Nanoscale Self-Assembly

A Computational View

Philip KuekesQuantum Science Research

HP Labs

What’s Cooking?

Everybody likes Recipes

•Invent a new switching device

•Develop a new fabrication process

Examine Architecture First

Two Challenges for Nanoelectronics

HPL Teramacmulti-architecture computer

• 106 gates operating at 106 cycle/sec

• 100 times workstation performance

• Largest defect-tolerant computer ever built

• 220,000 (3%) defective components

Defect Theology

• Original Sin• Redemption Through Good Works• Guilt by Association

Redundant Testing

PASS

FAIL

PASS

PASS

PASS

PASS

FAIL

PASSPASS PASS

Defect Tolerance for Free

• CMOS Technology –Configuration bit >20 x wire crossing area

• Molecular Technology –Configuration bit smaller than wire crossing

Teramac Crossbar ArchitectureMemory0

Switch

Teramac crossbar

OO

ONN

N

OO

O

NN

N

O

OO

OO

O

OO

OO

4PF6-

CH2OH

+ +

++

Rotaxane Molecular Switch -Prof. Fraser Stoddart, UCLA

C.P. Collier, E.W. Wong et al.

Experimental Realization of aExperimental Realization of a Molecular-Tunneling Switch Molecular-Tunneling Switch

-10

-5

0

5

10

Cur

rent

(A

)

-2.0 -1.0 0.0 1.0

Voltage (V)

Ti

PtDevice =

Molecule + Electrodes

Moletronics Architecture

• Wires• Memories• Logic• Integrated Circuits

Crossbar at 17 nm half-pitch width

Smallest virus 30-42 nmhepatitis B

Parallel ErSi2 wires grown by self-assembly2 nm width with a nine nanometer separation

Logic Array DesignU V W X Y Z

a

b

c

d

e

f

Y = (U AND V) OR (W AND X)

Z = V+ C = V-

MOLECULAR SWITCH LATCH: EXPT DATA

DDatainput

Clock /control

C1 C2

QDataout

SW1 SW2E

-0.5

-0.25

0

0.25

0.5

Dat

a (V

)

Test 1 input +0.5V out -0.46V

2

1

0

-1

Con

trols

(V)

-2

-1

0

1

C1

C2

-500

0

500

Cur

rent

(uA

)

-1 0 1Voltage (V)

SW1 200

100

0

-100

-1 0 1Voltage (V)

SW2

-0.5

-0.25

0

0.25

0.5

Dat

a (V

)

121086420Time (s)

Test 2 input -0.5V out +0.50V

RES

ET

SET

1SE

T 2

ENA

BLE

RES

TOR

E&

INVE

RT

Expt: Latch works!

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

Volta

ge (V

)

Input Output

Trial 1

2

3

4

5

6

Signal restorationInversion, if desired>100mV operating margin

No nanoscale transistor!

J. Appl. Phys. Feb 1, 2005

Random Demultiplexer

COH

OH3C

Pt

TiAl

Pt

TiAl

SiO2

Pt

TiAl

VLB

Si

‘C20

’

-20

-10

0

10

Cur

rent

den

sity

(103 A

/cm

2 )

-2 -1 0 1Voltage (V)

C20_1

C20_2

C20_3

2002

20031

64 2004

1 k

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0.5Vo

ltage

(V)

Input Output

Trial 1

2

3

4

5

6

(ITRS 2018)

[ 0 0

0 ]

[ 1 0

0 ]

[ 0 1

0 ]

[ 0 0

1 ]

[ 1 1

0 ]

[ 1 0

1 ]

[ 0 1

1 ]

[ 1 1

1 ]

[ 0 0

0 ]

Boolean inputs [ A B C ]

100

0

Outp

ut Vo

ltage

(mV)

VT

( A · C ) + B

10 July 2001 7 Jan 2004

Output

VA

DrivingJunction A

R

DrivingJunction B

ReceivingJunction C

VB VC

Figure 1. A 1×3 array of inverting hysteretic resistor latches. This tiny serial logic array is sufficient for implementation of a NAND gate.

Output

VA

DrivingJunction A

R

DrivingJunction B

ReceivingJunction C

VB VC

Output

VA

DrivingJunction A

R

DrivingJunction B

ReceivingJunction C

VB VC

Figure 1. A 1×3 array of inverting hysteretic resistor latches. This tiny serial logic array is sufficient for implementation of a NAND gate.

NAND

2

1

0151050

4

3

2

1

0

-1

Cur

rent

(mA

)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5Voltage (V)

1

23

4

5

6

7

8

9

10

1617

C20

-0.18

-0.16

-0.14

-0.12

-0.10

Cur

rent

(A)

-3 -2 -1 0 1 2Voltage (V)

-1.0

-0.5

0

0.5

1.0

Curre

nt (m

A)

-0.5 0 0.5Voltage (V)

16 k

2005

HP crossbar switches & circuits

How does a Molecular Computer Grow Up?

• Conventional Computer Teacher

• Low Bandwidth Link• Initially Stupid Molecular

Student

I Get By With A Little HelpFrom My Friends

• Tutors• Doctors

Complexity

• Self Assembly & Thermodynamics

• Arbitrary Graphs

Tradeoffs

• Cost of doing the chemistry

• Cost of doing the computing

The Pure and the Grubby

- Expanders

- Cayley Graphs

- Ramanujan Graphs

The Math

Today

• Physical Scientists can only do very simple self-assembly

• Mathematicians can create interesting complex structures with very simple generators

The new capability

• Combine the simple physical processes with the mathematical constructions

• Nanoscale self-assembled systems with enough complexity to do useful computation.

The Physics

• Self-Assembled DNA Nanostructures • Self-Assembled Surface Chemistry • Viral Self-Assembly • Molecular Electronic Circuit Assembly • DNA-linked Nano-particle Structures

The MathAdvantages of Simple

Construction

• amenable to self-assembly • short explicit description• highly-connected• sparse

Physical StructuresNot Just Abstract Graphs

• defect-tolerance• efficiently embedded in three-dimensional

space • relatively short edge-lengths.

•Local rules

•Global structure

Algorithmic Manufacturing

•Computer Code

•Biology

• Chemistry, Physics, Materials Science

Feedback and the Way Forward

•Computer Code

•Biology

• Chemistry, Physics, Materials Science Reaction Diffusion

Feedback and the Way Forward

Stealing from Biology

DNA and Proteinsversus Cells

Logic Design as Geometry

Spatial Structure

Controlled diffusion

Compartments as wires

Organelles

Garbage Collection

Ubiquitin

Apoptosis

Mass transport

The Best of Both Worlds

Self-assembly

Adaptive External Programming

Self-disassembly

Tradeoffs

• Cost of doing the chemistry

• Cost of doing the computing