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Nanoscale Self-Assembly A Computational View. Philip Kuekes Quantum Science Research HP Labs. What’s Cooking? Everybody likes Recipes. Two Challenges for Nanoelectronics. Invent a new switching device Develop a new fabrication process Examine Architecture First.
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Nanoscale Self-AssemblyA Computational View Philip Kuekes Quantum Science Research HP Labs
Two Challenges for Nanoelectronics • Invent a new switching device • Develop a new fabrication process • Examine Architecture First
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 PASS PASS FAIL PASS PASS FAIL PASS PASS PASS
Defect Tolerance for Free • CMOS Technology –Configuration bit >20 x wire crossing area • Molecular Technology –Configuration bit smaller than wire crossing
Memory 0 Switch Teramac crossbar Teramac Crossbar Architecture
4PF6- O O O O O O O O O O O O O O O O + + N N N N N N + + CH2OH Rotaxane Molecular Switch -Prof. Fraser Stoddart, UCLA C.P. Collier, E.W. Wong et al.
10 Ti 5 0 Current (mA) -5 Pt -10 -1.0 0.0 -2.0 1.0 Voltage (V) Experimental Realization of aMolecular-Tunneling Switch Device = Molecule + Electrodes
Moletronics Architecture • Wires • Memories • Logic • Integrated Circuits
Crossbar at 17 nm half-pitch width • Smallest virus 30-42 nm • hepatitis B
Parallel ErSi2 wires grown by self-assembly 2 nm width with a nine nanometer separation
a b c d e f Logic Array Design U V W X Y Z Y = (U AND V) OR(W AND X) Z = V+ C = V-
RESET SET 1 SET 2 ENABLE RESTORE & INVERT Clock / control C1C2 SW1 SW2 E D Data input Q Data out MOLECULAR SWITCH LATCH: EXPT DATA
Expt: Latch works! Signal restoration Inversion, if desired >100mV operating margin No nanoscale transistor! J. Appl. Phys. Feb 1, 2005
‘C20’ O C C H H O Pt 3 TiAl TiAl Pt Al Ti V LB Pt SiO2 Si 2003 NAND HP crossbar switches & circuits 16 k 1 k 2005 (ITRS 2018) 64 2004 1 2002
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 Math - Expanders- Cayley Graphs- Ramanujan Graphs
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.
Algorithmic Manufacturing • Local rules • Global structure
Feedback and the Way Forward • Computer Code • Biology • Chemistry, Physics, Materials Science
Feedback and the Way Forward • Computer Code • Biology • Chemistry, Physics, Materials Science • Reaction Diffusion
DNA and Proteinsversus Cells Logic Design as Geometry Spatial Structure Controlled diffusion Compartments as wires
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