Brain-Like Computing Chips: A New Era In Electronics


Scientists have revealed a radically new ‘neurochip’ that can work like neurons or human brain. The neural network based on polymeric memristors (devices that can potentially be used to build fundamentally new computers) can help in creating technologies for machine vision, hearing, and other machine sensory systems and also for intelligent control systems in various applications, including autonomous robots.

The researchers focused on the field of memristive neural networks or polymer-based memristors and demonstrated that it is possible to create very simple polyaniline-based neural networks. Furthermore, these networks are able to learn and perform specified logical operations. Scientists from the Kurchatov Institute, MIPT, the University of Parma (Italy), Moscow State University, and Saint Petersburg State University were involved in the breakthrough.

A memristor is an electric element similar to a conventional resistor. The difference between a memristor and a traditional element is that the electric resistance in a memristor is dependent on the charge passing through it, therefore it constantly changes its properties under the influence of an external signal.


A memristor has a memory and at the same time is also able to change data encoded by its resistance state. Therefore,  it is similar to a synapse (a connection between two neurons in the brain) and enables scientists to build a true neural network. Scientists predict that they also can be made as small as conventional chips with their size reduced up to ten nanometers.

Using a polyaniline solution, a glass substrate, and chromium electrodes, the scientists created a prototype with dimensions that, at present, are much larger than those typically used in conventional microelectronics. The strip of the structure was approximately one millimeter wide.

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All of the memristors were tested for their electrical characteristics. It was found that the current-voltage characteristic of the devices is non-linear, which is in line with expectations. This means that if you gradually increase the voltage supplied to the memristor, it will increase the current passing through it not in a linear fashion, but with a sharp bend in the graph and at a certain point its resistance will fall sharply.

Scientists found that the polyaniline memristors were able to emulate the function of the brain’s synapses between its neurons. After checking the basic properties of individual memristors, they conducted experiments to train the neural network and found that the new memristive network was capable of performing NAND and NOR logical operations. In addition to downsizing to nanoscales, the researchers further want to explore multi-layer neural networks using stacking network layers vertically into 3-D structures.



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