Guest Writer - Gastautor - Gast Schrijver

The Bugbear of Entropy


Entropy and thermodynamics are often cited as a reason why diamondoid mechanosynthesis can't work. Supposedly, the perfection of the designs violates a law of physics that says things always have to be imperfect and cannot be improved.

It has always been obvious to me why this argument was wrong. The argument would be true for a closed system, but nanomachines always have an energy source and a heat sink. With an external source of energy available for their use, they can certainly build near-perfect structures without violating thermodynamics. This is clear enough that I've always assumed that people invoking entropy were either too ignorant to be critics, or willfully blind.

It appears I was wrong. Not about the entropy, but about the people. Consider John A. N. (JAN) Lee. He's a professor of computer science at Virginia Tech, has been vice president of the Association for Computing Machinery, has written a book on computer history, etcetera. He's obviously intelligent and well-informed. And yet, he makes the same mistake about entropy--not in relation to nanotech, but in relation to Babbage, who designed the first modern computer in the early 1800's.

In Lee's online history of Babbage, he asserts, "the limitations of Newtonian physics might have prevented Babbage from completing any Analytical Engine." He points out that Newtonian mechanics has an assumption of reversibility, and it wasn't until decades later that the Second Law of Thermodynamics was discovered and entropy was formalized. Thus, Babbage was working with an incomplete understanding of physics.

Lee writes, "In Babbage's design for the Analytical Engine, the discrete functions of mill (in which 'all operations are performed') and store (in which all numbers are originally placed, and, once computed, are returned) rely on this supposition of reversibility." But, says Lee, "information cannot be shuttled between mill and store without leaking, like faulty sacks of flour. Babbage did not consider this, and it was perhaps his greatest obstacle to building the engine."

Translated into modern computer terms, Lee's statement reads, "Information cannot be shuttled between CPU and RAM without leaking, like faulty sacks of flour." The fact that my computer works as well as it does shows that there's something wrong with this argument.
In a modern computer, the signals are digital; each one is encoded as a voltage in a wire, above or below a certain threshold. Transistors act as switches, sensing the incoming voltage level and generating new voltage signals. Each transistor is designed to produce either high or low voltages. By the time the signal arrives at its destination, it has indeed "leaked" a little bit; it can't be exactly the same voltage. But it'll still be comfortably within the "high" or "low" range, and the next transistor will be able to detect the digital signal without error.
This does not violate thermodynamics, because a little energy must be spent to compensate for the uncertainty in the input signal. In today's designs, this is a small fraction of the total energy required by the computer. I'm not even sure that engineers have to take it into account in their calculations, though as computers shrink farther it will become important.

In Babbage's machine, information would move from place to place by one mechanism pushing on another. Now, it's true that entropy indicates a slightly degraded signal--meaning that no matter how precisely the machinery was made, the position of the mechanism must be slightly imprecise. But a fleck of dust in a bearing would degrade the signal a lot more. In other words, it didn't matter whether Babbage took entropy into account or even knew about it, as long as his design could tolerate flecks of dust.

Like a modern computer, Babbage's machine was designed to be digital. The rods and rotors would have distinct positions corresponding to encoded numbers. Mechanical devices such as detents would correct signals that were slightly out of position. In the process of correcting the system, a little bit of energy would be dissipated through friction. This friction would require external energy to overcome, thus preserving the Second Law of thermodynamics. But by including mechanisms that continually corrected the tiny errors in position caused by fundamental uncertainty (along with the much larger errors caused by dust and wear), Babbage's design would never lose the important, digitally coded information. And, as in modern computers, the entropy-related friction would have been vastly smaller than friction from other sources.

Was Babbage's design faulty because he didn't take entropy into account? No, it was not. Mechanical calculating machines already existed, and worked reliably. Babbage was an engineer; he used designs that worked. There was nothing very revolutionary in the mechanics of his design. He didn't have to know about atoms or quantum mechanics or entropy to know that one gear can push another gear, that there will be some slop in the action, that a detent can restore the signal, and that all this requires energy to overcome friction. Likewise, the fact that nanomachines cannot be 100% perfect 100% of the time is no more significant than the quantum-mechanical possibility that part of your brain will suddenly teleport itself elsewhere, killing you instantly.

Should Lee have known that entropy was not a significant factor in Babbage's designs, nor any kind of limitation in their effectiveness? I would have expected him to realize that any digital design with a power supply can beat entropy by continually correcting the information. After all, this is fundamental to the workings of electronic computers. But it seems Lee didn't extend this principle from electronic to mechanical computers.

The point of this essay is not to criticize Lee. There's no shame in a scientist being wrong. Rather, the point is that it's surprisingly easy for scientists to be wrong, even in their own field. If a computer scientist can be wrong about the effects of entropy on an unfamiliar type of computer, perhaps we shouldn't be too quick to blame chemists when they are likewise wrong about the effects of entropy on nanoscale machinery. If a computer scientist can misunderstand Babbage's design after almost two centuries, we shouldn't be too hard on scientists who misunderstand the relatively new field of molecular manufacturing.

But by the same token, we must realize that chemists and physicists talking about molecular manufacturing are even more unreliable than computer scientists talking about Babbage. Despite the fact that Lee knows about entropy and Babbage did not, Babbage's engineering was more reliable than Lee's science. How true it is that "A little learning is a dangerous thing!"

There are several constructive ways to address this problem. One is to continue working to educate scientists about how physics applies to nanoscale systems and molecular manufacturing. Another is to educate policymakers and the public about the limitations of scientific practice and the fundamental difference between science and engineering. CRN will continue to pursue both of these course

Chris has studied nanotechnology and molecular manufacturing for more than a decade. After successful careers in software engineering and dyslexia correction, Chris co-founded the Center for Responsible Nanotechnology in 2002, where he is Director of Research. Chris holds an MS in Computer Science from Stanford University.

Copyright © 2004 Chris Phoenix


Chris Phoenix

CRN Director of Research