A
widely acknowledged goal of nanotechnology is to build intricate,
useful nanoscale structures. What usually goes unstated
is how the
structures will be specified. Simple structures can be created
easily: a
crystal is an atomically precise structure that can be created
from
simple molecules and conditions. But complex nano-products
will require
some way to deliver large quantities of information to the
nanoscale.
A
key indicator of a technology's usefulness is how fast it
can deliver
information. A kilobyte is not very much information--less
than a page
of text or a thumbnail image. A dialup modem connection
can transfer
several kilobytes per second. Today's nanoscale manufacturing
techniques
can transfer at most a few kilobytes per second. This will
not be enough
to make advanced products--only simple materials or specialized
components.
The
amount of information needed to specify a product is not
directly
related to the size of the product. A product containing
repetitive
structures only needs enough information to specify one
of the
structures and control the placement of the rest. The amount
of
information that needs to be delivered also depends on whether
the
receiving machine must receive an individual instruction
for every
operation, or whether it can carry out a sequence of operations
based on
stored instructions. Thus, a primitive fabrication system
may require a
gigabyte of information to place a million atoms, while
a gigabyte may
be sufficient to specify a fairly simple kilogram-scale
product built
with an advanced nanofactory.
There
are several ways to deliver information to the nanoscale
so as to
construct things. Information can either be encoded materially,
in a
stable pattern of atoms or electrons, or it can be in an
ephemeral form
such as an electric field, a pattern of light, a beam of
charged
particles, the position of a scanning probe, or an environmental
condition like temperature. The goal of manufacturing is
to embody the
information, however it is delivered, into a material product.
As we
will see, different forms of delivery have different advantages
and
limitations.
Today's
Techniques
To
create a material pattern, it is tempting to start with
materially
encoded information. This is what self-assembly does. A
molecule can be
made so that it folds on itself or joins with others in
quite intricate
patterns. An example of this that is well understood, and
has already
been used to make nanoscale machines, is DNA. (See our previous
science
essay, “Nucleic Acid Engineering.”) Biology uses DNA mainly
to store
information, but in the lab it has been used to make polyhedra,
grid
structures, and even a programmable machine that can synthesize
DNA
strands.
http://crnano.org/essays04.htm#nucleic
One
problem with self-assembly is that all the information in
the final
structure must be encoded in the components. In order to
make a
complicated structure, a lot of information must be programmed
into the
component molecules. There are only a few ways to get information
into
molecules. One is to make the molecules a piece at a time.
In a long
linear chain like DNA, this can be done by repeating a few
operations
many times--specifically, by changing the chemical environment
in a way
that adds one selected block to the chain in each operation.
(This can
be viewed either as chemistry or as manufacturing.) Automated
machines
exist that will do this by cycling chemicals through a reactor,
but they
are relatively slow, and the process is expensive. The information
rate
can be greatly increased by controlling the process with
light; by
shining light in programmed sequence on different regions
of a surface,
DNA can be grown in many different patterns in parallel.
This can create
a large “library” of different DNA molecules with programmed
sequences.
Another
problem with self-assembly is that when the building blocks
are
mixed together, it is hard to impose long-range order and
to build
heterogeneous engineered structures. This limitation may
be partially
alleviated by providing a large-scale template, either a
material
structure or an ephemeral spatial pattern. Adding building
blocks in a
programmed sequence rather than mixing them all together
all at once
also may help. A combination of massively parallel programmable
molecule
synthesis and templated or sequenced self-assembly may be
able to
deliver kilobytes per second of information to the nanoscale.
A
theoretical possibility should be mentioned here. Information
can be
created by starting with a lot of random codes, throwing
away all the
ones that don't work, and duplicating the ones that do.
One problem with
this is that for all but the simplest criteria, it will
be too difficult
and time-consuming to implement tests for the desired functionality.
Another problem is that evolved solutions will require extra
work to
characterize, and unless characterized, they will be hard
to integrate
into engineered systems. Although evolution can produce
systems of great
subtlety and complexity, it is probably not suitable for
producing
easily characterized general-purpose functional modules.
Specific
molecular bio-designs such as molecular motors may be worth
characterizing and using, but this will not help with the
problem of
controlling the construction of large, heterogeneous, information-rich
products.
Optical
lithography of semiconductors now has the capability to
generate
nanoscale structures. This technique creates a pattern of
light using a
mask. The light causes chemical changes in a thin surface
layer; these
changes can then be used to pattern a substrate by controlling
the
deposition or removal of material. One drawback of this
approach is that
it is not atomically precise, since the pattern of light
is far too
coarse to resolve individual atoms. Another drawback is
that the masks
are pre-built in a slow and very expensive process. A computer
chip may
embody billions of bytes of information, but the masks may
take weeks to
make and use; again, this limits the data rate to kilobytes
per second.
There has been recent talk of using MEMS (micro electro
mechanical
systems) technology to build programmable masks; if this
works out, it
could greatly increase the data rate.
Several
tools can modify single points in serial fashion with atomic
or
near-atomic resolution. These include scanning probe microscopes
and
beams of charged particles. A scanning probe microscope
uses a large but
sensitive positioning and feedback system to bring a nanoscale
point
into controlled physical contact with the surface. Several
thousand
pixels can be imaged per second, so in theory an automated
system could
deliver kilobytes per second of changes to the surface.
An electron beam
or ion beam can be steered electronically, so it can be
relatively fast.
But the beam is not as precise as a scanning probe can be,
and must work
in vacuum. The beam can be used either to remove material,
to chemically
transform it, or to deposit any of several materials from
low-pressure
gas. It takes a fraction of a millisecond to make a shallow
feature at a
chosen point. Again, the information delivery rate is kilobytes
per second.
Nanoscale
Tools
To
deliver information at a higher rate and use the information
for more
precise construction, new technology will be required. In
most of the
techniques surveyed above, the nanoscale matter is inert
and is acted on
by outside forces (ephemeral information) created by large
machines. In
self-assembly, the construction material itself encodes
static patterns
of information--which probably were created by large machines
doing
chemistry. By contrast, nanoscale tools, converting ephemeral
information to concrete operations, could substantially
improve the
delivery rate of information for nanoscale construction.
Large tools
acting on inert nanoscale objects could never come close
to the data
rates that are theoretically possible with nanoscale tools.
One
reason why nanoscale tools are better is that they can move
faster.
To a first approximation, the operating frequency of a tool
increases in
direct proportion as its linear size shrinks. A 100-nm tool
should be
about a million times faster than a 10-cm tool.
The
next question is how the information will be delivered.
There are
several candidates for really fast information delivery.
Light can be
switched on and off very rapidly, but is difficult to focus
tightly.
Another problem is that absorption of light is probabilistic,
so a lot
of light would have to be used for reliable information
delivery.
Perhaps surprisingly, mechanical signals may be useful;
megahertz
vibrations and pressure waves can be sent over useful distances.
Electrical signals can be sent along nanoscale wires so
that multiple
independent signals could be delivered to each tool. In
principle, the
mechanical and electrical portions of the system could be
synchronized
for high efficiency.
Nanoscale
computing elements can help with information handling in
two
ways. First, they can split up a broadcast signal, allowing
several
machines receiving the same signal to operate independently.
This can
reduce the complexity of the macro-to-nano interface. Second,
nanoscale
computation can be used to implement some kinds of error
handling at a
local level.
A
final advantage of nanoscale tools, at least the subset
of tools built
from molecules, is that they can be very precise. Precision
is a serious
problem in micron-sized tools. A structure built by lithography
looks
like it has been whittled with a pocket knife--the edges
are quite
ragged. This has made it very difficult to build complex,
useful
mechanical devices at the micron scale using lithography.
Fortunately,
things get precise again at the very bottom, because atoms
are discrete
and identical. Small and simple molecular tools have been
built, and
work is ongoing to build larger and more integrated systems.
The
structural precision of molecular tools promises several
advantages,
including predictable properties and low-friction interfaces.
Several
approaches could be used, perhaps in combination, to build
a
nanoscale fabrication system. If a simple and repetitive
system can be
useful, then self-assembly might be used to build it. A
repetitive
system, once fabricated, might be made less repetitive (programmed
heterogeneously) by spatial patterns such as an array of
light. If it
contains certain kinds of electronics, then signals could
be sent in to
uniquely reconfigure the circuitry in each repeating sub-pattern.
Of
course, the point of the fabrication system is to build
stuff, and a
particularly interesting kind of system is one that can
build larger or
better fabrication systems. With information supplied from
outside, a
manufacturing system of this sort could build a larger and
more complex
version of itself. This approach is one of the goals of
molecular
manufacturing. It would allow the first tiny system to be
built by a
very expensive or non-scalable method, and then that tiny
system can
build larger ones, rapidly scaling upward and drastically
reducing cost.
Or if the initial system was built by self-assembly, then
subsequent
systems could be more complex than self-assembly could easily
achieve.
The
design of even a tabletop general-purpose manufacturing
system could
be relatively simple, heterogeneous but hierarchical and
repetitive.
Once the basic capabilities of nanoscale actuation, computation,
and
fabrication are achieved in a way that can be engineered
and recombined,
it may not take too long to start developing nanoscale tools
that can do
this in parallel, using computer-supplied blueprints to
build larger
manufacturing systems and a broad range of products.
