▎ 摘　　要

A novel method is employed for the derivation of an analytical model for a carbon-dioxide (CO2) gas sensor based on graphene nanoribbon (GNR) conductance variation. The capacitance gradient created between the channel and the gate of a field effect transistor device is employed as an important property in the interpretation. Gas concentration and its effect on capacitance are incorporated as a modelling platform. In another attempt to model the electrical conductance in GNRs, an intelligent artificial neural network scheme is used in the modelling stage. A satisfactory agreement is presented by comparison between the empirical data extracted from a study conducted by Yoon et al. and the proposed models.