by Michio Kaku
One promising candidate for the molecular transistor comes from a substance called graphene, which was first isolated from graphite in 2004 by Andre Geim and Kostya Novoselov of the University of Manchester, who won a Nobel Prize for their work. It is like a single layer of graphite. Unlike carbon nanotubes, which are sheets of carbon atoms rolled up into long, narrow tubes, graphene is a single sheet of carbon, no more than one atom thick. Like carbon nanotubes, graphene represents a new state of matter, so scientists are teasing apart its remarkable properties, including conducting electricity. “From the point of view of physics, graphene is a goldmine. You can study it for ages,” remarks Novoselov. (Graphene is also the strongest material ever tested in science. If you placed an elephant on a pencil, and balanced the pencil on a sheet of graphene, the graphene would not tear.)
Novoselov’s group has employed standard techniques used in the computer industry to carve out some of the smallest transistors ever made. Narrow beams of electrons can carve out channels in graphene, making the world’s smallest transistor: one atom thick and ten atoms across. (At present, the smallest molecular transistors are about 30 nanometers in size. Novoselov’s smallest transistors are thirty times smaller than that.)
These transistors of graphene are so small, in fact, they may represent the ultimate limit for molecular transistors. Any smaller, and the uncertainty principle takes over and electrons leak out of the transistor, destroying its properties. “It’s about the smallest you can get,” says Novoselov.
Although there are several promising candidates for molecular transistors, the real problem is more mundane: how to wire them up and assemble them into a commercially viable product. Creating a single molecular transistor is not enough. Molecular transistors are notoriously hard to manipulate, since they can be thousands of times thinner than a human hair. It is a nightmare thinking of ways to mass-produce them. At present, the technology is not yet in place.
For example, graphene is such a new material that scientists do not know how to produce large quantities of it. Scientists can produce only about .1 millimeter of pure graphene, much too small for commercial use. One hope is that a process can be found that self-assembles the molecular transistor. In nature, we sometimes find arrays of molecules that condense into a precise pattern, as if by magic. So far, no one has been able to reliably re-create this magic.
QUANTUM COMPUTERS
The most ambitious proposal is to use quantum computers, which actually compute on individual atoms themselves. Some claim that quantum computers are the ultimate computer, since the atom is the smallest unit that one can calculate on.
An atom is like a spinning top. Normally, you can store digital information on spinning tops by assigning the number “0” if the top is spinning upward, or “1” if the top is spinning down. If you flip over a spinning top, then you have converted a 0 into a 1 and have done a calculation.
But in the bizarre world of the quantum, an atom is in some sense spinning up and down simultaneously. (In the quantum world, being several places at the same time is commonplace.) An atom can therefore contain much more information than a 0 or a 1. It can describe a mixture of 0 and 1. So quantum computers use “qubits” rather than bits. For example, it can be 25 percent spinning up and 75 percent spinning down. In this way, a spinning atom can store vastly more information than a single bit.
Quantum computers are so powerful that the CIA has looked into their code-breaking potentials. When the CIA tries to break the code of another nation, it searches for the key. Nations have devised ingenious ways of constructing the key that encodes their messages. For example, the key may be based on factorizing a large number. It’s easy to factorize the number 21 as the product of 3 and 7. Now let’s say that you have an integer of 100 digits, and you ask a digital computer to rewrite it as the product of two other integers. It might take a digital computer a century to be able to factorize this number. A quantum computer, however, is so powerful that in principle it can effortlessly crack any such code. A quantum computer quickly outperforms a standard computer on these huge tasks.
Quantum computers are not science fiction but actually exist today. In fact, I had a chance to see a quantum computer for myself when I visited the MIT laboratory of Seth Lloyd, one of the pioneers in the field. His laboratory is full of computers, vacuum pumps, and sensors, but the heart of his experiment is a machine that resembles a standard MRI machine, except much smaller. Like the MRI machine, his device has two large coils of wire that create a uniform magnetic field in the space between them. In this uniform magnetic field, he places his sample material. The atoms inside the sample align, like spinning tops. If the atom points up, it corresponds to a 0. If it points down, it corresponds to a 1. Then he sends an electromagnetic pulse into the sample, which changes the alignment of the atoms. Some of the atoms flip over, so a 1 becomes a 0. In this way, the machine has performed a calculation.
So why don’t we have quantum computers sitting on our desks, solving the mysteries of the universe? Lloyd admitted to me the real problem that has stymied research in quantum computers is the disturbances from the outside world that destroy the delicate properties of these atoms.
When atoms are “coherent” and vibrating in phase with one another, the tiniest disturbances from the outside world can ruin this delicate balance and make the atoms “decohere,” so they no longer vibrate in unison. Even the passing of a cosmic ray or the rumble of a truck outside the lab can destroy the delicate spinning alignment of these atoms and destroy the computation.
The decoherence problem is the single most difficult barrier to creating quantum computers. Anyone who can solve the problem of decoherence will not only win a Nobel Prize but also become the richest man on earth.
As you can imagine, creating quantum computers out of individual coherent atoms is an arduous process, because these atoms quickly decohere and fall out of phase. So far, the world’s most complex calculation done on a quantum computer is 3 × 5 = 15. Although this might not seem much, remember that this calculation was done on individual atoms.
In addition, there is another bizarre complication coming from the quantum theory, again based on the uncertainty principle. All calculations done on a quantum computer are uncertain, so you have to repeat the experiment many times. So 2 + 2 = 4, at least sometimes. If you repeat the calculation of 2 + 2 a number of times, the final answer averages out to 4. So even arithmetic becomes fuzzy on a quantum computer.
No one knows when one might solve this problem of decoherence. Vint Cerf, one of the original creators of the Internet, predicts, “By 2050, we will surely have found ways to achieve room-temperature quantum computation.”
We should also point out that the stakes are so high that a variety of computer designs have been explored by scientists. Some of these competing designs include:
• optical computers: These computers calculate on light beams rather than electrons. Since light beams can pass through each other, optical computers have the advantage that they can be cubical, without wires. Also, lasers can be fabricated using the same lithographic techniques as ordinary transistors, so you can in theory pack millions of lasers onto a chip.
• quantum dot computers: Semiconductors used in chips can be etched into tiny dots so small they consist of a collection of perhaps 100 atoms. At that point, these atoms can begin to vibrate in unison. In 2009, the world’s smallest quantum dot was built out of a single electron. These quantum dots have already proven their worth with light-emitting diodes and computer displays. In the future, if these quantum dots are arranged properly, they might even create a quantum computer.
• DNA computers: In 1994, the first computer made of DNA molecules was created at the University of Southern California. Since a strand of DNA encodes information on amino acids represented by the letters A,T,C,G instead of 0s and 1s, DNA can be viewed as ordinary computer tape, except it can store more information. In the same way that a large digital number can be manipulated and r
earranged by a computer, one can also perform analogous manipulations by mixing tubes of fluids containing DNA, which can be cut and spliced in various ways. Although the process is slow, there are so many trillions of DNA molecules acting simultaneously that a DNA computer can solve certain calculations more conveniently than a digital computer. Although a digital computer is quite convenient and can be placed inside your cell phone, DNA computers are more awkward, involving mixing tubes of liquid containing DNA.
SHAPE-SHIFTING
In the movie Terminator 2: Judgment Day, Arnold Schwarzenegger is attacked by an advanced robot from the future, a T-1000, which is made of liquid metal. Resembling a quivering mass of mercury, it can change shape and slither its way through any obstacle. It can seep through the tiniest cracks and fashion deadly weapons by reshaping its hands and feet. And then it can suddenly re-form into its original shape to carry on its murderous rampage. The T-1000 appeared to be unstoppable, the perfect killing machine.
All this was science fiction, of course. The technology of today does not allow you to change a solid object at will. Yet by midcentury a form of this shape-shifting technology may become commonplace. In fact, one of the main companies driving this technology is Intel.
Ironically, by 2050, most of the fruits of nanotechnology will be everywhere, but hidden from view. Almost every product will be enhanced via molecular manufacturing techniques, so they will become superstrong, resistant, conductive, and flexible. Nanotechnology will also give us sensors that constantly protect and help us, distributed in the environment, hidden away, beneath the surface of our consciousness. We will walk down the street and everything will appear to be the same, so we will never know how nanotechnology has changed the world around us.
But there is one consequence of nanotechnology that will be obvious.
The Terminator T-1000 killer robot is perhaps the most dramatic example of an object from the field called programmable matter, which may allow us one day to change the shape, color, and physical form of an object with the push of a button. On a primitive level, even a neon sign is a form of programmable matter, since you can flick a light switch and send electricity through a tube of gas. The electricity excites the gas atoms, which then decay back to their normal state, releasing light in the process. A more sophisticated version of this is the LCD display found on computer screens everywhere. The LCD contains a liquid crystal that becomes opaque when a small electrical current is applied. Thus, by regulating the electrical current flowing inside a liquid crystal, one can create colors and shapes on a screen with the push of a button.
The scientists at Intel are much more ambitious. They visualize using programmable matter to actually change the shape of a solid object, just like in science fiction. The idea is simple: create a computer chip in the shape of a tiny grain of sand. These smart grains of sand allow you to change the static electric charge on the surface, so that these grains can attract and repel each other. With one set of charges, these grains can line up to form a certain array. But you can reprogram these grains so that their electrical charges change. Instantly, these grains rearrange themselves, forming an entirely different arrangement. These grains are called “catoms” (short for claytronic atoms) since they can form a wide range of objects by simply changing their charges, much like atoms. (Programmable matter has much in common with the modular robots we saw in Chapter 2. While the modular robots contain smart blocks, about 2 inches in size, that can rearrange themselves, programmable matter shrinks these building blocks to submillimeter size and beyond.)
One of the promoters of this technology is Jason Campbell, a senior researcher at Intel. He says, “Think of a mobile device. My cell phone is too big to fit comfortably in my pocket and too small for my fingers. It’s worse if I try to watch movies or do my e-mail. But if I had 200 to 300 milliliters of catoms, I could have it take on the shape of the device that I need at that moment.” So one moment, I have a cell phone in my hand. The next moment, it morphs into something else. This way, I don’t have to carry so many electronic gadgets.
In its laboratories, Intel has already created an array of catoms that are about an inch in size. The catom resembles a cube with scores of tiny electrodes spread evenly on its surfaces. What makes the catom unique is that you can change the charge on each of its electrodes, so that catoms bind to each other in different orientations. With one set of charges, these cubes might combine to create a large cube. Change the charges on each cube’s electrode, and then the catoms disassemble and quickly rearrange themselves into an entirely different shape, such as a boat.
The point is to shrink each catom to the size of a grain of sand, or even smaller. If one day silicon-etching techniques allow us to create catoms that are as small as a cell, then we might be able to realistically change one shape into another, simply by pushing a button. Justin Rattner, a senior fellow at Intel, says, “Sometime over the next forty years, this will become everyday technology.” One immediate application would be for automobile designers, airline engineers, artists, architects, and anyone who has to design three-dimensional models of their projects and then continually modify them. If one has a mold of a four-door sedan, for example, one can grab the mold, stretch it, and it suddenly morphs into a hatchback. Compress the mold a bit more and it turns into a sports car. This is far superior to molding clay, which has no memory or intelligence. Programmable matter has intelligence, can remember previous shapes, adapt to new ideas, and respond to the designers’ wishes. Once the mold is finalized, the design can simply be e-mailed to thousands of other designers, who can then create exact copies.
This could have a profound effect on consumer products. Toys, for example, can be programmed to change shape by inserting new software instructions. So for Christmas, one need only download the software for a new toy, reprogram the old toy, and an entirely new toy appears. Children might celebrate Christmas not by opening presents under the tree but by downloading software for their favorite toy that Santa has e-mailed them, and the catoms making up last year’s toy become the hottest thing on the market. This means that a wide array of consumer products may eventually be reduced to software programs sent over the Internet. Instead of hiring a truck to deliver your new furniture and appliances, you may simply download the software off the net and recycle your old products. Renovating homes and apartments won’t be such a chore with programmable matter. In your kitchen, replacing the tiles, tabletops, appliances, and cabinets might simply involve pushing a button.
In addition, this could cut down on waste disposal. You don’t have to throw out many of your unwanted things if you can simply reprogram them. If an appliance or piece of furniture breaks, you have only to reprogram it and it becomes new again.
Despite its enormous promise, there are also numerous problems facing the Intel team. One is how to orchestrate the movements of all these millions of catoms. There will be bandwidth problems when we try to upload all this information into the programmable matter. But there are also shortcuts one can take.
For example, in science fiction movies it is common to see “morphing,” that is, one person suddenly changing into a monster. This used to be a very complex, tedious process to create on film, but can now be done easily by computer. First, you identify certain vectors that mark different key points on the face, such as the nose and eyes, for both the human and the monster. Each time a vector is moved, the face changes gradually. Then computers are programmed to move these vectors, from one face to the next, thereby slowly changing one face into another. In the same way, it might be possible to use shortcuts when shape-shifting a 3-D object.
Another problem is that the static electrical forces between the catoms are weak when compared to the tough interatomic forces that hold most solids together. As we have seen, quantum forces can be quite powerful, responsible for the tough properties of metals and the elastic properties of plastic. Duplicating these quantum forces with static electrical forces to ensure that these products remain stable
is going to be an issue in the future.
I had a chance to witness firsthand the remarkable, rapid advances in programmable matter when I took a Science Channel film crew to visit Seth Goldstein at Carnegie Mellon University. In his laboratory you could see large stacks of cubes scattered all over a table in various sizes, each with chips inside. I saw two of these cubes bound tightly together by electrical forces, and he asked me to try to rip them apart by hand. Surprisingly, I couldn’t. I found that the electrical forces binding these two cubes were quite powerful. Then he pointed out that these electrical forces would be correspondingly greater if you miniaturized the cubes. He took me to another lab, where he showed me just how small these catoms can become. By employing the same techniques used to carve out millions of transistors on silicon wafers, he could carve out microscopic catoms that were only millimeters across. In fact, they were so small that I had to look at them under a microscope to see them clearly. He hopes that eventually, by controlling their electrical forces, he can get them to arrange in any shape with a push of a button, almost like a sorcerer conjuring up anything he wants.
Then I asked him, How can you give detailed instructions to billions upon billions of catoms, so that a refrigerator, say, might suddenly transform into an oven? It seems like a programming nightmare, I said. But he replied that it wasn’t necessary to give detailed instructions to every single catom. Each catom has to know only which neighbors it must attach to. If each catom is instructed to bind with only a tiny set of neighboring catoms, then the catoms would magically rearrange themselves into complex structures (much like the neurons of a baby’s brain need to know only how to attach themselves to neighboring neurons as the brain develops).