Nano-scale Study of Low Energy Plasma Reduced Graphene Oxide for Transparent Electrode Application of Organic Photovoltaics

Transparent, conductive, and mechanically flexible graphene films are seen as an alternative to indium tin oxide thin films as transparent conducting electrodes. Reduction of graphene oxide appears to be a promising approach for a large scale production of graphene. However the low quality of graphene obtained by this method and time consuming, high temperature, toxic reduction procedures required hinder its usefulness. In this work reduction of graphene oxide (GO) films using low energy hydrogen plasma as a simple and low cost approach to large scale production of graphene for transparent conductor application was demonstrated. GO films of different thickness were fabricated by repeated spin coating on quartz substrates. Films were reduced using radio frequency (RF) hydrogen plasma for different exposure times. A stainless-steel mesh electrode was used to moderate the etching damage of film by high energy charged species in plasma. UV visible absorption spectroscopy indicated that extent of the reduction was higher on thinner films for the same duration of plasma treatment. Raman spectroscopy showed that the reduction of defects was directly related to the duration of treatment and the thickness of the films. Current sensing atomic force microscopy were used to study the nanoscale structure and conductivity and were correlated to sheet resistance of the films. The sheet resistance of the films decreased with the increased number of coatings and plasma treatment time. The results of this study can help to develop a more effective plasma based reduction procedures to reduce sheet resistance. The sheet resistance of graphene based transparent electrode films obtained in this work was comparable to that obtained using hydrazine reduction. To obtain optimum sheet resistance and transmittance a tradeoff between chemical reduction and damage due to plasma etching is required. More effective reduction can be achieved by optimizing exposure time and sample distance