(2021) Length prediction of silicon nanowires (SiNWs) prepared by the MACE method using the ANN-COA-PSO algorithm for high supercapacitor applications. Journal of Physics and Chemistry of Solids. p. 11. ISSN 0022-3697
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Abstract
In this study, the metal-assisted chemical etching of silicon with the help of metal is used to fabricate large-scale silicon nanowire arrays (SiNWs). This method was optimised by artificial neural networks (ANN) and the cuckoo optimization algorithm (COA) was used to optimize ANN. Finally, the particle swarm optimization (PSO) method has been used to achieve the maximum length of silicon nanowires. As a result, the nanowires produced by the 1 M NaOH electrolyte had the properties of a capacitive cloud with a capacity of 758 mF/cm(2). It has the potential to be an excellent candidate for supercapacitor applications.
| Item Type: | Article |
|---|---|
| Keywords: | SiNWs Metal-assisted chemical etching Artificial neural networks Cuckoo optimization algorithm Particle swarm optimization Supercapacitor fabrication growth arrays electrodes orientation absorption surface Chemistry Physics |
| Divisions: | |
| Page Range: | p. 11 |
| Journal or Publication Title: | Journal of Physics and Chemistry of Solids |
| Journal Index: | ISI |
| Volume: | 156 |
| Identification Number: | https://doi.org/10.1016/j.jpcs.2021.110146 |
| ISSN: | 0022-3697 |
| Depositing User: | مهندس مهدی شریفی |
| URI: | http://eprints.mubam.ac.ir/id/eprint/957 |
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