The group’s work, reported in the Journal of Applied Physics, centres around the use of single-walled carbon nanotube composites (SWCNTs) as a material in ’unconventional’ computing.
“Instead of creating circuits from arrays of discrete components (transistors in digital electronics), our work takes a random disordered material and then ‘trains’ the material to produce a desired output,” explained Mark K. Massey, research associate, School of Engineering and Computing Sciences at Durham University.
This emerging field of research is known as ’evolution-in-materio,’ and blends together materials science, engineering and computer science.
Although still in its early stages, the concept has already shown that by using an approach similar to natural evolution, materials can be trained to mimic electronic circuits without needing to design the material structure in a specific way.
“The material we use in our work is a mixture of carbon nanotubes and polymer, which creates a complex electrical structure,” Massey said in a statement. “When voltages (stimuli) are applied at points of the material, its electrical properties change. When the correct signals are applied to the material, it can be trained or ‘evolved’ to perform a useful function.”
While the group doesn’t expect to see their method compete with high-speed silicon computers, it could turn out to be a complementary technology.
“With more research, it could lead to new techniques for making electronic devices,” he said. The approach may find applications within the realm of “analog signal processing or low-power, low-cost devices in the future.”
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