Communications of the ACM
Carbon Nanotube Computing?
Bright colors represent localized heating which suggests conductive pathways within the liquid crystal-based nanotube material.
Credit: Mark K. Massey / Durham University
As circuitry approaches the miniaturization limits of conventional electronics, alternatives to silicon-based transistors — the building blocks of everyday electronics — are being hotly pursued.
Inspired by the way living organisms have evolved in nature to perform complex tasks with remarkable ease, a group of researchers from Durham University in the U.K. and the University of São Paulo-USP in Brazil is exploring similar "evolutionary" methods to create information processing devices.
In "Computing with Carbon Nanotubes: Optimization of Threshold Logic Gates using Disordered Nanotube/Polymer Composites," published in the Journal of Applied Physics, from AIP Publishing, the group describes using single-walled carbon nanotube composites (SWCNTs) as a material in "unconventional" computing. By studying the mechanical and electrical properties of the materials, they discovered a correlation between SWCNT concentration/viscosity/conductivity and the computational capability of the composite.
"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," says Mark K. Massey, a research associate in the School of Engineering and Computing Sciences at Durham University.
This emerging field of research is known as "evolution in materio," a term coined by Julian Miller at the University of York in the U.K., referring to an interdisciplinary field that blends 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 says. "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 electronics devices," Massey says. The approach may find applications within the realm of "analog signal processing or low-power, low-cost devices in the future," he says.
Beyond pursuing the current methodology of evolution in materio, the next stage of the group's research will be to investigate evolving devices as part of the material fabrication "hardware-in-the-loop" evolution. "This exciting approach could lead to further enhancements in the field of evolvable electronics," Massey says.
The group's research is part of the Nanoscale Engineering for Novel Computation using Evolution project, which is funded by the European Union.
The Journal of Applied Physics article is authored by M.K. Massey, A. Kotsialos, F. Qaiser, D.A. Zeze, C. Pearson, D. Volpati, L. Bowen, and M.C. Petty. The authors are affiliated with Durham University and the University of São Paulo-USP.
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