TY - JOUR ID - TI - Predictive Modeling of Multilayer Graphene Growth by Chemical Vapour Deposition on Co-Ni/Al2O3 Substrate using Artificial Neural Network AU - Bamidele V. Ayodele AU - Zainab Yousif AU - Mohamed A. Abdel Ghany AU - May A. Muslim PY - 2019 VL - 37 IS - 1 Part (c) special SP - 113 EP - 119 JO - Engineering and Technology Journal مجلة الهندسة والتكنولوجيا SN - 16816900 24120758 AB - Abstract- The uniqueness of multilayer graphene as extremely high carriermobility, tune-able band gap and high elasticity has made it be considered asa high prospect engineering material that can be employed for severalapplications such as solar cells, field effect transistors, super-capacitors,batteries and sensors. In this study, the application of Artificial NeuralNetworks (ANN) for the predictive modeling of multilayer graphene (MLG)growth by chemical vapor deposition (CVD) on Co-Ni/Al2O3 substrate wasinvestigated. Data comprises temperature, catalyst compositions, ethanolflowrates were generated using central composite experimental design andemployed to obtain the MLG yield as the response. The data weresubsequently used for predictive modeling using ANN. The findings show thatthe predictive values of the MLG yields were in good agreement with thoseobtained from the experimental runs having a coefficient of determination (R2)of 0.988.

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