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Article on Nano Technologies
Article on Nano Technologies - Beyond the Small: Nano, Bio and Quantum Technologies
The size of a single transistor has been reducing in an exponential manner for several decades, leading to integrated circuits containing tens of millions of transistors. But as the size of the transistor decreases a physical limit is encountered where the transistor becomes too small and quantum effects become significant. When this limit is reached the exponential growth in computing power that has been characteristic of the 1980s and 1990s will come to an end. This event is expected to occur somewhere between 2010 and 2020. This will be the end of the road for pure silicon technology. At this point completely new technologies will be needed. So the question is, what is coming next?
The field of Nano, Bio and Quantum is concerned with the future, with technologies that do not yet exist. The field at present is therefore one of science, but interestingly, it is technology that is enabling this science of the very small. The technological tools now exist that provide a means of working at the level beyond micro. These tools are allowing scientists to interact with and to manipulate matter at a level that has not been previously possible.
At the technological level however, there is an increasing realisation that there is not much to be gained in a practical sense by manipulating single atoms or molecules. Therefore novel concepts are needed such as self fabrication and self assembly, which raise problems both at the physics level but also at the level of architecture, computer science and systems engineering.
The Challenges of Working beyond the Small
What are the challenges of miniaturisation beyond the level of micro technologies? One issue is when to stop investing in the current micro technologies, which can be taken down to the nano scale. Miniaturisation of microelectronics will probably be able to take the size of a transistor down to 30 nanometres. The next issue would be how to take the transistor size down to 5 nanometres, for which entirely new concepts would be needed.
The success of microelectronics has been in its scalability. As things became smaller the principles and underlying physics did not change. New steps in the technology built on previous knowledge and the financing of development came from the profits from sales of the previous generation of the technology. Technology development was non-disruptive.
The problem with nanotechnologies is that they are not completely scalable. Also there is no miniaturisation perspective. In microelectronics the goal has been to make things smaller, faster and cheaper. In the nano regime one is at the level of single electron transistors, single atoms, or single molecules. So adding value becomes important and that will mean making things more intelligent.
Interfacing on the nano scale is going to be a big problem. At this level as soon as an interface is made to a nano object, its properties change.
The new concepts in the field of nanotechnology will come from nature. The nano scale operates at the transition point between condensed matter and molecular behaviour and quantum effects. Ideas will therefore come from the fields of biology, chemistry and quantum physics.
The Contribution of Quantum Physics
One of the new concepts that may have a role to play in the post microelectronics world is quantum computation, which is about using the states of atoms as a basis for computation. Unlike classical logical devices, which only exist in two states (0 or 1), atoms can have three states (0 or 1 or 01 where the latter is a superposition of the first two states).
There are several different reasons for the interest in quantum computation. Technologists are interested because they want to address the problems that arise when the physical limits of silicon are reached. Physicists on the other hand, want to understand more about quantum mechanics. Computer scientists however are interested in changes to complexity classes, where problems that are today seen as difficult may become easy to solve. Logicians are also interested in this area because it opens up the possibility of proving logical propositions through a physical process.
It is very difficult to build a quantum computer. Single quantum bit (qubit) logic gates are possible. Two qubit gates (a controlled NOT logic gate) are currently being investigated. Building single qubit gates using trapped ion technology is feasible, but the big problem and major difficulty is creating a 2 qubit gate. The difficulty lies in controlling the state of a target atom based upon the state of the control atom, and keeping the system stable over time. Most of the ideas that have gone into quantum computing have been focused on entangling two atoms to create a 2 qubit gate. The successful development of a 2 qubit gate is now very near and it is to be expected that within a few years 10 qubit gates will have been developed.
A number of competing technologies are being considered including trapped ions, superconductors and quantum dots.
Another issue is how to construct quantum memory. Quantum memory exists and is workable in laboratory environments. This involves storing and trapping single atoms in space.
Part of the problems in building quantum computers lies in the area of engineering the components. A major difficulty lies in controlling the quantum effects. There is knowledge about how to control quantum optics in a laboratory environment, but in the long term the emerging technology may be solid state physics. At the moment however this field needs a lot of development work.
Another element of quantum computation is quantum communications, which involves transmitting quantum states in a reliable way. One way to do this is to use photons, and to write the quantum state of an atom onto photons and then to transmit these. At the receiver these photons are then used to write the state back onto atoms. The technologies for building this kind of quantum communication system, including error correction, will probably be available in a few years time.
The Contribution of Biology
Moving on from the area of quantum physics, another discipline that may have a role to play in shaping future generations of computer technologies, is biology. Can chemical processes at the bio cell and molecular level be used for information processing? Can knowledge of biological molecules help with the development of new information technologies? These are very much, open questions.
Life has a big advantage in terms of technology. There is 3.5 billion years of evolutionary development. DNA provides an example of long term information storage. It is very compact and replicable, however it is not very fast. So its use as a model for information processing seems to be limited. Short-term information storage is handled in biological systems by energy consuming processes. Brain activity is, for example, linked to increased energy consumption, but again the time scales are very slow when compared with microelectronics.
However, in photosynthesis, photon inputs result in virtually instantaneous (pico second range) charge separation which then drives the energy making process in the system. This is an example where biological systems are very fast. Many biological systems are very efficient electron or ion carriers.
Life provides examples of sophisticated biological information mechanisms that might provide models for technological concepts. But which components of biological systems provide useful models? Looking to nature for models is a different approach from trying to incorporate biological materials into computers. This latter objective may in fact not work because biological systems tend to be too slow for most information processing applications. For this reason the emphasis should be more on using biology to discover how to improve information processing.
The Contribution of Chemistry
Another disciplinary area that potentially provides useful concepts for computation is chemistry. Here the focus is on molecular electronic components based on single molecules. A few years ago this idea of molecular electronic was seen as fantasy, but the field is now established and a significant amount of industrial funding is being directed at the area.
A lot of work in the field of molecular electronics is focused on reinvesting the transistor at the molecular level. This seems to be the wrong thing to do, as the scale is wrong, since transistors are not molecules. Another way forward is to try and reinvent the computer, to build computers from molecules. The basic architecture for such a computer already exists. An interesting feature of the architecture is that it is default tolerant. Defects in the computer can be ignored. This is a key requirement for a molecular computer as manufacturing processes working at the molecular level are always going to produce defects. Eliminating the defects in manufacturing would be too difficult and too expensive.
To make this architecture work switches and wires need to be manufactured using molecules. And this is now possible. One current question is how small these switches and wires can be made.
The semiconductor industry needs to decide when to stop investing in silicon technologies and when to switch over to the new concepts. There is always a temptation to go a little further with existing technologies, when the most appropriate response would be to move on to new technologies.
One of the implications of quantum computing is a change to complexity classes, where previously difficult problems become easy to solve. This has major implications for security and privacy as current cryptography techniques rely on current complexity classes. As soon as difficult computational problems become easy to solve today's security systems become useless.
In the field of biology the most fruitful path to follow is using nature as a model to find better ways of doing information processing. Biology can provide models that lead to new concepts which would be implemented with non-biological materials.
Of great interest are the self-organising capabilities of biological system. If such processes can be better understood, then this might be an area where biology can make a significant input to computer technology.
Molecular electronics is based on building computers out of molecular switches and wires. A combination of molecular electronics and conventional CMOS seems to have the potential to extend the exponential growth in computer power for another 50 years.
Three dimensions systems have fundamental problems. The interconnections needed to pass information through three dimensions are very complex. A three dimensional system is not defect tolerant. Separation of bits is also difficult in three dimensions.
Interfacing at the nano scale is difficult. There is a need for protection from fluctuations in the environment.
The nano scale is more than just about developing new computer technology. The nano scale is also about new materials that may serve other purposes, for example in medical treatments.
A big issue is whether the computing power that is foreseen will actually be needed. The answer to this question is that no one really knows. The same question could have been asked about electricity or Charles Babbage's mechanical analytical engine. It is an issue of human curiosity. If more powerful computers are not built then the potential will never be explored or discovered.
One potential benefit of more powerful computers would be to get rid of the keyboard and to be able to hold intelligent conversations with a computer.
Building powerful computers that are seen as being intelligent is an issue that needs to be discussed. Does society want computers that are capable of thinking? This is an open question.
The issue of knowing when to stop long term research was raised. This is important as there are examples of research that have been stopped just as the results were about to become highly relevant. There is a need for faith in ones work and results and determination to bring technologies to market.
Many things are open-ended. It is difficult to say something is impossible. Problems that are hard should not be dropped because often the solution to hard problems is very valuable.
Technology roadmaps for technology can be constructed. But one problem is how to create roadmaps for algorithms. It is very difficult to predict algorithms. At the moment there are not many good algorithms for quantum computation.
Computers have improved significantly over the years, but programmers have not improved to the same extent. There is a need to build machines that can decide how to work in parallel with programmers.
The notion of self-assembly is important. To be able to manufacture regular but defective structures and then to be able to work around these defects through self-assembly is a power concept.
One of the benefits of biology will be to show how to control complex systems and how to handle complexity, not how to do computing. Biology will provide the insights into how to do things differently.
Research that is high risk in its nature and long term and deals with strange ideas needs public funding. The question of return on investment should not be asked or a return expected. Public money should support high quality high-risk work regardless of return. It is an investment in society. It is impossible to state what is and is not valuable. The research should just be supported.
Conclusions and Future Directions
In the longer-term quantum computation may replace classical computation. These are challenges that need to be addressed in this particular field. An important question is how to design larger qubit gates. Scalability is a central and difficult issue. What is likely is a convergence between nanotechnology concepts and quantum optics. However whatever technology is used, the ability to scale up to larger and larger numbers of qubit gates will be a fundamental requirement of the technology. Small-scale qubit gates are very near in time, but large scale is far away and very large scale is a very far way.
Biology shows us that nature uses many different systems for storage and processing of information. Generally life does not care about the system as long as it works. This is an important point and its implications need to be understood. The direct incorporation of biological molecules in current microelectronic components is generally difficult if not impossible. The value of biological systems and molecules is that they offer interesting models that might provide new concepts for information technology.
The industrial interest in the area of molecular electronics is concerned with developing strategic technologies that might be useful in 10 to 15 year's time. These technologies are high risk, but are ones where the investment is counted in terms of millions of dollars and the potential payoff comes in billions of dollars.
The past several decades have seen a massive improvement in computer technology in terms of size shrinkage and reduction in the power cost of information processing. The question arises how much better can things get and how much further can developments move without resorting to quantum computing? The answer is that there is no physical law that says that efficiency improvements of another factor of one billion cannot be achieved! This could mean that there is no reason why in one handheld computer, consuming one watt of power, it should not be possible to achieve computer power equivalent to all the computers that are in existence in the year 2000! The challenge is how to do this - avoiding problems with physics and economics (in terms of the high costs of building fabrication facilities).
The challenge for molecular electronics is not the making switches, or wires or circuits. The main problem is interfacing between the micro scale world and the nano scale world.
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