A New Surface Potential Based Poly-Si TFT Model for Circuit Simulation

Tsuji, Hiroshi; Kuzuoka, Takashi; Kishida, Yuji; Shimizu, Yoshiyuki; Kirihara, Masaharu; Kamakura, Yoshinari; Morifuji, Masato; Miyano, S.; Taniguchi, Kenichi

doi:10.1109/iedm.2006.346991

Cited by 12 publications

(5 citation statements)

References 17 publications

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“…Equations ( 14) and (17) indicate that the increase in electron density is equal to n ph , which suggests the linear increase in off-state I ph with light intensity. Equations ( 17) and ( 18) are validated by introducing the relationship eq.…”

Section: Energy ( Ev )mentioning

confidence: 99%

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Analysis of Photon-Induced Drain Current in Polycrystalline-Silicon Thin-Film Transistors

Ikeda

Sano

2009

Jpn. J. Appl. Phys.

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The electrical properties of illuminated polycrystalline-silicon thin-film transistors (poly-Si TFTs) were investigated by measurement and device simulation. Several features were revealed in n-channel poly-Si TFTs: the flat-band voltage (Vfb) shifts to a positive direction on the order of 0.1 V. The trap density increases around the midgap. In the on-state, the grain boundary barrier height slightly decreases owing to the increase in donor-type and the decrease in acceptor-type trap densities. In the off-state, the reverse current of pn-junction at the drain edge becomes much larger than the generation current or gate-induced drain leakage current, showing almost linear dependence on light intensity. A hump appears in off-current below Vfb, which is derived from the transition of carrier transport from the reverse diffusion at pn-junction in the off-state to the drift-diffusion in the on-state. Considering all these features, a surface-potential-based drain current model was proposed. Calculations using the model were compared with device simulation and measurement by varying the light intensity or drain voltage. The good agreements between them confirm the validity of the model.

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Section: Energy ( Ev )mentioning

confidence: 99%

“…is applied at the back surface, where t Si refers to the poly-Si film thickness. 16,17) By integrating eq. ( 25) from b to s , we acquire surface charge Q s .…”

Section: Poisson Equationsmentioning

confidence: 99%

Analysis of Photon-Induced Drain Current in Polycrystalline-Silicon Thin-Film Transistors

Ikeda

Sano

2009

Jpn. J. Appl. Phys.

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“…To capture more accurate features of poly-Si TFTs, Shimizu et al developed a compact model based on a new surface-potential-based [ 67 ]. Firstly, in the model the states are approximated by the sum of exponential distributions for the deep and tail states as:

where

and

are the inverse slope of deep states and tail states, respectively,

and

are the density of deep state and tail state at bottom of conduction band

, respectively.…”

Section: Surface-potential-based Compact Modelsmentioning

confidence: 99%

A Review for Compact Model of Thin-Film Transistors (TFTs)

Jiang

et al. 2018

Micromachines

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Thin-film transistors (TFTs) have grown into a huge industry due to their broad applications in display, radio-frequency identification tags (RFID), logical calculation, etc. In order to bridge the gap between the fabrication process and the circuit design, compact model plays an indispensable role in the development and application of TFTs. The purpose of this review is to provide a theoretical description of compact models of TFTs with different active layers, such as polysilicon, amorphous silicon, organic and In-Ga-Zn-O (IGZO) semiconductors. Special attention is paid to the surface-potential-based compact models of silicon-based TFTs. With the understanding of both the charge transport characteristics and the requirement of TFTs in organic and IGZO TFTs, we have proposed the surface-potential-based compact models and the parameter extraction techniques. The proposed models can provide accurate circuit-level performance prediction and RFID circuit design, and pass the Gummel symmetry test (GST). Finally; the outlook on the compact models of TFTs is briefly discussed.

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“…Two independent trap-density distributions are considered as schematically shown in Figure 3.4. One represents the shallow trap density distribution and the other represents the deep trap density distribution [44]. Circuit simulators work only with node potentials.…”

Section: Introductionmentioning

confidence: 99%