Performance estimates for the various types of emerging memory devices Victor Zhirnov (SRC) and Ramachandran Muralidhar (Freescale)

Slides:



Advertisements
Similar presentations
Numbers Treasure Hunt Following each question, click on the answer. If correct, the next page will load with a graphic first – these can be used to check.
Advertisements

1 A B C
AP STUDY SESSION 2.
1
1 Vorlesung Informatik 2 Algorithmen und Datenstrukturen (Parallel Algorithms) Robin Pomplun.
Copyright © 2003 Pearson Education, Inc. Slide 1 Computer Systems Organization & Architecture Chapters 8-12 John D. Carpinelli.
Processes and Operating Systems
Copyright © 2011, Elsevier Inc. All rights reserved. Chapter 6 Author: Julia Richards and R. Scott Hawley.
Author: Julia Richards and R. Scott Hawley
1 Copyright © 2013 Elsevier Inc. All rights reserved. Chapter 3 CPUs.
STATISTICS HYPOTHESES TEST (I)
STATISTICS POINT ESTIMATION Professor Ke-Sheng Cheng Department of Bioenvironmental Systems Engineering National Taiwan University.
Properties Use, share, or modify this drill on mathematic properties. There is too much material for a single class, so you’ll have to select for your.
Work in Progress --- Not for Publication 1 ERD WG 4/2/08 Koenigswinter FxF Meeting ERD ITWG Emerging Research Devices Working Group Face-to-Face Meeting.
30 nm © 2005 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice Atomic Switch ITRS Emerging.
Objectives: Generate and describe sequences. Vocabulary:
Balanced Device Characterization. Page 2 Outline Characteristics of Differential Topologies Measurement Alternatives Unbalanced and Balanced Performance.
UNITED NATIONS Shipment Details Report – January 2006.
RXQ Customer Enrollment Using a Registration Agent (RA) Process Flow Diagram (Move-In) Customer Supplier Customer authorizes Enrollment ( )
David Burdett May 11, 2004 Package Binding for WS CDL.
Chapter 6: Field-Effect Transistors
1 RA I Sub-Regional Training Seminar on CLIMAT&CLIMAT TEMP Reporting Casablanca, Morocco, 20 – 22 December 2005 Status of observing programmes in RA I.
Conversion Problems 3.3.
Properties of Real Numbers CommutativeAssociativeDistributive Identity + × Inverse + ×
1 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt BlendsDigraphsShort.
PUBLIC KEY CRYPTOSYSTEMS Symmetric Cryptosystems 6/05/2014 | pag. 2.
1 Click here to End Presentation Software: Installation and Updates Internet Download CD release NACIS Updates.
REVIEW: Arthropod ID. 1. Name the subphylum. 2. Name the subphylum. 3. Name the order.
Break Time Remaining 10:00.
Turing Machines.
Table 12.1: Cash Flows to a Cash and Carry Trading Strategy.
Advance Nano Device Lab. Fundamentals of Modern VLSI Devices 2 nd Edition Yuan Taur and Tak H.Ning 0 Ch9. Memory Devices.
PP Test Review Sections 6-1 to 6-6
Bright Futures Guidelines Priorities and Screening Tables
Floating Gate Devices Kyle Craig.
Chapter 4 Gates and Circuits.
Chapter 3 Logic Gates.
Circuit Modeling of Non-volatile Memory Devices
1 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt Vocabulary.
Bellwork Do the following problem on a ½ sheet of paper and turn in.
IP Multicast Information management 2 Groep T Leuven – Information department 2/14 Agenda •Why IP Multicast ? •Multicast fundamentals •Intradomain.
Exarte Bezoek aan de Mediacampus Bachelor in de grafische en digitale media April 2014.
Copyright © 2012, Elsevier Inc. All rights Reserved. 1 Chapter 7 Modeling Structure with Blocks.
1 RA III - Regional Training Seminar on CLIMAT&CLIMAT TEMP Reporting Buenos Aires, Argentina, 25 – 27 October 2006 Status of observing programmes in RA.
Factor P 16 8(8-5ab) 4(d² + 4) 3rs(2r – s) 15cd(1 + 2cd) 8(4a² + 3b²)
Basel-ICU-Journal Challenge18/20/ Basel-ICU-Journal Challenge8/20/2014.
1..
CONTROL VISION Set-up. Step 1 Step 2 Step 3 Step 5 Step 4.
Adding Up In Chunks.
1 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt 10 pt 15 pt 20 pt 25 pt 5 pt Synthetic.
Model and Relationships 6 M 1 M M M M M M M M M M M M M M M M
: 3 00.
5 minutes.
1 hi at no doifpi me be go we of at be do go hi if me no of pi we Inorder Traversal Inorder traversal. n Visit the left subtree. n Visit the node. n Visit.
Analyzing Genes and Genomes
Speak Up for Safety Dr. Susan Strauss Harassment & Bullying Consultant November 9, 2012.
1 Titre de la diapositive SDMO Industries – Training Département MICS KERYS 09- MICS KERYS – WEBSITE.
©Brooks/Cole, 2001 Chapter 12 Derived Types-- Enumerated, Structure and Union.
Essential Cell Biology
Converting a Fraction to %
Clock will move after 1 minute
Intracellular Compartments and Transport
PSSA Preparation.
Essential Cell Biology
Immunobiology: The Immune System in Health & Disease Sixth Edition
Energy Generation in Mitochondria and Chlorplasts
Select a time to count down from the clock above
Chapter 5 The Mathematics of Diversification
1 Nanoelectronic Memory Devices: Space-Time-Energy Trade-offs Ralph Cavin and Victor Zhirnov Semiconductor Research Corporation.
Presentation transcript:

Performance estimates for the various types of emerging memory devices Victor Zhirnov (SRC) and Ramachandran Muralidhar (Freescale)

2 Rationale u We seek to identify fundamental physical limits for various types of memory devices v Best projections for scaling n e.g. no consolidated theory has been developed for Flash scaling Flash Memories, P. Cappelletti et al (Eds), Kluwer 2001

3 Attributes of an ideal memory u Nonvolatility with long retention (e.g.. > 10 years) u High density u Low power u In-system rewrittability u Fast read/write u High endurance (the number of erase/write/read cycles) u Integration with CMOS logic: v Matching operational voltage v Matching time (speed) Focus of this talk

4 Three Components of Memory Device u Three equally important components of memory systems: n Memory cell (Physics of of Write/Erase/Program) n Sensing (Physics of Read/Sense) n Wires (implication of the physics of Write and Read to accessibility) n The key of a cells usefulness is whether the cell can be written to and read from without affecting the surrounding cells. Focus of this analysis

5 ERD ITWG Memory Discussion 10:45 Quantitative estimates of performance for the various types of memories Engineered barrier Muralidhar and Zhirnov Ferroelectric Waser NanoelectromechanicalZhirnov Fuse/AntifuseWaser and Akinaga 12:00-12:30 Lunch IonicWaser and Akinaga Electronic EffectsWaser and Zhirnov MacromolecularZhirnov Molecular Waser 1:30 Break - Adjourn Memory Discussion

6 Charge-based Memories AB e- Control Requirements: 1) Efficient charge injection during programming 2) Suppressed back-flow of charge in store/read modes 3) Efficient erase 4) Min. charge/bit: q=e=1.6x Q DRAM/SRAM Floating Gate Memory SONOS

7 Barrier-less Ohmic Transport: The most efficient injection, but… Write Store … difficult retention EbEb What is the minimum barrier height for the charge- based NVM? Example: DRAM Charge-based memory is a two-barrier system

8 What is the minimum barrier height for the charge-based NVM? Store Problem: In Si devices E bmax <E g =1.1 eV EbEb Thermionic leakage current (ideal case): E bmin Min. barrier height for NVM High-barrier are needed for Non-volatile memory

9 Charge injection problem in high- barrier systems BUT: Barrier formed by an insulating material (large E b ) cannot be suppressed) – charge transport in the presence of barriers: Non-ohmic charge transport High-barriers are needed for Non-volatile memory Tunneling Hot-electron injection Newly proposed nanomechanical DRAM addresses this problem

10 Two-barrier charge-based NVM C. Y. Chang, S. M. Sze (Eds.), ULSI Devices (John Wiley & sons 2000) Floating gate memory M. H. White,Y. Yang, A. Purwar, and M. L. French, IEEE Trans. Compon. Packag. and Manufact. Technol. Pt A 20 (1997) 190 SONOS memory

11 Floating gate memory: WRITE and STORE modes V Control gate Floating gate FET channel 0 V leakage WRITE STORE

12 V Floating gate cell: Write – triangle barrier Retention – trapezoidal barrier We need to create an asymmetry in charge transport through the gate dielectric to maximize the I write /I ret ratio The asymmetry in charge transport between WRITE and STORE modes is achieved through different shape of barrier (triangle vs. trapezoidal)

13 Floating Gate Cell Retention and WRITE characteristics Ideal case Retention: direct tunneling k B T/e < V stored <E b a The retention time strongly depends on thickness V F-N VWVW EbEb Write: F-N tunneling: V F-N >E b Si/SiO 2 : E b =3.1 V, V WSiO2 >6.2 V For lower WRITE voltage E b should be decreased: E bmin =1.5 eV V min >3 V

14 The Industry Standard Flash Memory Cell Flash Memories, P. Cappelletti et al (Eds), Kluwer 2001

15 Parameters Projections for n-FG This Analisis SiO 2, E b =3.1eV v V min >6.8 V (slow operation) v V~12 V (ms operation) a min >5.4 nm (reliability issue) v L min >15 nm (gate stack AR, FET issues…) u Optimized FG memory cell v E b =1.5 eVHfO 2 v V min >3 V (slow operation) v V~4 V (ms operation) a min ~6.3 nm v L min ~12 nm Standard FLASH SiO 2 E b =3.1eV v - v V v ~6 nm v ~18 nm Flash Memories, P. Cappelletti et al (Eds), Kluwer 2001 Nanocrystals, Charge trapping High-K !

16 Parameters Projections for n-FG SiO 2 HfO 2 ~2x F~6x F x J7.2x J Lower bound (slow operation) 3x J V~12 V (ms operation) Statistical issue

17 Materials Challenges of symmetrically graded barrier : vs. K = Kramers-Kronig relation K 1 <K 2

18 Symmetrically graded (crested) barrier V=0 E b =2 V V=1 V E b =1.5 V E b =1 V V=2 V V=2*E b =4 V E b =0 Likharev, K.K., Single-electron devices and their applications, Proc. IEEE 87 (1999) Uses a stack of insulating materials to create a special shape of barrier enabling effective transport into/from the storage node V w ~8 V

19 Engineered tunnel barrier memory Likharev

20 Charge injection problem in high- barrier systems Hot-electron injection More accurate estimates based on Shockleys lucky electron model TBD

21 Summary on Floating Gate Memory u Operation voltage cannot be small (e.g. V>6 V for Si/SiO2) u V-t dilemma Question: How to reduce the write voltage for the tunneling based memories? Answer: v To perform write operation in direct tunneling mode n In principle, the voltage can be as small as wished n There are two problems though: 1) Very slow writing 2) Very small retention

22 SONOS M. H. White,Y. Yang, A. Purwar, and M. L. French, IEEE Trans. Compon. Packag. and Manufact. Technol.Pt A 20 (1997) 190 For lower voltage operation of floating charge memory, direct tunneling needs to be used for charge injection. Tunnel insulator must be very thin for reasonably small WRITE time We now have a problem of of how to create the asymmetry between WRITE and STORE charge transport paths

23 SONOS : Write and Retention Write: Direct tunneling: V tun <3.1 V, a write =d 1 a ret d1d1 d2d2 d3d3 a ret >a write The asymmetry between WRITE and STORE charge transport paths is achieved by different path length X. Wang, et al, IEEE Trans. El. Dev. 51 (2004) 597 Retention: BUT: We now have a problem of of how to create the symmetry between WRITE and ERASE operations Retention?? ? Erase???

24 Solutions to improve characteristics of charge-trapping memory? u Alternative dielectrics, e.g. with lower barrier height, high K u Is it possible to control/engineer the trap sites in silicon nitride: concentration, distribution, position, energy levels? X. Wang, et al, IEEE Trans. El. Dev. 51 (2004) 597 HfO 2 Ta 2 O 5 ERM

25 Conclusion on ultimate charge- based memories u All charge-based memories suffer from the barrier issue: v High barriers needed for long retention do not allow fast charge injection v It is difficult (impossible?) to match their speed and voltages to logic n Voltage-Time Dilemma Non-charge-based NVMs?

Electronic Effects

27 Electronic Effects Memory u 1) Charge injection and trapping v Simmons and Verderber, New conduction and reversible memory phenomena in thin insulating films u 2) Mott transition u 3) Ferroelectric polarization effects.

28 Simmons-Verderber theory u Unipolar/non-polar switching v Charging trapes in insulator u Forming process is critical v Strongly suggestive of positive ion injection into insulator 2 ns 100 ns WriteErase I

29 Energy Diagram, V=0

30 Energy Diagram, V>0 V< 0 (energy of localized levels) V> 0 (energy of localized levels)

31 Memory effect: Charge injection

32 Memory effect: Charge travel

33 Memory effect: Charge storing

34 Memory effect: Charge erase

35 Switching (Erase) time estimate Quantum harmonic Oscillator N~10 19 cm -3 s~2 nm E trap ~1 eV

36 Switrching time

37 Thickness scaling N~10 19 cm -3 ~9 nm L min ~20nm L

38 Scaling limits depend on materials properties N~10 19 cm -3 s~2 nm E trap ~1 eV ~9 nm L min ~20nm t min ~60ns

39 Macromolecular Memory u Polymer memory u Organic memory u Different mechanisms proposed v Filaments v Ionic v Charged traps in polymer etc u Verbakel et al. Reproducible resistive switching in nonvolatile organic memories, APL 91 (2007) v Resistive switching in organic memories can be due to the presence of a native oxide layer at an aluminum electrode