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Nanotechnology and Cryonics: An Introduction

Nanotechnology and Cryonics: An Introduction

By Robert Ettinger

Newcomers to cryonics--and even those not so new--often have serious gaps in their understanding of its relation to nanotechnology. Let me try to bridge some of these gaps by trying to spell out the main ideas simply enough for the intelligent but uninformed layman, yet with enough specificity and detail to begin to convince more sophisticated readers that we are not just blowing smoke.


The prefix "nano-" means "one billionth"--a nanometer is one billionth of a meter, or roughly a few times the diameter of a hydrogen atom. Nanotechnology therefore means, as a first approximation, technology on the scale of atoms and molecules.

But this is still pretty vague, and not exactly new. After all, chemists for centuries have attempted, often with striking success, to juggle atoms and molecules, to combine and separate atoms and to change molecules.

But they do it in bulk, while Nobel physicist Richard Feynman in the 1950s envisioned doing it with individual atoms and molecules, modifying or moving them one by one as needed, to do production and repair work (on any solid system, at least, although not excluding fluids) with ultimate precision. Actually, this wasn't totally new either, since our bodies do something like that all the time--enzyme molecules, for example, work by changing other molecules, one by one, while not undergoing any net change themselves. In other words, enzyme molecules can be considered tools, sometimes used to "saw" molecules apart or "nail" them together.

All this suggests that "nanotechnology" might also be called "molecular engineering," and that improves our mental picture, but it still falls short of capturing the diversity and potential of this new field. In the Eighties, K. Eric Drexler emerged as the leading guru of a much broader and higher vision. His projections included "assemblers"--nano-scale devices, or assemblages of nano-scale devices, which could build things in more or less the same way that biology can build things--by "growing" them, using materials from the environment. These assemblers could also assemble themselves--i.e., reproduce or replicate themselves, to make as many as the job requires.

This seems to suggest that the right machines could make almost anything out of air, water, or dirt--and do it dirt cheap.

Pushing the concept further, the tiny-tech assemblers would be guided by tiny-tech computers, which could have varying degrees of specialization and learning capacity. Pulling all this together, what do we get?

What we got more than 30 years ago (1966) was the movie Fantastic Voyage, with Raquel Welch. A microscopic submarine, carrying surgeons reduced to microscopic size, was injected into a patient's circulatory system. Silly? Yes, if we are talking about Honey-I-Shrunk-the-Doctor. But if we are talking about microscopic robodocs swimming through your blood stream and burrowing through your tissues, that is not silly. They could work tirelessly to maintain or restore your health--removing plaque from arteries, killing and removing viruses and bacteria, replacing damaged DNA sections with normal sections, and in fact repairing or replacing any diseased, damaged, or missing cells or tissues, or even whole organs.

All this seems to suggest that we could wave our nano-wand to cure any ailment, disease, or trauma--including old age and freezing damage.

People are made of atoms and molecules. To restore youth and health, all you have to do is make wrong molecules into right molecules, and get them in the right places. Simple, isn't it?


Does all the above seem too good to be true? To many people, it did, and to some it still does. Stating a concept is not the same as proving its soundness; and even if a concept is sound in principle, its practical achievability must be demonstrated. Fortunately, progress in both theory and practice has been relatively rapid.

In 1986, the same year Drexler's Engines of Creation was published, two IBM physicists won the Nobel Prize for the Scanning Tunneling Microscope (STM)--the first of several devices that can "see" individual atoms, and even move them around. Research and development programs are under way or planned at Yale, Princeton, MIT, CalTech, Duke, Rice, Rutgers, Purdue; also at the universities of Chicago, Glasgow, Hamburg, Lausanne, Texas, Tokyo, Toronto, Washington, and dozens of others; at companies such as IBM, Xerox, AT&T, Dow Chemical, Exxon, Hitachi, Honeywell, McDonnel Douglas, Merck, and Zyvex; at national laboratories including, in the U.S., the Ames and Los Alamos, and Lawrence Livermore; by national agencies or departments such as the U.S. Army and Air Force, NASA, the National Science Foundations, the National Institutes of Health, and the Departments of Commerce and Energy.

For timely updates on progress, see the Foresight Update, a publication of the Foresight Institute, of which Dr. Drexler is Chairman--web site at Or go to the links on this web site. (See Contents.)

Among cryonicists, some point to the promise of nanotech as evidence (not proof, but evidence) that it will become possible to revive, repair, and rejuvenate even the most badly damaged of our present and future patients. But others say "nanotech" should not be used as a mantra or as an excuse for complacency about our current freezing methods.

Both are right. We agree with the skeptics, that as little burden as possible should be placed on the future, and our patients should be frozen by the best methods we can learn or devise and have the capability to implement. But it is also obvious that patients frozen--for whatever reason--by cruder methods should also have their chance, if that chance can be shown to be an appreciable one and not just a forlorn hope.

My aim in this brief discussion is to show a little of the evidence that the chance is, indeed, not a negligible one.

One of the important names in nanotech theory is that of Ralph Merkle. When he gives one of his many talks introducing nanotech in its relation to cryonics, he says something along these lines:

In medicine, new procedures usually progress through various stages, including animal trials and finally human clinical trials. If the results of the clinical trials are good enough, the FDA may approve the procedure for routine use.

Patients are divided into two groups--the controls, who do not receive the treatment being investigated--and the experimental group, who do receive it. In the cryonics case, the controls are buried or cremated; those in the experimental group are frozen.

Although the outcome for the experimental group will not be known for sure for a long time, we do have a pretty good line on the outcome for the control group--those who were buried or cremated. So which group would you rather be in?


Drexler, Merkle, and others have written at length on many aspects of cryonics-related nanotechnology, and in particular repair of freezing damage. Much of that is available on our web site. What I want to do right now is merely to convey a flavor of some of the detail, to begin to show skeptics that the investigation, although certainly still very preliminary, nevertheless endeavors to come to grips with reality and to provide hard answers to hard questions. Scientists and engineers tend to be more impressed by numbers than by qualitative arguments. So here are some nice numbers--selected, edited, abridged and paraphrased from works of Dr. Merkle and Dr. Drexler. References are omitted, but can readily be found on our web site or its links.
Overview of the Brain.

The brain has a volume of 1350 cubic centimeters (about one and a half quarts) and a weight of slightly more than 1400 grams (about three pounds). It is almost 80% water by weight. An average brain has slightly over 100 grams of protein, about 175 grams of lipids, and some 30 to 40 grams of "other stuff".

How Many Molecules

An "average" protein molecule has a molecular weight of about 50,000 amu (atomic mass units; one amu is about the mass of a hydrogen atom or a proton or a neutron). One mole (gram molecular weight) of "average" protein is 50,000 grams (by definition), so the 100 grams of protein in the brain is 100/50,000 or .002 moles. One mole is 6.02 x 10^23 molecules, so .002 moles is 1.2 x 10^21 molecules.

The brain has about 175/500 x 6.02 x 10^23 or about 2 x 10^23 lipid molecules.

[W]ater has a molecular weight of 18, so there will be about 1400 x 0.8/18 x 6.02 x 10^23 or about 4 x 10^25 water (or cryoprotectant) molecules in the brain.

How Much Time

The more repair devices there are, the faster the repair will be. The more molecules there are, and the more time it takes to repair each molecule, the slower repair will be.

The time required for a ribosome to manufacture a protein molecule of 400 amino acids is about 10 seconds, or about 25 milliseconds to add each amino acid. DNA polymerase III can add an additional base to a replicating DNA strand in about 7 milliseconds. In both cases, synthesis takes place in solution and involves significant delays while the needed components diffuse to the reactive sites. The speed of assembler-directed reactions is likely to prove faster than current biological systems. The arm of an assembler should be capable of making a complete motion and causing a single chemical transformation in about a microsecond. However, we will conservatively base our computations on the speed of synthesis already demonstrated by biological systems, and in particular on the slower speed of protein synthesis.

We must also analyze the existing molecules, possibly repair them, and move them from their original location to the desired location. Existing antibodies can identify specific molecular species by selectively binding to them, so identifying individual molecules is feasible in principle. It seems reasonable to multiply the synthesis time by a factor of a few to provide an estimate of time spent per molecule. This should, in principle, allow time for the complete disassembly and reassembly of the selected molecule using methods no faster than those employed in biological systems. A factor of 10 should be sufficient. The total time required to move a molecule from its original location to its correct location in the repaired structure should be smaller than the time required to disassemble and reassemble it, so we will assume that the total time required for analysis, repair and movement is 100 seconds per protein molecule.

Total Repair Machine Seconds

We shall assume that the repair time for other molecules is similar per unit mass. That is, we shall assume that the repair time for the lipids (which each weigh about 500 amu, 100 times less than a protein) is about 100 times less than the repair time for a protein. The repair time for one lipid molecule is assumed to be 1 second. We will neglect water molecules in this analysis, assuming that they can be handled in bulk.

We have assumed that the time required to analyze and synthesize an individual molecule will dominate the time required to determine its present location, the time required to determine the appropriate location it should occupy in the repaired structure, and the time required to put it in this position. These assumptions are plausible but will be considered further when the methods of gaining access to and of moving molecules during the repair process are considered.

This analysis accounts for the bulk of the molecules -- it seems unlikely that other molecular species will add significant additional repair time.

Based on these assumptions, we find that we require 100 seconds x 1.2 x 10^21 protein molecules + 1 second times 2 x 10^23 lipids, or 3.2 x 10^23 repair-machine-seconds. This number is not as fundamental as the number of molecules in the brain. It is based on the (probably conservative) assumption that repair of 50,000 amu requires 100 seconds. Faster repair would imply repair could be done with fewer repair machines, or in less time.

How Many Repair Machines

If we now fix the total time required for repair, we can determine the number of repair devices that must function in parallel. We shall rather arbitrarily adopt 10^8 seconds, which is very close to three years, as the total time in which we wish to complete repairs.

If the total repair time is 10^8 seconds, and we require 3.2 x 10^23 repair-machine-seconds, then we require 3.2 x 10^15 repair machines for complete repair of the brain. This corresponds to 3.2 x 10^15 / (6.02 x 10^23) or 5.3 x 10^-9 moles, or 5.3 nanomoles of repair machines. If each repair device weighs 10^9 to 10^10 amu, then the total weight of all the repair devices is 53 to 530 grams: a few ounces to just over a pound.

Thus, the weight of repair devices required to repair each and every molecule in the brain, assuming the repair devices operate no faster than current biological methods, is about 4% to 40% of the total mass of the brain.

By way of comparison, there are about 10^14 cells in the human body and each cell has about 10^7 ribosomes, giving 10^21 ribosomes. Thus, there are about six orders of magnitude more ribosomes in the human body than the number of repair machines we estimate are required to repair the human brain.

Errors in these estimates of even several orders of magnitude can be easily tolerated. A requirement for 530 kilograms of repair devices (1,000 to 10,000 times more than we calculate is needed) would have little practical impact on feasibility. Although repair scenarios that involve deployment of the repair devices within the volume of the brain could not be used if we required 530 kilograms of repair devices, a number of other repair scenarios would still work. Given that nanotechnology is feasible, manufacturing costs for repair devices will be small. The cost of even 530 kilograms of repair devices should eventually be significantly less than a few hundred dollars. The feasibility of repair down to the molecular level is insensitive to even large errors in the projections given here.


The least sophisticated criterion of "survival" requires retention of function. Most people today regard as "dead" someone who cannot function spontaneously--heartbeat and breathing, for example. Obviously, this is too simplistic, since many people--many thousands-- have been revived after their hearts and lungs stopped working.

The next criterion is retention of structure. By way of analogy, if a wire is loose in an auto, it won't run--but obviously it isn't dead. Its structure is still 99.999% intact, and only a trivial repair is needed to restore function. Similar considerations apply to people. A slightly damaged organ may fail entirely to function, yet it is still only slightly damaged, and amenable to relatively easy repair.

So we get to the "information-theoretic" criterion. If we know or can infer the information we need--what molecules, and where located, will represent a restoration and cure or repair of the patient--then, in principle, with advanced nanotech, we can repair and revive him. But some skeptics claim that frozen people are so degraded that essential information is irretrievably lost, and so is hope.

This pessimistic contention seems totally unrealistic, in view of the fact that many biological specimens have in fact been revived after warming from liquid nitrogen temperature; these include most types of human tissue, human embryos, some whole insects, and a few small mammalian organs. Rabbit brain pieces have shown coordinated electrical activity in networks of neurons--on and on. Still, can we yet be absolutely certain that some vital type of information is not lost?

No, absolute certainty in this--or in almost anything else--is not yet in our grasp. But there are plenty of reasons for optimism, in addition to those already mentioned.

For one thing, there may exist a Law of Conservation of Information, analogous to the Law of Conservation of Energy. Information can be lost (or created) locally, but not globally. Recent ideas about "quantum entanglement" tend to support this. However, space precludes further discussion here, except that we can make a brief mention of the jigsaw-puzzle analogy.

Putting together the scattered pieces of a jig-saw puzzle can be time-consuming, but it is basically easy. The pieces, after all, fit together in only one way. Over-simplifying just a little, we can say that the same is true, very nearly, of a frozen brain. There is only one way the atoms and molecules can fit together to restore the original configuration. (Actually, of course, most of them don't need to have their original locations known or restored, since a water molecule here or there doesn't matter, and housekeeping cells such as glial cells are generic, etc.) When you first start to put the puzzle together, there seem to be many possibilities for each piece, but as the work progresses the choices become fewer, and finally it becomes easy. The three-dimensional character of our brain puzzle makes it easier, since there are fewer possibilities of reasonable fit.

Another reason for optimism arises from thinking about cryptography and cryptanalysis--code or cipher making and code breaking. The difficulty of hiding information is stunningly impressive. Even when experts try their utmost to conceal information in codes or ciphers, and even in the presence of a lot of "noise" or random data bits, other experts frequently are able to break the codes. Now, recall that Dame Nature, while perhaps not exactly maternal, is not malicious either. She does not try to conceal clues, and perhaps cannot.

Recall also that Dr. Merkle, besides his prominence in Nanotech theory, is a recognized expert in cryptography. His belief that cryostasis patients have not suffered information theoretic death should be accorded corresponding respect.
Those who think the "random" movement of brain bits during freezing will destroy information have to contend with Dr. Merkle in another way also. There really isn't any such thing as "random" motion (except putatively at the quantum level), but one might claim that turbulent flow produces enough chaos to offer reason for pessimism. But Merkle has explicitly considered the question, displayed calculations (see our link), and concluded that there is very little if any turbulent flow during freezing.


I have not seen the following suggestion in the literature, but it seems likely to offer further tools.

Instead of trying to work backward from the final, observed, degraded condition of a frozen patient, why not use computer simulation--under a wide variety of initial conditions and treatment regimens--to watch what would develop and what the intermediate and end results would be? The correlations should then provide strong implications about the initial state.

For example, we use treatment regimen A with initial condition of the clinically dead patient designated as A0. We run the computer simulation, with resulting conditions at subsequent times being A1, A2,…..and finally (say) the frozen condition An. (Each of the conditions A1, A2, … will of course be a huge set of numbers showing all of the critical or unique features of the brain in question.)

Now if we see an actual frozen patient closely fitting the description of An, we can infer that his initial condition was probably close to A1. Then additional clues from other sources might allow us considerable confidence as to what we are trying to regain--which memories, for example.

Needless to say, this approach would involve a staggering amount of computation, far beyond present capabilities; and it would also require advanced brain scanning methods to provide the data in-put. But future computational resources (perhaps including quantum computation) are indeed very widely expected to represent tremendous advances--and the frozen patients can be patient.


When you listen to can-do experts and can't-do experts, whom should you believe? Other things equal, it is no contest--the can-do person wins hands down, and the reason is extremely simple. The can't-do person has merely looked at the question and formed a pessimistic conclusion and turned away; or in a few cases perhaps he has actually tried to do it and failed and given up. The can-do person, on the other hand, wants to do it and keeps on trying, and if one approach fails he devises a new approach, and he doesn't quit.

Henry Ford said: "Some think they can do it. Some think they can't do it. They are both right."

---- R.C.W. Ettinger