Hot Spot Management and Micro Refrigeration in...

Ali Shakouri Director, Thermionic Energy Conv. CenterBaskin School of EngineeringUniversity of California Santa Cruz

Hot Spot Management and Micro Refrigeration in Integrated

Circuits

Acknowledgement:National Semiconductor,

Intel, Canon, Agility, SRC-Interconnect Focus Center, Packard, NSF,

DARPA, ONR

IEEE CSS and CMPT Santa Clara Valley; San Jose, CA; 20 April 2009

A. Shakouri 3/24/2009

Motivation: Microprocessor Evolution

Source: IntelSource: Intel

1,000,0001,000,000

100,000100,000

10,00010,000

1,0001,000

100100

1 Billion 1 Billion TransistorsTransistors

808680868028680286

i386i386i486i486

PentiumPentium®®

PentiumPentium®® IIII

’’7575 ’’8080 ’’8585 ’’9090 ’’9595 ’’0000 ’’0505 ’’1010

PentiumPentium®® IIIIIIPentiumPentium®® 44

’’1515Source: IntelSource: Intel

1,000,0001,000,000

100,000100,000

10,00010,000

1,0001,000

100100

1 Billion 1 Billion TransistorsTransistors

808680868028680286

i386i386i486i486

PentiumPentium®®

PentiumPentium®® IIII

’’7575 ’’8080 ’’8585 ’’9090 ’’9595 ’’0000 ’’0505 ’’1010

PentiumPentium®® IIIIIIPentiumPentium®® 44

’’1515

A. Shakouri 3/24/2009Non Uniform Heat Generation in VLSI Chips

Steve Kang et al. Electrothermal analysis of VLSI Systems, Kluwer 2000

Problem:Problem:

∆T=20C

Mean-time-to-failure due to electromigration increase x5

108C90C80C

On chip temperature contour

Impact of temperature on IC performance15oC temperature increase:• Cell and interconnect delay (10-15%)• Crosstalk noise level increase (up to 25%)• Leakage power exponential increase with

temperature – 90nm →25-40% of total power– 60nm→50-70% of total power– Potential thermal runaway

• Lifetime exponential decrease with temperature (x ¼) – e.g. electromigration, oxide breakdown

• Clock gating and multithreshold CMOS increase on-chip thermal variation

Thermal integrity: a must for low-power-IC digital design, EDN 15 Sept. 2005

• Silicon Chip 10x10x0.5 mm3, assume 100W• 400µm diameter hot spot in the center, 1KW/cm2 heat

flux (1.25W) → ∆Thot spot ~7C

∆Thot spot is approximately independent of the technique used to cool the whole chip.Example: If the heat transfer coefficient changes from 5 to 20 KW/m2K, this will change Taverage from 225 to 75C; when the average power dissipation is ~100W/cm2 but this will not change ∆Thotspot

Heat Spreader

Hot spot temperature riseHot spot temperature rise

TIM2TIM1

Scheerer et al., Siemens AG, Elec. Lett. 35, (20, Sept. 1999)

Typical DFB Laser:∆λ/∆T= 0.1 nm/oCHeat generation kW/cm2

High Speed WDM Fiber Optics SystemsHigh Speed WDM Fiber Optics Systems

• Optoelectronic device used in high-speed, multi wavelength fiber optic communication systems generate kW/cm2 and they need temperature stabilization.

Fiber Optic Link: 3200 Gbit/s80 Lasers, 40 Gb/s per laser0.8nm channel spacing

Wavelength Division Multiplexing

0 1 0 1 1 00 1 0 1 1 0

~ 100 km~ 100 km ~ 100 km

∆λ ~ 0.4 nm∆λ ~ 0.8 nm

Thermal Issues in ElectroabsorptionModulator (EAM) • EAM can be easily integrated into tunable lasers to offer

high bandwidth (>10Gb/s), low chirp, low drive voltage and high extinction ratio

Akulova, et. al., IEEE Journal of Selected Topics in Quantum Electronics, 8 (6), Nov/Dec 2002

Collaborators: P. Kozodoy, P. Abraham (Agility Communications)

Thermal Imaging of Integrated Thermal Imaging of Integrated Electroabsorption ModulatorElectroabsorption Modulator

Electroabsorption modulator

Waveguide Ridge

Optical Image Thermal Image

V=-2.8V

Thermal ImageV=0V

A. Shakouri, J. Christofferson, Z. Bian, and P. Kozodoy, Proceeding of Photonic Devices and System Packaging Symposium (PhoPack 2002), pp22-25, July 2002, Stanford CA.

Temperature Profile along ElectroabsrorptionModulator

Position (µm)

Input power 6mW

Input Output

Peak Surface Temperature at High Input Power

Bias (V)

Standard Thermal Design

Improved Thermal Design

measurement (points)

theory (line)

Input power ~ 35 mWWavelength ~1.55 µm.

There is thermal runawaywith standard device design

Z. Bian, J. Christofferson, P. Kozodoy, A. Shakouri, Applied Physics Letters 2003

π ab = π a − π b =QIPeltier:

Peltier Effect (1834)Peltier Effect (1834)

When the current flows from material (a) into material (b) and then back to material (a), it heats the first junction and cools the second one (or vice versa). Thus, heat is transferred from one junction to the other one.

π = S ⋅ TdSdT

⎧ ⎨ ⎩ ⎪

Commercial TE Module• ∆T=72C (no heat load)• Cooling density <10W/cm2

• Efficiency 6-8% of Carnot

A. Shakouri 3/24/2009Efficiency of TE CoolersEfficiency of TE Coolers

Fraction of

Carnot

Efficiency

ZT1 2 3 4

Commercial TE’s

Typical CFC System

Z = S2σβ

Z = (Seebeck)2 (electrical conductivity)(thermal conductivity)

Single ratio Z determines efficiency (COP) and the maximum cooling of thermoelectric coolers .

Cooling Power DensityCooling Power Density

Vandersande, J.W., and Fleurial, J-P., Proceedings of the 15th International Conference on Thermoelectrics, pp. 252-255, 1996.

High Cooler Power Density Micro Peltier Coolers

H. Bottner

A. Shakouri 3/24/2009Microrefrigerators on a chip

Nanoscale heat transport and microrefrigerators on a chip; A. Shakouri, Proceedings of IEEE, July 2006

Featured in Nature Science Update, Physics Today, AIP April 2001

Hot Electron Cold Electron• Monolithic integration on silicon• ∆Tmax~4C at room temp. (7C at 100C)• Cooling power density > 500W/cm2

A. Shakouri 3/24/2009Microrefrigerators on a chip

Featured in Nature Science Update, Physics Today, AIP April 2001

UCSC, UCSB, HRL Labs

Relative Temp. (C)

J. Christofferson

0 200 400 600 800 1000

SiGeC Thin Film Cooler (sample 91)

40x40 µm2, Tambient

Heat Load (W/cm2)

Micro Refrigerator Integrated with Thin Film Heater

Heat Load (W/cm2)

680 W/cm2

Cooling power density >500W/cm2 even though ZT~0.1. This is due to 3D device geometry

Transient Thermal Imaging of a microcooler

100nsec, 300nm, 0.1C resolution

80x80 microns

20µs 50µs

10-7 10-6 10-5 0.0001 0.001

Transient Response 50x50 Micron Device

TheoryExperiment

Time(s)

J. Christofferson et al. SemiTherm 2009

Spot Cooling with SiGe microrefrigerators in a packaged device

Si chip inside a package with non-uniform heating Qh=10xQb –reference-

Solutions:(A) Passive cooling: Cu substrate(B) Active localized cooling: SiGe

superlattice (no contact/parasitic resistances, optimized thickness)

Package thermal resistanceR2=61 K/W (per unit area: 6×10-5 m2K/W)

1000μm

500μm

0 200 400 600 800 1000

optimum current

consumed powerOpt

Qh (W/cm2)Qh (W/cm2)O

)(c) Consum

ed Power (W

0 0.21 0.41 0.62 0.82 1.03Total heat (W)

0 200 400 600 800 1000

optimum current

consumed powerOpt

Qh (W/cm2)Qh (W/cm2)O

)(c) Consum

ed Power (W

Qh (W/cm2)O

)(c) Consum

ed Power (W

0 0.21 0.41 0.62 0.82 1.03Total heat (W)

T ｈ(K

Qh (W/cm2)

0 200 400 600 800 1000

Thin film microcoolerBulk Si

T ｈ(K

Qh (W/cm2)

0 200 400 600 800 1000

Thin film microcoolerBulk Si

Hot spot temperature

Power Analysis

Silicon substrate

Copper substrate

SiGe superlattice microrefrigerator

Fukutani and Shakouri (InterPACK06)

What could be achieved if SiGe material properties could be improved?

0 200 400 600 800 1000

ZT=0.125ZT=0.627 (SeebZT=0.627 (ResisZT=0.627 (The

T loca

Qh (W/cm2)

(a)T l

Qh (W/cm2)

by αby ρby k

0 200 400 600 800 1000

ZT=0.125ZT=0.627 (SeebZT=0.627 (ResisZT=0.627 (The

T loca

Qh (W/cm2)

(a)T l

Qh (W/cm2)

by αby ρby k

Thermal conductivity of SL

reduced by 5

Seebeck coefficient of SL increased by √5SiGe micro

refrigeratorZT~0.125

Si Substrate

Fukutani and Shakouri (InterPACK2006)

Thin Film Microrefrigerator Optimization

Current SiGe material

Decrease thermal conductivity

Increase Seebeck coef.

Younes Ezzahri et al. InterPACK07

• 10 microns thick, 50x50µm2 monolithic microrefrigerator with ZT~0.5 can cool a 1000W/cm2 hot spot by >15C.

A. Shakouri 3/24/2009Silicide nanoparticles in SiGe

300K 0.8% nanoparticles

Silicon

Si0.5Ge0.5

GeNiSi2

ZT (300K) ~0.5

ZT (900K) ~1.8

Natalio Mingo et al. Nano Letters 2009

Predictions:

RejectedEnergy 61%

Lawrence Livermore National Lab., http://eed.llnl.gov/flow

Power ~3.3TW

A. Shakouri 3/24/2009Direct Conversion of Heat into ElectricityDirect Conversion of Heat into Electricity

)()()( 2

tyconductivithermaltyconductivielectricalSeebeckZ

∆V~ S ∆T

Electrical Conductor

Hot Cold

Efficiency function of thermoelectric figure-of-merit (Z)

Rload = RTE internal

∆∆

=Seebeck coefficient

(1821)

A. Shakouri 3/24/2009Recent Advances in Thermoelectrics

• Recent advances in nanostructuredthermoelectric materials led to a sudden increase in (ZT)300K > 1

A. Majumdar, Science 303, 777 (2004)

Power Generation Efficiencies of Different Technologies

400 600 800 1000 1200

ZTm=0.5ZTm=1ZTm=2ZTm=3Carnot limit

Carnot

Solar/ Rankine

Geothermal/ Organic Rankine

ZTavg=20Coal/ Rankine

Cement/ Org. Rankine

Solar/ Stirling

ZT= S2σΤ/κ

Cronin Vining

Radioisotope Thermoelectric Generators(Voyager, Galileo, Cassini, …)

• 55 kg, 300 We, ‘only’ 7 % conversion efficiency• But > 1,000,000,000,000 device hours without a single

failure

B-doped Si0.78Ge0.22

P-doped Si0.78Ge0.22

B-doped Si0.63Ge0.36

P-doped Si0.63Ge0.36

Hot Shoe (Mo-Si)

Cold Shoe

n-type legp-type leg

SiGe unicoupleCronin Vining, ZT Services

Best Thermoelectric MaterialsBest Thermoelectric Materials

Free carrier concentration

Thermal Conductivity

κLattice contribution

Electronic contribution

Seebeck Electrical Conductivity

Insulator Semiconductor Metal

For almost all materials, if doping is increased, electrical conductivity increases but Seebeck coefficient is reduced. Similarly σ ↔ κ

ZT= S2σΤ/κ

Solid-State Thermionics

Go beyond the “energy band” trade offs in bulk semiconductors.

Deg. Semiconductor/Metal+ Energy Filter (barriers)

A. Shakouri, “Thermoelectric, thermionic and thermophotovoltaic energy conversion”, ICT 2005

Energy

Density of States

Ebarrier

Distance

0 2 4 6 8 10 12 14

(Ebarrier -E

f ) / kB T

Fermi Energy (eV)

Conserved

Non-conserved

Optimize TE Efficiency:Optimize TE Efficiency:(Metal/Semiconductor Nanocomposites) (Metal/Semiconductor Nanocomposites)

Assume: κlattice=1W/mK, mobility ~10 cm2/Vs

Even with only modestly low lattice thermal conductivity and electron mobility of typical metals, ZT > 5 is possible with hot electron filters

Fermi energy eV (↔ free electron concentration)

Planar Barrier

Metal/Semiconductor Nanostructure

Hot and cold electrons in equilibrium

Hot electron filter

D. Vashaee and A. Shakouri, Phys. Rev. Lett. 92, 106103/1 (2004).

BowersUC Santa BarbaraTE elements and

devices

Shakouri (PI)UC Santa Cruz

Overall organizationTE measurements

GossardUC Santa Barbara

MBEp-Er_III-V

ZideDelaware

MBE Non-Er III-V

Sands/RamdasPurdue

Sputtering /BulkZrN/HfN /Er_III-V

Thermionic Energy Conversion CenterThermionic Energy Conversion CenterAli Shakouri, DirectorAli Shakouri, Director

MATERIALSMATERIALS

CHARACTERIZATION / MODELINGCHARACTERIZATION / MODELING

DEVICES/ SYSTEMSDEVICES/ SYSTEMS

MajumdarUC Berkeley

ThermalCharact./Modeling

RamMIT

Thermal Imaging, Z-meter

BellBSST

Modules, Modeling Technology Transition

KobayashiUC Santa Cruz

MOCVDEr_III-V

BianUC Santa Cruz

Transport TheoryZT Characterization

ErAs Semi-metal Nanoparticlesimbedded in InGaAs Semiconductor Matrix

Molecular Beam Epitaxy (MBE) provides atomic layer control

ErAs dots are lattice-matched and incorporate without any visible defects in InGaAs despite different crystal structures (Cubic vs. Zinc-blende)

• “Random” ErAs particles ~ 2-3 nm

• Size is invariant to growth conditions

In0.53Ga0.47As matrix

0.3% ErAs/In0.53Ga0.47As (superlattice)

0.3% ErAs:In0.53Ga0.47As (random)

3.0% ErAs:In0.53Ga0.47As (random)

Beating the Alloy Limit in Thermal Conductivity Beating the Alloy Limit in Thermal Conductivity Ordered and Random ErAs:InOrdered and Random ErAs:In0.530.53GaGa0.470.47AsAs

From superlattice to “random” nanoparticle distributionFaster deposition rates enable record thick MBE grown films – up to 60µm

Phonon scattering by ErAs nanoparticles3-fold reduction in thermal conductivity beyond the alloy limit

Initial interruptedsuperlattice growth

Alloy limit of InGaAs

Accelerated“random nanodot” growth

Two Beneficial Effects of Metal Nanoparticles on Thermoelectric Performance

Nanoparticle

InGaAs

Metal nanoparticles scatter phononsreduced thermal conductivity

Metal nanoparticles donate electronsenhanced electrical conductivityincreased electron mobility in the matrix(Seebeck)2(electrical conductivity)

(thermal conductivity)Z =

(Seebeck)2(electrical conductivity)(thermal conductivity)

AlN_low pIate

200 elements of p-ErAs array

Wafer scale module fabrication

AlN_upper plate

200 elements of n-ErAs array

AlN_low plate

AlN_upper plate20 µm elements

400 element generatorGehong Zeng, John Bowers (UCSB)

A. Shakouri 3/24/2009Module Power generation results

140 µm/140 µm AlN

400 elements (10-20 microns ErAs:InGaAlAs thin films, 120x120µm2), array size 6x6 mm2

G. Zeng, J. Bowers, et al. (UCSB, UCSC) Appl. Physics Letters 2006

0 20 40 60 80 100 120 140

10 µm module20 µm module

∆T (K)Working with BSST on high power density module demonstration

• ZrN layers alloyed with W2N– Reduction in thermal conductivity– Closer lattice match with ScN layer

HAADF/STEM image of (Zr,W)N/ScNsuperlattice Courtesy: Joel Cagnon and Susanne Stemmer, UCSB

Refractory (Zr,W)N/ScN Metal/SemiconductorSuperlattices for Higher Temperature OperationRefractory (Refractory (Zr,W)N/ScNZr,W)N/ScN Metal/SemiconductorMetal/SemiconductorSuperlattices Superlattices for for HHighigher er TTemperatureemperature OOperationperation

V. Rawat, T. Sands, J. Cagnon, S. Stemmer et al. 2008

Monte Carlo simulation of TE energy exchange

InGaAs InGaAsP InGaAs

Heat SinkAnodeBias

Hot SourceCathode

Cathode contactlayer

Anode contact layer

Barrier (main-layer)

Mona Zebarjadi, Keivan Esfarjani, Ali Shakouri (Phys. Rev. B 2006)

Large Seebeck

Q =-∆S.Tc.I

electrons

Small Seebeck

Q =∆S.Th.I

A. Shakouri 3/24/2009Electron-lattice energy exchange

Peltier Cooling

Peltier Heating

Energy relaxation length in cathode

Energy relaxation length in anode

M. Zebarjadi, A. Shakouri and K. Esfarjani, Phys. Rev. B, Vol 74, 195331 (2006)

Length (micron)

0.25 0.5 0.75 1 1.25 1.5 1.75

Tjunction

θ_jc Package Resistance θ_jc

IC Chip thermal modelingIC Chip thermal modelingHeatsink (HS)Resistance θ_sa

Tambient

Second InterfaceResistance θ_cs θ_cs

Thermal Resistor Network Model

Real package

Yi-Kan Cheng, et al., “Temperature-Driven Cell Placemnt.” ElectrothermalAnalysis of VLSI Systems, 2000. 157-179.

A. Shakouri 3/24/2009Package Model

Power Map Temperature Map

~16 sec

(Pentium 4, 65MB)

Finite Element Analysis (power map => temperature map)

A. Shakouri 3/24/2009The road to a fast algorithm–Analytic methods based on Green's Function

≈pyramid

[1] York C. Gerstenmaier, Gerhard K.M. Wachutka, “Efficient Calculation of Transient Temperature Fields Responding to Fast Changing Heat Sources Over Long Duration in Power Electronic Systems” IEEE Trans on Components and Packaging Techn, 27 (1) March 2004

[2] YONG ZHAN and SACHIN S. SAPATNEKAR. A High Efficiency Full-Chip Thermal Simulation Algorithm. Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design.

V. Martin et al. Semitherm 2007

Limitation of simplified geometry

(analytical solution)

≈pyramid

101C 109C

79C 90C

∫∫∫'

')',','()',(V

dvzyxqrrG rr∑∑ ++=

s ttysxftswyxg ),(),(),(

Use of Image Blurring for full chip temperature calculation

w(-1,-1) w(-1,0) w(-1,1)

w(0,0)w(0,-1) w(0,1)

w(1,0)w(1,-1) w(1,1)

TRAVIS KEMPER, YAN ZHANG, ZHIXI BIAN and ALI SHAKOURI. Ultrafast Temperature Profile Calculation in IC chips. THERMINIC 2006

Convolution by Images

Images (electrostatics):

“A complicated problem can be solved by finding a simpler problem, as long as it is described by the same differential equation and the boundary conditions are equivalent”

Adiabatic Boundary Conditions

Go back to the stack geometry...

∂T/∂n = 0≈

Transient Temperature Change in IC

Input Pattern

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.535

Time (sec)

Power BlurringANSYS

Computation Time

ANSYS:10056 (sec)

PB: 100 (sec)

Reduction Factor: 101

Virginia Martin Heriz, A. Shakouri et al. THERMINIC 2007

Transient temperature at the chip center

A. Shakouri 3/24/2009Inverse problem (temperature -> power)

Measured temperature profile (include noise)

IMAGE DEBLURRINGREGULARIZATION:Tikhonov Regularization (does notpreserve edges)Bilateral Total Variation (Maximum a Postiori Cost function) Farsiu, et

al. IEEE Trans on Image Processing, 13 (10), p. 1327 October, 2004.

(Semitherm 2007 -Xi Wang et al.)

A. Shakouri 3/24/2009Inverse problem (temperature -> power)

Measured temperature profile (include noise)

(Semitherm 2007 -Xi Wang et al.)

• Metal / semiconductor nanocomposites can improve thermoelectric energy conversion– Mid/long wavelength phonon scattering– Hot electron energy filtering

• Micro Refrigerators on a Chip• Localized cooling (10 –150µm, 4-7C), based on SiGe, InP, > 500 W/cm2

• Potential to reach 20C cooling, 1kW/cm2

• Fast transient thermal imaging using thermoreflectance– Resolution: ~250nm, 0.01C, 100ns

• Fast transient thermal calculation– Using image blurring/ de-blurring, ~100x faster than FEA

• Thermal issues in electro-absorption modulators

Summary

Acknowledgement

Mona Zebarjadi (UCSC) - Material Research Society Gold Graduate Student Award, Boston, MA 2007

Yan Zhang, James Christofferson, et al. (UCSC/UCSB) – IEEE Transactions on Components and Packaging Best Paper Award 2006

Je-Hyoung Park, Xi Wang, Yan Zhang (UCSC) - Student Award, Advanced Thermal Workshop International Microelect. Packaging Society, 2005-2009

Daryoosh Vashaee (UCSC), Joshua Zide (UCSB), Xiaofeng Fan (UCSB) -Goldsmid Award (Best Graduate Student Research), International Conference on Thermoelectrics, 2001, 2004, 2007

Alumni: Daryoosh Vashaee (Prof. Oklahoma State), Yan Zhang (Tessera) , Rajeev Singh (Sun Power), Zhixi Bian (Adj. Prof. UCSC),James Christofferson (Res. Scientist UCSC), Kazuhiko Fukutani(Canon), Javad Shabani (PhD student, Princeton), Tammy Humphrey, Virginia Martin, Travis Kemper

Postdocs/Graduate Students: Younes Ezzahri, Helene Michel, Mona Zebarjadi, Xi Wang, Kerry Maize, Hiro Onishi, Tela Favaloro, Paul Abumov, Phil Jackson, Je-Hyoung Park, Oxana Pantchenko

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