Science & Engineering gg - Cornell...

Nanoscale,,

Science & Engineering

& Our Place in the World

g g

Sandip Tiwari

[email protected]

Science -> Engineering -> Society

Science Engineering Society

16 1 00’…

16-1700’s

Gottfried Leibnitz Isaac Newton Thomas Savery

James Watt…

17-1800’s

Charles Darwin Dmitri Mandeleev

F it H bFritz Haber

18-1900’s

Albert Einstein Alexander Claude

Keck_Howard – Nov 6, 2007

19-2000’s??

Albert Einstein AlexanderFleming

Claude Shannon

Our Life Expectancy + Information Society

Information Revolution

TechnologyGiant Magnetoresistance – 1990s

Single-electron and Quantum-EffectMemories – 1990s

Q W ll L 1980

ComputingBusiness and scientific computers, personal computers, optical and magnetic storage,

Quantum-Well Lasers – 1980sLarge Scale Computation – 1970s

Hetero-Semiconductor Laser – 1970sLaser – 1960’s

Integrated Circuit – 1950’s

p , p g g ,liquid crystal displaysCommunicationsInformation superhighway, cellular phones, satellite communications, high capacity fib ti blIntegrated Circuit 1950 s

Transistor – 1947Vacuum Tubes – 1910’s

Telephony - 1876Science

fiber optic cablesSecurityAdvances in communications, command and control, sensors, weapon systems, mobile electronics

Correlated Electron States – 1980sScanning Tunneling Microscopy – 1980s

Single-electron effects – 1960sSemiconductor Tunneling – 1950s

BCS Th f S d ti it 1957

mobile electronicsEnergyPhotovoltaics, sensors, light-weight motors, high performance transformersTransportation

BCS Theory of Superconductivity – 1957Electron Microscopy – 1930

Electronic States in Crystals – 1920Wave Nature of the Electron – 1927

Quantum Mechanics – 1920s

pAutomotive electronics, sensors, avionics, air-traffic controlEntertainmentConsumer electronics


Quantum Mechanics 1920sX-Ray Diffraction – 1911Magnetoresistance - 1856

MedicineLasers, medical imaging, sensors

Based on National Academy Report

A Recent Timeline for Computing

?IBM 360

1964Micro/PC/Risc

1981?

Intel 4004

1971Cellphones, iPods, …IBM 360 c o/ C/ sc

IBM 801

Intel 40040.3 cm

0.4

cm

Cellphones, iPods, …Low power

Signal processingLeverage from integration

Software-hardware optimization

2300 Tx

0

Parallelized SupercomputersMulti-processor chips

Network switches

Semiconductors

Altair 8000 using intel 8080

2300 Tx10000 nm

~ENIAC(18000 tubes)

Network switchesReduced power-embedded memory

IntegrationSemiconductors

Reliability

Programming: Virtual machine and

IntegrationSystem Compaction

Integration

An Inflection Point(?) arising from

underlying science


Virtual machine and common software Reduced Complexity

in Programming-Hardware

eg a o

Scales, Energies & Small

Power Densities

102

A300

ConcordeF15

PhantomTurbines

)

cm2 )

10

747707

Phantom

cal

(kW

/kg

High end processors

ssin

g

(W/c

Air-Cooled Silicon

1 LibertyCyclone

or

Mec

han

ic

Low Power Processors nfo

. P

roce

s Limit

Propellers

10-1Wright

M b h

Den

sity

fo Low Power Processors

nsi

ty f

or

In

10-2

Otto

Maybach

PistonsPo

wer

Po

wer

Den


1880 1920 1960 200010-3

Source for mechanical engines: V. Smil (1991)

Scales

Physical LifeLarge

(Integration of many into a system)

Atoms, Molecules, Chemical Reactions,

Life forms,Weather, Environment, …

Fractal FormsAdaptation

…

Chaos??

D i i i N d i i i

Anthropic

Deterministic Non-deterministic

Small


Small

(Nano; small materials, structures and devices)

Simple rules connect the scales

The Sinking of RMS Titanic!A Nanoscale Effect

Continuum

MesoScale

100

esoSca e

10-3

Atomistic

SemiEmpirical

10-6

Sca

le (

s)

Ab I iti

10-9

Tim

e S

Ab-Initio10-12

HMS Titanic


10-10 10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1 1 101 102 103

10-15

Length Scale (m)

Complex Oxides

Fe2O3 (ironstone) and Fe3O4 (magnetite)Found in cells and believed responsible for navigationMinimum units – domains stable – large sensitivity

La2/3Ca1/3MnO3, manganites, have large magnetoresistance

La1-xSrxCuO4, YBa2Cu3O7 or Bi2Sr2SaCu2O8 are high Tc

d

Magnetospirillum magnetotacticum

(Frankel)

superconductors

Some the strongest magnets are not metallic, but ceramic oxide insulators

NiO, CoO, MnO – antiferromagnetic oxides - insulators (naively expected to be conducting)

Va2O3 or Ti2O3 show a metal-insulator transition below characteristic temperature TMI

Even after multiple Nobel prizes in areas related to phase transitions, we can not predict these connections of scale well – how do single entities interact with ensembles.


Delocalized d-electrons of transition metals (e.g. Cu, Ni, Fe, Ru etc.) strongly coupling to oxygen p-orbitals. The enormous diversity of complex oxides arises from a delicate balance between de-localized electrons and effects of Coulomb interaction which localize electrons

Mott Hubbard transitions

Connections of Scale

Traveling particles: 2001 NASA satellite image of dust arriving in California from Asian deserts. SeaWiFS Project, NASA/Goddard Space Flight Center and

Traveling particles from recent (Oct-Nov , 2007) California fires leaving for China.


NASA/Goddard Space Flight Center and ORBIMAGE

2007) California fires leaving for China.

So, What is New in Nano?

We now have the ability to construct by synthesizing from atoms up (bottom-up) and pattern down from larger assemblies (top-down) We have sophisticated tools to characterize the nanoscaledown). We have sophisticated tools to characterize the nanoscale.

We can explore, characterize, and utilize phenomena across a breadth of the disciplines.

Nanoscale has brought together approaches of different disciplines - physical and life sciences, and engineering - at the length scale of the building blocks of the physical and living worldlength scale of the building blocks of the physical and living world.

POWERFUL INTERSECTION OF NATURE, SCIENCE & ENGINEERINGBut, So are the Difficulties with Complexities of Scale

The opportunities of understanding and in turn benefiting humanity by harnessing these capabilities is enormous

The scientific and engineering potential is vast


The scientific and engineering potential is vast.

The interdisciplinary research and applications are exciting.

Electronics

PhysicalBehavioral

Structural

ContinuumHi h Ab t ti (HDL)

100

Chip Floor Planning

PlacementTiming

C

High Abstraction (HDL)

10-3

Compartmentalization

DeviceBoltzmann

CompactASX, Spice, …

Lumped

CongestionRouting

VerificationTemperature

P

10-6

Sca

le (

s) A good way to lower cost and efficient and robust designs when within parameter band

HydrodynamicDrift-DiffusionMonte CarloAtomistic

InterconnectNoise

PowerElectromagnetic10-9

Tim

e S parameter band

What happens when at “allowed” limits?

QuantumMaster Eq.NEG

10-12


10-10 10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1 1 101 102 103

Length Scale (m)

10-15

Power & Energy in Computing


Source: Roger Schmidt, IBM??

Variability

30% in frequency

5x in leakage

Keck_Howard – Nov 6, 2007Borkar (2007)

Process Variability – Energy at Nanoscale


Source: Dennard (2005)

Energy per Operation

10-12

Logic Operation

10-14J)

Memory Read 10000 e-

10-16

Ope

ratio

n (J

1000 e-

100 e-

10

These energy numbers are related to error rates and acceptable speeds

10-18

10 kT ln2nerg

y pe

r O 10 e- acceptable speeds

for cmos static

10-20

kT ln2

E

Limit in dissipative information processingBits deleted

inverter


10-22

1 10 100 Feature Size (nm)

Bits deleted

Stochastic Variance of Nanoscale

10 nm 5 nm 3nm 1 nm

3D B d Th h ld J ti C it3D: Bandgap, Threshold, Junctions, Capacitances, …

n ~28,000 ~3,500 ~750 ~28

σ(n) / n 0.6% 1.7% 3.7% 19%( )

2D: Inversion Charge, Interface Defects, Contacts, …

n 920 230 83 9

σ(n) / n 3.3% 6.6% 11% 33%

1D: Wire Resistance, Wire Defects, Molecular Contacts, …

n 30 15 9 3

Yield of chain: Y = (1 – pf)m where pf is failure property of each element

n 30 15 9 3

σ(n) / n 18% 26% 33% 57%


f f

From DOE Reports

Nearly 13% of electricity is used for computers and peripherals

39% of primary energy input goes towards generating

peripherals

goes towards generating electricity

69% of this electrical energy is69% of this electrical energy is lost in transmission and inefficiencies

72% of this electrical energy is generated by greenhouse emission processes


emission processesWe should care!We are responsible.

Edvard Munch

Energy, Heat & Work

STHG Δ−Δ≡ΔGibbs Free Energy Entropy

Enthalpypy

TH

Reversible isothermal expansion/isothermal heat addition

A B

Carnot Cycle

TC

H

Reversible adiabatic expansion

CD

Reversible adiabatic compression

SA SB

CDReversible isothermal compression

No engine operating between two heat reservoirs can be more efficient than a Carnot engine operating between the same reservoirs

Work Efficiency for Combustion Engine < 30% (typically ~25%)


y g ( yp y )

Work Efficiency for Information Engine too has Constraints

Energy: A Fundamental Constraint at Nanoscale

In any approach based on charge transport and change in electromagnetic fieldsPower /Energy dissipation and heat removal set the

αU

S. Tiwari et al., IEEE Conf. Em. Tech. (2006)

Power /Energy dissipation and heat removal set the fundamental constraints of system operationA

Q energy per operation

activity factor

Individual devicesLarge collection of devices

x-section area of heat removal

density of heat removal

time constant

Individual devicesQ =105 W/cm2

t ~ 5 ps

Large collection of devicesQ = 100 W/cm2

t ~ 5 ns

Error rates are related to energy

Minimum energy: U ~ 1000kT

Error rates are related to energyCMOS Inverter: pf ~ exp (-2VDD/σ(VT))Synthesis: variance ~ exp (-ΔE/kT)

ΔE ~ 0.1 eV => pf ~ 2x10-2


Energy/Power Dissipation Complexity/Adaptation

Energy Scales of Processing

Koyama et al. Nuzzo et al.Self Assembly: Oxide Growth Self Assembly: Molecular

ΔE = 0.1 to 0.5 eV (self-assembly)

Vladiviroma et al.

ΔE = 1.5 to 2.5 eV (oxide growth)

Probabilities proportional to exp (-ΔE/kT)Smaller activation energies lead to larger varianceShort range and long range order

Energy Error Rates


5 o 5 e (o de g o )ΔE > 2 eV for dopants used

Energy Error Rates0.1 eV ~2x10-2

0.5 eV ~5x10-9

1.5 eV ~1x10-26

Electronics at Massive Integration Using Nanoscale

Terascale integration capacityg p y

Billions will be unusable due to variations

General cores

Special cores

f ti l bl k

Many will fail in time

Intermittent failures

Interconnect fabric

functional blocks

TB/s memory bw Intermittent failures

A desired performance at power and cost still needed

low power buses

configurability

fi bilit

hierarchy

TB/s memory bw

Dynamically self-test, detect errors, reconfigure, & adapt

sensors for temp, time

adaptation

reconfigurability


Configurability: Defects and Testing

Defects have non-local effect

Enormous penalty arising from non-linear rate of connectivity with defects; affects congestion, power, area, ….


Digital Circuits: Configurability

A. Kumar et al., DFT, 280(2004)

Defects limit testability and limit the 80

100

ule

s te

ste

ddINT=10-2

N=1x106

p=0.5

yusable devices and interconnects

High yields, similar to current electronics are required

20

40

60

nta

ge

of m

odu dINT 10

dINT=10-3

dINT=10-4

dINT=10-5

electronics, are required

0 500 1000 1500 20000

Per

cen

Number of iterations

dINT=0

ion

60

8

12dINT = 0.001

ower

dis

sipa

ti

p=0.5 p=0.6 p=0.7

40

60

dINT = 0.001

e in

are

a

p=0.5 p=0.6 p=0.7

4

8

ncre

ase

in p

o

20

acto

r in

crea

se


104 105 106

0

Fac

tor

in

Number of modules104 105 106

0

Fa

Number of modules

Simulated Performance of Defect Tolerant Architectures

R-fold modular redundancyNAND multiplexingReconfiguration (using knowledge of faulty

uir

ed

knowledge of faulty devices)

ncy

Req

F 90%

Red

un

da For 90%

chipyield

R

Keck_Howard – Nov 6, 2007 Nikolic, Sadek and Forshaw

Allowable probability of failure1012 devices assumed

Adaptation

5.8 nm

Front Gate

Front OxideGateSiO2 SiO2GateSiO2 SiO2GateSiO2 SiO2

Self-aligned Back-Gate:

A structure where the

5.3 nm

7 0 nm

5.8 nmFront Oxide

Silicon

Back Oxide

Source DrainSi Channel

Back Gate

SiO2


Back Gate


Back Gate

SiO2

threshold voltage can be changed so that the device, circuit &

system can be 7.0 nm

Back Gate

Back Oxide

V 0 3 i

VBG

= 0 to -3 in

yadapted to needs.

1E-8

1E-6

Increasing VBG

VBG

= 0 to -3 in

steps of -0.5 V

nt, I

DS (

A)

1E-8

1E-6

Increasing VBG

ent,

I DS (

A)

BG

steps of -0.5 V

1E-12

1E-10

VDS

= 1.0 V

Dra

in C

urre

n

1E-12

1E-10

VDS

= 0.1V

Dra

in C

urre


-1.5 -1.0 -0.5 0.0 0.5 1.0

Front Gate Voltage, VFG

(V)

-1.5 -1.0 -0.5 0.0 0.5 1.0

Front Gate Voltage, VFG

(V)

Sub-Threshold Swing

L~ 1 μm


W. Chan et al., (2007)

Adaptive Imagers

computational sensors

tunableoptics

low latencyVladimir BrajovicIntrigue Technologies

processingsensing

“soft”computation

on-chipprocessing

computational sensors

sensoryadaptation

imageformationadaptation

algorithmicadaptation

LIi

Ij

Adaptive Pixel-to-Pixel “Switch”

top down adaptationLi

Li < Lj

Li Ii

top-down adaptation Lj

Li > Lj Lj

1Ω

1Ω


jΩ Ω

Vladimir Brajovic


Vladimir BrajovicIntrigue Technologies Local gain, offset adaptive compensation

Geometric Leverage: Operational Amplifier

VDD

CC

CLVIN- VIN+

VOUT

VSS

Supply 1.5V 0.6V

Threshold voltage change through buried bias

Supp y 5 0 6

Gain (dB) 108.9 99.8

Gain Bandwidth (MHz) 32.1 29.5

Open-Loop Gain Voltage


Open-Loop Gain Voltage Gain (V/V)

4.3x104 3.9x104

Phase Margin (degrees) 84 89.8 A. Kumar et al. (2006)

Environment of the Challenge

System-level OptimizationHierarchy

P i f T h l

Power In: ~100 W/cm2

Energy Error Rates, S/NProperties of Technology

AdaptationEnergy Partitioning

Network/Communication

Energy Error Rates, S/N

10 nm F 4x1013 F2 in 2.5 inch& more in multilayer 3D

Network/CommunicationDesign Tools

Hardware-Software

(reproducibility, resilience, robustness, routing, reconfiguration, …)


So, the Biggest Problems

Today’s challenge: Power and DesignAdapt

H d S ft d iHardware-Software co-design

Future challenge: Reliable Systems from Unreliable ComponentsVariations and reliability

Resiliency

CostNew technologies that are efficient at hardware-software co-designg g

Non-compartmentalized education and practice


Major Problems of Society

Efficient low cost sustainable photovoltaicsNumerous “nano” ideas – Gretzel cell, new organics, inexpensive silicon approaches multi bandgapssilicon approaches, multi-bandgaps, …

Efficient low energy sustainable technologiesNumerous “nano” ideas – Efficient catalysis, self-assembly techniques in fabrication, novel material synthesis, low power electronics, low power displays, …

HealthcareNumerous “nano” ideas – health diagnostics and repair, local treatments neural probes new characterization methods smallertreatments, neural probes, new characterization methods, smaller portable instruments, …


Hydrogen Use: Fuel Cells

H2 Electricity

Elimination of combustion and heat from energy conversion

Hydrogen provides up to 60% efficiency

Storage for 300 mile driving(capacity higher than liq. H2!

-

Pt

metal

better catalystshigher activity

Hydrogen provides up to 60% efficiency

++

+

e

H2

O2

metal

core-shell nanoparticle medium

high surface area+

+

++ +

H2O

O

shell : dissociation H2 ⇔ 2 H

H2 gas

OOSO3

-H+

SO3-

H+

OOSO3

-

H+SO3

-

H+ core: high density storage

nanoscale ⇒ fast transit time

~ 10 nm


better membraneshigher temperature

higher ion conductivity

designed nanoscale materials

World Map (Normalized to Population)


R. Webb, Nature 439, 800(2006)

A Narrow View

The Russians play Chess, plotting their moves with a strategy that looks decades into the future.strategy that looks decades into the future.

The Japanese play Go, systematically surrounding each technological territory with their pieces until they make ittechnological territory with their pieces until they make it their own.

The Europeans play Bridge, kicking a lot under the table while presenting a smooth performance above its surface.

USA: We play Monopoly.

The world does not know how China and India play


The world does not know how China and India play.

From Prof. Les Eastman’s Bulletin Board

From the 1980’s

This is more true now than everPursuit of science, engineering and technology

is more central to our world’s well being now gmore than ever.

We all need to do our part and contribute to collective


pprogress

NanoExpress

Mobile Nanotechnology Demonstration Laboratory

Developed at Howard UniversityDeveloped at Howard University

>4000 Visitors in ~ 6 months

S h l S t J dSchools, Scouts, Judges, Community …

Hands-On Equipment:a Photolithographya. Photolithographyb. AFMc. SEM/TEMd. Probe Statione FTIRe. FTIRf. Optical Microscope


Conclusions

We all need to work together

We need to think deeper

Small has large effects; there are connections of scaleWe are all individually an important contributor and cause of successes and failure of our society

Education

Research and Technological Innovation working together


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