Length prediction of silicon nanowires (SiNWs) prepared by the MACE method using the ANN-COA-PSO algorithm for high supercapacitor applications

作     者：Zeraati, Malihe Chen, Tzu-Chia Ebri, Masoumeh Chauhan, Narendra Pal Singh Sargazi, Ghasem 

作者机构：Shahid Bahonar Univ Kerman Dept Mat Engn Kerman 761694111 Iran Krirk Univ Int Coll Business Adm Program 3 Soi Ramindra 1 Bangkok 10220 Thailand Islamic Azad Univ Dept Comp Syst Architecture Branch Electron Tehran Iran Bhupal Nobles Univ Fac Sci Dept Chem Udaipur 313002 Rajasthan India Bam Univ Med Sci Noncommunicable Dis Res Ctr Bam Iran 

出 版 物：《JOURNAL OF PHYSICS AND CHEMISTRY OF SOLIDS》 (固体物理学与固体化学杂志)

年 卷 期：2021年第156卷

页      面：110146-110146页

核心收录：

学科分类：07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 070205[理学-凝聚态物理] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0703[理学-化学] 0702[理学-物理学] 

基　　金：Bam University of Medical Sciences 

主　　题：SiNWs Metal-assisted chemical etching Artificial neural networks Cuckoo optimization algorithm Particle swarm optimization Supercapacitor 

摘      要：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.