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Chemical element
◦ 2nd most abundant in
Earth’s crust
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Metalloid
◦ Neither metal or
nonmetal
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Intrinsic semiconductor
Electrical conductivity varies
with conditions
◦ Voltage
◦ Temperature
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Not soluble in water
Problems with Silicon
There are two main
problems with using
silicon chips:
1.) Number of Transistors
2.) Overheating
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Real world example
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Moore’s Law
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Dark Silicon
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Carbon nanotubes
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Copper
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Problem: Bus Method
Solution: Better
connections between
cores
◦ Similar to mesh
◦ Nanotechnological advances
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Process more information
at rapider pace
Synapse
Goal: To have computers
mimic brain functioning
◦ In this way, computers could
“learn”

Currently being researched
by IBM
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One atom thick sheets of
carbon
◦ Hexagons
◦ Strongest material ever made
when yanked along sheets
◦ Flexible and outstanding heat
conductor
◦ 100 times the mobility of
silicon
-ease of electron flow
Nanotubes
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Faster performance
Efficient, single transistor,
clean output
Form of pure carbon first
identified in 2004
MIT researchers built
experimental graphene
chip
◦ “frequency multiplier”
◦ Can double the frequency of
an electromagnetic signal
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• University of Manchesster
• Graphene is too conductive
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Cannot be packed densely
Vertical vs. horizontal
Tunnelling diode
Exploited unique feature of
graphene
Concept by Leonard
Adleman in 1994
DNA-Based Computers:
not advanced
Can solve issues of
Moore’s Law, as DNA is:
◦ not scarce; relatively
cheap
◦ environmentally friendly
◦ very compact
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Potential Performance:
◦ DNA-Based: 4 options (“A,”
“T,” “C,” and “G”)
◦ Silicon-Based: 2 options
(“0” or “1”)

Logic Gates:
◦ Used in Boolean functions
◦ DNA-Based computation does not occur
instantaneously
◦ Could allow DNA-computing to help in biological
functions
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• Richard Feynman (1982)
• The Ultimate Computer
• Quantum theory : explains the nature and
behavior of energy and matter on the
quantum level
• Outside interests

Interference

Error Correction

Output observance
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• A computational scheme that uses individual atoms
or molecules as means of solving computational
problems
• Founded in 1994
• Involves nanoelectronic components conducting
processing a more conventional, universal and
controlled manner
• More powerful and cheaper than today’s machines as
well as cheaper and easier to manufacture.

Lacking of manufacturing
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http://www.nanowerk.com/spotlight/spotid=1762.php

http://whatis.techtarget.com/definition/0,,sid9_gci332254,00.html.

http://www.technologyreview.com/computing/12109/

http://www.wisegeek.com/what-is-molecular-computing.htm.

http://www.nytimes.com/2011/08/01/science/01chips.html?pagewanted=all

http://bigthink.com/ideas/42825
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2009). "Carbon Sheets an Atom Thick Give Rise to Graphene Dreams". Science (New York, N.Y.) (00368075), 324 (5929), p.875.
“New Material Could Lead to Faster Chips” Chandler, David L.
http://web.mit.edu/newsoffice/2009/graphene-palacios-0319.html
Kolata, Gina. "SCIENTIST AT WORK: Leonard Adleman; Hitting the High Spots Of
Computer Theory." The New York Times. Web.
<http://www.nytimes.com/1994/12/13/science/scientist-at-work-leonardadleman-hitting-the-high-spots-of-computertheory.html?pagewanted=all&src=pm>.
"KurzweilAI | Accelerating Intelligence." Unifying Silicon- and DNA-based
Computing. Web. <http://www.kurzweilai.net/unifying-silicon-and-dna-basedcomputing>.
"Largest DNA-Based Computer Ever Built Can Calculate Square Roots." Popular
Science. Web. <http://www.popsci.com/science/article/2011-06/largest-dnabased-circuit-can-compute-simple-math-step-toward-control-chemicalreactions>.
Marquit, Miranda. "The next Computer: Your Genes." The next Computer: Your
Genes. 6 May 2011. Web. <http://phys.org/news/2011-05-genes.html>.
Rannals, Lee. "Forward Thinking Of Computer Chips Could Pave Way For Future." Technology News. 13 Apr. 2012. Web.
<http://www.redorbit.com/news/technology/1112513294/forward-thinking-ofcomputer-chips-could-pave-way-for-future/>.
Trafton, Anne. "Mimicking the Brain, in Silicon." MIT's News Office. Web.
<http://web.mit.edu/newsoffice/2011/brain-chip-1115.html>.
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