Characterisation of the High Temperature Performance of 4H-SiC Schottky Barrier Diodes

Blasciuc-Dimitriu, C.; Horsfall, Alton B.; Vassilevski, Konstantin; Johnson, C.M.; Wright, Nicolas G.; O’Neill, Anthony

doi:10.4028/www.scientific.net/msf.433-436.823

Cited by 4 publications

(1 citation statement)

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“…This paper reports on the development of a model, first introduced in [13], that describes the forward and reverse characteristics of 4H-SiC SBDs. This model is based on the self-consistent transfer matrix evaluation of the quantummechanical probabilities of carriers (also called transmission coefficients) to traverse the metal-semiconductor barrier.…”

Section: Introductionmentioning

confidence: 99%

Quantum modelling of I–V characteristics for 4H–SiC Schottky barrier diodes

Blasciuc-Dimitriu¹,

Horsfall²,

Wright³

et al. 2004

Semicond. Sci. Technol.

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The prediction of reverse bias I-V characteristics in 4H-SiC Schottky barrier diodes over a wide range of temperatures and bias is not possible using established modelling techniques. This paper reports on the development of an established general model for both reverse and forward characteristics that is applied to 4H-SiC Schottky barrier diodes. This model is based on the self-consistent evaluation of the quantum-mechanical probabilities of carriers to traverse the metal-semiconductor barrier. These are integrated over all possible energies to describe the transport process not only at energies below the barrier but also at energies equal and superior to the barrier height. In this manner the model naturally covers the entire range of the traditional theories of tunnelling, thermionic-field and thermionic emission. The model relies on a single set of parameters, extracted from the experimental forward characteristics of each device using a modified Norde method, to predict both forward and reverse characteristics. The model is compared to measured I-V characteristics, in both forward and reverse bias conditions, for 4H-SiC Schottky barrier diodes fabricated using two different edge termination technologies. Comparisons with models previously described in the literature show a superior fit to experimental data, without the need for additional fitting parameters.

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Section: Introductionmentioning

confidence: 99%