New ion-based device that operates like a brain synapse

MIT researchers, including Professors Ju Li and Bilge Yildiz, have made strides toward a neural network system using physical, analog devices that can much more efficiently mimic brain processes. Neural networks attempt to simulate the way learning takes place in the brain, which is based on the gradual strengthening or weakening of the connections between neurons, known as synapses.

So far, most candidate analog resistive devices for such simulated synapses have either been very inefficient, in terms of energy use, or performed inconsistently from one device to another or one cycle to the next. The new system overcomes both of these challenges--the resistive switch is an electrochemical device, which is made of tungsten trioxide (WO3) and works in a way similar to the charging and discharging of batteries. Ions, in this case protons, can migrate into or out of the crystalline lattice of the material, explains Yildiz, depending on the polarity and strength of an applied voltage. These changes remain in place until altered by a reverse applied voltage — just as the strengthening or weakening of synapses does.