Transcript Matisoo
Post-CMOS Grand Challenges
Juri Matisoo
Vice-President, Technology
Semiconductor Industry Association
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Acknowledgements
SIA TSC Working Group
Bob Doering, TI, Chair;
George Bourianoff, Intel
Philip Wong, IBM
Luan Tran, Micron
Papu Maniar, Motorola
Jim Hutchby, SRC
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Agenda/Overview
Value and Need for Investment in
Nanoelectronics* Research
Long-Term Manufacturing Research
Long-Term Device Research
Recommendations Summary
* In this presentation: “nanoelectronics” ≡ “future IC technology”
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Benefits to the U.S.
from the Semiconductor Industry
Powers other Industries
Spurs Economic Growth
~3% of GDP growth due to “computer quality” increase
Creates High-Wage Jobs
~300K jobs in the U.S. currently
Fosters International Competitive Advantage
Bolsters National Defense/Homeland Security
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Intelligence gathering/processing
Guidance/Control systems (e.g., for E2C2)
Logistics management/efficiency
Communications Technology
The Need for New Enablers
of Progress in Future ICs
The industry productivity gains of 25%/year reduction in
cost/function and improved performance and reduced
power consumption over the last 40 years have been driven
by miniaturization of semiconductor devices.
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The International Technology Roadmap for
Semiconductors (ITRS) predicts that over the next 10-15
years, this trend will end.
New devices and manufacturing techniques are needed.
Long-Range Grand Challenges
In the long term, the SIA TSC feels that we face two grand
challenges worthy of very large federal funding:
(1) Scaling limits of “evolutionary lithography/thin-film
manufacturing”
(2) Scaling limits of “charge-transport devices/interconnect”
We suggest that these might be overcome through new and
synergistic research in the under-funded broad areas of:
(1) “Directed self-assembly” of complex structures with
“nanoelectronics-functionality” (computation, comm., etc.)
(2) “Beyond (classical) charge transport” signal-processing/
computational technology (e.g., based on quantum-states)
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Rationale for Directed Self-Assembly
Break the manufacturing “scaling tyranny” of:
(1) Maintaining adequate process-control margin
(2) Contamination-density-limited yield
(3) Escalating wafer-fab capital cost
(4) Lengthening production cycle time
(5) Rapidly increasing photomask cost
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Desired Consequences
of Directed Self-Assembly
(1) Approaching “atomic-level” perfection/control in
manufacturing of nano-systems (“future SOCs”)
(2) Providing radically enhanced and affordable
functionality in nano-systems
(3) Revolutionizing fab economics and logistics
(4) Application to a broad range of devices (e.g., from
“ultimate CMOS” to “quantum-state”)
Note: the principal barrier to implementation of
advanced device concepts is often “manufacturing
feasibility”
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Current Examples of Self-Assembly Techniques
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The Self-Assembly “Place and Route” Problem
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IC Metrics that Should Guide Research
on NanoManufacturing
Cost/Integrated-Function
(e.g., $/gate or $/bit integrated into system)
Operations/Second
(computation speed, e.g. MIPS)
Power Dissipation
(both operating and standby power)
Integration Density
(e.g., integrated functions/cm2 or /cm3)
Integration Diversity
(SOC functions - e.g., analog, RF, e-RAM)
Capital Cost/Capacity
(e.g., capital investment $/chips/month)
Mfg. Cycle Time
(impacts time-to-market and ASIC delivery)
R&D Cost
(e.g., cost per new product or tech node)
NanoManufacturing Goals: 100x beyond limits of the evolutionary approach
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Rationale for Beyond-Charge-Transport
Signal-Processing/Computation
Break the “CMOS electrical scaling tyranny,” e.g.:
(1) Voltage (limiting speed/power/error-rate tradeoff)
(2) Resistance (limiting speed and low power)
(3) Capacitance (limiting speed and low active power)
(4) Charge-Leakage Mechanisms (limiting standby power)
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Desired Consequences
of Beyond-Charge-Transport
Computation/Signal-Processing
(1) Providing significant performance improvements via
mechanisms beyond merely scaling physical
dimensions (e.g., multiple logic states, far-fromequilibrium operation)
(2) Providing qualitatively new types of nano-system
functionality (e.g., direct sensing/actuating)
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Some Potential State Variables
Alternative to Classical Electric Charge
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Atomic/molecular quantum states
(including “artificial atoms”)
Magnetic-dipole magnitude/orientation
(e.g., electron/nuclear spin)
Electric-dipole magnitude/orientation
Magnetic flux quanta
Photon number
Photon polarization
Mechanical state
Example: Spin-Resonance Transistor (SRT)
Transistors that control spins
rather than charge
More energy efficient than
conventional transistors
Combines magnetic and
electrostatic fields
May enable quantum
computing
Courtesy Eli Yablanovitch, UCLA
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Challenges to Metrology
Instrumentation and techniques for
Identification and visualization of atomic species
and structure
Observation of short-range and long-range order,
defects
Device characterization
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Summary
We have identified two major challenges for
nanoelectronics, worthy of significant Government
funding via NNI
We presented these findings to PCAST as part of their
NNI review, and strategy development
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