Tag Archives: Tsuyoshi Hasegawa

Studying quantum conductance in memristive devices

A September 27, 2022 news item on phys.org provides an introduction to the later discussion of quantum effects in memristors,

At the nanoscale, the laws of classical physics suddenly become inadequate to explain the behavior of matter. It is precisely at this juncture that quantum theory comes into play, effectively describing the physical phenomena characteristic of the atomic and subatomic world. Thanks to the different behavior of matter on these length and energy scales, it is possible to develop new materials, devices and technologies based on quantum effects, which could yield a real quantum revolution that promises to innovate areas such as cryptography, telecommunications and computation.

The physics of very small objects, already at the basis of many technologies that we use today, is intrinsically linked to the world of nanotechnologies, the branch of applied science dealing with the control of matter at the nanometer scale (a nanometer is one billionth of a meter). This control of matter at the nanoscale is at the basis of the development of new electronic devices.

A September 27, 2022 Istituto Nazionale di Ricerca Metrologica (INRIM) press release (summary, PDF, and also on EurekAlert), which originated the news item, provides more information about the research,

Among these, memrisistors are considered promising devices for the realization of new computational architectures emulating functions of our brain, allowing the creation of increasingly efficient computation systems suitable for the development of the entire artificial intelligence sector, as recently shown by INRiM researchers in collaboration with several international universities and research institutes [1,2].

In this context, the EMPIR MEMQuD project, coordinated by INRiM, aims to study the quantum effects in such devices in which the electronic conduction properties can be manipulated allowing the observation of quantized conductivity phenomena at room temperature. In addition to analyzing the fundamentals and recent developments, the review work “Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications” recently published in the prestigious international journal Advanced Materials (https://doi.org/10.1002/adma.202201248) analyzes how these effects can be used for a wide range of applications, from metrology to the development of next-generation memories and artificial intelligence.

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

Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications by Gianluca Milano, Masakazu Aono, Luca Boarino, Umberto Celano, Tsuyoshi Hasegawa, Michael Kozicki, Sayani Majumdar, Mariela Menghini, Enrique Miranda, Carlo Ricciardi, Stefan Tappertzhofen, Kazuya Terabe, Ilia Valov. Advanced Materials Volume 34, Issue32 August 11, 2022 2201248 DOI: https://doi.org/10.1002/adma.202201248 First published: 11 April 2022

This paper is open access.

You can find the EMPIR (European Metrology Programme for Innovation and Research) MEMQuD (quantum effects in memristive devices) project here, from the homepage,

Memristive devices are electrical resistance switches that couple ionics (i.e. dynamics of ions) with electronics. These devices offer a promising platform to observe quantum effects in air, at room temperature, and without an applied magnetic field. For this reason, they can be traced to fundamental physics constants fixed in the revised International System of Units (SI) for the realization of a quantum-based standard of resistance. However, as an emerging technology, memristive devices lack standardization and insights into the fundamental physics underlying its working principles.

The overall aim of the project is to investigate and exploit quantized conductance effects in memristive devices that operate reliably, in air and at room temperature. In particular, the project will focus on the development of memristive model systems and nanometrological characterization techniques at the nanoscale level of memristive devices, in order to better understand and control the quantized effects in memristive devices. Such an outcome would enable not only the development of neuromorphic systems but also the realization of a standard of resistance implementable on-chip for self-calibrating systems with zero-chain traceability in the spirit of the revised SI.

I’m starting to see mention of ‘neuromorphic computing’ in advertisements (specifically a Mercedes Benz car). I will have more about these first mentions of neuromorphic computing in consumer products in a future posting.

Memristor shakeup

New discoveries suggest that memristors do not function as was previously theorized. (For anyone who wants a memristor description, there’s this Wikipedia entry.) From an Oct. 13, 2015 posting by Alexander Hellemans for the Nanoclast blog (on the IEEE [Institute for Electrical and Electronics Engineers]), Note: Links have been removed,

What’s going to replace flash? The R&D arms of several companies including Hewlett Packard, Intel, and Samsung think the answer might be memristors (also called resistive RAM, ReRAM, or RRAM). These devices have a chance at unseating the non-volatile memory champion because, they use little energy, are very fast, and retain data without requiring power. However, new research indicates that they don’t work in quite the way we thought they do.

The fundamental mechanism at the heart of how a memristor works is something called an “imperfect point contact,” which was predicted in 1971, long before anybody had built working devices. When voltage is applied to a memristor cell, it reduces the resistance across the device. This change in resistance can be read out by applying another, smaller voltage. By inverting the voltage, the resistance of the device is returned to its initial value, that is, the stored information is erased.

Over the last decade researchers have produced two commercially promising types of memristors: electrochemical metallization memory (ECM) cells, and valence change mechanism memory (VCM) cells.

Now international research teams lead by Ilia Valov at the Peter Grünberg Institute in Jülich, Germany, report in Nature Nanotechnology and Advanced Materials that they have identified new processes that erase many of the differences between EMC and VCM cells.

Valov and coworkers in Germany, Japan, Korea, Greece, and the United States started investigating memristors that had a tantalum oxide electrolyte and an active tantalum electrode. “Our studies show that these two types of switching mechanisms in fact can be bridged, and we don’t have a purely oxygen type of switching as was believed, but that also positive [metal] ions, originating from the active electrode, are mobile,” explains Valov.

Here are links to and citations for both papers,

Graphene-Modified Interface Controls Transition from VCM to ECM Switching Modes in Ta/TaOx Based Memristive Devices by Michael Lübben, Panagiotis Karakolis, Vassilios Ioannou-Sougleridis, Pascal Normand, Pangiotis Dimitrakis, & Ilia Valov. Advanced Materials DOI: 10.1002/adma.201502574 First published: 10 September 2015

Nanoscale cation motion in TaOx, HfOx and TiOx memristive systems by Anja Wedig, Michael Luebben, Deok-Yong Cho, Marco Moors, Katharina Skaja, Vikas Rana, Tsuyoshi Hasegawa, Kiran K. Adepalli, Bilge Yildiz, Rainer Waser, & Ilia Valov. Nature Nanotechnology (2015) doi:10.1038/nnano.2015.221 Published online 28 September 2015

Both papers are behind paywalls.

Synaptic electronics

There’s been a lot about the memristor, being developed at HP Labs, at the University of Michigan, and elsewhere, on this blog and significantly less on other approaches to creating nanodevices with neuromorphic properties by researchers in Japan and in the US. The Dec. 20, 2012 news item on ScienceDaily notes,

Researchers in Japan and the US propose a nanoionic device with a range of neuromorphic and electrical multifunctions that may allow the fabrication of on-demand configurable circuits, analog memories and digital-neural fused networks in one device architecture.

… Now Rui Yang, Kazuya Terabe and colleagues at the National Institute for Materials Science in Japan and the University of California, Los Angeles, in the US have developed two-, three-terminal WO3-x-based nanoionic devices capable of a broad range of neuromorphic and electrical functions.

The originating Dec. 20, 2012 news release from Japan’s International Center for Materials draws a parallel between the device’s properties and neural behaviour,  explains the ‘why’ of the process, and mentions what applications the researchers believe could be developed,

The researchers draw similarities between the device properties — volatile and non-volatile states and the current fading process following positive voltage pulses — with models for neural behaviour —that is, short- and long-term memory and forgetting processes. They explain the behaviour as the result of oxygen ions migrating within the device in response to the voltage sweeps. Accumulation of the oxygen ions at the electrode leads to Schottky-like potential barriers and the resulting changes in resistance and rectifying characteristics. The stable bipolar switching behaviour at the Pt/WO3-x interface is attributed to the formation of the electric conductive filament and oxygen absorbability of the Pt electrode.

As the researchers conclude, “These capabilities open a new avenue for circuits, analog memories, and artificially fused digital neural networks using on-demand programming by input pulse polarity, magnitude, and repetition history.”

For those who wish to delve more deeply, here’s the citation (from the ScienceDaily news item),

Rui Yang, Kazuya Terabe, Guangqiang Liu, Tohru Tsuruoka, Tsuyoshi Hasegawa, James K. Gimzewski, Masakazu Aono. On-Demand Nanodevice with Electrical and Neuromorphic Multifunction Realized by Local Ion Migration. ACS Nano, 2012; 6 (11): 9515 DOI: 10.1021/nn302510e

The news release does not state explicitly why this would be considered an on-demand device. The article is behind a paywall.

There was a recent attempt to mimic brain processing not based in nanoelectronics but on mimicking brain activity by creating virtual neurons. A Canadian team at the University of Waterloo led by Chris Eliasmith made a sensation  with SPAUN (Semantic Pointer Architecture Unified Network) in late Nov. 2012 (mentioned in my Nov. 29, 2012 posting).