In this article, by means of a 2-D ensemble Monte Carlo simulator, the Schottky barrier diodes (SBDs) with realistic geometries based on GaAs and GaN are studied as promising devices for increasing the high-frequency performance-and power-handling capability of frequency mixers and multipliers. The nonlinearity of the capacitance-voltage (C-V) characteristic is the most important parameter for optimizing the performance of SBDs as frequency multipliers. The small size of the diodes used for ultrahigh-frequency applications makes the value of its intrinsic capacitance to deviate from the ideal one due to fringing effects. We have observed that the value of the edge capacitance well into reverse bias does not depend on the applied voltage. We define an edge-effect parameter β, which, interestingly, is affected by the presence or absence of surface charges at the semiconductor-dielectric interface σ . Two physical models have been considered: a fixed σ related to a surface potential V s constant surface-charge model (CCM) and a self-consistent model in which the local value of σ is dynamically evaluated depending on the surrounding electron density self-consistent surface-charge model (SCCM). Using the CCM, we obtain that β depends on the depth of the depletion region W s created by the surface charges, nearly irrespectively of the epilayer doping or semiconductor type. The more realistic SCCM indicates that, at low frequencies, when the surface charges are able to follow the variations of the applied voltage, the value of β approaches the one obtained without surface charges, while the high-frequency value (the significant one) is smaller. Index Terms-Edge effects (EEs), GaAs and GaN planar Schottky barrier diodes (SBDs), Monte Carlo (MC) simulation.
A model to predict the ideal reverse leakage currents in Schottky barrier diodes, namely, thermionic emission and tunneling components, has been developed and tested by means of current–voltage–temperature measurements in GaN-on-SiC devices. The model addresses both current components and both forward and reverse polarities in a unified way and with the same set of parameters. The values of the main parameters (barrier height, series resistance, and ideality factor) are extracted from the fitting of the forward-bias I–V curves and then used to predict the reverse-bias behavior without any further adjustment. An excellent agreement with the I–V curves measured in the forward bias in the GaN diode under analysis has been achieved in a wide range of temperatures (275–475 K). In reverse bias, at temperatures higher than 425 K, a quasi-ideal behavior is found, but additional mechanisms (most likely trap-assisted tunneling) lead to an excess of leakage current at lower temperatures. We demonstrate the importance of the inclusion of image-charge effects in the model in order to correctly predict the values of the reverse leakage current. Relevant physical information, like the energy range at which most of the tunnel injection takes place or the distance from the interface at which tunneled electrons emerge, is also provided by the model.
The influence of passivation on the edge effects (EEs) present in the capacitance-voltage (C-V ) characteristics of GaN Schottky barrier diodes (SBDs) with realistic geometry is analyzed by means of Monte Carlo simulations. The enhancement of the performance of SBDs as frequency multipliers is based on the optimization of the nonlinearity of the C-V curve, where EEs, strongly influenced by the dielectric passivation of the diode, play a significant role and must be carefully considered. The extra capacitance associated with EEs is affected by the presence of surface charges at the semiconductor/dielectric interface, which is considered by means of a self-consistent model in which the local value of the surface charge is updated according to the surrounding electron density. Our results indicate that, in realistic SBD geometries, a higher dielectric constant of the passivation material leads to more pronounced EEs. The thickness of the dielectric and the lateral extension of the epilayer are also important parameters to be taken into account when dealing with EEs.
This work shows that for a correct analysis of Schottky barrier diodes operating under strong reverse-bias conditions, it is necessary to account for the self-consistency between the shape of the energy barrier and carrier concentration in the depletion region, since the full-depletion approximation fails to estimate the current. This happens for very high applied voltages, at which impact ionization must also be considered. Two example GaN diodes with different doping concentration and barrier height are analyzed. The results are relevant to regions of the diodes where a very high tunnel injection takes place, like the contact edge or surface inhomogeneities.
Schottky barrier diodes (SBDs) with realistic geometries have been studied by means of a 2-D ensemble Monte Carlo simulator. The non-linearity of the Capacitance-Voltage (C-V) characteristic is the most important parameter for optimizing SBDs as frequency multipliers. In this paper, by changing the values of several technological parameters, we analyze their influence on the edge fringing capacitance in a GaN SBD. We have found that the parameters related with the dielectric used for the passivation and the lateral extension of the epilayer significantly affect the fringing capacitance, thus increasing the value of the total capacitance above the ideal one.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.