Physical modelling of large area 4H-SiC PiN diodes

Bryant, A.T.; Jennings, Michael R.; Parker-Allotey, N.-A.; Mawby, P.A.; Pérez‐Tomás, Amador; Brosselard, Pierre; Godignon, P.; Jordà, X.; Millán, José del R.; Palmer, P.R.; Santi, Enrico; Hudgins, J.L.

doi:10.1109/ecce.2009.5316233

Cited by 5 publications

(5 citation statements)

References 45 publications

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“…This can be due to external resistance not included in the simulations (contact resistance, oxide resistance, etc.) or difficulties with the measurements [10,11]. Sentaurus TCAD allows device/circuit mixed-mode simulations.…”

Section: Results and Analysismentioning

confidence: 99%

Tailoring the Charge Carrier Lifetime Distribution of 10 kV SiC PiN Diodes by Physical Simulations

Yuan

Schöner

Reshanov

et al. 2023

KEM

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In this paper, Shockley-Read-Hall (SRH) lifetime depth profiles in the drift layer of 10 kV SiC PiN diodes are calculated after MeV proton implantation. It is assumed that the carbon vacancy will be the domination trap for charge carrier recombination and the SRH lifetime is calculated with defect parameters from the literature and proton-induced defect distributions deduced from SRIM calculations. The lifetime profiles are imported to Sentaurus TCAD and static and dynamic simulations using tailored lifetime profiles are carried out to study the electrical effect of proton implantation parameters. The results are compared to measurements, specializing on optimization of the trade off between on-state and turn-off losses, represented by the forward voltage drop, VT, and reverse recovery charge, Qrr, respectively. Both the simulated and measured IV characteristics show that increasing proton dose, or energy, has the effect on increasing forward voltage drop and on-state losses, while simultaneously, the localized SRH lifetime drop decreases the plasma level, increases the speed of recombination and decreases reverse recovery charge. Finally, TCAD simulations with different combinations of proton energies and fluences are used to optimize the trade-off between static and dynamic performances. Reverse recovery charge and forward voltage drops of these groups of diodes are plotted together, showing that a medium energy which induces the most defects in the depletion region relatively close to the anode gives the best dynamic performances, with a minimum cost of static performance.

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Section: Results and Analysismentioning

confidence: 99%

Tailoring the Charge Carrier Lifetime Distribution of 10 kV SiC PiN Diodes by Physical Simulations

Yuan

Schöner

Reshanov

et al. 2023

KEM

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“…The switching experiment was done using a high-voltage Schottky diode C3D20060, while during the simulation a power SiC PN − N + diode model was used. The details of the diode model are given in [11] and [16]. The intent of using the pin diode structure was to verify the robustness of the device models through convergence of the simulation to the correct results when using more than one power device.…”

Section: Measurement and Simulation Results Of Sic Bjtmentioning

confidence: 99%

“…The feedback subsystem uses the output data from the CSR subsystem, the charge carrier densities p x 1 and p x 2 , as inputs. These carrier densities are used to determine V d 1 and V d 2 using (16). The boundary positions x 1 and x 2 are calculated using (17) and (18).…”

Section: Realization In Simulinkmentioning

confidence: 99%

Modeling, Simulation, and Validation of a Power SiC BJT

Gachovska

Hudgins

Bryant³

et al. 2012

IEEE Trans. Power Electron.

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This paper presents a physics-based model of a silicon carbide bipolar junction transistor and verification of its validity through experimental testing. The Fourier series solution is used to solve the ambipolar diffusion equation in the transistor collector region. The model is realized using MATLAB and Simulink. The experimental results of static operation and also the simulated and experimental results of switching waveforms are given. Index Terms-Silicon carbide (SiC) bipolar junction transistor (BJT), power semiconductor modeling. NOMENCLATURE A Device area (cm 2). C J 1 and C J 2 Capacitance of the depletion layers (F). D Ambipolar diffusivity (cm 2 s −1). D p and D p Electron and hole diffusivities (cm 2 s −1). ε Dielectric permittivity of SiC (F/cm). h n N + emitter recombination parameter (cm 4 s −1). h p P + emitter recombination parameter (cm 4 s −1). I B Base current (A). I C Collector current (A). I disp1 and I disp2 Displacement currents at junctions J 1 and J 2 (A). I L 0 Initial inductor current (A). I n 0 , I n 1 , and I n 2 Electron currents at junctions J 0 , J 1 , and J 2 (A).

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“…At present, researchers have made great achievements in establishing diode models such as the behavioural model, numerical model and physical model, but only limited work has been done for the SiC merged PiN Schottky (MPS) diodes. This can be explained by the fact that MPS diodes are hybrid diodes and have become commercially available only recently [4–12]. A typical method to establish the correct SiC MPS physical model is to solve the ambipolar diffusion equation [9].…”

Section: Introductionmentioning

confidence: 99%

“…This can be explained by the fact that MPS diodes are hybrid diodes and have become commercially available only recently [4–12]. A typical method to establish the correct SiC MPS physical model is to solve the ambipolar diffusion equation [9]. However, some of its parameters are fitted and have no physical meaning.…”

Section: Introductionmentioning

confidence: 99%