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The missing link between spaghetti sauce & Memristors: Labs researchers solve a 50-year-old mystery

memristorgraphic.PNGBy Curt Hopkins, Managing Editor, Hewlett Packard Labs

Today, two Labs researchers, Suhas Kumar and HPE Senior Fellow Stan Williams, published a paper in Nature Communications that solves a long-standing mystery about how electrical current can flow through electronic devices that have a strongly nonlinear relation between voltage (v) and current (i), i.e. that do not obey the standard Ohm’s law v = iR, where R is the resistance of a usual resistor.

In “Separation of current density and electric field domains caused by nonlinear electronic instabilities,” Kumar and Williams explain their successful investigation into the mechanism by which memristors and other electronic devices, even including transistors, can become unstable and respond by simultaneously conducting electric current at two different densities.

On a particular poetic note is the fact that this year is the 10-year anniversary of Williams’ discovery of the Memristor, or, more accurately, his development of the first physical expression of Leon Chua’s identification of the theoretical memristor.

Here is how they put it in their abstract.

In 1963 Ridley postulated that under certain bias conditions circuit elements exhibiting a current- or voltage-controlled negative differential resistance will separate into coexisting domains with different current densities or electric fields, respectively, in a process similar to spinodal decomposition of a homogeneous liquid. The ensuing debate, however, failed to agree on the existence or causes of such electronic decomposition. Using thermal and chemical spectro-microscopy, we directly imaged signatures of current-density and electric field domains in several metal oxides. The concept of local activity successfully predicts initiation and occurrence of spontaneous electronic decomposition, accompanied by a reduction in internal energy, despite unchanged power input and heat output. This reveals a thermodynamic constraint required to properly model nonlinear circuit elements. Our results explain the electroforming process that initiates information storage via resistance switching in metal oxides and has significant implications for improving neuromorphic computing based on nonlinear dynamical devices.

If you understood that, congratulations. But for those of us who do not work on memristor technology, Kumar was good enough to provide a lay person’s version. It starts, as all good science stories do, with pasta.

Here is how Kumar explains it.

When you cook a pasta sauce, you will often notice that a mixture of water and oil blends together to form a uniform liquid (known as a homogeneous liquid mixture) when the heat is high. But once you turn the heat off, the oil can separate out of the uniform liquid and float to the top. The uniform oil-water mixture was stable at high temperatures; but at low temperatures, the mixture became unstable so the two components separated (known as spinodal decomposition). This is why many recipes suggest that it is easier to mix different ingredients when they are hot. One can actually predict this behavior using theories of thermodynamics, the same theories that allow us to build refrigerators and car engines.

What we have shown both experimentally and with the theory of ‘Local Activity’ created by Leon Chua is that similar instabilities can happen in electronic devices, too. For example, the electrical current in devices that have negative differential resistance, for which the current decreases when the voltage is increased, or vice versa, can become unstable like the cooled oil and water mixture. We figured out that a similar thermodynamic process that happens in a liquid mixture can also happen in electronic devices. If one applies an electric current within an unstable region of operation, the current will "decompose" into two parallel currents with different densities, one representing ‘oil’ and the other ‘water’.

This phenomenon and its connection to the thermodynamics behind liquid mixture separation was what many famous physicists struggled with for more than 50 years. Our discovery has also allowed us to create a simple new model for certain types of memristor behavior. Our improved understanding is helping us to look at our recent description of a new type of computer (described last year in a paper published in Nature) that employs chaos to speed up computation in a circuit that emulates brain function. Every time we open up a door, we find a new one that beckons us onward.

Read the full paper on Nature Communications.

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Managing Editor, Hewlett Packard Labs