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Random Dopant Fluctuation (RDF)

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Variation-Aware Advanced CMOS Devices and SRAM

Part of the book series: Springer Series in Advanced Microelectronics ((MICROELECTR.,volume 56))

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Abstract

Following Moore’s Law (Moore in Progress in digital integrated electronics. In: IEDM technical digest, pp 11–13, 1975, [1], semiconductor industries have doubled the density of transistors in integrated circuits (ICs) every two years. This has rapidly increased the performance of ICs because the degree of integration has grown exponentially. However, below the 1 μm technology node, a serious technical issue was encountered that frustrated further shrinking of the gate pitch, namely, the short channel effect (SCE) (Yau in Solid-State Electron 17(10):1059–1063, 1974, [2]; Yan in IEEE Trans Electron Devices 39(7):1704–1710, 1992, [3]).

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References

  1. Moore GE (1975) Progress in digital integrated electronics. In: IEDM technical digest, pp 11–13

    Google Scholar 

  2. Yau LD (1974) A simple theory to predict the threshold voltage for short-channel IGFET’s. Solid-State Electron 17(10):1059–1063

    Article  ADS  Google Scholar 

  3. Yan R-H, Ourmazd A, Lee KF (1992) Scaling the Si MOSFET: from bulk to SOI to bulk. IEEE Trans Electron Devices 39(7):1704–1710

    Article  ADS  Google Scholar 

  4. Hanafi HI, Noble WP, Bass RS, Varahramyan K, Lii Y, Dally AJ (1993) A model for anomalous short-channel behavior in submicron MOSFET’s. IEEE Electron Device Lett 14(12):575–577

    Article  ADS  Google Scholar 

  5. Sadana D, Acovic A, Shahidi G, Hanafi H, Warren A, Grutzrnacher D, Cardone F, Sun J, Davari B (1992) Enhanced short-channel effects in NMOSFET’s due to boron redistribution induced by arsenic source and drain implant. In: IEDM technical digest, pp 849–852

    Google Scholar 

  6. Gwoziecki R, Skotnicki T, Bouillon P, Gentil P (1999) Optimization of VTH roll-off in MOSFET’s with advanced channel architecture—retrograde doping and pockets. IEEE Trans Electron Devices 46(7):1551–1561

    Article  ADS  Google Scholar 

  7. Troutman RR (1979) VLSI limitations from drain-induced barrier lowering. IEEE Trans Electron Devices 26(4):461–469

    Article  ADS  Google Scholar 

  8. Fjeldly TA, Shur M (1993) Threshold voltage modeling and the subthreshold regime of operation of short-channel MOSFETs. IEEE Trans Electron Devices 40(1):137–145

    Article  ADS  Google Scholar 

  9. Chamberlain SG, Ramanan S (1986) Drain-induced barrier-lowering analysis in VSLI MOSFET devices using two-dimensional numerical simulations. IEEE Trans Electron Devices 33(11):1745–1753

    Article  ADS  Google Scholar 

  10. Dennard RH, Gaensslen FH, Yu H-N, Rideout VL, Bassous E, LeBlanc AR (1974) Design of ion-implanted MOSFET’s with very small physical dimensions. IEEE J Solid-State Circ 9(5):256–268

    Article  Google Scholar 

  11. Nam H, Lee GS, Lee H, Park IJ, Shin C (2014) Analysis of random variations and variation-robust advanced device structures. J Semicond Technol Sci 14(1):8–22

    Article  Google Scholar 

  12. Zhao W, Cao Y (2006) New generation of predictive technology model for sub-45 nm early design exploration. IEEE Trans. Electron Device 53(11):2816–2823

    Article  ADS  Google Scholar 

  13. Kuhn K, Kenyon C, Kornfeld A, Liu M, Maheshwari A, Shih W-K, Sivakumar S, Taylor G, VanDerVoorn P, Zawadzki K (2008) Managing process variation in Intel’s 45 nm CMOS technology. Intel Technol. J. 12(2):93–109

    Google Scholar 

  14. Plummer JD, Deal MD, Griffin PB (2000) Silicon VLSI technology: fundamentals, practice and modeling. Prentice Hall, New Jersey

    Google Scholar 

  15. Jaeger RC (2002) Introduction to microelectronic fabrication, 2nd edn. Prentice Hall, New Jersey

    Google Scholar 

  16. Brice DK (1975) Recoil contribution to ion implantation energy deposition distribution. J Appl Phys 46(8):3385–3394

    Article  ADS  Google Scholar 

  17. Sze SM (2008) Semiconductor devices: physics and technology, 2nd edn. Wiley, New Jersey

    Google Scholar 

  18. Nichols CS, Van de Walle CG, Pantelides ST (1989) Mechanisms of dopant impurity diffusion in silicon. Phys Rev B 40(8–15):5484–5497

    Article  ADS  Google Scholar 

  19. Nichols CS, Van de Walle CG, Pantelides ST (1989) Mechanisms of equilibrium and nonequilibrium diffusion of dopants in silicon. Phys Rev Lett 62(9–27):1049–1052

    Article  ADS  Google Scholar 

  20. Cowern NEB, van de Walle GFA, Gravesteijn DJ, Vriezema CJ (1991) Experiments on atomic-scale mechanisms of diffusion. Phys Rev Lett 67(2–8):212–215

    Article  ADS  Google Scholar 

  21. Bukhori MF (2011) Simulation of charge-trapping in nano-scale MOSFETs in the presence of random-dopants-induced variability. PhD thesis, University of Glasgow

    Google Scholar 

  22. Reid D, Millar C, Roy G, Roy S, Asenov A (2009) Analysis of threshold voltage distribution due to random dopants: A 100,000-sample 3-D simulation study. IEEE Trans Electron Devices 56(10):2255–2263

    Article  ADS  Google Scholar 

  23. Wong H.-SP, Taur Y (1993) Three-dimensional “atomistic” simulation of discrete random dopant distribution effects in sub-0.1 μm MOSFETs. In: IEDM technical digest, pp 705–708

    Google Scholar 

  24. Frank DJ, Taur Y, Ieong N, Wong H-SP (1999) Monte Carlo modeling of threshold variation due to dopant fluctuations, In: Symposium on VLSI technical digest, pp 169–170

    Google Scholar 

  25. Li Y, Yu S-M, Hwang J-R, Yang F-L (2008) Discrete dopant fluctuations in 20-nm/15-nm-gate planar CMOS. IEEE Trans Electron Devices 55(6):1449–1455

    Article  ADS  Google Scholar 

  26. Asenov A, Slavcheva G, Brown AR, Davies JH, Saini S (2001) Increase in the random dopant induced threshold fluctuations and lowering in sub-100 nm MOSFETs due to quantum effects: a 3-D density-gradient simulation study. IEEE Trans Electron Devices 48(4):722–729

    Article  ADS  Google Scholar 

  27. Asenov A (1998) Random dopant induced threshold voltage lowering and fluctuations in sub-0.1 m MOSFET’s: A 3-D “atomistic” simulation study. IEEE Trans Electron Devices 45(12):2505–2513

    Article  ADS  Google Scholar 

  28. Asenov A, Brown AR, Davies JH, Kaya S, Slavcheva G (2003) Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs. IEEE Trans Electron Devices 50(9):1837–1851

    Article  ADS  Google Scholar 

  29. Brown AR, Asenov A, Watling JR Intrinsic fluctuations in sub 10-nm double-gate MOSFETs introduced by discreteness of charge and matter. IEEE Trans. Nanotechnol 1(4):195–200

    Google Scholar 

  30. Hane M, Fukuma M (1990) Ion implantation model considering crystal structure effects. IEEE Trans Electron Devices 37(9):1959–1963

    Article  ADS  Google Scholar 

  31. Hane M, Ikezawa T, Takeuchi K, Gilmert GH (2001) Monte Carlo impurity diffusion simulation considering charged species for low thermal budget sub-50 nm CMOS process modeling. In: IEDM Technical Digest, pp 38.4.1–38.4.4

    Google Scholar 

  32. Ziegler JF, Biersack JP (1985) The stopping and range of ions in matter. Springer, New York

    Book  Google Scholar 

  33. Sano N, Matsuzawa K, Mukai M, Nakayama N (2000) Role of long-range and short-range coulomb potentials in threshold characteristics under discrete dopants in sub-0.1 μm Si-MOSFETs. In: IEDM technical digest, pp 275–278

    Google Scholar 

  34. Ezaki T, Ikezawa T, Hane M (2002) Investigation of realistic dopant fluctuation induced device characteristics variation for sub-100 nm CMOS by using atomistic 3D process/device simulator. In: Proceedings of IEEE IEDM, pp 311–314

    Google Scholar 

  35. Ezaki T, Ikezawa T, Notsu A, Tanaka K, Hane M (2002) 3D MOSFET simulation considering long-range Coulomb potential effects for analyzing statistical dopant-induced fluctuations associated with atomistic process simulator. In: Proceedings of SISPAD, pp 91–94

    Google Scholar 

  36. Shin C, Sun X, Liu T-JK (2009) Study of random-dopant-fluctuation (RDF) effects for the trigate bulk MOSFET. IEEE Trans Electron Devices 56(7):1538–1542

    Article  ADS  Google Scholar 

  37. Roy G, Brown AR, Adamu-Lema F, Roy S, Asenov A (2006) Simulation study of individual and combined sources of intrinsic parameter fluctuations in conventional nano-MOSFETs. IEEE Trans Electron Devices 53(12):3063–3070

    Article  ADS  Google Scholar 

  38. Heinrich J (2004) A guide to the Pearson type IV distribution. University of Pennsylvania, Philadelphia, PA, Technical Report

    Google Scholar 

  39. Millar C, Reid D, Roy G, Roy S, Asenov A (2008) Accurate statistical description of random dopant-induced threshold voltage variability. IEEE Electron Device Lett 29(8):946–948

    Article  ADS  Google Scholar 

  40. Kovac U, Reid D, Millar C, Roy G, Roy S, Asenov A (2008) Statistical simulation of random dopant induced threshold voltage fluctuations for 35 nm channel length MOSFET. Microelectron Reliab 48(8/9):1572–1575

    Article  Google Scholar 

  41. Toriyama S, Sano N (2003) Probability distribution functions of threshold voltage fluctuations due to random impurities in deca–nano MOSFETs. Phys E 19(1/2):44–47

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Seoul, Seoul, South Korea

    Changhwan Shin

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  1. Changhwan Shin
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Correspondence to Changhwan Shin .

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Shin, C. (2016). Random Dopant Fluctuation (RDF). In: Variation-Aware Advanced CMOS Devices and SRAM. Springer Series in Advanced Microelectronics, vol 56. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7597-7_3

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