The image demonstrates the design of an artificial brain built using a nano-brain reported in this issue of PNAS. Several molecular nano-brain are arranged in a way to work as powerful as our central nervous system. Numerical digits and alphabets float across the architecture demonstrating a matrix generated during a real-time operation similar to the Hollywood blockbuster The Matrix. Credit: Arindam Bandyopadhyay
A powerful new molecular computing device and architecture is making progress. Hat tip: Center for Responsible nanotechnology This looks like a promising approach to radically more powerful computers and a possible pathway to very interesting and powerful molecular devices, machines and factories. The researchers are predicting within 18 months to have 1024 machines working together. They may also be working with Nanoink (maker of dip lithography arrays) for the input and output to the devices. A 2 inch sphere of the devices would equal the computing power of the human brain.
The device can simultaneously carry out 16 times more operations than a normal computer transistor. Researchers suggest the invention might eventually prove able to perform roughly 1,000 times more operations than a transistor.
This machine could not only serve as the foundation of a powerful computer, but also serve as the controlling element of complex gadgets such as microscopic doctors or factories, scientists added.
The device is made of a compound known as duroquinone. This molecule resembles a hexagonal plate with four cones linked to it, “like a small car,” explained researcher Anirban Bandyopadhyay, an artificial intelligence and molecular electronics scientist at the National Institute for Materials Science at Tsukuba in Japan.
Bandyopadhyay and his colleagues revealed they could hook up eight other such “molecular machines” to their invention, working together as if they were part of a miniature factory.
Bandyopadhyay added they could expand their device from a two-dimensional ring of 16 duroquinones around the center to a three-dimensional sphere of 1,024 duroquinones. This means it could perform 1,024 instructions at once, for 4**1024 different outcomes — a number larger than a 1 with 1,000 zeroes after it. They would control the molecule at the center of the sphere by manipulating “handles” sticking out from the core.
“We are definitely going to 3-D from 2-D immediately,” Bandyopadhyay said.
The abstract of the paper: A 16-bit parallel processing in a molecular assembly
A machine assembly consisting of 17 identical molecules of 2,3,5,6-tetramethyl-1–4-benzoquinone (DRQ) executes 16 instructions at a time. A single DRQ is positioned at the center of a circular ring formed by 16 other DRQs, controlling their operation in parallel through hydrogen-bond channels. Each molecule is a logic machine and generates four instructions by rotating its alkyl groups. A single instruction executed by a scanning tunneling microscope tip on the central molecule can change decisions of 16 machines simultaneously, in four billion (4**16) ways. This parallel communication represents a significant conceptual advance relative to today’s fastest processors, which execute only one instruction at a time.
[multilevel logic | parallel communication | self-assembly]
Using electrical pulses from the tip of a scanning tunneling microscope, the researchers could flip the control molecule to any one of four configurations, or states. Those flips, in turn, could change the states of the other 16 molecules – just as, say, knocking down one domino can simultaneously set off several chains of falling dominoes.
Mark Ratner, a chemist at Northwestern University who specializes in nanotechnology, said the newly published research represented a significant step toward molecular-scale computers as well as molecular-scale medicine. “People have been talking about both these things for a long time,” Ratner told me. “People have even thought about putting these two things together. … But this is quite pretty because [the researchers] actually use all of the constituents, and that’s really neat.”
“Is it useful tomorrow? No,” he said.
One of the biggest conceptual hurdles has to do with the input/output device: Although the assemblies themselves are at the molecular scale, the scanning tunneling microscope is a big piece of equipment. It wouldn’t be practical to use those microscopes to read out the result of a nanocomputer, or harvest the chemicals produced by nanofactories.
Bandyopadhyay said other control methods would be developed for working devices – perhaps optical readers for the nanocomputers, or chemical triggers for the medical nanochips. Ratner said several companies, including an outfit called NanoInk, were working on technologies that might work. [Nanoink created the the dip pen lithography arrays (tens of thousands and million AFMs working in parallel.]
In the meantime, Bandyopadhyay is working to ramp up his molecular machines from two-dimensional arrays to three-dimensional structures. “Within one and a half years we will have 1,024 machines connected,” he told me.
Theoretically, the technology could allow for the development of a super-duper information processor contained in a sphere less than 2 inches in diameter, Bandyopadhyay said.
“That will contain the equal amount of components and connectivity that is required inside our brain,” he told me.
For Bandyopadhyay, this is just a starting point for building up to more complex assemblies of quinone molecules. ‘Now the architecture is like a disk on a surface; I will build a spherical one and realize similar “one to many” communication on that structure’s surface,’ he says.
However, computation experts contacted by Chemistry World are not yet convinced that this is the way forward. It is not clear, one expert said, whether this system can actually perform parallel computation, or whether it only acts as a hub that distributes a signal. Without a clear demonstration of parallel computation, the work is ‘clearly clever, but probably unimportant,’ he said.
I think there are challenges ahead but it looks like it can be adapted to a parallel 3d architecture that does computation.