Abstract
This project examines and analyzes the process parameter variance towards on-state drive current (ION) and leakage current (IOFF) towards the 16 nm double-gate FinFET (DG-FinFET) device by the implementation of 2k-factorial design, with comparisons made against an L25 Taguchi statistical method. Alterations with two levels for six process parameters consisting of the threshold voltage (VTH) doping dose, VTH doping tilt, polysilicon doping dose, polysilicon doping tilt, Source and Drain (S/D) doping dose and S/D doping tilt will be done to analyze and improve the results of both ION and IOFF. The physical characteristics of the device will be defined on the ATHENA module, with the ATLAS module then used to characterize its electrical properties. Consideration is made with the responses from both modules by the assistance of the L32 2k-factorial design to reduce the device’s variability as well as maximizing the value of ION while minimizing the IOFF value. By achieving both values, the ION/IOFF ratio are able to be maximized in order to reduce the power consumption of the device subsequently. The most dominant factor towards both ION and IOFF values is identified with polysilicon doping tilt, showcasing the largest standardized effects at the end of this experiment. The optimum values achieved with 2k-factorial design with ION and IOFF at 1648.48 μA/μm and 42.096 pA/μm respectively while achieving better ION/IOFF ratio with 39.160 × 106 as its ION have surpassed the value of ION achieved in Taguchi method that was valued at 1559.96 μA/μm. Importantly, the results acquired have met the predictions of the International Technology Roadmap Semiconductor (ITRS) 2013 for the year 2020.
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Acknowledgements
The authors would like to thank the Ministry of Higher Education (MOHE) for sponsoring this work under project (FRGS/1/2017/TK04/FKEKK-CeTRI/F00335) and MiNE, CeTRI, Faculty of Electronics and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) for the moral support throughout the project.
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Roslan, A.F. et al. (2020). Comparisons in L32 2k-Factorial and L25 Taguchi for the 16 nm FinFET Statistical Optimization Applications. In: Jamaludin, Z., Ali Mokhtar, M.N. (eds) Intelligent Manufacturing and Mechatronics. SympoSIMM 2019. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-9539-0_41
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