Researchers at the MESA+ Institute for Nanotechnology and the CTIT Institute for ICT Research at the University of Twente in the Netherlands have developed functional electronic circuits using a novel method that resembles Darwinian evolution. In terms of size, the new circuits are comparable to their conventional counterparts, but are much more similar to natural networks, such as the human brain.
The findings have been published in the leading British journal Nature Nanotechnology.
One of the key ways in making computers – arguably, the most important invention of the 20th century – more powerful is by integrating more and more tiny components on silicon chips. The process of miniaturisation, however, is exceedingly difficult and costly – producing chips that have millions of transistors (which are now comprised of only a handful of atoms) with the same characteristics is a major challenge. Couple that with unsustainable levels of energy consumption and we clearly have a problem.
Faced with these challenges, researchers are increasingly turning back to the natural world for inspiration – after all, evolution has led to such powerful computing substrates as organic brains, capable of solving many tasks in parallel without demanding a lot of energy.
The new “designless” systems (which do away with conventional circuits altogether) have been built by plugging gold nanoparticles, charged with the task of carrying out all of the essential computational tasks, into a process of artificial evolution that takes less than an hour, rather than millions of years.
By applying electrical signals, a single network can be configured into 16 different logic gates. This approach works around – and can even use to its advantage – potential material defects that would be fatal in conventional electronics. This is the first time scientists had succeeded in realising electronics with dimensions that can compete with commercial technology.
According to Prof. Wilfred van der Wiel, these circuits currently still have limited computing power. “But with this research we have delivered proof of principle: demonstrated that our approach works in practice. By scaling up the system, real added value will be produced in the future. Take for example the efforts to recognize patterns, such as with face recognition. This is very difficult for a regular computer, while humans and possibly also our circuits can do this much better.”
Given that these new systems are not reliant on regular circuits, the research team hopes they will be much less expensive to manufacture and will consume significantly less energy when made. Potential applications vary from various medical devices to portable electronics.