This project studied the optoelectronic properties of silver nanowires for transparent conductive electrode applications and investigated the effect of network damage on the electrical resistance and optical transmittance after fatigue mechanical straining deformation. The work focuses on developing and completing a predictive model based on percolation theory that considers the effect of dimension of nanowires, nanowire resistance and junction resistance. Spray coating was used as the deposition method of the Ag NW networks which can generate networks with stochastic distributed nanowires. The post treatment methods of thermal annealing and mechanical pressing were used to improve the contact at the NW-NW junctions and the adhesion between networks and the substrates, which optimise the electrical and optical properties of Ag NW networks. In this study, the effect of mechanical pressing was found to be better than thermal annealing for the nanowires used. The same deposition and post treatment method were carried out for all subsequent experiments. By comparing with the Ag NW networks created by other groups, our Ag NW networks exhibit comparable electrical and optical properties with Rs = 17 Î©/â¡ for T = 90%. A predictive model based on percolation can be used to predict the electrical resistance of a Ag NW network if the dimensions of nanowires and the mean nanowire coverage are known. The validity of this model for NW networks with induced bending strains have been verified. Furthermore, this thesis provides a systematic analysis of the damage mechanisms (fractions of fractured nanowires and broken NW-NW junctions) of the Ag NW network, which was predicted from the increase of its electrical resistance with the expanded application of the predictive model.
|Date of Award||31 Dec 2021|
- The University of Manchester
|Supervisor||William Sampson (Supervisor) & Brian Derby (Supervisor)|