Metal oxide-graphene field-effect transistor: interface trap density extraction model

• Main Authors: Najam, F., Lau, K. C., Lim, C. S., Yu, Y. S., Tan, M. L. P.
• Format: Article
• Language: English
• Published: Beilstein-Institut Zur Forderung der Chemischen Wissenschaften 2016
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/72074/1/FarazNajam2016_MetalOxideGrapheneFieldEffectTransistor.pdf; http://eprints.utm.my/id/eprint/72074/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84990842235&doi=10.3762%2fbjnano.7.128&partnerID=40&md5=b4b0ca42f1c9cb625791d0d644f9e2cf

A simple to implement model is presented to extract interface trap density of graphene field effect transistors. The presence of interface trap states detrimentally affects the device drain current-gate voltage relationship Ids-Vgs. At the moment, there is no analytical method available to extract the interface trap distribution of metal-oxide-graphene field effect transistor (MOGFET) devices. The model presented here extracts the interface trap distribution of MOGFET devices making use of available experimental capacitance-gate voltage Ctot-Vgs data and a basic set of equations used to define the device physics of MOGFET devices. The model was used to extract the interface trap distribution of 2 experimental devices. Device parameters calculated using the extracted interface trap distribution from the model, including surface potential, interface trap charge and interface trap capacitance compared very well with their respective experimental counterparts. The model enables accurate calculation of the surface potential affected by trap charge. Other models ignore the effect of trap charge and only calculate the ideal surface potential. Such ideal surface potential when used in a surface potential based drain current model will result in an inaccurate prediction of the drain current. Accurate calculation of surface potential that can later be used in drain current model is highlighted as a major advantage of the model.