Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

An atomic switch network, showing (a) the array of platinum electrodes and (b) an SEM image of self-organized silver nanowires on a grid of copper posts. Overlapping junctions of wires form atomic switches. Scale bar = 500 µm. Credit: Demis, et al. ©2015 IOP Publishing

IOP Science Nanotechnology – Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

Researchers at UCLA and the National Institute for Materials Science in Japan have developed a method to fabricate a self-organized complex device called an atomic switch network that is in many ways similar to a brain or other natural or cognitive computing device.

“Complex phenomena and self-organization—though ubiquitous in nature, social behavior, and the economy—have never been successfully used in conventional computers for prediction and modelling,” James Gimzewski, Chemistry Professor at UCLA, told Phys.org. “The device we have created is capable of rapidly generating self-organization in a small chip with high speed. Furthermore, it bypasses the issue of exponential machine complexity required as a function of problem complexity as in today’s computers. Our first steps form the basis for a new type of computation that is urgently needed in our ever increasingly connected world.”

As the researchers explain, an atomic switch is a nanoscale device that exhibits memristive resistance, meaning that it adjusts its resistance to an applied current or voltage based on its memory of previous encounters. This trait is essential for complex systems because it underlies the ability to learn, interact with the environment, and address problems in which data is constantly changing or incomplete.

Although some natural computing devices use natural materials, the atomic switch network developed here is made entirely of inorganic materials. Lithographically patterned copper posts form a “patterned seed network,” on top of which silver nanowires are grown. The end result is a network of silver sulfide switches and silver nanowires that connect the switches.

Experiments demonstrated that the atomic switch network exhibits emergent behavior, in which interactions between the individual atomic switches lead to patterns of electrical activity that cannot be attributed to any individual switch, but only to the network as a whole. The atomic switch network also has an intrinsic capacity for adaptation, since the silver nanowire connections are constantly reconfiguring themselves and the switches are constantly forming and dissolving in different locations in the network.

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