Optimization of process parameter variations on leakage current in in silicon-oninsulator vertical double gate mosfet device

Authors

  • K.E. Kaharudin Centre for Telecommunication Research and Innovation, Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
  • F. Salehuddin Centre for Telecommunication Research and Innovation, Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
  • A.S.M. Zain Centre for Telecommunication Research and Innovation, Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
  • M.N.I. Abd Aziz Centre for Telecommunication Research and Innovation, Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia

DOI:

https://doi.org/10.15282/jmes.9.2015.9.0157

Keywords:

Analysis of variance; DG-MOSFET; SNR; SOI

Abstract

This paper presents a study of optimizing input process parameters on leakage current (IOFF) in silicon-on-insulator (SOI) Vertical Double-Gate [1] Metal Oxide Field-EffectTransistor (MOSFET) by using L36 Taguchi method. The performance of SOI Vertical DG-MOSFET device is evaluated in terms of its lowest leakage current (IOFF) value. An orthogonal array [2], main effects, signal-to-noise ratio (SNR) and analysis of variance (ANOVA) are utilized in order to analyze the effect of input process parameter variation on leakage current (IOFF). Based on the results, the minimum leakage current ((IOFF) of SOI Vertical DG-MOSFET is observed to be 0.009 nA/µm or 9 ρA/µm while keeping the drive current (ION) value at 434 µA/µm. Both the drive current (ION) and leakage current (IOFF) values yield a higher ION/IOFF ratio (48.22 x 106 ) for low power consumption application. Meanwhile, polysilicon doping tilt angle and polysilicon doping energy are recognized as the most dominant factors with each of the contributing factor effects percentage of 59% and 25%.

References

Kassim DH, Putra A, Nor MJM, Muhammad NS. Effect of pyramidal dome geometry on the acoustical characteristics in a mosque. Journal of Mechanical Engineering and Sciences. 2014;7:1127-33.

Joardder MUH, Karim A, Kumar C. Effect of temperature distribution on predicting quality of microwave dehydrated food. Journal of Mechanical Engineering and Sciences. 2013;5:562-8.

Yadav VK, Rana AK. Impact of channel doping on DG-MOSFET parameters in nano regime-TCAD simulation. International Journal of Computer Applications. 2012;37:36-41.

K. Roy SM, H. M. Meimand. leakage current mechanisms and leakage reduction techniques in deep-submicrometer CMOS circuits. Proceedings of the IEEE. 2003;91:305-27.

Mead C. Scaling of MOS technology to submicrometer feature sizes. Analog Integrated Circuits Signal Process. 1994;6:9–25.

Sivananth V, Vijayarangan S. Fatigue life analysis and optimization of a passenger car steering knuckle under operating conditions. International Journal of Automotive and Mechanical Engineering. 2015;11:2417-29.

Shukri MR, Rahman MM, Ramasamy D, Kadirgama K. Artificial neural network optimization modeling on engine performance of diesel engine using biodiesel fuel. International Journal of Automotive and Mechanical Engineering. 2015;11:2332-47.

Meenu, Kumar S. Optimization of the material removal rate in turning of UD- GFRP using the particle swarm optimization technique. International Journal of Automotive and Mechanical Engineering. 2013;8:1226-41.

Chaki S, Ghosal S. A GA–ANN hybrid model for prediction and optimization of CO2 laser-mig hybrid welding process. International Journal of Automotive and Mechanical Engineering. 2015;11:2458-70.

Esme U. Application of Taguchi method for the optimization of resistance spot welding process. The Arabian Journal for Sciences and Engineering. 2009;30.

Salehuddin F, Ahmad I, Hamid FA, Zaharim A, Elgomati HA, Majlis BY, Apte PR. Optimization of HALO structure effects in 45nm p-type MOSFETs device using Taguchi method. World Academy of Science, Engineering and Technology. 2011;51:1136-42.

Naidu NVR. Mathematical model for quality cost optimization. Proc International Conference on Flexible Automation and Intelligent Manufacturing. 2008. p. 811-5.

Supeni EE, Epaarachchi JA, Islam MM, Lau KT. Development of artificial neural network model in predicting performance of the smart wind turbine blade. Journal of Mechanical Engineering and Sciences. 2014;6:734-45.

Abdullah H, Jurait J, Lennie A, Nopiah ZM, Ahmad I. Simulation of fabrication process VDMOSFET transistor using silvaco software. European Journal of Scientific Research. 2009;29:461-70.

Yang K, Teo EC, Fuss FK. Application of Taguchi method in optimization of cervical ring cage. International journal of Biomechanics. 2007;40:3251-6.

Tangjitsitcharoen S, Nunya N. Reduction of oil contamination on hard disk drive parts using automatic hydrocarbon washing machine. Journal of Mechanical Engineering and Sciences. 2011;1:113-23.

Kaharudin KE, Hamidon AH, Salehuddin F. Impact of height of silicon pillar on vertical DG-MOSFET device. International Journal of Computer, Information, Systems and Control Engineering. 2014;8:576-80.

Elgomati HA, Ahmad I, Salehuddin F, Hamid FA, Zaharim A, Majlis BY, Apte PR. Optimal solution in producing 32nm cmos technology transistor with desired leakage current. International Journal Semiconductor Physics Quantum Electron Optoelectron. 2011;14:145-51.

Najiha MS, Rahman MM, Yusoff AR. Modeling of the end milling process for aluminum alloy AA6061T6 using HSS tool. International Journal of Automotive and Mechanical Engineering. 2013;8:1140-50.

Haniff MHM, Ismail AR, Deros BM, Rahman MNA, Kardigama K. The Taguchi approach in optimizing the environmental factors towards productivity at automotive industry. International Journal of Automotive and Mechanical Engineering. 2011;3:306-17.

Belavendram N. Application of genetic algorithms for robust parameter optimization. International Journal of Automotive and Mechanical Engineering. 2010;2:211-20.

Phadke MS. Quality engineering using robust design: Pearson Education, Inc. and Dorling Kindersley Publishing, Inc; 2001.

Beale S, Spalding D. Numerical study of fluid flow and heat transfer in tube banks with stream-wise periodic boundary conditions. Transactions of the CSME. 1998;22:397-416.

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Published

2015-12-31

How to Cite

[1]
K. . Kaharudin, F. . Salehuddin, A. Zain, and M. . Abd Aziz, “Optimization of process parameter variations on leakage current in in silicon-oninsulator vertical double gate mosfet device”, J. Mech. Eng. Sci., vol. 9, pp. 1614–1627, Dec. 2015.

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