Systematic Modeling of Electrostatics, Transport, and Statistical Variability Effects of Interface Traps in End-of-the-Roadmap III–V MOSFETs

Abstract

Thanks to their superior transport properties, Indium Gallium Arsenide (InGaAs) Metal-Oxide-Semiconductor Field-Effect-Transistors (MOSFETs) constitute an alternative to conventional Silicon MOSFETs for digital applications at ultrascaled nodes. The successful integration of this technology is challenged mainly by the high defect density in the gate oxide and at the interface with the semiconductor channel, which degrades the electrostatics and could limit the potential benefits over Si. In this work, we i) establish a systematic modeling approach to evaluate the performance degradation due to interface traps in terms of electrostatics and transport of InGaAs Dual-Gate Ultra-Thin Body (DG-UTB) FETs, and ii) investigate the effects of random interface-trap concentration as another roadblock to the scaling of the technology, due to statistical variability of the threshold voltage. Variability is assessed with a Technology CAD (TCAD) simulator calibrated against Multi-Subband Monte Carlo (MSMC) simulations. The modeling approach overcomes the TCAD limitations when dealing with ultra-thin channels (i.e., below 5 nm) without altering crucial geometrical parameters that would compromise the dependability of the variability analysis. Our results indicate that interface-trap fluctuation becomes comparable with the other variability sources dominating the total variability when shrinking the device dimensions, thus contrasting the trend of reduced variability with scaling. This in turn implies that interface and border traps may strongly limit the benefits of InGaAs over Silicon if not effectively reduced by gate process optimization.

Modeling Nanoscale III–V Channel MOSFETs with the Self-Consistent Multi-Valley/Multi-Subband Monte Carlo Approach

“…Furthermore, the computational burden of the MV-MSMC prevents its use for extensive sensitivity/variability studies. Following our previous work in [14,15], we show in Section 3.2 how to calibrate the channel transport models in a commercial drift-diffusion TCAD based on the MV-MSMC simulation results. This step then allows us to exploit the available TCAD models to analyze more complex device architectures, consider tunneling from/to border traps, and perform AC/noise as well as variability analysis.…”

“…Since the QDD, differently from the MSMC, does not consider the electron wave function penetration (WFP) in the gate oxide, an effective TW is employed in order to reproduce the NINV-vs.-VGS curve (see Figure 11a). This approach is different from the one used in [14,15,23], where TW was kept equal to the geometrical value, and the parameters…”

“…Since the QDD, differently from the MSMC, does not consider the electron wave function penetration (WFP) in the gate oxide, an effective T W is employed in order to reproduce the N INV -vs.-V GS curve (see Figure 11a). This approach is different from the one used in [14,15,23], where T W was kept equal to the geometrical value, and the parameters of the MV-MSMC were recalibrated disabling the WFP. Although the value T W = 4.9 nm appears to fit better the N INV -vs.-V GS curve in Figure 11a, a value of 4.7 nm was chosen because it improved the overall agreement between the QDD and MV-MSMC models when considering the complete IV curves, as shown in Figure 12.…”

“…In recent years, models have been proposed to include quantization effects [13] as well as high-field transport in short-channel MOSFETs [14]. These models open the door to accurate device design and optimization spanning a large set of parameters not possible with NEGF simulators, as well as variability studies [15]. However, the various model ingredients require calibration against more accurate (although time consuming) simulation approaches.…”