The device, known as memristor, was able to “remember” stored images, reproducing them several times with little noise.
Engineers at the Massachusetts Institute of Technology (MIT), in the United States, developed a chip composed of memristors, tens of thousands of artificial brain synapses. The results of the discovery were published on Tuesday (08) in the journal Nature Nanotechnology.
Memristors are made from silver, copper, and silicon. They are devices capable of mimicking the way the human brain transmits information. When scientists tested the chip in various visual tasks, it was able to “remember” the images stored on it and reproduce them several times, very clearly, and with little noise.
According to scientists, memory transistors (memristors) are essential for the development of neural implants, as they serve as a circuit of transmitters. Like a cerebral synapse, a memristor is also able to “remember” the value associated with a given current strength and produce exactly the same signal the next time it receives a similar current.
Existing memristors have limited performance, as they are composed of a positive and negative electrode. When a voltage is applied to one side of the mechanism, the electrode ions flow through the medium that separates one device from the other, forming a “conduction channel” to the other electrode, transmitting the “message”.
According to MIT engineers, existing memristors work very well in cases where the voltage stimulates a large conduction channel or an intense flow of ions from one electrode to another. However, this effectiveness decreases when the devices need to generate more subtle signals, through more “thin” conduction channels.
The smaller the flow of ions from one electrode to the other, the more difficult it is for these particles to stay together, which can cause them to separate. As a result, it is difficult for the receiving electrode to capture and therefore transmit the same signal when stimulated.
The new memristors
Generally, the positive electrode of a memristor is composed of silver – so the MIT team decided to look for an element that they could combine with silver to effectively keep the ions together, allowing them to flow quickly through the device. The scientists ended up concluding that copper would be the ideal material, as it is able to bind both with silver and silicon.
“So far, artificial synapse networks exist as software. We’re trying to build real neural network hardware for portable artificial intelligence systems,” explained Jeehwan Kim, associate professor of mechanical engineering at MIT and co-author of the study, in a statement. “Imagine connecting a neuromorphic device to a camera on your car, and having it recognize lights and objects and make a decision immediately, without having to connect to the internet. We hope to use energy-efficient memristors to do those tasks on-site, in real-time.”