This work investigates p+ n− n GaN-on-Si vertical structures, through dedicated measure-ments and TCAD simulations, with the ultimate goal of identifying possible strategies for leakage and breakdown optimization. First, the dominant leakage processes were identified through temperature-dependent current–voltage characterization. Second, the breakdown voltage of the diodes was modelled through TCAD simulations based on the incomplete ionization of Mg in the p+ GaN layer. Finally, the developed simulation model was utilized to estimate the impact of varying the p-doping concentration on the design of breakdown voltage; while high p-doped structures are limited by the critical electric field at the interface, low p-doping designs need to contend with possible depletion of the entire p-GaN region and the consequent punch-through. A trade-off on the value of p-doping therefore exists to optimize the breakdown.

Understanding the leakage mechanisms and breakdown limits of vertical GaN-on-Si p+ n− n diodes: The road to reliable vertical MOSFETs

Mukherjee K.;De Santi C.;Buffolo M.;Gerosa A.;Meneghesso G.;Zanoni E.;Meneghini M.
2021

Abstract

This work investigates p+ n− n GaN-on-Si vertical structures, through dedicated measure-ments and TCAD simulations, with the ultimate goal of identifying possible strategies for leakage and breakdown optimization. First, the dominant leakage processes were identified through temperature-dependent current–voltage characterization. Second, the breakdown voltage of the diodes was modelled through TCAD simulations based on the incomplete ionization of Mg in the p+ GaN layer. Finally, the developed simulation model was utilized to estimate the impact of varying the p-doping concentration on the design of breakdown voltage; while high p-doped structures are limited by the critical electric field at the interface, low p-doping designs need to contend with possible depletion of the entire p-GaN region and the consequent punch-through. A trade-off on the value of p-doping therefore exists to optimize the breakdown.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3390780
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