by
Ralph C. Merkle
Xerox PARC
3333 Coyote Hill Road
Palo Alto, CA 94304
merkle@xerox.com
This is an extended web version of the article
published in the Feb/Mar 1997 issue of MIT Technology Review. This
version has greater technical detail and embedded links.
SECTIONS:
Manufactured products are made from atoms. The properties of those
products depend on how those atoms are arranged. If we rearrange
the atoms in coal, we get diamonds. If we rearrange the atoms in
sand (and add a pinch of impurities) we get computer chips. If we
rearrange the atoms in dirt, water and air we get grass.
Since we first made stone tools and flint
knives we have been arranging atoms in great thundering
statistical heards by casting, milling, grinding, chipping and the
like. We've gotten better at it: we can make more things at lower
cost and greater precision than ever before. But at the molecular
scale we're still making great ungainly heaps and untidy piles of
atoms.
That's changing. In special cases we can
already arrange atoms and
molecules
exactly as we want. Theoretical
analyses make it clear we can do a lot more. Eventually, we
should be able to arrange and rearrange atoms and molecules much
as we might arrange LEGO blocks. In not too many decades we
should have a manufacturing technology able to:
- Build products with almost every atom in the right place.
- Do so inexpensively.
- Make most arrangements of atoms consistent with physical
law.
Often called
nanotechnology, molecular
nanotechnology or molecular manufacturing, it will
let us make most products lighter, stronger, smarter, cheaper,
cleaner and more precise.
One warning: in contrast to the useage in
this article some
researchers use the word "nanotechnology" to refer to high
resolution lithographic technology while others use it to refer to
almost any research where some critical size is less than a micron
(1,000 nanometers). When there is risk of confusion, the more
specific terms "molecular nanotechnology" or "molecular
manufacturing" should be used.
There are two main issues in
nanotechnology:
- What might molecular manufacturing systems look like?
- How could we build such systems given our current
technology?
As molecular manufacturing systems do not yet exist, and as it will
likely be a few decades before we can build them, the answer to the
first question must be based on theoretical and computational
models. Such models serve several purposes. First and most obvious,
some might argue that the goal is itself inherently impossible,
e.g., that such systems cannot be made within the framework of
existing physical law. Theoretical and computational models provide
an inexpensive way to examine this question and provide assurances
that proposed systems are possible.
Second, such models give us a feel for what
molecular manufacturing systems might look like. The better you
understand the goal, the better your chances of actually achieving
it. To illustrate this point, we consider a historical example
based on the single most important invention of the 20th century:
the computer. The basic idea of the relay was known in the 1820's,
and the
concept of a mechanical stored program computer was understood by
Babbage by the mid 1800's. Practical computers could have been
built using relays by the 1860's if there had been an adequate
theoretical understanding of "computation." An adequate theoretical
understanding of molecular manufacturing should likewise ease the
problems of practical development by opening for consideration
approaches and designs that might not otherwise be developed for
decades or -- as happened in the case of the computer -- almost a
century.
In this paper we'll first address the question
of what molecular manufacturing systems could look like, and
then consider how to build them given our current technology. This
second question involves not only a consideration of current
experimental triumphs and how they might be extended, but also the
definition of intermediate goals and systems.
If you'd like to see what's available on the
web about nanotechnology (and there's quite a lot), a good
starting place is http://www.zyvex.com/nano.
What would it mean if we could inexpensively make things with every
atom in the right place? For starters, we could continue the
revolution in computer hardware right down to molecular gates and
wires -- something that today's lithographic methods (used to make
computer chips) could never hope to do. We could inexpensively make
very strong and very light materials: shatterproof diamond in
precisely the shapes we want, by the ton, and over fifty times
lighter than steel of the same strength. We could make a Cadillac
that weighed fifty kilograms, or a full-sized sofa you could pick
up with one hand. We could make surgical instruments of such
precision and deftness that they could operate on the cells and
even molecules from which we are made -- something well beyond
today's medical technology. The list goes on -- almost any
manufactured product could be improved, often by orders of
magnitude.
One of the basic principles of nanotechnology is positional
control. At the macroscopic scale, the idea that we can hold parts
in our hands and assemble them by properly positioning them with
respect to each other goes back to prehistory: we celebrate
ourselves as the tool using species. Our wisdom and our knowledge
would have done us scant good without an opposable thumb: we'd
still be shivering in the bushes, unable to start a fire.
At the molecular scale, the idea of holding and
positioning molecules is new and almost shocking. However, as
long ago as 1959 Richard Feynman, the
Nobel prize winning physicist, said that nothing in the laws of
physics prevented us from arranging atoms the way we want: "...it
is something, in principle, that can be done; but in practice, it
has not been done because we are too big."
Before discussing the advantages of positional
control at the molecular scale, it's helpful to look at some of
the methods that have been developed by chemists -- methods that
don't use positional control, but still let chemists synthesize a
remarkably wide range of molecules and molecular structures.
The ability of chemists to synthesize what they want by stirring
things together is truly remarkable. Imagine building a radio by
putting all the parts in a bag, shaking, and pulling out the radio
-- fully assembled and ready to work! Self assembly -- the art and
science of arranging conditions so that the parts themselves
spontaneously assemble into the desired structure -- is a well
established and powerful method of synthesizing complex molecular
structures. A basic principle in self assembly is selective
stickiness: if two molecular parts have complementary shapes and
charge patterns -- one part has a hollow where the other part has a
bump, and one part has a positive charge where the other part has a
negative charge -- then they will tend to stick together in one
particular way. By shaking these parts around -- something which
thermal noise does for us quite naturally if the parts are floating
in solution -- the parts will eventually, purely by chance, be
brought together in just the right way and combine into a bigger
part. This bigger part can combine in the same way with other
parts, letting us gradually build a complex whole from molecular
pieces by stirring them together and shaking.
Many viruses use this approach to make more
viruses -- if you stir the parts of the T4 bacteriophage
together in a test tube, they will self assemble into fully
functional viruses.
While self assembly is a
path to nanotechnology, by itself
it would be hard pressed to make the very wide range of products
promised by nanotechnology. We don't know how to self assemble
shatterproof diamond, for example. (We'll later discuss a way of
making diamond using positional control). During self assembly the
parts bounce around and bump into each other in all kinds of ways,
and if they stick together when we don't
want them to stick
together, we'll get unwanted globs of random parts. Many types of
parts have this problem, so self assembly won't work for them. To
make diamond, it seems as though we need to use indiscriminately
sticky parts (such as radicals, carbenes and the like). These parts
can't be allowed to randomly bump into each other (or much of
anything else, for that matter) because they'd stick together when
we didn't want them to stick together and form messy blobs instead
of precise molecular machines.
We can avoid this problem if we can hold and
position the parts. Even though the molecular parts that are
used to make diamond are both indiscriminately and very
sticky (more technically, the barriers to bond formation are low
and the resulting covalent bonds are quite strong), if we can
position them we can prevent them from bumping into each other in
the wrong way. When two sticky parts do come into contact with each
other, they'll do so in the right orientation because we're
holding them in the right orientation. In short, positional
control at the molecular scale should let us make things which
would be difficult or impossible to make without it. Given our
macroscopic intuition, this shouldn't be surprising. If we couldn't
use our hands to hold and position parts, there are lots of things
we'd have a very hard time making!
If we are to position molecular parts we must
develop the molecular equivalent of "arms" and "hands." We'll
need to learn what it means to "pick up" such parts and "snap them
together." We'll have to understand the precise chemical reactions
that such a device would use.
One of the first questions we'll need to answer is: what does a
molecular-scale positional device look like? Current proposals are
similar to macroscopic robotic devices but on a much smaller scale.
The illustrations (from Nanosystems,
the best technical introduction to nanotechnology) show a
design for a molecular-scale robotic arm proposed by Eric Drexler, a
pioneering researcher in the field. Only 100 nanometers high and 30
nanometers in diameter, this rather squat design has a few million
atoms and roughly a hundred moving parts. It uses no lubricants,
for at this scale a lubricant molecule is more like a piece of
grit. Instead, the bearings are "run dry" (following a suggestion
by Feynman) as
described in the following paragraph.
Running bearings dry should work both because the diamond surface
is very slippery (see the coefficient of friction for diamond in
the table) and because we can make the surface very smooth -- so
smooth that there wouldn't even be molecular-sized asperities or
imperfections that might catch or grind against each other.
Computer models support our intuition: analysis of the
bearings shown here using computational chemistry programs
shows they should rotate easily.
Our molecular arms will be buffeted by something we don't worry
about at the macroscopic scale: thermal noise. This makes
molecular-scale objects wiggle and jiggle, just as Brownian motion
makes small dust particles bounce around at random.
Can our molecular robotic
arm maintain its position in the face of thermal noise?
The critical property we need here is
stiffness. Stiffness is a measure of how far something
moves when you push on it. If it moves a lot when you push on it a
little, it's not very stiff. If it doesn't budge when you push
hard, it's very stiff.
Big positional devices, used in today's
Scanning Probe Microscopes (SPMs), have been made stiff enough
to image individual atoms despite thermal noise. In SPMs, a very
sharp tip is brought down to the surface of the sample being
scanned. Like a blind man tapping in front of him with his cane, we
can tell that the tip is approaching the surface and so can "feel"
the outlines of the surface in front of us. Many different types of
physical interactions with the surface are used to detect its
presence. Some scanning probe microscopes literally push on the
surface -- and note how hard the surface pushes back. Others
connect the surface and probe to a voltage source, and measure the
current flow when the probe gets close to the surface. A host of
other probe-surface interactions can be measured, and are used to
make different types of SPMs. But in all of them, the basic idea is
the same: when the sharp tip of the probe approaches the surface a
signal is generated -- a signal which lets us map out the surface
being probed.
The SPM can not only map a surface, in many
cases the probe-surface interaction changes the surface as
well. This has already been used experimentally to spell out
molecular words, and the obvious opportunities to modify the
surface in a controlled way are being investigated both
experimentally and theoretically.
A few big SPMs making a few molecular
structures won't let us make much -- certainly not tons of
precisely structured shatterproof diamond. We'll need vast numbers
of very small positional devices operating in parallel.
Unfortunately, as we make our positional devices smaller and
smaller, they will be more and more subject to thermal noise. To
make something that's both small and stiff is more
challenging. It helps to get the stiffest material you can find.
Diamond, as usual, is stiffer than almost anything else and is an
excellent material from which to make a very small, very stiff
positional device. Theoretical analysis
gives firm support to the idea that positional devices in the 100
nanometer size range able to position their tips to within a small
fraction of an atomic diameter in the face of thermal noise at room
temperature should be feasible. Trillions of such devices would
occupy little more than a few cubic millimeters (a speck slightly
larger than a pinhead).
While Drexler's proposal for a small robotic
arm is easy to understand and should be adequate to the task,
more recent work has focused on the Stewart platform. This
positional device has the great advantage that it is stiffer than a robotic
arm of similar size. Conceptually, the Stewart platform is
based on the observation that a polyhedron, all of whose faces are
triangular, will be rigid. If some of the edges of the polyhedron
can be adjusted in length, then the position of one face can be
moved with respect to the position of another face. If we want a
full six degrees of freedom (X, Y, Z, roll, pitch and yaw) then we
must be able to independently adjust the lengths of six different
edges of the polyhedron. If we further want one triangular face of
the polyhedron to remain of fixed size and hold a "tool," and a
second face of the polyhedron to act as the "base" whose size and
position is fixed, then we find that the simplest polyhedron that
will suit our purpose is the octahedron.
In the Stewart platform, one triangular face of
the octahedron is designated the "platform," while the opposing
triangular face is designated the "base." The six edges that
connect the base to the platform can then be adjusted in length to
control the position of the platform with respect to the base.
Mechanically, this adjustment is often done using six hydraulic
pistons. A picture of the Stewart platform (from
Nanosystems) is shown above.
The advantage of the Stewart platform can now
be seen: because the six adjustable-length edges are either in pure
compression or pure tension and are never subjected to any
bending force, this positional device is stiffer than a long
robotic arm which can bend and flex. The Stewart platform is also
conceptually simpler than a robotic arm, having fewer different
types of parts; for this reason, we can reasonably expect that
making one will be simpler than making a robotic arm.
From airplanes and space ships to cars and chairs, making products
lighter and stronger is almost always an improvement. Sometimes, as
in the
case of space flight, this is a quantum leap all by itself. At
other times it's just a convenience: moving heavy furniture is a
chore most of us would avoid if we could.
The strength and lightness of materials depends on the number
and strength of the bonds that hold their atoms together, and the
lightness of those atoms. Light atoms that form many strong bonds
are at the heart of strong, light stiff materials. Boron, carbon
and nitrogen are lighter and form more and stronger bonds than
other atoms. The carbon-carbon bond in particular is very strong,
and carbon atoms can form four bonds to four neighboring atoms. In
diamond, this makes a very dense network of very strong bonds,
which creates a very strong, light and stiff material. Besides
light weight and great strength, diamond has a host of materials
properties that make it an excellent choice for almost any
application. (See the table for a list of diamond's material
properties).
Note: the following table is optimized for
Netscape 2.0
Diamond's Material Properties
Source: Crystallume
| Property |
Diamond's value |
Comments |
| Chemical reactivity |
Extremely low |
|
| Hardness (kg/mm2) |
9000 |
CBN: 4500 SiC: 4000 |
| Thermal conductivity (W/cm-K) |
20 |
Ag: 4.3 Cu: 4.0 |
| Tensile strength (pascals) |
3.5 x 109(natural) |
1011(theoretical) |
| Compressive strength (pascals) |
1011(natural) |
5 x 1011(theoretical) |
| Band gap (ev) |
5.5 |
Si: 1.1 GaAs: 1.4 |
| Resistivity (W-cm) |
1016 (natural) |
|
| Density (gm/cm3) |
3.51 |
|
| Thermal Expansion Coeff (K-1)< /td> |
0.8 x 10-6 |
SiO2: 0.5 x 10-6 |
| Refractive index |
2.41 @ 590 nm |
Glass: 1.4 - 1.8 |
| Coeff. of Friction |
0.05 (dry, varies) |
Teflon: 0.05 |
| Hole mobility(cm2/V-s) |
1600 |
Si: 600 |
| Electron mobility (cm2/V-s) |
1900 |
Si: 1500 |
| Breakdown voltage (V/cm) |
greater than 107 |
Si: 5 x 106 |
Another material with remarkable properties is graphite: carbon
atoms arranged in a hexagonal lattice with each carbon atom having
three bonds to its three neighbors. While graphite has fewer bonds
per atom, the strength of these bonds is greater and so graphitic
materials also have remarkable properties.
Diamond is also a wonderful material for making
transistors and computer gates, though it takes a bit of
explanation to understand why.
Computer gates should switch as quickly as
possible: that's what makes computers so fast. To do this, the
gates must be made of transistors in which the electrons move as
fast as possible over the shortest possible distances. But as
electrons move through a material, they generate heat: think of how
hot the tungsten wire in a light bulb can get! So the faster we
make our computer the faster the electrons move through the
material and the hotter it gets. When it gets too hot the computer
stops working.
Diamond excels in its electronic
properties. Fundamentally, it lets us move charge around much
faster before things stop working. There are several reasons for
this. First, diamond transistors can operate at much higher
temperatures because diamond has a larger "bandgap" than other
materials (particularly silicon). Electrons in semiconductors (such
as diamond or silicon) are either in the "conduction band" or the
"valence band." An electron in the conduction band can move freely
and transport charge. Moving an electron from the valence band to
the conduction band requires adding a specific amount of energy to
the electron. In silicon, this is 1.12 electron volts. In diamond,
it is 5.47 electron volts. As the temperature increases, more and
more electrons can jump into the conduction band from the valence
band because of thermal noise. When too many electrons do this the
semiconductor becomes conductive everywhere and the transistors
short out and stop working. Because diamond has a wider bandgap, it
shorts out at a proportionally higher temperature than silicon.
Diamond also has greater thermal
conductivity, which lets us move heat out of a diamond
transistor more quickly to prevent it from getting too hot.
To move an electron faster we want to "pull" on
it harder. The stronger the electric field, the harder we're
pulling the electrons. But as the electric field gets too strong,
it tears electrons out of the valence band causing the transistors
to short out. This "breakdown" field varies from material to
material, and (you guessed it) diamond leads the pack.
Finally, electrons (and holes) move with
different speeds through different materials, even when the
electric field is the same. Again, electrons and holes in diamond
move faster than in silicon.
Because diamond transistors can be hotter, are
more easily cooled, can tolerate higher voltages before
breaking down, and electrons move more easily in them; they make
better transistors than other materials. Diamond would be ideal for
electronic devices if only we could manufacture it inexpensively
and with precisely the desired structure.
In summary: from cars to airplanes to
spaceships, from furniture to buildings, from pocket
calculators to supercomputers, materials similar to diamond are
just better than other materials, often a lot better.
Just as the stone age, the bronze age and the steel age were named
after the materials that we could make, this new age we are
entering might be called the diamond age.
We can in principle make a great many very useful structures from
diamond, including very powerful computers and molecular robotic
devices able to position molecular components to within a fraction
of an atomic diameter. But how can we synthesize diamond? One
answer to this question comes from looking at how we grow diamond
today using
Chemical Vapor
Deposition (CVD). In a process somewhat reminiscent of
spray painting, we build up layer after layer of diamond on a
surface by holding that surface in a cloud of very reactive
molecules and atoms -- like H; CH
3, C
2H, etc.
When these reactive molecules bump into the surface they change it,
either by adding, removing, or re-arranging atoms. By carefully
controlling the pressure, temperature, and the exact composition of
the gas, we can create conditions that favor the growth of diamond
on the surface.
While these are the right chemical reactions to
make diamond, randomly bombarding the growing surface with
reactive molecules doesn't offer the finest control over the growth
process. It would be like trying to build a wristwatch using a
sandblaster. We want the chemical reactions to take place at
precisely the places on the surface that we specify -- not wherever
random gusts of turbulent gas might dictate.
A
second problem is that the hydrogenated diamond surface is
chemically inert: it's difficult to add carbon (or anything else)
to it. We could overcome this problem by removing a hydrogen atom
from the surface, leaving behind a very reactive dangling bond.
This is a critical first step during CVD diamond growth but it
happens at random, anywhere on the growing diamond surface, when
the right kind of reactive gas molecule happens to strike the
surface in the right way. We want to do something similar but more
controlled: remove a specific hydrogen atom from a
specific spot on the diamond surface. To do this, we'll need
a "hydrogen abstraction tool".
What might such a tool look like? If we base it
on our understanding of diamond CVD, it should be a highly
reactive radical with a high affinity for hydrogen. At the same
time it must be possible to position it, so it must have a stable
region which can serve as a "handle." The tool would be held by
(for example) the molecular robotic arm discussed earlier, and
would be positioned directly over the hydrogen we wish to
abstract.
A simple strategy for finding such radicals
is to look through the table of bond strengths in the Handbook
of Chemistry and Physics and pick the molecule with the
strongest bond to hydrogen. The radical created by removing the
hydrogen should then have a very high affinity for hydrogen, as
desired. Unfortunately, this strategy first produces fluorine.
While atomic fluorine does indeed have a very high affinity for
hydrogen, there is no obvious way to attach a "handle" to it.
Interest therefore turns to the molecule with the second strongest
bond to hydrogen: acetylene. Here, we are in luck. Not only does
the acetylene radical have a high affinity for hydrogen, it also
has a chemically stable region which can be modified into a
"handle" (see illustration above).
Drexler realized this sometime in the early
1980's. The author subsequently and independently followed the
same line of logic and reached the same conclusions. An initial
check of the validity of this idea was provided by semi-empirical
calculations at Xerox PARC (easily done on a workstation using
freely available programs). Discussions with Bill Goddard and members of his
molecular modeling group at Caltech resulted in more accurate
calculations using high level ab initio quantum chemistry
methods on a more powerful computer. (These methods have the
interesting property that the calculations will converge on the
correct answer if enough computing power is used). Drexler published
this observation in Nanosystems in 1992. A group at NRL
interested in diamond growth found the proposal intriguing and
modeled the abstraction of a hydrogen at room temperature using a
qualitatively different computational model of molecular behavior
(which permitted them to model the behavior of several hundreds of
atoms in the vicinty of the abstraction). As the results of three
different computational approaches have all produced the same
qualitative answer, and as the results are also in accord with our
intuition about what should happen, it's safe to say that
this hydrogen abstraction tool will, when finally implemented, be
able to abstract hydrogen.
The hydrogen abstraction tool illustrates
some important ideas common to other proposals for molecular
tools for the synthesis of diamond. First, the tool has a reactive
end which is brought into contact with the molecular workpiece and
an inert end which is held by a molecular positional device.
Second, the point of application of the tool is controlled by the
molecular positional device. Third, the environment around the tool
is itself inert (typical proposals involve the use of either vacuum
or a noble gas). The inert environment prevents the tool (which is
quite reactive) from reacting with anything undesired.
While the hydrogen abstraction tool creates a very reactive
spot on the surface we also need a tool that will deposit one
or more carbon atoms on the growing surface. One proposal is
the dimer deposition tool. (a "dimer" is just two of something
stuck together. In this case, two carbon atoms are stuck
together by a triple bond, hence the two carbon atoms form a
"dimer"). A dimer deposition tool is simply a dimer with two
weak bonds to a supporting structure. A proposal by Drexler is
shown to the left. A second proposed dimer deposition tool,
which has particularly weak bonds to the dimer, is illustrated
at the right. [Subsequent note: further investigation of the
proposal at right suggests it might not be stable except at
very low temperatures. A variety of alternative dimer
deposition tools are possible, so even if this particular
structure should prove unsastisfactory for room temperature
operation, other tools able to carry out the same function
should be feasible.]
To illustrate how we might combine the use of
the hydrogen abstraction tool with the dimer deposition tool,
we proceed in three steps. First, we start with the hydrogenated
diamond (111) surface. (The notation (111) refers to a particular
surface of the diamond crystal. When diamond shatters, it shatters
along certain planes and not along others. As these different
planes have surfaces with different properties, it's important to
specify which plane you're talking about). Second, we use the
hydrogen abstraction tool to remove two adjacent hydrogen atoms.
Third, we use the dimer deposition tool to deposit two carbon atoms
on the surface -- the two ends of the carbon dimer are originally
single-bonded to the rest of the tool. The two dangling bonds on
the surface are very reactive, and react with the ends of the
carbon dimer. When this happens, the bonds holding the dimer to the
dimer deposition tool break, and the bonds in the deposition tool
rearrange to eliminate what would otherwise be two radicals.
Result: the carbon dimer is transferred from the tool to the
surface. The following illustration shows the dimer deposition tool
adding a dimer to a small cluster which represents the diamond
(111) surface. (Because accurate ab initio calculations are
computationally less expensive for a small cluster of atoms, the
following illustrations show only the atoms directly involved in
the reaction).
This sequence of steps starts with a flat
diamond surface and adds two carbon atoms to it. It could be
repeated at other sites. A computational investigation of the final
step was reported by
Stephen Walch at the recent workshop on computational
nanotechnology sponsored by the NAS program at NASA. Because
the energy released during the reaction is much larger than thermal
noise (e.g., the reaction is quite exothermic), the reverse
reaction is very unlikely to occur. The barrier to the reaction is
also small. Taken together, these mean the reaction can take place
easily and irreversibly. The dimer will "snap" onto the surface and
stay there. (Calculations at the 6-31G* MP2 level show all positive
vibrational frequencies for this tool. Further investigation of its
stability is in progress).
A third proposed tool is the carbene insertion tool. "It is no
exaggeration to claim a major role for carbenes in the modern
chemists's attitude that he can very probably make anything he
wants." (W. J. Baron). A positionally controlled carbene should be
correspondingly more useful, as it could be made to react at any
position on a growing molecular workpiece. Carbenes are very
reactive and can insert readily into double and triple bonds. A
plausible reaction would be to insert a carbene into the dimer
described above. This is illustrated in the following figure. (Some
intermediates in the reaction pathway have been omitted for
clarity).
A fourth proposal is for a hydrogen deposition
tool. Where the hydrogen abstraction tool is intended to make
an inert structure reactive by creating a dangling bond, the
hydrogen deposition tool would do exactly the opposite: make a
reactive structure inert by terminating dangling bonds. This tool
could be used during the synthetic process to stabilize a structure
that might otherwise undergo a spontaneous and undesired
rearrangement or reconstruction, or it could be used at the end of
the synthetic process to stabilize the finished product.
There are many possible candidates for such a
tool: any molecular structure that has a weak bond to a
hydrogen. One particularly attractive candidate is the use of tin.
The hydrogen-tin bond is quite weak, and so a tin-based hydrogen
deposition tool should be quite effective.
These four tools let us (a) make an inert
surface reactive by removing a hydrogen from one or more
specific sites, (b) add one or two carbon atoms to a surface at
selected sites and (c) make a reactive surface inert by adding
hydrogen to it -- which lets us prevent undesired surface
rearrangements.
These four molecular tools -- by themselves -- should be sufficient
to make a remarkably wide range of stiff hydrocarbons. This
suggests that we define a simplified model of nanotechnology that
we might call "hydrocarbon-based nanotechnology." This simplified
version would only be able to make things from hydrogen and carbon
-- a much less ambitious goal than making things from the
approximately 100 elements found in the full periodic table. But in
exchange for confining ourselves to this more limited class of
structures, we make it much easier to analyze the structures that
can be fabricated and the synthetic reactions needed to make them.
This narrower proposal can be more readily and more thoroughly
investigated than full nanotechnology.
At the same time, hydrocarbon-based
nanotechnology retains several of the key features of general
nanotechnology. Diamond and shatterproof variants of diamond still
fall within its purview; and it can still make all the parts needed
for the operation of basically mechanical devices, including:
struts, bearings, gears, robotic arms, and the like.
It's often useful to define a somewhat broader
class than the stiff hydrocarbons, but a class which is still
much more restrictive than the class of "most structures consistent
with physical law." We'd like to be able to build molecular
structures that are similar to diamond but which incorporate some
other elements. We might want to add impurities (as in diamond
electronic devices) or terminate a bearing surface with fluorine.
Perhaps we're bending the diamond structure, and want to add some
silicon internally to relieve the strain, (the silicon-carbon bond
is longer than the carbon-carbon bond, so adding silicon to a
region will "puff it up"). Or we find that adding some nitrogen to
the internal surface of a bearing will relieve some strain (the
nitogen-carbon bond is slightly shorter than the carbon-carbon
bond). The term "diamondoid" is used to cover these (and related)
possiblities. Diamondoid materials are made primarily of the
elements hydrogen; first row elements like carbon, nitrogen, oxygen
or fluorine; and second row elements like silicon, phosphorous,
sulfur or chlorine; all held together by many strong covalent
bonds. While including only about a tenth of the elements in the
periodic table, the diamondoid materials include many structures of
striking utility.
Positional control combined with appropriate molecular tools should
let us build a truly staggering range of molecular structures --
but a few molecular devices built at great expense would hardly
seem to qualify as a revolution in manufacturing. How can we keep
the costs down?
Potatoes are a miracle of biology with tens of
thousands of genes and proteins and intricate molecular
machinery; yet we think nothing of eating this miracle, mashed with
a little butter. Potatoes, along with many other agricultural
products, cost less than a dollar a pound. The key reason: provide
them with a little dirt, water and sunlight and a potato can make
more potatoes.
If we could make a general purpose programmable
manufacturing device which was able to make copies of itself
(the author does work
at Xerox, after all....), then
the manufacturing costs for both the devices and anything they made
could be kept quite low -- likely no more than the costs for
growing potatoes.
Drexler called such devices
"assemblers."
The first serious analysis of self replicating systems was by
von
Neumann in the 1940's. He carried out a
detailed analysis of one such system in a theoretical cellular
automata model (The best known example of a cellular automata
model is
Conway's Game of Life, which is played out on a giant
checkerboard and uses a simple set of rules to decide what happens
at each square of the checkerboard at each time step). In von
Neumann's cellular automata model he used a universal computer for
control and a "universal constructor" to build more automata. The
"universal constructor" was a robotic arm that, under computer
control, could move in two dimensions and alter the state of the
cell at the tip of its arm. By sweeping systematically back and
forth, the arm could "build" any structure that the computer
instructed it to. In his three-dimensional "kinematic" model, von
Neumann retained the idea of a positional device (now able to
position in three dimensions rather than two) and a computer to
control it.
A NASA study in
1980 extended the general conclusions of von Neumann and
concluded that a fully automated lunar mining and manufacturing
operation, able to extend itself using its own mining and
manufacturing capabilities, would be feasible and could be built
given a multi-billion dollar budget and a few decades of work.
(Note that this kind of budget and time frame was in keeping with
other proposed aerospace projects of the time).
The architecture for Drexler's assembler is a specialization of the
more general architecture proposed by von Neumann. As before,
there is a computer and constructor, but now the computer has
shrunk to a "molecular computer" while the constructor combines two
features: a robotic positional device (such as the robotic arm
discussed earlier) and a well defined set of chemical operations
that take place at the tip of the positional device (such as the
hydrogen abstraction reaction and the other reactions involved in
the synthesis of diamond).
The complexity of a self replicating
system need not be excessive. In this context the complexity is
just the size, in bytes, of a "recipe" that fully describes how to
make the system. The complexity of an assembler needn't be beyond
the complexity that can be dealt with by today's engineering
capabilities. As shown in the following table, there are several
self replicating systems whose complexity is well within current
capabilities. Drexler estimated the complexity of his original
proposal for an assembler at about 10,000,000 bytes. Further work
should reduce this.
Complexity of self replicating
systems (bytes)
| Von
Neumann's universal constructor |
about 60,000 |
| Internet
worm |
60,000 |
|
Mycoplasma genitalia |
145,018 |
| E. Coli |
1,000,000 |
| Drexler's assembler |
12,000,000 |
| Human |
800,000,000 |
| NASA
Lunar Manufacturing Facility |
over 10,000,000,000 |
What is the "complexity" of a living system?
We'll take this to mean the number of bytes in the DNA
"blueprints." As each base pair in DNA can be one of four
possibilities, it encodes two bits. One byte (8 bits) can be
encoded in four base pairs. This means we count the number of base
pairs in the DNA and divide by four to get the number of bytes in
the "blueprints." For Mycoplasma genitalia, which has 580,070 base
pairs, this results in 145,017.5 bytes. For humans, with roughly
3.2 billion base pairs, this results in 800 million bytes. (We're
using the haploid base pair count: each cell in your body has DNA
from your mother and DNA from your father -- but much of this is
similar. We're counting only the DNA from one parent). The
complexity and sophistication of most living systems goes well
beyond anything we might need just to achieve low cost
manufacturing. Much of the complexity of the human genome is
unrelated to issues of self-replication: people do more than just
self-replicate!
The complexity of the internet worm is just an
estimate of the number of bytes in its C program. Because the
environment in which it operates is highly structured and provides
relatively easy access to complex and sophisticated software, it
could be argued that its complexity might be much less than the
complexity of a system that operated in a "simple" environment.
We'll leave it in our table anyway, as it's an interesting data
point. This argument is less applicable to von Neumann's universal
constructor which operates in a simple environment: just a large
two-dimensional checkerboard with a finite number of states at each
square. Its complexity is an estimate of the number of bytes needed
to describe the constructor. The complexity of the NASA Lunar
Manufacturing Facility was estimated in the NASA study.
Today, most airplanes are made from metal despite the fact that
diamond has a strength-to-weight ratio over 50 times that of
aerospace aluminum. Diamond is expensive, we can't make it in the
shapes we want, and it shatters. Nanotechnology will let us
inexpensively make shatterproof diamond (with a structure that
might resemble diamond fibers) in exactly the shapes we want. This
would let us make a Boeing 747 whose unloaded weight was 50 times
lighter but just as strong.
Today, travel in space is very expensive
and reserved for an elite few. Nanotechnology
will dramatically reduce the costs and increase the capabilities of
space ships and space flight. The strength-to-weight ratio and
the cost of components are absolutely critical to the performance
and economy of space ships: with nanotechnology, both of these
parameters will be improved by one to two orders of magnitude.
Improvements in these two parameters alone (ignoring other
advantages provided by nanotechnology) should improve the overall
cost/performance ratio by over three orders of magnitude. This has
led the National Space Society
(NSS) to adopt a position
paper supporting nanotechnology; Dan Goldin, NASA's chief administrator, to support
nanotechnology; and NAS at NASA
Ames Research Center to start a project (now with perhaps half a
dozen researchers) to examine molecular manufacturing systems and
molecular machines using computational models.
Beyond inexpensively providing remarkably light
and strong materials for space ships, nanotechnology will also
provide extremely powerful computers with which to guide both those
ships and a wide range of other activities in space.
Today, computer chips are made using
lithography -- literally "stone writing." It's our finest
manufacturing technology, but there seem to be fundamental limits
in how much further we can improve it. In lithography, we draw fine
lines on a silicon wafer by using methods borrowed from
photography. A light-sensitive film -- called a "resist" -- is
spread over the silicon wafer. The resist is exposed to a complex
pattern of light and dark, like a negative in a camera, and
developed. The exposed resist is then washed away, and a particular
chemical is sprayed over the surface. Where the resist has been
washed away, the chemical reaches the surface of the silicon and
can diffuse a short distance into it. Where the resist has not been
washed away, the spray is blocked. Finally, the remaining resist is
washed away, along with any chemicals that it prevented from
reaching the silicon surface. The result: a fine pattern of some
desired chemical is laid out on the silicon surface. By repeating
this process, an intricate set of interlocking patterns can be made
that defines the complex logic elements of a modern computer
chip.
If the computer hardware revolution is to
continue at its current pace, in a decade or so we'll have to move
beyond lithography to some new post lithographic manufacturing
technology. Making patterns on a resist and spraying chemicals
around simply can't arrange atoms with the ultimate precision that
should be feasible. More precise methods will be needed.
Ultimately, each logic element will be made from just a few atoms.
Designs for computer gates with less than 1,000 atoms have already
been proposed -- but each atom in such a small device has to be in
exactly the right place. To economically build and interconnect
trillions upon trillions of such small and precise devices in a
complex three dimensional pattern we'll need a manufacturing
technology well beyond today's lithography: we'll need
nanotechnology. With it, we should be able to build mass storage
devices that can store more than a hundred billion billion bytes in
a volume the size of a sugar cube; RAM that can store a mere
billion billion bytes in such a volume; and massively parallel
computers of the same size that can deliver a billion billion
instructions per second.
Today, "smart" weapons are fairly big -- we
have the "smart bomb" but not the "smart bullet." In the
future, even weapons as small as a single bullet could pack more
computer power than the largest supercomputer in existence today,
allowing them to perform realtime image analysis of their
surroundings and communicate with weapons tracking systems to
acquire and navigate to targets with greater precision and control.
We'll also be able to build weapons both inexpensively and much more
rapidly, at the same time taking full advantage of the
remarkable materials properties of diamond. Rapid and inexpensive
manufacture of great quantities of stronger more precise weapons
guided by massively increased computational power will alter the
way we fight wars. Changes of this magnitude could destabilize
existing power structures in unpredictable ways.
Military applications of nanotechnology raise a
number of concerns that prudence suggests we begin to
investigate before, rather than after, we develop this new
technology. While molecular manufacturing will not arrive for many
years, its obvious military potential will increasingly attract the
interest of strategic planners. For example, in a talk titled
Nanotechnology
and global security at the Fourth Foresight
Conference on Molecular Nanotechnology, Admiral David
E. Jeremiah, USN (Ret), former Vice Chairman of the Joint
Chiefs of Staff, said "Military applications of molecular
manufacturing have even greater potential than nuclear weapons to
radically change the balance of power." As it seems implausible
that military applications of this technology will never be
developed and deployed, it would seem safer to encourage the
relatively early interest of those organizations less prone to the
abuse of power and more likely to curb its abuse by others.
To make power today we dig coal and oil from
the ground, we dam rivers, and we burn nuclear fuel in nuclear
power plants. Yet the sunshine all around us could provide orders
of magnitude more power than we use -- and do so more cleanly and
less expensively -- if only we could make low cost solar cells and
batteries. We already know how to make solar cells that are
efficient enough for this application: it just costs too much to
make them. Nanotechnology will cut costs both of the solar cells
and the equipment needed to deploy them, making solar power
economical. In this application we need not make new or technically
superior solar cells: making inexpensively what we already know how
to make expensively would move solar power into the mainstream.
Today, our surgical tools are large and
crude at the molecular scale -- yet the cellular and molecular
machinery in our tissue is small and precise. There is a
fundamental mismatch between the capabilities of our tools and
what's needed to cure the injuries in our tissue. Today's scalpels
are, as seen by a cell, large crude scythes that are more suited to
cut and tear than to heal and mend. Ripping through tissue, they
leave dead and maimed cells in their wake. The only reason that
modern surgery works is the remarkable ability of cells to regroup,
bury their dead, and heal over the wound.
It is not modern medicine that does the
healing, but the cells themselves: we are but onlookers. If we
had surgical tools that were molecular both in their size and
precision, we could develop a medical technology that for the first
time would let us directly heal the injuries at the molecular and
cellular level that are the root causes of disease and ill health.
With the precision of drugs combined with the intelligent guidance
of the surgeon's scalpel, we can
expect a quantum leap in our medical capabilities.
Nanotechnology should let us make almost every
manufactured product faster, lighter, stronger, smarter, safer
and cleaner. We can already see many of the possibilities as these
few examples illustrate. New products that solve new problems in
new ways are more difficult to foresee, yet their impact is likely
to be even greater. Could Edison have foreseen the computer, or
Newton the communications satellite?
We can now see the fundamental shape of a molecular manufacturing
technology. Self replicating assemblers, operating under computer
control, let us inexpensively build more assemblers. The assemblers
can be reprogrammed to build other products. The assemblers use
programmable positional control to position molecular tools and
molecular components, permitting the inexpensive fabrication of
most structures consistent with physical law. Diamondoid materials
in particular become inexpensive and commonplace, and their
remarkable properties usher in what has been called the Diamond
Age.
In the preceding discussion of nanotechnology we gave scant
attention to possible developmental pathways that would let us
migrate from our current technology to what we might call "mature"
systems able to inexpensively manufacture most diamondoid
structures. The proposals advanced so far have been driven largely
by the desired goal: a system able to inexpensively synthesize most
diamondoid structures. The proposal that emerged was a general
purpose programmable manufacturing system which uses positionally
controlled highly reactive tools in vacuum and is able to self
replicate.
No constraint was imposed requiring that the
proposed system be easy to fabricate given our current technology
-- and indeed, this problem appears non trivial. But we must
eventually build such systems if they are to be of any use -- how
can we do this? To give the reader some feeling for the magnitude
of the effort involved, we can compare the requirements for a
mature system with present capabilities.
A mature system must be able to build an
assembler with hundreds of millions or billions of atoms with no
atom out of place. If we are to do this, and if each unit operation
typically handles one or a few atoms (a hydrogen abstraction, a
carbene insertion, etc), then either the error rate per unit
operation must be low (less than one in a billion) or we must adopt
error detection and correction methods.
A general rule of thumb is that making
something right the first time is easier than making it wrong and
fixing it. Given the choice between a manufacturing process that
has a low enough error rate that most finished products will simply
work correctly the first time versus a process which requires
elaborate error detection and correction to make any working
products at all, the former is greatly to be preferred. Because
analysis of the fundamental causes of errors during the manufacture
of diamondoid products in general and assemblers in particular
supports the idea that error rates substantially lower than one in
a billion should be achievable, and hence that an assembler can
make another assembler with a high probability of success while
using no error detection or correction, existing design proposals
adopt the simpler and higher performance approach. Had the opposite
conclusion been reached, i.e., that error rates could not be
driven below one in one billion, then design proposals would have
adopted a smaller module size (consistent with the error rate) and
incorporated appropriate mechanisms for module testing, the
rejection of bad modules, and the assembly of working modules into
larger systems.
This line of logic results in proposals for
assemblers in which error rates are very low. These low error
rates, however, are predicated on the prior existence of diamondoid
assemblers. Unfortunately, we do not have assemblers today. Worse,
current technology would be hard pressed to achieve such error
rates. Chemists view a synthesis that provides 99% yield as
very good. The synthesis of proteins from amino acids by ribosomes
has an error rate of perhaps one in 10,000. Replication of DNA, by
using extensive error detection and correction, along with built in
redundancy (DNA has two complementary strands), achieves an error
rate of roughly one base in a billion (which varies depending on
particular circumstances).
The size of structure that can be built by
today's SPMs without error is smaller than has been achieved by
chemists. The first such work arranged 35
xenon atoms on a nickel surface at 4 kelvins in vacuum to spell out
"IBM." Later work in Japan spelled out "NANO SPACE" at room
temperature in vacuum by removing individual sulfur atoms from the
surface. More recently, 6 molecules were
arranged in a hexagonal pattern at room temperature in vacuum.
As each molecule had 173 atoms, this modular approach was able to
position over 1,000 atoms. While these are great successes we have
not yet seen a long sentence spelled out in this fashion, let alone
a paragraph or a book. Further, SPMs can "see" the structure that's
being built. Current successes use this ability to provide constant
feedback to the human operator, who can detect and correct
errors.
In short, today's SPMs can build structures
that are only a small fraction of the size of proposed assemblers
and have error rates high enough that they must use relatively
sophisticated error detection and correction methods.
The situation is made more difficult by the
additional requirement that unit operations be fast. If an
assembler is to manufacture a copy of itself in about a day, and if
this takes one hundred million to a billion operations, then each
unit operation must take place in a fraction of a millisecond.
Ribosomes take tens of milliseconds to add a single amino acid to a
growing protein. Today's SPMs can take hours to arrange a few atoms
or molecules.
At the same time, the use of vacuum prevents us
from using self assembly or any of the other solution-based
techniques developed by chemistry. Abandoning these powerful tools
does not seem like a good first step.
While speed, reliability and operation in
vacuum do not pose fundamental problems, the conclusion is obvious:
directly building a diamondoid assembler using existing technology
is a daunting task. Perhaps, rather than attempting to solve
all the problems in a single giant leap, we should instead approach
them in a more incremental fashion. To this end, we need to define
one or more intermediate systems. Almost by definition, an
intermediate system is easier to build from current technology, but
is still able to make systems that are more powerful than itself. A
series of intermediate systems, each able to build the next system
in the chain, would let us adopt more incremental methods.
One approach is to eliminate the requirement
that the assembler be made from diamondoid structures. We
wanted to make diamondoid structures because of their remarkable
strength, stiffness, electrical properties, etc. But an
intermediate system need only be able to make a more advanced
system, and perhaps products that are impressive in comparison with
today's products. It doesn't have to be diamondoid itself.
This suggests what might be called
"building block based nanotechnology." Rather than building
diamond, we'll build some other material from molecular building
blocks that are relatively large: tens, hundreds or even thousands
of atoms in size. Larger building blocks reduce the number of
assembly steps, so fewer unit operations are needed and they need
not be as reliable. Soluble building blocks, with "linkage" groups
that are selective (the building blocks only stick to other
building blocks, not to the solvent or low concentrations of
contaminants) eliminate the need for vacuum. We certainly have many
choices: any of the wide range of molecules that chemists have
synthesized or could reasonably synthesize which has the desired
properties. Krummenacker
concluded that each molecular building block should have at least
three sites where it can link to other building blocks (two sites
leads to the familiar polymers so ubiquitous in biological systems:
proteins, DNA, RNA, etc. Addition of a third site makes the design
of three dimensional stiff structures much easier). While such
building blocks could be linked to each other using any one of a
variety of reactions, a particularly attractive possibility is the
Diels-Alder reaction. This reaction, well known to chemists, works
in most solvents (or even in vacuum). It involves a reaction
between a diene and a dieneophile. The reaction is specific: the
diene and the dieneophile react with each other but seldom with
other groups (see illustration above, courtesy of Krummenacker).
Because it works in vacuum and doesn't produce any small molecules
(which would destroy the vacuum), it could be used both in
intermediate systems in solution, and later in systems that use
vacuum to make diamondoid materials. 
Solution based systems could use positional
control to assemble the building blocks, but can also use the
methods of self assembly. In particular, the self assembly of a
positional device should be feasible. If you ask someone familiar
with the field if it would be feasible to self assemble a robotic
arm, the usual response is some variation of "no." If, instead, you
ask whether it would be feasible to self assemble an octahedron,
the usual response is to point out that Nadrian Seeman
of New York University has already self assembled a truncated octahedron
from DNA and plans to do the same for a regular octahedron
(both for reasons unrelated to positional control). (The computer
generated graphic of the truncated octahedron at right is courtesy
of Nadrian Seeman). For this work he received The 1995 Feynman
Prize in nanotechnology.
As we have seen, an octahedron is the basic
structure required for the Stewart platform. The truncated
octahedron, because it has sides that aren't triangular, is
floppier than a regular octahedron. Even the regular octahedron is
likely to be too floppy for this application because of the limited
stiffness of DNA. Further, the length of the edges cannot be
changed (a requirement if we wish to control the position of the
platform with respect to the base). However, self assembling a
Stewart platform able to assemble molecular building blocks seems
much less difficult than directly building a diamondoid assembler
able to synthesize diamond in vacuum. Several ways to deal with the
problem of inadequate stiffness and adjustable length edges are
possible. One way would be to attach selectively sticky strands of
DNA to a stiff molecular structure. This would let us use DNA
(which has been intensively studied and whose selective stickiness
is well known) to guide the process of self assembly, while the
stiff molecular structure would would let us deal with concerns
about inadequate stiffness. To change the length of an edge, we
would need to use molecular structures that change shape in
response to light, pressure, temperature, chemicals, or some other
external signal. Many such molecular structures are known. Self
assembling a Stewart platform whose edges are stiff enough to make
a useful positional device, and the length of whose edges can be
changed by a suitable signaling mechanism, is no longer a challenge
that seems beyond our reach.
A second approach for positioning molecular
building blocks in solution is to use an Atomic Force
Microscope (AFM). This type of SPM relies on "touch" to create an
image. By pushing on the structure being scanned, and feeling how
hard it pushes back, the AFM can build up an image of stiff
structures (it doesn't work very well when the applied force is
strong enough to deform the structure). Because the AFM touches the
surface of the structure being probed, it can also change that
surface. To do this, it's very useful if the precise molecular
structure of the tip can be controlled, so that the precise nature
of the tip-surface interaction can be well defined.
This line of reasoning leads to the
"molecular manipulator:" an AFM with a reactive fragment of an
antibody bound to its tip. By changing the
antibody, we can change what type of molecule will stick to the
AFM tip. If the antibody both sticks selectively to a particular
molecular building block, and also is bound to the AFM tip, we can
now position the molecular building block by positioning the AFM
tip. We can use any one of a wide range of possible molecular
building blocks (
antibodies can today be created that will bind to most small
molecules). Again, this no longer seems beyond our reach.
Another developmental pathway is defined by
the desire of the semiconductor industry to make ever smaller
transistors despite the fact that optical lithography -- the
current workhorse manufacturing method for making computer chips --
will reach a limit in a few more years. Transistors are made today
by "drawing" very fine lines on silicon -- but the optical methods
in use today are limited by the wavelength of light: a few hundred
nanometers. SPMs could let us make much smaller circuits by drawing
much finer lines. Already demonstrated for making the finest and
most critical lines in a transistor, if this approach can be made
low cost and reliable it would let the entire semiconductor
industry be retooled to use these finer lines to make more and
smaller transistors. This, by itself, is not molecular
nanotechnology; but once we learn to draw the smallest and finest
lines of all, lines where every atom is in the right place (and
there will be strong economic incentives to move in this
direction), we could use the same techniques to make molecular
machines. At first, these molecular machines would be very
expensive and useful only for applications where their remarkable
precision would justify the cost -- but they should eventually lead
to machines sophisticated enough to make simple assemblers.
Whether through self-assembly, by
improvements in SPMs, some hybrid approach, or perhaps by some
other path; we are moving from an era of expensive and imprecise
products to an era of inexpensive products of molecular precision.
We are going to replace most of the manufacturing base of the world
with a fundamentally new and much better manufacturing
technology.
Arguments that nanotechnology is infeasible are relatively rare and
uniformly poor in technical quality. The best known are the
arguments of David Jones, a
Nature columnist and chemist.
Quoted extensively in a
Scientific American article on
nanotechnology (see
http://www.foresight.org/SciAmDebate/SciAmOverview.html
for commentary) he advanced arguments like the following: "Single
atoms ... are amazingly mobile and reactive. They will combine
instantly with ambient air, water, each other, the fluid supporting
the assemblers, or the assemblers themselves." However, as the
proposals involving reactive molecular tools specify that the
environment should be inert (i.e., vacuum) there is no "ambient
air" to react with. As the molecular tools are positionally
controlled, they will not react with each other or the assembler
itself for the same reason that a hot soldering iron does not react
with the skin of the person doing the soldering. Jones' criticisms
raise greater questions about his understanding of the field than
about the feasibility of nanotechnology. Other arguments against
the feasibility of nanotechnology have likewise had obvious flaws,
reminiscent of the 1920 New York Times editorial which said that
rockets to the moon were impossible because there was no air to
push against in space.
As should be clear from this article there are
major technical challenges that must be overcome if we are to
develop molecular manufacturing systems able to synthesize
diamondoid structures. The serious questions, however, are about
which development pathways should be pursued and how long it will
take.
The single most frequently asked question about nanotechnology is:
how
long?. How long before it will let us make molecular
computers? How long before inexpensive solar cells let us use clean
solar power instead of oil, coal, and nuclear fuel? How long before
we can explore space at a reasonable cost?
The scientifically correct answer is: I
don't know.
Having said that, it is worth pointing out that
the trends in the development of computer hardware have been
remarkably steady for the last 50 years. Such parameters as
- the number of atoms required to store one bit
- the size of a transistor
- the energy dissipated by a single logic operation
- the resolution of the finest machining technology
- the cost of a computer gate
have all declined with great regularity, even as the underlying
technology has changed dramatically.
From
relays to vacuum tubes to transistors to integrated circuits to
Very Large Scale Integrated circuits (VLSI) we have seen steady
declines in the size and cost of logic elements and steady
increases in their performance.
Extrapolation of these trends suggests we will
have to develop molecular manufacturing in the 2010 to 2020
time frame if we are to keep the computer hardware revolution on
schedule.
Of course, extrapolating past trends is a
philosophically debatable method of technology forecasting. While
no fundamental law of nature prevents us from developing
nanotechnology on this schedule (or even faster), there is equally
no law that says this schedule will not slip.
Much worse, though, is that such trends imply
that there is some ordained schedule -- that nanotechnology
will appear regardless of what we do or don't do. Nothing could be
further from the truth. How long it takes to develop this
technology depends very much on what we do. If we pursue it
systematically, it will happen sooner. If we ignore it, or simply
hope that someone will stumble over it, it will take much longer.
And by using theoretical, computational and experimental approaches
together, we can reach the goal more quickly and reliably than by
using any single approach alone.
While some advances are made through
serendipitous accidents or a flash of insight, others require
more work. It seems unlikely that a scientist would forget to turn
off the bunsen burner in his lab one afternoon and return to find
he'd accidentally made a Space Shuttle.
Like the first human landing on the moon,
the Manhatten project or the development of the modern computer the
development of molecular manufacturing will require the coordinated
efforts of many people for many years. How long will it take? A lot
depends on when we start.