Memristor technology to make computers operate like human brain

Brain-like computing is a step closer after US researchers devised a new material to build more functional memristors for complex electronic circuits.

Researchers at Northwestern University changed the way memory resistors work – the resistors in a circuit that ‘remember’ how much current has flowed through them – to function more like a network of neurons.

Mark Hersam, the Bette and Neison Harris Chair in Teaching Excellence in Northwestern University’s McCormick School of Engineering, said: “Memristors could be used as a memory element in an integrated circuit or computer.

“Unlike other memories that exist today in modern electronics, memristors are stable and remember their state even if you lose power.”

Most computers use RAM, which moves quickly as a user works, but does not retain unsaved data if power is lost, while flash drives can store information when they are not powered but work much more slowly.

Although a memristor could provide a memory that is both fast and reliable, the fact that it is a two-terminal electronic device means that it can only control one voltage channel.

But scientists transformed it into a three-terminal device by using an atomically thin, two-dimensional nanomaterial conductor – single-layer molybdenum disulphide (MoS2). This way when a large electric field is applied the grain boundary literally moves, causing a change in resistance.

“Because the atoms are not in the same orientation, there are unsatisfied chemical bonds at that interface,” Hersam explained. “These grain boundaries influence the flow of current, so they can serve as a means of tuning resistance.”

The method allowed the team to present a novel three-terminal memristive device that is widely adjustable with a gate electrode.

“With a memristor that can be tuned with a third electrode, we have the possibility to realise a function you could not previously achieve, Hersam said. “A three-terminal memristor has been proposed as a means of realising brain-like computing. We are now actively exploring this possibility in the laboratory.”

The research was published this week in the journal Nature Nanotechnology.

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