface methodology (RSM) by the design of experiments and was predicted through a trained artificial neural network (ANN). The pro...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2013-11-01
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| Series: | Science and Engineering of Composite Materials |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/secm-2013-0017 |