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Nanoelectronic Memory Devices: Space-Time-Energy Trade-offs

Nanoelectronic Memory Devices: Space-Time-Energy Trade-offs. Ralph Cavin and Victor Zhirnov Semiconductor Research Corporation. Main Points. Many candidates for beyond-CMOS nano -electronics have been proposed for memory, but no clear successor has been identified.

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Nanoelectronic Memory Devices: Space-Time-Energy Trade-offs

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  1. Nanoelectronic Memory Devices:Space-Time-Energy Trade-offs Ralph Cavin and Victor Zhirnov Semiconductor Research Corporation

  2. Main Points • Many candidates for beyond-CMOS nano-electronics have been proposed for memory, but no clear successor has been identified. • Methodology for system-level analysis • How is maximum performance related to device physics?  SRC/NSF A*STAR Forum on 2020 Semiconductor Memory Strategies: Processes, Devices, and Architectures, Singapore, October 20-21, 2009 http://grc.src.org/member/event/e003676/e003676_MeetingResults.asp

  3. Space-Time-Energy Metrics • Essential parameters of the memory element are: • cell size/density, • retention time, access time/speed • operating voltage/energy. • None of known memory technologies, perform well across all of these parameters • At the most basic level, for all memory elements, there is interdependence between operational voltage, the speed of operation and the retention time. • Cell dimensions are also part of the trade-off, hence the Space-Time-Energy compromise

  4. Space-Action Principle for Memory The Least Action principle is a fundamental principle in Physics (h) Plank’s constant h=6.62x10-34 Js

  5. Three essential components of a Memory Device: • 1) ‘Storage node’ • physics of memory operation • 2) ‘Sensor’ which reads the state • e.g. transistor • 3) ‘Selector’ which allows a memory cell in an array to be addressed • transistor • diode • All three components impact scaling limits for all memory devices

  6. Three Major Memory State Variables • Electron Charge (‘moving electrons’) • e.g. DRAM, Flash • Electron Spin (‘moving spins’) • (STT-) MRAM • Massive particle(s) (‘moving atoms’) • e.g. ReRAM, PCM, Nanomechanical, etc. Note: Electrical I/O always wanted

  7. DRAM schematic Problem 1: In Si devices Ebmax<Eg=1.1 eV Barrier+Selector Storage: N carriers Only volatile memory possible with FET barrier

  8. Volatile electron-based memory: DRAM Selector dC Eb,C Sensor Eb,tr SA a 25fF Storage Node (a=10 nm, K=100) Nel~105 Vcap=10-15 cm3 Problem 2a: External sensing requires large Nel Problem 2b: Large Nelrequires large size of storage node (capacitor) Problem 2c: Series resistance of the storage capacitor increases with scaling

  9. Charge-based injection “easy” in DRAM: Barrierless transport… Write K=100 a~10 nm (>25fF) Dominates at a<10 nm tw~0.1-1 ns

  10. DRAM summary Ta=1 s Ta=10y Ew~10-14 J Ew~310-14 J a=15 nm a=30 nm Volcap~5105 nm3 Volcap~106 nm3 VolFET=104 nm3 VolFET=105 nm3 EtV~10-9 J-ns-nm3 EtV~10-8J-ns-nm3 DRAM inherent issues: Selector -Low barrier height-Volatility - Remote sensing – Large size of Storage node Sensor

  11. Flash in the limits of scaling Volstorage=2000nm3 Storage Node Nel~10 Selector ~10 nm Sensor ~6nm Nel~10 ~20nm VolFET~3a3 ~3000nm3

  12. Voltage-Time Dilemma • For an arbitrary electron-charge based memory element, there is interdependence between operational voltage, the speed of operation and the retention time. • Specifically, the nonvolatile electron-based memory, suffers from the “barrier” issue: • High barriers needed for long retention do not allow fast charge injection • It is difficult (impossible?) to match their speed and voltages to logic

  13. Flash Summary E~10-16 J t~1 ms=1000 ns Volstorage=2000nm3 VolFET~3a3 ~3000nm3 EtV~10-9J-ns-nm3 The minimum space-action metric is approximately the same as for the DRAM

  14. Conclusion on ultimate charge-based memories • All charge-based memories suffer from the “barrier” issue: • High barriers needed for long retention do not allow fast charge injection • It is difficult (impossible?) to match their speed and voltages to logic • Voltage-Time Dilemma Non-charge-based NVMs? The Choice of Information Carrier

  15. Spin torque transfer MRAM (Moving spins): Energy Limit (f0~109-1010 c-1) tstore>10 y the anisotropy constant of a material Eb= KV >~1.4 eV volume D. Weller and A. Moser, “Thermal Effect Limits in Ultrahigh-Density Magnetic Recording”, IEEE Trans. Magn. 36 (1999) 4423

  16. FET selector is biggest component of STT-MRAM in the limits of scaling Eb= KV >1.4eV K~0.1-1 J/cm3 (the anisotropy constant of a material) volume V=1500nm3 Nspin~105 11 nm Storage Node Selecting FET VolFET~3a3 ~3000nm3 J-G. Zhu, Proc. IEEE 96 (2008) 1786

  17. STT-RAM summary VolFET~3a3 ~3000nm3 V=1500nm3 (e.g. 11nm22 nm) Ew~Nspin Eb~105  10-19~10-14J (Alternative estimate based on optimistic write current/write time projections: Iw~107 A/cm2 and tw~1 ns Ew~107A/cm2 11nm21V 1 ns~10-14 J EtV~10-11-10-10 J-ns-nm3 This looks a little better than the electron-based we looked at earlier!

  18. Scaled ReRAM(courtesy Dr. In YOO/Samsung)

  19. A B Ultimate ReRAM: 1-atom gap ON/OFF~1.61 V=0.5 V Eb=0.38 eV dt=0.075 nm dt<<a

  20. B A Ultimate ReRAM: 2-atom gap ON/OFF~476 V=0.5 V Eb=2.63 eV dt=0.37 nm dt<a

  21. Energy Ultimate Atomic Relay: 4-atom gap Eb (energy barrier for diffusion) 0.5-1 eV

  22. Energy Ultimate Atomic Relay: 4-atom gap Eb (energy barrier for diffusion) 0.5-1 eV (Eb=0.5 eV, n>5)

  23. Ultimate ReRAM: A summary V=1nm3 Nat~100 (64) E~Nat*1eV~10-17J tw~1 ns (can be shown) EtV~10-17 J-ns-nm3 without FET VolFET~3a3 ~3000nm3 EtV~10-14J-ns-nm3 with FET

  24. Summary Main constraints due to sensor Space-Action, J-ns-nm3 Biggest component Vstor, nm3 tw, ns Ncarriers Ew, J DRAM 105 1 ns Storage Node 105 10-14 ~10-8-10-9 Flash 10 ~10-9 10-16 103 ns 103 Sensor FET Selector STT-RAM 105 103 10-14 1 ns FET ~10-10 ReRAM ~10-14 Selector 1 ns 10-17 1 100 FET Constraints by sensor not considered without FET VolFET~3000nm3 With FET

  25. Summary • Memory cell design is a tradeoff between physical variables needed to achieve long retention times, and short write/read times. • A global metric, space-action, for all memory categories provides insights into most promising extremely-scaled memory devices based on fundamental physics • Scaling Limits of semiconductor component often dominate overall scaling for the memory cell • Our preliminary study suggests a good potential for ReRAM (some constraints are not considered) • Today’s memory technology meets Feynman’s challenge of placing the 24 volumes of Encyclopedia Britannica (~200 MB) on the head of a pin (~.025 cm^2). • Library of Congress (10 Terabytes) on 1 cm^2 by 2020?

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