New generations of memristors could reliably store information directly within the molecular structures of graphene-like materials. In a new review published in Nanoenergy Advances, Gennady Panin of the Russian Academy of Sciences shows how these atomically thin materials are ideally suited for electrical circuits that mimic the function of our own brains—and could help address the vast power requirements of emerging AI technologies.

A memristor is a cutting-edge electrical component whose resistance depends on the amount of current that previously passed through it. Because it “remembers” this history even after charge is no longer flowing, it can store data when the power is switched off. In this way, memristors operate in a way remarkably similar to the neurons in our brains and the synapses connecting them.

With their fast response times, combined with simple, two-electrode structures that allow them to be packed into dense arrays, memristors are increasingly forming the building blocks of modern circuits—especially those designed for AI.