Ferroelectric memristors may lead to brain-like computers

(Phys.org)—As electrical pulses travel through the body's nervous system, they are passed from neuron to neuron by synapses. A synapse, which consists of a gap junction and the cell membranes of the transmitting and receiving neurons on either side of this gap, has a structure that is a lot like the electrical component called a memristor. Memristors and synapses also function in a similar way: by remembering the resistance of a current passing through them, they enable memory.

In a new study, a team of researchers from France, the UK, and Japan has demonstrated that a device called a ferroelectric (FTJ) that experiences voltage-controlled resistance variation represents a new class of memristor. Due to the FTJ's quasi-continuous resistance variations exceeding two orders of magnitude, along with its rapid 10-ns , the device could one day serve as the basic hardware of neuromorphic computational architectures, or computers that function like brains.

The study, led by Agnès Barthélémy, a professor at Paris-Sud University in Orsay, France, is published in a recent issue of .

"We have conceptualized, designed and realized a completely new type of memristor that performs as well as classical ionic memristors, but operates through an electronic mechanism," coauthor Manuel Bibes, a CNRS research scientist, told Phys.org. "While this should have clear advantages in terms of reproducibility, the key breakthrough is that our ferroelectric memristor behaves according to well-established physical models. This allows a precise understanding of the memristive response, and also opens the door for engineering memristive functions on-demand."

An FTJ consists of two metal electrodes separated by a thin ferroelectric layer, with the ferroelectric material defined by its spontaneous . As previous research has shown, switching the polarization between "up" and "down" using an applied electric field changes the FTJ's electrical resistance from "low"/"on" to "high"/"off."

In the current study, the researchers have shown that they can produce a virtually continuous range of resistance levels between the low and high states by controlling the pulse amplitude, duration, and number of pulses. By applying a consecutive sequence of positive pulses, the researchers could gradually increase the resistance, demonstrating the cumulative effects of multiple pulses. Likewise, a sequence of negative pulses results in a gradual decrease in resistance.

To model the resistance switching dynamics, the researchers first analyzed the relative fraction of ferroelectric domains with "down" polarization orientation. The fraction of down domains varies from 0 in the "on" state to 1 in the "off" state. So the application of positive pulses increases the fraction of down domains, increases the resistance, and eventually leads to the "off" state. Negative pulses do the opposite.

Experimental tests showed that the fraction of down domains does not evolve smoothly with the application of pulses, but instead has more of a "wavy dependence." This type of evolution suggests that different zones of the FTJ have different switching dynamics, causing some zones to flip their domains more easily than others. The researchers modeled this observation by accounting for different propagation speeds and nucleation kinetics throughout the FTJ. Their model closely agrees with the experimental data.

The ability to reversibly tune the FTJ's resistance by more than two orders of magnitude by varying the pulse amplitude and/or number qualifies FTJs as memristive devices. And they're good ones, too, compared with previous purely electronic memristors where the resistance can be tuned over a range of no more than a factor of two.

These features make FTJ memristors promising components for brain-inspired computational architectures. In particular, the ability to change the level by applying consecutive pulses makes them appealing for fabricating artificial synapses, since the pulses act similarly to the consecutive spikes emitted by neurons.

"Ferroelectric memristors may be arranged in complex architectures to connect electronic neurons (typically based on CMOS elements), just as biological synapses connect to 'real' neurons on the brain," Bibes said. "If the number of both the neurons and the memristive connections between them is sufficiently large, the architecture may be used very efficiently to perform tasks such as pattern recognition, data mining, and eventually for 'learning.'"

In the future, the researchers plan to make further improvements in the memristors along with pursuing applications.

"On one hand, we want to get deeper into the physics of our ferroelectric memristors by studying, for instance, the role of the materials involved (not only the ferroelectric but also the electrodes)," Bibes said. "On the other hand, we also plan to build small-scale neuromorphic architectures and run brain-inspired computing tasks."

Explore further

Memristors: 'Computer synapse' analyzed at the nanoscale

More information: Andre Chanthbouala, et al. "A ferroelectric memristor." Nature Materials 11, 860–864 (2012) DOI:10.1038/nmat3415
Journal information: Nature Materials

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Oct 04, 2012
Looks like humans may be the ancestors afterall, to be displaced all too soon...

Oct 04, 2012
If computers became more brain/human like, then it will randomly melt down, talk too much, be irrational with only 20 minutes of actual productivity in one day. This is the future of computing. I can't wait.

Oct 04, 2012
Computers will literally have minds of their own.

Oct 04, 2012

You mean Microsoft already built it?

Oct 04, 2012
"Memristors and synapses also function in a similar way: by remembering the resistance of a current passing through them, they enable memory."

That is not an accurate depiction of neuron functioning from neurobiology.

A neuron is a whole damn universe of complexity, and very little like a memristor circuit. Science not only cannot make the statement I quoted from the article, it cannot explain how neurons give rise to minds.

Y'know, this sort of self-puffery in computer science isn't new. Back in the day, when analog computing was still competing with digital for supremacy, some of its advocates mouthed off in exactly the same way. "Analog computer junctions are just like neurons!" they gushed.

Memristors may not be the dead end that analog computing proved to be, but if not, it still says nothing about how minds are formed and operate.


Oct 04, 2012
I am writing to program the Bible and the Koran into the first commercial memristors-based brain! should be a blast to see what it will do! On second thoughts, one for each! and then let them argue!

Oct 05, 2012
I know absolutely nothing about any of this, but it sounds pretty cool. I'll stick to Physics of Systems and Econ.

Oct 08, 2012
A ferroelectric memristor was invented several years ago- Patent UA #76691 "The control method of the electromagnetic flow intensity and amplifying elements on its basis" (Bull. 9, 2006- www.frontiersin.o..._people) and further developed in my papers: "CNT and Organic FETs Based Two-Way Transducing of the Neurosignals", in: Nanotech 2008 vol. 2, Cambridge, MA, USA, CRC Press, vol. 2, chapt. 6: Nano Medicine & Neurology, pp. 475-478 (www.nsti.org/proc.../M81.404 or www.frontiersin.o..._people) and "Analytical Treatment of the Signal Propagation in an EM Transistor/Memristor (EMTM)", INDS'09, July 20–21, 2009, Klagenfurt, Austria, pp. 116-120 (ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5228000); also some others.

Oct 08, 2012
It accumulates it, usually with electrochemical reaction similar to chemical reaction in battery. For example titanium dioxide based memristor is getting reduced to lower oxidation state when the current flows through it and becomes gradually more and more conductive, because the titanium suboxide formed has a metallic conductivity. You should know about it, if you're spreading private theories about it.

Oct 09, 2012
So from the perspective of the comments here a memristor is akin to an NTC or PTC resistor but without the thermal/temperature effect and with an added non-volatile memory ?

Please no lectures, been doing electrical/electronic/power engineering for decades, just looking for opinions on the overlapping paradigms and models applicable to circuit designs etc and 'other', should make it open enough...

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