Molecular Quantum-dot Cellular Automata (QCA): Beyond Transistors - - PowerPoint PPT Presentation

Center for Nano Science and Technology

Craig S. Lent University of Notre Dame

Molecular Quantum-dot Cellular Automata (QCA): Beyond Transistors

Supported by National Science Foundation ND Collaborators: Greg Snider, Peter Kogge, Mike Niemier, Marya Lieberman, Thomas Fehlner, Alex Kandel, Alexei Orlov, Mo Liu,Yuhui Lu

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Outline of presentation

• Introduction and motivation
• QCA paradigm
• QCA implementations

– Metal-dot – Semiconductor-dot – Magnetic – Molecular

• Circuit and system architecture
• Summary

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Goal: Electronics at the single-molecule scale

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The Dream of Molecular Transistors

Why don’t we keep on shrinking transistors until they are each a single molecule?

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Dream molecular transistors

V

• ff

low conductance state V high conductance state

• n

I 1 nm fmax=1 THz Molecular densities: 1nm x 1nm 1014/cm2

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Transistors at molecular densities

Suppose in each clock cycle a single electron moves from power supply (1V) to ground. V

Frequency (Hz) 1014 devices/cm2 1013 devices/cm2 1012 devices/cm2 1011 devices/cm2 1012 16,000,000 1,600,000 160,000 16,000 1011 1,600,000 160,000 16,000 1,600 1010 160,000 16,000 1,600 160 109 16,000 1600 160 16 108 1600 160 16 1.6 107 160 16 1.6 0.16 106 16 1.6 0.16 0.016

Power dissipation (Watts/cm2)

ITRS roadmap: 7nm gate length, 109 logic transistors/cm2 @ 3x1010 Hz for 2016

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The Dream of Molecular Transistors

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New paradigm: Quantum-dot Cellular Automata

Revolutionary, not incremental, approach Beyond transistors – requires rethinking circuits and architectures

Use molecules, not as current switches, but as structured charge containers. Represent information with molecular charge configuration. Zuse’s paradigm

• Binary
• Current switch
• charge configuration

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Quantum-dot cellular automata

Represent binary information by charge configuration of cell. “0” “null” “1”

QCA cell

• Dots localize charge
• Two mobile charges
• Tunneling between dots
• Clock signal varies relative

energies of “active” and “null” dots active Clock need not separately contact each cell.

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“null”

Quantum-dot cellular automata

Neighboring cells tend to align in the same state. “1”

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Quantum-dot cellular automata

Neighboring cells tend to align in the same state. “1” “1”

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Quantum-dot cellular automata

Neighboring cells tend to align in the same state. “1” “1”

This is the COPY operation.

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QCA cell-cell response function

Neighbor Polarization Neighbor Polarization Cell Polarization Cell Polarization Clock: off Clock: on

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Majority Gate

“1” “1” “0” “null”

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Majority Gate

“1” “1” “0” “1”

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Majority Gate

Three input majority gate can function as programmable 2-input AND/OR gate.

“A” “C” “B” “out”

M

A B C

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QCA single-bit full adder

Hierarchical layout and design are possible. Simple-12 microprocessor (Kogge & Niemier)

result of SC-HF calculation with site model

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Outline of presentation

• Introduction and motivation
• QCA paradigm
• QCA implementations

– Metal-dot – Semiconductor-dot – Magnetic – Molecular

• Circuit and system architecture
• Summary

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QCA devices exist

“dot” = metal island electrometers 70-300 mK

Al/AlOx on SiO2 Metal-dot QCA implementation

Greg Snider, Alexei Orlov, and Gary Bernstein

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Metal-dot QCA cells and devices

• Majority Gate

M

A B C

Amlani, A. Orlov, G. Toth, G. H. Bernstein, C. S. Lent, G. L. Snider, Science 284, pp. 289-291 (1999).

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QCA Shift Register

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QCA Shift Register

Gtop Gbot

electrometers

V

IN+

V

IN–

V

CLK1

V

CLK2

D1 D4

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Metal-dot QCA devices exist

• Single electron analogue of molecular QCA
• Gates and circuits:

– Wires – Shift registers – Fan-out – Power gain demonstrated – AND, OR, Majority gates

• Work underway to raise operating temperatures

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Power Gain in QCA Cells

• Power gain is crucial for practical devices

because some energy is always lost between stages.

• Lost energy must be replaced.

– Conventional devices – current from power supply – QCA devices – from the clock

• Unity power gain means replacing exactly as

much energy as is lost to environment. Power gain > 3 has been measured in metal-dot QCA.

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GaAs-AlGaAs QCA cell

• Dots defined by top gates depleting 2DEG
• Direct measurement of cell switching

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Silicon P-dot QCA cell

• Dots defined by implanted phosphorus
• Single-donor creation foreseen
• Direct measurement of cell switching

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Magnetic QCA

• Dots defined by magnetic

domains

• Room temperature operation

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Molecular QCA

“dot” = metal island 70 mK Mixed valence compounds “dot” = redox center room temperature+

Metal tunnel junctions

Key strategy: use nonbonding orbitals (π or d) to act as dots.

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Experiments on molecular double-dot

Thomas Fehlner et al. (Notre Dame chemistry group) Journal of American Chemical Society, 125:15250, 2003

Ru Ru Fe Fe

“0” “1” Fe group and Ru group act as two unequal quantum dots.

trans-Ru-(dppm)2(C≡CFc)(NCCH2CH2NH2) dication

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Surface attachment and orientation

N Si Si

3.8 Α 2.4 Α 106o

PHENYL GROUPS “TOUCHING” SILICON

Molecule is covalent bonded to Si and oriented vertically by “struts.”

Si(111) molecule Si-N bonds “struts”

Center for Nano Science and Technology Fe Ru Fe Ru Fe Ru Si Hg Fe Ru Si Hg Fe Ru Si Hg Fe Ru ac Capacitance voltage excited state switching Energy ground state

Applied field equalizes the energy of the two dots

When equalized, capacitance peaks.

applied potential

Measurement of molecular bistability

• 1.5
• 1.0
• 0.5

0.0 0.5 1.0 1.5 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7

C (oxidized) C (reduced) ∆C

V

H g (V)

C (nF)

• 0.25
• 0.20
• 0.15
• 0.10
• 0.05

0.00 0.05 0.10 0.15

∆C (nF) layer of molecules

Ru Fe Ru Fe

2 counterion charge configurations on surface

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Longer molecular double-dot

Isopotential surface HOMO

• rbital

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Double-dot click-clack

• 1.5
• 1.0
• 0.5

0.0 0.5 1.0 1.5 0.9 1.0 1.1 1.2 1.3

COxidized Cas prepared ∆C

VHg (V)

C (nF)

• 0.2
• 0.1

0.0 0.1

∆C (nF)

Ph2 P Ru P Ph2 Ph2 P P Ph2 Ph2 P R u P Ph2 Ph2 P P Ph2N N H2N NH2

3+

d1=1.8 nm dm=2.8 nm

Hua & Fehlner

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Square 4-dot QCA molecules

0.6 nm

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Imaging molecular double-dot

structure toluene solution Goal: single-molecule imaging on surfaces

Kandel group

Molecules are pulse-injected from solution into vacuum onto a clean, crystalline gold [Au(111)] surface.

Ru-Ru molecule with no surface binding. Not mixed-valence species.

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Ru2 clustering

Some clustering and alignment of molecules

• ccurs automatically during
• deposition. (50 nm image

shown.) We should be able to compare isolated molecules with those in larger clusters.

Experimental conditions: 0.5 V, 20 pA, 298 K

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Molecular motion

Changing tunneling conditions (from 1.0 V, 20 pA to 1.0 V, 100 pA) increases tip/molecule interaction. We observe a change in orientation for one Ru2 molecule. This suggests the possibility of using the STM tip for controlled manipulation of these molecules on the surface.

Experimental conditions: 250 ×180 Å, 1.0 V, 20 (100) pA, 298 K

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Imaging charge localization

Neutral molecules Mixed-valence molecules Preliminary results for Fe-Fe fabricated by Claude Lapinte (Rennes)

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Single-atom quantum dots

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Outline of presentation

• Introduction and motivation
• QCA paradigm
• QCA implementations

– Metal-dot – Semiconductor-dot – Magnetic – Molecular

• Circuit and system architecture
• Summary

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Field-clocking of QCA wire: shift-register

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Computational wave: majority gate

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Computational wave: adder back-end

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Permuter

Deep pipe-lining at very small scale

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Wider QCA wires

Redundancy results in defect tolerance.

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Molecular circuits and clocking wires

Next: zoom out to dataflow level

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Universal floorplan

Peter Kogge

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QCA design tools

Design tools are starting to enable new systems ideas.

QCADesigner Konrad Walus

• U. British Columbia

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System + Application Architectures

Grounded in device physics & simulation Incorporate clock driven dataflow

A B C D A B

Device architecture maps well to many system architectures…

A A’ B B’ C C’ AB AC AND Plane OR Plane AB + BC + AC BC

Reconfigurable General Purpose Systolic

Good for FIR, FT, Matrix multiply, graph algorithms, etc.

Mike Niemier

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Summary

• QCA offers possible path to limits of downscaling –

molecular computing.

– General-purpose computing – New architecture – Low power dissipation which is essential

• Single-electron metal-dot QCA devices exist.
• First steps in molecular-scale QCA
• Clear path but much research remains to be done.

– Rethinking architecture to match problem – Chemistry, physics, electrical engineering, computer science

Thanks for your attention.