Similar ideas of tiny machines made of molecular gears propelled an MIT engineer, K. Eric Drexler (b. 1955), to write a now-famous book about the possibility of molecular machines. When he read Feynman’s talk in the late 1970s, Drexler had already thought about the possibility of making machines out of molecules, and reading Feynman gave him an additional impetus. In 1986, he published the founding work of modern nanotechnology: Engines of Creation: The Coming Era of Nanotechnology. Much of Drexler’s ideas have so far remained science fiction, although there has been substantial progress in some areas. For example, moving single atoms and molecules around one by one and making structures such as circles or triangles made of atoms on a surface is, if not routine, certainly an achievable feat with the right tools.
The right tools were being invented about the same time Drexler wrote his books. The most iconic of these tools, scanning probe microscopes, had a great impact on the burgeoning science of the nanoscale and an equally great impact on my own life.
Touching Atoms
When you defend your Ph.D. at the University of Oxford, you’d better know your stuff. Examiners are brought in from other universities, preferably from outside the country. They don’t know you, but are there to ensure you’re no slacker. When my friend Steve got his Ph.D. at Oxford from his work with atomic force microscopes (AFMs), his examiners were two of the best-known AFM experts in the world: Christoph Gerber, who together with Nobel Prize–winner Gerd Binnig, had invented and built the world’s first AFM in 1986; and Ernst Mayr, who runs one of the largest and most successful AFM groups in the world. Gerber, who works for IBM, is a technical genius. When he visited Oxford in 2000 to be an examiner for Steve’s Ph.D. defense, he told us about a new AFM spinoff: an artificial nose. This nose works by coating tiny cantilevers (micrometer-long beams of silicon) with different substances that absorb airborne chemicals. When the chemicals are absorbed, the substance on the cantilever expands, and the cantilever bends. Using an array of differently coated cantilevers, each sensitive to different types of chemicals, this mechanical nose can be trained to distinguish many different smells. Gerber, a connoisseur of Scottish whiskeys, was excited to find that his mechanical nose had no problem distinguishing a Craigellachie from a Laphroaig, but he was even more surprised when the nose told him that one of his whiskeys had a hint of cherry. He called up the distillery in Scotland, and, indeed, the whiskey had been aged in cherry wood casks.
The AFM is the most common member of a group of instruments called scanning probe microscopes (SPMs). SPMs have revolutionized the measurement and manipulation of matter at the nanoscale more than any other instrument invented since Feynman’s famous talk. The first SPM was the scanning tunneling microscope (STM), invented in 1982 by Gerd Binnig, Christoph Gerber, and Heinrich Rohrer at the IBM laboratory in Zurich, Switzerland. The capability of this new instrument to image single atoms and measure their electronic properties was so astounding that Binnig and Rohrer received the 1986 Nobel Prize for their invention.
The working principle behind SPMs is surprisingly simple. Instead of detecting light from an object, as we would do in conventional microscopy, SPMs “feel” the surface by means of a sharp probe. The way the SPM feels the surface depends on the nature of the probe: In a STM, the microscope feels a “tunneling current” between the probe (a sharp metallic needle) and a conducting surface. Tunneling, a purely quantum-mechanical effect, is the ability of an electron to traverse an energy barrier it should not be able to cross, according to classical physics. In STM, this energy barrier is posed by the gap between the probe and the surface it is imaging. The tunneling current measured by STM depends on the width of the barrier (the distance between the probe and the surface) and the amount of electrons in the sample. Measuring the tunneling current across a sample surface provides a map of the changing heights on the surface, or changing electron density, or both. Tunneling is so sensitive to tunnel barrier width that each time the probe is moved away from the surface by only a tenth of a nanometer, the tunnel current decreases by a factor of ten! This extreme sensitivity allows the STM to obtain images of single atoms.
The images obtained with an STM are a convolution of changing heights on a surface and the changing electron densities (which vary around atoms). However, that’s not all. Forces between atoms on the tip and surface also play an important role. This was becoming clear soon after the invention of STM, when eager researchers around the world built their own STMs to look at a plethora of different surfaces. On some surfaces, the images obtained did not square with theoretical predictions taking only tunneling barrier widths and electron densities into account. One group of researchers, for example, noted that on some surfaces, the forces were so high that the distance calibration of the instrument was thrown off. This problem was addressed with the invention of a second, and now the most popular, scanning probe microscope, the AFM.
The (E)squires of Oxford
The scientist who inspired the creation of the AFM was John Pethica, of the University of Oxford, who fifteen years later became my postdoc advisor. Gerber called him the godfather of the AFM. (Which makes me, by scientific genealogy, the nephew of the godfather of the AFM, which probably is not much to brag about.) At Oxford, under the benevolent, inspirational, and deliberately hands-off guidance of John Pethica, my friends Steve Jeffery, Ralph Grimble, Ahmet Oral, Özgür Özer, Chandra Ramanujan, and I learned how to be innovative scientists. We built and used STMs and AFMs (actually combining the two) and measured the nanomechanics of atoms on crystal surfaces and molecules in liquids. It was a good time.
John is an easygoing person, but he is an exacting scientist. When I visited Oxford for my interview, an envelope with instructions was waiting for me at the hotel. John had written “Dr. Peter Hoffmann, Esq.” on the envelope. I didn’t know that I was an Esquire, but it showed John’s respect for everybody, even a lowly postdoc looking for a job. When my wife and I finally arrived a few months later, it was the beginning of summer. John typically disappeared for extended periods, only to reappear with a bagful of new ideas. After John’s return from his mysterious summer travels, I got into one of the typical—as I soon realized—conversations with him. These conversations always involved new ideas, connections, and recent publications. Listening to John, I would often be reduced to nodding and saying, “aha, yeah, mmmh,” only to scramble back to the office to look up the papers he was talking about.
John is particularly interested in how we make the transition from the noisy but reversible world of the atom, to the more ordered but typically irreversible world of macroscopic objects, a passion I inherited. In one experiment, we measured the loss of energy an oscillating AFM tip experiences when it interacts with randomly oscillating atoms on a surface, in a process we called atomic-scale energy dissipation. For small numbers of atoms involved, the motions of the atoms seemed structurally reversible. Each time we lowered the tip, we measured the same force curve. Yet when we pushed harder, we passed the threshold to permanent rearrangement of atoms. When too many atoms were involved, there were too many possible configurations, and the system did not find its way back to its original arrangement. At this point, our experiment had passed from the microscopic to the macroscopic.
The interaction of atoms and the myriad possibilities of atomic arrangements in modestly large systems is also of great importance in molecular biology, as we will see. So is the transition from noise to order. Small nanoscale systems, such as the molecules in living cells, are subject to influences and laws that are quite different from what we encounter in our familiar, macroscopic world.
The Incredible Strangeness of Small Things
When Feynman pushed for the creation of atomic-scale technology in his talk, he also pointed out unique challenges that come with building machines out of just a few atoms. Indeed, since nanoscience has become a serious science, the most interesting feature has been that tiny things play by different physical rules. This sometimes creates problems and, other
times, opportunities, but it is a source of continuing fascination to nanotechnologists.
When systems are shrunk to the nanoscale, effects that play little or no role at the macroscale suddenly become important. In his famous lecture, Feynman mentioned a few of these: problems of lubrication—because he surmised that the effective viscosity of any lubricant is much higher at a small scale—and the observation that at small scales, things are more likely to stick together. These problems are due to two more general effects that are common at the nanoscale: the graininess of matter and the problem of interfaces.
Matter is grainy; it is made of atoms, molecules, and larger grains, such as small crystals. On a large scale, this graininess of matter averages out. Following the laws of statistical mechanics and continuum physics (in continuum physics, we ignore the fact that matter is made of particles, but treat it as a smooth continuum), we can determine such average quantities as Young’s modulus (which determines how springy a solid material is) or viscosity (how resistant to flow a liquid is). But once we reduce the size of a system to just a few, ten, or one hundred molecules, these averaged quantities become meaningless, and measurements of mechanical or electrical properties show jumps, rather than smooth, averaged-out changes. In my lab, we measure the graininess of simple liquids, such as water. When I measure the mechanical properties of water, it doesn’t matter if I take a bucketful of water, or a few cubic centimeters from a syringe. A cubic centimeter of water contains 3 × 1022 water molecules (that’s a 3 with 22 zeros behind it). Adding or subtracting a few million or billion molecules from such a giant number of molecules is not going to change the average properties of the liquid. In our lab, however, we can measure the mechanical properties of much smaller numbers of water molecules. We can squeeze water between an AFM tip and a surface until the water layer between the tip and surface is a single molecule thick (however, since the tip has an area of about 50 nanometers by 50 nanometers, the single molecule layer under the tip contains about 25,000 molecules). Now, adding or subtracting single layers of molecules makes a huge difference to the mechanical properties of the liquid. As a result, when we push from a layer 6 molecules thick to one 5 molecules thick, and then from 5 to 4, and so on, the stiffness and the apparent viscosity of the layers alternate between high and low values.
These experiments also illustrate the other nanoscale problem Feynman was talking about. When we make something smaller, its surface to-volume ratio increases. A golf ball has a greater surface-to-volume ratio than does a bowling ball. Shrunk to the nanoscale, this ratio would be more extreme. As volumes become small, surfaces start to dominate and the forces that are important at the macroscale become irrelevant at the nanoscale, and vice versa. At the macroscale, forces associated with mass, such as gravity and inertia, dominate. Surface forces, such as stickiness, are usually unimportant, unless specifically engineered, as in a glue. For example, in a baseball game, inertia (when the bat hits the ball) and gravity (when the ball comes back down) dominate. But, typically, the baseball does not stick to the bat. In a game of nanobaseball, however, inertia would be unimportant, as the ball would weigh next to nothing. Ditto gravity. But the relatively large surface area compared with the tiny bulk of the nanobaseball would make it difficult to get the nanobaseball off the nanobat. This is an example of one peculiar property of nanoscale systems: profound changes in behavior depending on the size of the system.
Of course, not everything at the nanoscale sticks together. Otherwise, we’d be in trouble. Our cellular components have to be able to stick and separate when needed. This is achieved through a careful balance of forces between molecules and the surrounding salty water. In a vacuum, in the absence of water, most surfaces simply tend to stick.
At the nanoscale, there are some peculiarities that Feynman did not mention: quantum-mechanical effects, the importance of thermal noise and entropy, cooperative dynamics, large ranges of relevant time scales, and the convergence of energy scales. A daunting list of strange properties. We will discuss these peculiarities through different examples in the remaining chapter.
Quantum-Mechanical Effects
Most books on nanotechnology will focus on the strange quantum-mechanical effects we encounter at the atomic scale. I alluded to some of these in the discussion of tunneling. Indeed, a large part of nanotechnology relies on new quantum-mechanical effects. However, for molecular biology, these are almost irrelevant. Essentially all of molecular biology can be explained using classical physics (except bonding between atoms, which requires quantum mechanics). Many of the more interesting quantum-mechanical effects in nanosystems are completely destroyed by thermal motion. Therefore, much research on quantum computing, spintronics, or other fancy new quantum electronics is done at low temperatures—much too low for any living system.
Thermal Noise
By contrast, thermal motion (or, what physicists like to call thermal noise), already discussed in the previous chapter, is of great importance in biology and most of room-temperature nanotechnology. So are questions of size dependence, cooperative dynamics and time scales (which go hand-in-hand), and the convergence of energy scales. To understand what these things are, and how they influence systems at the nanoscale, let us consider the important question: How can we make stuff at the nanoscale?
Assemble Thyself!
Feynman believed machines and structures at the nanoscale could be assembled by some kind of demagnifying technology that could turn a macroscopic template into a small pattern using electron or ion beams (now a reality in devices called electron-beam writers or focused-ion beams) or by building machines that make smaller copies of themselves ad infinitum until the nanoscale is reached (not yet a reality). Both of these approaches could be described as top-down: They start with a large template or machine and then miniaturize down to the nanoscale.
This top-down approach is still used in building electronic devices, such as computer memory or processors. Life, however, works differently: Plants, animals, and all other living organisms are built from the bottom up. We are all assembled atom by atom, molecule by molecule.
A common fallacy that people hear over and over is that our DNA contains all the information needed to make a human being. Nonsense! The amount of information contained in our DNA is staggering, but it is not nearly enough to specify each molecule’s or cell’s location, or even the shape of an organ. Rather than being a blueprint (as DNA is often mistakenly called), DNA is more like a cooking recipe. When I make a cake, I don’t have to specify where each starch or sugar molecule goes. I just follow the instructions, and the molecules go where they are supposed to. Much of the information to make a cake or a human being is contained in the laws of physics and chemistry. Molecules “know” how to put themselves together.
This self-assembly of molecules is ubiquitous throughout nature and is a major research area in nanoscience. If we could coax molecules to arrange themselves into any structure we want—much like what we see in living organisms—we could make new devices incredibly cheaply, without million-dollar ion or electron-beam writers. We could simply put everything in a pot and stir. But it’s obviously not that simple.
One of my recent graduate students, Venkatesh Subba-Rao, likes to tell the following anecdote: He once listened to a talk by a visiting scientist about structures in liquid crystals. When Venkatesh asked him the reason why these structures arise, the scientist answered, “They minimize free energy!” Since then, if I ask my students why this or that is happening in their experiments, and they don’t know, this is their stock answer. Most of the time it’s correct. Everything that happens in nature minimizes free energy. But this answer does not tell us much. It is almost the scientific equivalent of “because God made it so.” A more useful answer would include the types of energies that make up the free energy of a system. An even more useful answer would identify how molecules move around and how energy is transformed as the system minimizes its free energy. Remember, free energy is the difference betw
een the total energy of the system and unusable thermal energy, leaving the usable, free part of the energy. Unusable energy is the product of temperature and entropy. When we minimize free energy, we can either lower the total energy, increase the amount of unusable energy, or both. In self-assembly, all of these possibilities come into play.
One of the most familiar and most stunning examples of self-assembly is the aforementioned snowflakes. Snowflakes are crystals of water ice. If you ask my students why snow crystals form, they would answer that it minimizes free energy! And, indeed, as we saw in Chapter 3, there is a critical temperature below which the lowering of the free energy leads to the formation of snow flakes, while above that temperature, free energy is minimal when water remains liquid. Yet, we would like to have more information. Snowflakes are such beautiful, intricate structures, and explaining their structure as a reduction in free energy seems like a copout. The result is a reduction in free energy, but how does it happen? How does the structure form?
Life's Ratchet: How Molecular Machines Extract Order from Chaos Page 12
