Theoretical study of the influence of surface effects on GaN-based chemical sensors

This paper presents the results of the theoretical study of various factors affecting the charging mechanism and characteristics of the Ga2O3/GaN/AlGaN based ion sensitive field effect transistor (ISFET). The relaxed atomic coordinates of electrolytes and water molecules at the alpha-gallium oxide (0 0 1) surface are used to calculate the interfacial properties of gallium nitride based ion selective field effect transistors. The hydration radius of electrolytes along with the distance of the first and the second layer of water on the surface are used to derive the equilibrium reaction rates of the protonation/deprotonation of surface sites and adsorption/desorption of ions to the second layer. The Triple Layer Model (TLM) is used to obtain the redistribution of electrolytes when they are exposed to the surface of the solid. Single site binding, TLM, Poisson-Boltzmann and Schrodinger equations are solved self-consistently to obtain the potential distribution across the device and electrolyte, accumulated charge at the surface and the density of electrons in the channel. Sensitivity of the device is affected by the thickness of the surface oxide on the GaN-cap layer. These results indicate that the inclusion of a thin layer of oxide at the surface of the GaN-based chemical sensor accounts for the surface chemistry, equilibrium reaction rates, and the relative surface conduction-band offset with the redox levels of electrolyte. The calculated values for the surface acidity, oxide/GaN-cap barrier height and the corresponding electron density in the channel as a function of the thickness of the AlGaN barrier, the GaN-cap and the surface oxide layer, distribution of electric fields within the device, and the Nernstian-slope of various structures, were compared with the literature for validation and were in close proximity of the experimental value. This model can be used to further refine GaN-based sensors for a range of applications. (C) 2018 Elsevier B.V. All rights reserved.