Abstract
The uniqueness of multilayer graphene as extremely high carrier mobility, tune-able band gap and high elasticity has made it be considered as a high prospect engineering material that can be employed for several applications such as solar cells, field effect transistors, super-capacitors, batteries and sensors. In this study, the application of Artificial Neural Networks (ANN) for the predictive modeling of multilayer graphene (MLG) growth by chemical vapor deposition (CVD) on Co-Ni/Al2O3 substrate was investigated. Data comprises temperature, catalyst compositions, ethanol flowrates were generated using central composite experimental design and employed to obtain the MLG yield as the response. The data were subsequently used for predictive modeling using ANN. The findings show that the predictive values of the MLG yields were in good agreement with those obtained from the experimental runs having a coefficient of determination (R2 ) of 0.988.
Highlights
The advent of nanotechnology and quest for miniaturization of electronic components in scientific equipment has aroused research interest in graphene and multilayer graphene [1]
The synthesized multilayer graphene was characterized by Scanning Electron Microscopy (SEM), Transmission Electron Microscopy, Energy Dispersive X-ray (EDX), Raman Spectroscopy, and X-Ray Diffraction analysis
This implies that the use of the 10 hidden neurons for subsequent training, validation and testing of the neural network will result in a minimum error with an accurate prediction of the multilayer graphene yield
Summary
The advent of nanotechnology and quest for miniaturization of electronic components in scientific equipment has aroused research interest in graphene and multilayer graphene [1]. Several techniques such as chemical vapour deposition, epitaxial growth, arc discharge, unzipping of carbon nanotube, electrochemical synthesis, total organic synthesis, chemical reduction of graphene oxide, and plasma discharge etching of graphite have been employed for the synthesis of graphene and multilayer graphene [4,6,8,9]. Amongst these techniques, chemical vapour deposition has been reported has suitable techniques to synthesized graphene and multilayer graphene in a commercial quantity [10,11].
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