Researchers led by Qiangfei Xia and Joshua Yang at the University of Massachusetts at Amherst in the US have made a "diffusive" memristor that emulates how a real synapse works. The device could be used as a key element in integrated circuits and next-generation computers that mimic how the human brain works.
Computers that function more like the human brain rather than conventional digital systems would be based on neuronal-like networks rather than series of binary 1s and 0s. They would be able to more easily deal with the vast data sets currently being generated around the world thanks to being massively parallel. To make these new generation of machines, researchers need to develop simple, energy-efficient electronic devices that mimic the brain’s building blocks – neurons and synapses.
The new device is made from a memory resistor or memristor (a resistor that “remembers” how much current has flowed through it). Unlike other modern-day electronics memories like those made from CMOS devices, memristors are able to remember their state (that is the information stored in them) even if you lose power. They also use much less energy and, importantly, so-called diffusive memristors can realistically mimic how ions, such as Ca2+, diffuse through synapses.
Synapses are the biological junctions between neurons and Ca2+ is a vital element in the process of neurotransmitter release between synapses.
“In our memristors, we looked at how metallic atoms, like silver (Ag) or copper (Cu), diffuse through dielectric oxide materials,” explains Yang. “The way these metals diffuse through a dielectric is very similar, physically, to the way Ca2+ diffuses through channels in biological synapses.”
The researchers made their silver-in-oxide memristors with two Pt or Au inert electrodes sandwiching a switching layer of a dielectric film with embedded Ag nanoclusters.
“The device is essentially a volatile memristor where Ag atoms diffuse under the influence of electrical bias,” says Yang. “This electrical stimulation turns on the devices to their low resistance state, forming a nanoscale conduction channel of Ag (around 4 nm in diameter). When the electrical bias is removed, the device spontaneously relaxes back to its high resistance state thanks to the silver channel reshaping into spherical silver clusters.
“The way the clusters relax, which we revealed using in situ high-resolution transmission electron microscopy for the first time, suggests that the relaxation dynamics is driven by the minimization of the interfacial energy between the silver and the dielectric material surrounding the silver nanoclusters,” he adds.
The devices might find use in a variety of applications in both neuromorphic computing and biology, he tells nanotechweb.org. “For computing applications diffusive memristors with fast switching speeds (that is, of less than a microsecond) could be used as selectors to enable large memristor crossbar arrays for non-volatile memory applications. Devices with slower switching speeds (of above a microsecond) might be used as neuromorphic emulators. These could allow us to make more bio-realistic artificial synapses with higher fidelity that could help neurobiologists better understand - and replicate – how real synapses work.”
The team, which includes researchers from Loughborough University in the UK, Hewlett Packard Labs in Palo Alto, California, and the Brookhaven National Laboratory, in Upton, New York, says that it is now busy trying to understand how the nanodevices work in more detail. “We will then be able to engineer the devices, optimize them and integrate them into large scale arrays for different applications,” says Yang.
The memristor is detailed in Nature Materials doi:10.1038/nmat4756.