25-05-2012, 01:06 PM
NANO TECHNOLOGY
65721585-Nano-Technology.pdf (Size: 96.7 KB / Downloads: 52)
Abstract:
Nanotechnology is the hybrid science combining engineering and chemistry
that have applications in the real world. The area of nanotechnology lets one build
elaborate structures ,atom by atom ,on a scale of 1 to 100 nanometers that can store
information, switch electrical signals, convert sunlight to electricity.
A nanometer is a billionth of a meter that is about 1/80,000 of the diameter of a
human hair, or 10 times the diameter of a hydrogen atom. In this paper we had dealt with
the main concepts involved in the field of nanotechnology which are as follows:
BioComputing
Molecular Computing
Quantum Computing
Optical Computing
Atoms and molecules stick together because they have complementary shapes that
lock together, or charges that attract. Just like magnets a positively charged atom will
stick to a negatively charged atom. A specific product will take shape as millions of these
atoms are pieced together by nanomachines.
The goal of nanotechnology is to manipulate atoms individually and place them
in a pattern to produce a desired structure of small size that spreads its wings in the
modern trends.
Reports indicate that Israeli scientists have built a DNA computer to tiny that a
trillion of them could fit in a test tube and perform a billion operations per second with
99.8 per cent accuracy. Researchers also found that a self assembled molecule could
sustain a current of about 0.2 microamperes at five volts - which meant that the molecule
could channel through itself roughly a million electron per second.
Molecular devices can be used as memory elements that forms the
basis for Nanotechnology.
Bio-Computing:
Nanocomputers, though have several applications, the one that stirs the
imagination is its identification of malfunctions in human beings by traveling inside the
human body. The molecular machines inside the living cell already posses the repertoire
of operations required to implement a universal computer. A design for a biological
nanocomputer shows that a Turing machine can be realized by a basic cycle consisting of
molecular recognition, two cleavages, two ligations and movement along a polymer, all
controlled by allostreic conformational changes. Each of these operations is routinely
performed by some molecular machine in the living cell, such as the ribosome,
splicesome and the replisome.
The computer’s input, and “software” are made up of DNA molecules. For
“hardware” the computer uses two naturally occurring enzymes that manipulate DNA,
Fokl, an enzyme that cuts DNA and Ligase and enzyme that seals two DNA molecules
into one. When mixed together in solution, the software and hardware molecules operate
in harmony on the input molecule to create the output molecule, forming a simple
mathematical computing machine, known as a finite automaton.
The automaton could be programmed to perform different tasks by selecting
different subsets of the molecules. Both input and software molecules are designed to
have one DNA strand longer than the other, resulting in a single strand overhand called a
“sticky end. “Two molecules with complementary sticky ends can temporarily stick to
each other (a process known as hybridization), allowing DNA Ligase to permanently seal
them into one molecule. The sticky end of the input molecule encodes the current symbol
and the current state of the computation, whereas the sticky end of each “software”
molecule is designed to detect a particular state-symbol combination. A two-state, twosymbol
automaton has four such combinations. For each combination, the nanocomputer
has two possible next moves, to remain in the same state or to change to the other state,
allowing eight software molecules to cover all possibilities.
In each processing step the input molecule hybridizes with a software molecule
that has a complementary sticky end, allowing Ligase to seal them together using two
ATP molecules as energy. Then comes Fok-I, detecting a special site in the software
molecule known as the recognition site. It cleaves the input molecule in a location
determined by the software molecule, thus exposing a sticky end that encodes the next
input symbol and the next state of the computation. Once the last input symbol is
processed, a sticky end encoding the final state of the computation is exposed and
detected, again by hybridization and ligation, by one of two “output display” molecules.
The resulting molecule, which reports the output of the computation, is made visible to
the human eye in a process known as gel electrophoresis.
The automation is so small that 1012 automata sharing the same software run
independently and in parallel on inputs (which could in principle be distinct) in 1201
solution at room temperature. Their combined rate is 109 transitions per second, their
transition fidelity is greater than 99.8% and together they consume less than 10-10
Watt.
Using DNA for Basic Logical and Arithmetic
Operations:
After the potential power of DNA computing has been described by Adleman and
Lipton, researchers have developed an interest in DNA computing for solving difficult
computational problems.
Guarnieri et al. and Vineet Gupta et.al have proposed DNA based methods to do
arithmetic and logical operations. But in their methods, the strands representing result
have to be polymerized for each and every instance of a specific operation, those strands
are not reusable. The limitation can be overcome by using sticker-based method to
perform arithmetic and logical operations. The advantage of the proposed method is
that output values are computed and stored parallely. The strands which represent the
output can be used repeatedly any number of times. The main idea of this method is
grouping the strands according to the output value are stored. The result tubes are the
tubes, which contain the result strands after completion of the annealing process with
stickers.
Biological operations and Notations:
Some of the biological operations used in this paper and their notations are
described below
Initializing
Stickers corresponding to input blocks and memory strands are poured into a tube
to represent all possible inputs. initialize (No)
Extracting
Particular Strands in a test tube are extracted based on whether the stickers stick
with specific region of memory strands or not
S (test tube label, Region, 1)
S (No, Io, 1) - extracts the strands from No with which sticker in the Io
th region.
S (No, In, 1) - extracts the strands from No with which sticker not stuck in the In
th region.
(Note : S’ (No, Io, 1) = S (No, Io, 0))
Setting
Multiple copies of a particular sticker are poured with memory strands to make a
specific region double stranded. Set (N1, Rn+1, 1) - add multiple copies of sticker
complementary to Rn+1
th region in N1.
Merging
The strands in two or more tubes are poured into a single tube. No = merge (N1,
N2) - pour the strands in N1 and N2 into N0.
65721585-Nano-Technology.pdf (Size: 96.7 KB / Downloads: 52)
Abstract:
Nanotechnology is the hybrid science combining engineering and chemistry
that have applications in the real world. The area of nanotechnology lets one build
elaborate structures ,atom by atom ,on a scale of 1 to 100 nanometers that can store
information, switch electrical signals, convert sunlight to electricity.
A nanometer is a billionth of a meter that is about 1/80,000 of the diameter of a
human hair, or 10 times the diameter of a hydrogen atom. In this paper we had dealt with
the main concepts involved in the field of nanotechnology which are as follows:
BioComputing
Molecular Computing
Quantum Computing
Optical Computing
Atoms and molecules stick together because they have complementary shapes that
lock together, or charges that attract. Just like magnets a positively charged atom will
stick to a negatively charged atom. A specific product will take shape as millions of these
atoms are pieced together by nanomachines.
The goal of nanotechnology is to manipulate atoms individually and place them
in a pattern to produce a desired structure of small size that spreads its wings in the
modern trends.
Reports indicate that Israeli scientists have built a DNA computer to tiny that a
trillion of them could fit in a test tube and perform a billion operations per second with
99.8 per cent accuracy. Researchers also found that a self assembled molecule could
sustain a current of about 0.2 microamperes at five volts - which meant that the molecule
could channel through itself roughly a million electron per second.
Molecular devices can be used as memory elements that forms the
basis for Nanotechnology.
Bio-Computing:
Nanocomputers, though have several applications, the one that stirs the
imagination is its identification of malfunctions in human beings by traveling inside the
human body. The molecular machines inside the living cell already posses the repertoire
of operations required to implement a universal computer. A design for a biological
nanocomputer shows that a Turing machine can be realized by a basic cycle consisting of
molecular recognition, two cleavages, two ligations and movement along a polymer, all
controlled by allostreic conformational changes. Each of these operations is routinely
performed by some molecular machine in the living cell, such as the ribosome,
splicesome and the replisome.
The computer’s input, and “software” are made up of DNA molecules. For
“hardware” the computer uses two naturally occurring enzymes that manipulate DNA,
Fokl, an enzyme that cuts DNA and Ligase and enzyme that seals two DNA molecules
into one. When mixed together in solution, the software and hardware molecules operate
in harmony on the input molecule to create the output molecule, forming a simple
mathematical computing machine, known as a finite automaton.
The automaton could be programmed to perform different tasks by selecting
different subsets of the molecules. Both input and software molecules are designed to
have one DNA strand longer than the other, resulting in a single strand overhand called a
“sticky end. “Two molecules with complementary sticky ends can temporarily stick to
each other (a process known as hybridization), allowing DNA Ligase to permanently seal
them into one molecule. The sticky end of the input molecule encodes the current symbol
and the current state of the computation, whereas the sticky end of each “software”
molecule is designed to detect a particular state-symbol combination. A two-state, twosymbol
automaton has four such combinations. For each combination, the nanocomputer
has two possible next moves, to remain in the same state or to change to the other state,
allowing eight software molecules to cover all possibilities.
In each processing step the input molecule hybridizes with a software molecule
that has a complementary sticky end, allowing Ligase to seal them together using two
ATP molecules as energy. Then comes Fok-I, detecting a special site in the software
molecule known as the recognition site. It cleaves the input molecule in a location
determined by the software molecule, thus exposing a sticky end that encodes the next
input symbol and the next state of the computation. Once the last input symbol is
processed, a sticky end encoding the final state of the computation is exposed and
detected, again by hybridization and ligation, by one of two “output display” molecules.
The resulting molecule, which reports the output of the computation, is made visible to
the human eye in a process known as gel electrophoresis.
The automation is so small that 1012 automata sharing the same software run
independently and in parallel on inputs (which could in principle be distinct) in 1201
solution at room temperature. Their combined rate is 109 transitions per second, their
transition fidelity is greater than 99.8% and together they consume less than 10-10
Watt.
Using DNA for Basic Logical and Arithmetic
Operations:
After the potential power of DNA computing has been described by Adleman and
Lipton, researchers have developed an interest in DNA computing for solving difficult
computational problems.
Guarnieri et al. and Vineet Gupta et.al have proposed DNA based methods to do
arithmetic and logical operations. But in their methods, the strands representing result
have to be polymerized for each and every instance of a specific operation, those strands
are not reusable. The limitation can be overcome by using sticker-based method to
perform arithmetic and logical operations. The advantage of the proposed method is
that output values are computed and stored parallely. The strands which represent the
output can be used repeatedly any number of times. The main idea of this method is
grouping the strands according to the output value are stored. The result tubes are the
tubes, which contain the result strands after completion of the annealing process with
stickers.
Biological operations and Notations:
Some of the biological operations used in this paper and their notations are
described below
Initializing
Stickers corresponding to input blocks and memory strands are poured into a tube
to represent all possible inputs. initialize (No)
Extracting
Particular Strands in a test tube are extracted based on whether the stickers stick
with specific region of memory strands or not
S (test tube label, Region, 1)
S (No, Io, 1) - extracts the strands from No with which sticker in the Io
th region.
S (No, In, 1) - extracts the strands from No with which sticker not stuck in the In
th region.
(Note : S’ (No, Io, 1) = S (No, Io, 0))
Setting
Multiple copies of a particular sticker are poured with memory strands to make a
specific region double stranded. Set (N1, Rn+1, 1) - add multiple copies of sticker
complementary to Rn+1
th region in N1.
Merging
The strands in two or more tubes are poured into a single tube. No = merge (N1,
N2) - pour the strands in N1 and N2 into N0.