We study by means of Monte-Carlo numerical simulations the resistance of two-dimensional random percolating networks of stick, widthless nanowires. We use the multi-nodal representation (MNR) 1 to model a nanowire network as a graph. We derive numerically from this model the expression of the total resistance as a function of all meaningful parameters, geometrical and physical, over a wide range of variation for each. We justify our choice of non-dimensional variables applying Buckingham π−theorem. The effective resistance of 2D random percolating networks of nanowires is found to write as R eq (ρ, Rc, Rm,w) = A N, L l * ρl * + B N, L l * Rc + C N, L l * Rm,w where N , L l * are the geometrical parameters (number of wires, aspect ratio of electrode separation over wire length) and ρ, Rc, Rm,w are the physical parameters (nanowire linear resistance per unit length, nanowire/nanowire contact resistance, metallic electrode/nanowire contact resistance). The dependence of the resistance on the geometry of the network, one the one hand, and on the physical parameters (values of the resistances), on the other hand, is thus clearly separated thanks to this expression, much simpler than the previously reported analytical expressions.
I. INTRODUCTIONThe study of random percolating networks of conducting nanowires has become in the last years a hot topic of investigation. Numerous applications are possible thanks to the outstanding electrical and optical performances of such thin films, combined to their low cost and ease of fabrication. Applications are as diverse as thin film transistors based on carbon nanotubes networks (CNNs) 2,3 , CNNs-based field-effect transistors 4 , transparent conductive (high transmittance, low resistance) thin-film electrodes based on silver nanowires 1,5 or carbon nanotubes (CNTs) 6 -useful for instance in the context of solar cells, the conducting nanowire network acting as a charge carrier collector 7 -and sensors 4 . The conductivity, as well as the sheet transmittance of such thin film nanowire networks has been extensively studied experimentally and theoretically 6,8,9 . These systems are well approximated by random 2D networks, and we study in this paper the dependence of their effective resistance on all structural and physical parameters. We focus on the functional dependence of the resistance on physical parameters, motivated by sensor applications of nanowire networks. In this context, physical parameters, such as nanowire linear resistance, or nanowire/nanowire contact resistance, can vary, due to environment changes. The geometry and structure of the network is thus not sufficient to understand properly the resistance variations.Many parameters impact the total effective resistance of nanowire random networks. Structural parameters such as the density (or coverage), the aspect ratio of electrode separation to wire length, and the alignment of the wires (i.e. the statistical distribution of their angles with respect to a fixed direction) are, among others, known to play on the trans...