Index of /intel-research/silicon

(1)

Nano-materials &

Silicon Nanotechnology

C. Michael Garner

Intel Corporation

C. Michael Garner

(2)

Agenda

•

Technology Scaling and Moore's Law

•

Technology Challenges

•

Nanotechnology Building Blocks

•

Nano

-

material Opportunities

•

Beyond the roadmap

…

.

•

(3)

Key Messages

•

Silicon Nanotechnology is production reality

and follows Moore’s law

•

Experimental data on 22nm

-

node/10nm

-

-minimum

minimum

-

feature

-

size

•

We believe that silicon nanotechnology is

extendable to 2015

•

Open minded about post

-

2015 options

•

Nano-

Nano

-

materials will play an important role in

the silicon nanotechnology platform

(4)

Technology Scaling

100 100 10 10 0.01 0.01

1970 1980 1990 2000 2010 2020

Nominal feature size

(5)

Intel’s Transistor Research in

Deep Nanotechnology Space

Experimental transistors for future process generations

30nm 30nm

20nm 20nm

15nm 15nm

10nm 10nm 65nm process

65nm process 2005 production

2005 production 45nm process45nm process 2007 production

2007 production 32nm process32nm process 2009 production

2009 production _{22nm process}_{22nm process} 2011 production 2011 production

Transistors will be improved

for production

Transistors will be improved

for production

(6)

Moore's Law Continues

1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000

1970 1980 1990 2000 2010

4004 ₈₀₈₀

8086

8008

Pentium® Processor

486™ DX Processor 386™ Processor

286

Pentium® II Processor Pentium® III Processor

Itanium® Processor

Heading toward 1 billion transistors in 2007

(7)

Flash

(ETOX

®

)

Technology Scaling

1986 / 1.5µm 1988 / 1.0µm 1991 / 0.8µm 1993 / 0.6µm

1996 / 0.4µm 1998 / 0.25µm _{2000 / 0.18}µ_m _{2002 / 0.13}_µ_m

5.4X

1986 / 1.5µm 1988 / 1.0µm 1991 / 0.8µm 1993 / 0.6µm

1996 / 0.4µm 1998 / 0.25µm _{2000 / 0.18}µ_m _{2002 / 0.13}_µ_m 1986 / 1.5µm

1986 / 1.5µm 1988 / 1.01988 / 1.0µµmm 1991 / 0.81991 / 0.8µµmm 1993 / 0.61993 / 0.6µµmm

1996 / 0.4µm

1996 / 0.4µm 1998 / 0.251998 / 0.25µµmm _{2000 / 0.18}_{2000 / 0.18}µµ_m_m _{2002 / 0.13}_µ_m

5.4X

234 X

Volume Production Year / Technology Generation

18 years and 8 Generations of ETOX® to 0.13

µ

m

18 years and 8 Generations of ETOX

(8)

Silicon Scaling Leads to Material

Challenges

•

Lithography

•

Transistors

•

Interconnects

•

(9)

PPT Shrink Source: Intel

Material Challenges

50nm

Print Features

Print Features Line Edge Roughness(LER)Line Edge Roughness(LER)

10nm 10nm

Resist Nano-domains

Low K Interlevel Dielectric Micelle Assembled….

Barrier Layer ~20nm

What Device Next? What Materials? How to Assemble? What Device Next? What Device Next? What Materials? What Materials? How to Assemble? How to Assemble?

Materials Challenges Everywhere

(10)

Nanotech

Building Blocks

Sub 100nm particles

c.

Molecular Assembly (directed and self assembly)

c.

Molecular Assembly (directed and self assembly)

Macromolecules

10nm 10nm

Sub 100nm structures

(11)

Lithography Challenges

1000 1000

100 100

10 10

’89

’89 ’91’91 ’93’93 ’95’95 ’97’97 ’99’99 ’01’01 ’03’03 ’05’05 ’07’07 ’09’09 ’11’11 Initial Production

Initial Production

Feature size

13nm (EUVL)

Lithography

Wavelength

193nm 193nm 248nm

248nm

Gap

nm

New Mask, Design Techniques, and Materials Needed to Support future Lithography Scaling

(12)

Future Lithography Resist Challenges

Line Edge Roughness(LER)

Atomic Force Microscope

Picture of Resist Nano-domains Atomic Force Microscope

Picture of Resist Nano-domains Line Edge Roughness(LER)

•Resist nano-domains limiting feature resolution and defects.

•Requires control at the molecular level

•Resist nano-domains limiting feature resolution and defects.

(13)

New Materials, Devices Extend Si

Scaling

Gate

Silicide Silicide added added

Channel

Strained Strained silicon silicon

Changes

Made

Future

Options

High

-

k

gate

dielectric

Transistor

Source: Source: Intel Intel PolySi Silicon PolySi Silicon Gate dielectric less than 3 atomic layers thick

Source: Intel

(14)

New Materials, Devices Extend Si

Scaling

Metal lines

Al Cu Al Cu

Insulating

dielectric

SiO

SiO22 SiOFSiOF CDO

CDO (low (low--k)k)

Changes

Made

Future

Options

Ultra

Low

(15)

Molecular Self

-

Assembly

Low

-

K Dielectric

Source: J. Brinker, UNM/Sandia National Labs

• Materials of the gel self-organize into a Low K dielectric

(16)

Conductivity Challenge

(17)

Integrated Thermal and Power

Delivery Management

Heat spreader for high heat flux from die

Capacitors for high current, low noise power delivery

Thermal Challenge

Ultra low thermal resistance Thermal Interface Material

Thermal Challenge

Ultra low thermal resistance Thermal Interface Material

Power Challenge Ultra fast,

high charge density capacitors

Power Challenge Ultra fast,

high charge density capacitors

Nano-material Opportunities in Thermal and Power Delivery

(18)

Characterization Techniques

Quantitative Understanding

Physics-based Computer Vision

Scientific

measurements Model Knowledge

•

Interpret images in conjunction with physical modelsInterpret images in conjunction with physical models

Î

ÎFocus on nanoscale sources such as AFMs, STMs, FIBFocus on nanoscale sources such as AFMs, STMs, FIB

•

New metrology is needed……New metrology is needed……

Î

ÎFaster structural analysisFaster structural analysis

Î

(19)

Beyond the roadmap….

•

Many device options….

•

Compatibility with CMOS for evolutionary

introduction

•

Directed or self assembly of arrays???

Î

Defect density or purity required….

•

Self correcting architectures??

•

Nanotechnology needs a richer suite of

functionality…

Collaboration between Industry, Universities,

and Government is essential

Collaboration between Industry, Universities,

and Government is essential

(20)

What are we looking for?

•

Required characteristics:Required characteristics:

Î

ÎScalabilityScalability

Î

ÎPerformancePerformance

Î

ÎEnergy efficiencyEnergy efficiency

Î

ÎGainGain

Î

ÎOperational reliability Operational reliability

Î

ÎRoom temp. operationRoom temp. operation

•

Preferred approach:Preferred approach:

Î

ÎCMOS process CMOS process compatibility

compatibility

Î

ÎCMOS architectural CMOS architectural compatibility

Alternative state variables

•

Spin

–

electron, nuclear,

photon

•

Phase

•

Quantum state

•

Magnetic flux quanta

•

Mechanical deformation

•

Dipole orientation

•

Molecular state

(21)

Some Alternative Logic Devices

Fas

ter

Sm

al

le

r

Cheaper

ITRS, 2000

George Bourianoff

(22)

Future Nanotechnology will compliment

& extend Silicon Technology

*Source: Holmes et al, University *Source: Holmes et al, University College Cork

College Cork

**Source: Blau et al, Trinity **Source: Blau et al, Trinity College Dublin

College Dublin

Silicon

Nanowire*

Nanotube/Nanowire

Transistors

Carbon

Nanotube**

Many options, but no clear winners…

(23)

Summary

•

Many new materials required for scaling

Î

ÎLithographyLithography

Î

ÎTransistorTransistor

Î

ÎInterconnectsInterconnects

Î

ÎNonNon--volatile Memoryvolatile Memory

Î

ÎThermal & Power Delivery Materials Thermal & Power Delivery Materials

•

Silicon is the platform for the future

•

Nanotechnology could deliver critical materials to

support Silicon Nanotechnology

•

For technology beyond 2015 collaboration between

Industry, Universities, and Government is essential

(24)

Back

(25)

Quest for New Materials

Metal Al Æ Cu Æ Æ Æ Æ ?

ILD SiO2 SiOF Æ SiOC Æ Æ ? ?

Gate Ox SiO2 Æ Æ Æ High-k ? ? ?

Gate

Electrode Poly Æ Æ Æ Æ Metal ? ?

Year 1997 1999 2001 2003 2005 2007 2009 2011 P856 P858 PX60 P1262 P1264 P1266 P1268 P1270 Node 0.25µm 0.18 µm 130nm 90nm 65nm 45nm 32nm 22nm

(26)

Transistors Shipped Per Year

Moore’s Law in Action...

'68 '70 '72 '74 '76 '78 '80 '82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02

1016 1014 1012 1010 Units 1018 S o u rce : Da ta ques t/I n te l, 12/02

Average Transistor Price By Year

0.0000001 0.000001 0.00001 0.0001 0.001 0.01 0.1 1 10

'68 '70 '72 '74 '76 '78 '80 '82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02

$ $

Moore’s Law is driven by economics

(27)

Precision Biology

Create a new generation of

Create a new generation of

bio

bio--instruments capable of instruments capable of operating in the

operating in the singlesingle- -molecule

molecule regimeregime Silicon Fluid

reservoirs and channel

20µm

280 nm

100nm

50nm

Transistor for

90nm Process

Source: Intel

Source: Intel

Influenza virus

Source: CDC

(28)

The road to smart dust.…

Configurable Configurable Silicon Radio Silicon Radio

MOTE MOTE

(a small piece of silicon)

Sensing +

Sensing +

Computing Computing + +

Communicating

(29)

Nanotechnology Opportunities

Extending Moore’s Law

•

Synergistic extension of Silicon Technology

Î

ÎSiSi--based CMOS transistors through 2015based CMOS transistors through 2015

Î

ÎRole for new materials based on nanotechnologyRole for new materials based on nanotechnology

Î

ÎOpen minded about options beyond 2015Open minded about options beyond 2015

Expanding Moore’s Law

•

Proactive Computing Vision

Collaboration between Industries, Universities, and

Governments is essential

(30)

What is Nanotechnology?

a.

New structures like carbon nanotubes

b.

Silicon devices made smaller

c.

Arranging atoms and molecules

d.

Letting atoms assemble themselves

e.

Something far in the future

f.

In production today

g.

All of the above

Correct answer: g.

(31)

$ per transistor decreased by > 6 orders in 30

years: This drives investments

0.0000001 0.000001 0.00001 0.0001 0.001 0.01 0.1 1 10

'68 '70 '72 '74 '76 '78 '80 '82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02 $

$

CPU ~3

micro

-$/xtor

DRAM ~30

nano

-$/xtor

(32)

What are the Alternative Devices?

(From ITRS ERD TWIG 2003)

Logic Device Perf. Arch. compat Reliab ility Proc. compa t Op. temp Energ eff Sensitiv ity Scala bility Flux quanta

3 2 3 2 1 1 2 1

1D 2 3 1 2 3 3 3 3

Resonant Tunneling Devices 29

2 2 2 2 2 3 1 2

SETs 1 1 1 2 1 2 1 2

Molecular 1 1 3 2 2 2 3 3

QCA 1 1 2 1 1 2 3 2

Spin 2 2 1 2 1 2 1 3

Quantum 3 2 1 1 1 3 1 3

(33)

Architecture Devices State variables Data represent ations CNT FETs Molecular Spintronics Quantum CNN Crossbar Quantum Boolean Molecular state Spin orientation

Flux quanta Quantum state Electric charge Associative Patterns Analog Digital Scaled CMOS Probabilities Hierarchy Biotech Logic/Memory Sensors NEMS

A Taxonomy for Nano

-

computing