Tag Archives: phase-change materials

Memristive capabilities from IBM (International Business Machines)

Does memristive mean it’s like a memristor but it’s not one? In any event, IBM is claiming some new ground in the world of cognitive computing (also known as, neuromorphic computing).

An artistic rendering of a population of stochastic phase-change neurons which appears on the cover of Nature Nanotechnology, 3 August 2016. (Credit: IBM Research)

An artistic rendering of a population of stochastic phase-change neurons which appears on the cover of Nature Nanotechnology, 3 August 2016. (Credit: IBM Research)

From an Aug. 3, 2016 news item on phys.org,

IBM scientists have created randomly spiking neurons using phase-change materials to store and process data. This demonstration marks a significant step forward in the development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing.

Inspired by the way the biological brain functions, scientists have theorized for decades that it should be possible to imitate the versatile computational capabilities of large populations of neurons. However, doing so at densities and with a power budget that would be comparable to those seen in biology has been a significant challenge, until now.

“We have been researching phase-change materials for memory applications for over a decade, and our progress in the past 24 months has been remarkable,” said IBM Fellow Evangelos Eleftheriou. “In this period, we have discovered and published new memory techniques, including projected memory, stored 3 bits per cell in phase-change memory for the first time, and now are demonstrating the powerful capabilities of phase-change-based artificial neurons, which can perform various computational primitives such as data-correlation detection and unsupervised learning at high speeds using very little energy.”

An Aug. 3, 2016 IBM news release, which originated the news item, expands on the theme,

The artificial neurons designed by IBM scientists in Zurich consist of phase-change materials, including germanium antimony telluride, which exhibit two stable states, an amorphous one (without a clearly defined structure) and a crystalline one (with structure). These materials are the basis of re-writable Blu-ray discs. However, the artificial neurons do not store digital information; they are analog, just like the synapses and neurons in our biological brain.

In the published demonstration, the team applied a series of electrical pulses to the artificial neurons, which resulted in the progressive crystallization of the phase-change material, ultimately causing the neuron to fire. In neuroscience, this function is known as the integrate-and-fire property of biological neurons. This is the foundation for event-based computation and, in principle, is similar to how our brain triggers a response when we touch something hot.

Exploiting this integrate-and-fire property, even a single neuron can be used to detect patterns and discover correlations in real-time streams of event-based data. For example, in the Internet of Things, sensors can collect and analyze volumes of weather data collected at the edge for faster forecasts. The artificial neurons could be used to detect patterns in financial transactions to find discrepancies or use data from social media to discover new cultural trends in real time. Large populations of these high-speed, low-energy nano-scale neurons could also be used in neuromorphic coprocessors with co-located memory and processing units.

IBM scientists have organized hundreds of artificial neurons into populations and used them to represent fast and complex signals. Moreover, the artificial neurons have been shown to sustain billions of switching cycles, which would correspond to multiple years of operation at an update frequency of 100 Hz. The energy required for each neuron update was less than five picojoule and the average power less than 120 microwatts — for comparison, 60 million microwatts power a 60 watt lightbulb.

“Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses, could be a key enabler for the creation of a new generation of extremely dense neuromorphic computing systems,” said Tomas Tuma, a co-author of the paper.

Here’s a link to and a citation for the paper,

Stochastic phase-change neurons by Tomas Tuma, Angeliki Pantazi, Manuel Le Gallo, Abu Sebastian, & Evangelos Eleftheriou. Nature Nanotechnology  11, 693–699 (2016) doi:10.1038/nnano.2016.70 Published online 16 May 2016

I gather IBM waited for the print version of the paper before publicizing the work. The online version is behind paper. For those who can’t get past the paywall, there is a video offering a demonstration of sorts,

For the interested, the US government recently issued a white paper on neuromorphic computing (my Aug. 22, 2016 post).

This team has published a paper that has a similar theme to the one in Nature Nanotechnology,

All-memristive neuromorphic computing with level-tuned neurons by Angeliki Pantazi, Stanisław Woźniak, Tomas Tuma, and Evangelos Eleftheriou. Nanotechnology, Volume 27, Number 35  DOI: 10.1088/0957-4484/27/35/355205 Published 26 July 2016

© 2016 IOP Publishing Ltd

This paper is open access.

An Aug. 18, 2016 news piece by Lisa Zyga for phys.org provides a summary of the research in the July 2016 published paper.

Research into phase changes in solids and control

A July 28, 2015 news item on ScienceDaily describes some practical reasons for research into phase changes from the Institute of Photonic Sciences (ICFO) in Spain in collaboration with Firtz-Haber-Institut der Max-Planck-Gesellschaft,

Rewritable CDs, DVDs and Blu-Ray discs owe their existence to phase-change materials, those materials that change their internal order when heated and whose structures can be switched back and forth between their crystalline and amorphous phases. Phase-change materials have even more exciting applications on the horizon, but our limited ability to precisely control their phase changes is a hurdle to the development of new technology.

A July 28, 2015 ICFO news release (also on EurekAlert), which originated the news item, describes the problem and the researchers’ solution,

One of the most popular and useful phase-change materials is GST, which consists of germanium, antimony, and tellurium. This material is particularly useful because it alternates between its crystalline and amorphous phases more quickly than any other material yet studied. These phase changes result from changes in the bonds between atoms, which also modify the electronic and optical properties of GST as well as its lattice structure. Specifically, resonant bonds, in which electrons participate in several neighboring bonds, influence the material’s electro-optical properties, while covalent bonds, in which electrons are shared between two atoms, influence its lattice structure. Most techniques that use GST simultaneously change both the electro-optical and structural properties. This is actually a considerable drawback since in the process of repeating structural transitions, such as heating and cooling the material, the lifetime of any device based on this material is drastically reduced.

In a study recently published in Nature Materials, researchers from the ICFO groups led by Prof. Simon Wall and ICREA Prof. at ICFO Valerio Pruneri, in collaboration with the Firtz-Haber-Institut der Max-Planck-Gesellschaft, have demonstrated how the material and electro-optical properties of GST change over fractions of a trillionth of a second as the phase of the material changes. Laser light was successfully used to alter the bonds controlling the electro-optical properties without meaningfully altering the bonds controlling the lattice. This new configuration allowed the rapid, reversible changes in the electro-optical properties that are important in device applications without reducing the lifetime of the device by changing its lattice structure. Moreover, the change in the electro-optical properties of GST measured in this study is more than ten times greater than that previously achieved by silicon materials used for the same purpose. This finding suggests that GST may be a good substitute for these commonly used silicon materials.

The results of this study may be expected to have far-reaching implications for the development of new technologies, including flexible displays, logic circuits, optical circuits, and universal memory for data storage. These results also indicate the potential of GST for other applications requiring materials with large changes in optical properties that can be achieved rapidly and with high precision.

Here’s a link to and a citation for the paper,

Time-domain separation of optical properties from structural transitions in resonantly bonded materials by Lutz Waldecker, Timothy A. Miller, Miquel Rudé, Roman Bertoni, Johann Osmond,  Valerio Pruneri, Robert E. Simpson, Ralph Ernstorfer, & Simon Wall. Nature Materials (2015)
doi:10.1038/nmat4359 Published online 27 July 2015

This paper is behind a paywall.