Title: Selection of the most influential parameters on vectorial crystal growth of highly oriented vertically aligned carbon nanotubes by adaptive neuro-fuzzy technique
Authors: Maryam Safa; Masoud Ahmadi; Javad Mehrmashadi; Dalibor Petkovic; Mohammad Mohammadhassani; Yousef Zandi; Yadollah Sedghi
Addresses: Department of Civil Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia ' Department of Civil Engineering, Ayatollah Boroujerdi University, Boroujerd, Iran ' Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA ' University of Niš, Pedagogical Faculty in Vranje, Partizanska 14, 17500 Vranje, Serbia ' Road, Housing and Development Research Center, Tehran, Iran ' Department of Civil Engineering, Qeshm International Branch, Islamic Azad University, Qeshm, Iran ' Department of Civil Engineering, Qeshm International Branch, Islamic Azad University, Qeshm, Iran
Abstract: The optimum raising conditions to synthesis the high crystallinity carbon nanotubes (CNTs) for improvement of their physical properties are presented in this study, thus, ANFIS has been used to optimise the most effectual characteristics for predicting the crystal growing of oriented vertically aligned carbon nanotubes (OVACNT) by discovering the subset of input characteristics' whole set. ANFIS has also been applied to delineate four characteristics as: 1) vaporising time (min); 2) annealing time (AT) (min); 3) precursor's concentration (mL); 4) deposition temperature (°C) have influenced the predicting of crystallinity of highly OVACNTs. The outcomes have shown that precursor's concentration has the highest influence to the crystallinity of OVACNTs predicting with higher accuracy.
Keywords: ANFIS; growing condition; crystalline CNTs; variable selection; explanatory variables; CVD.
International Journal of Hydromechatronics, 2020 Vol.3 No.3, pp.238 - 251
Received: 02 Sep 2019
Accepted: 11 Oct 2019
Published online: 29 Sep 2020 *