Tag Archives: memristors

Brain-on-a-chip 2014 survey/overview

Michael Berger has written another of his Nanowerk Spotlight articles focussing on neuromorphic engineering and the concept of a brain-on-a-chip bringing it up-to-date April 2014 style.

It’s a topic he and I have been following (separately) for years. Berger’s April 4, 2014 Brain-on-a-chip Spotlight article provides a very welcome overview of the international neuromorphic engineering effort (Note: Links have been removed),

Constructing realistic simulations of the human brain is a key goal of the Human Brain Project, a massive European-led research project that commenced in 2013.

The Human Brain Project is a large-scale, scientific collaborative project, which aims to gather all existing knowledge about the human brain, build multi-scale models of the brain that integrate this knowledge and use these models to simulate the brain on supercomputers. The resulting “virtual brain” offers the prospect of a fundamentally new and improved understanding of the human brain, opening the way for better treatments for brain diseases and for novel, brain-like computing technologies.

Several years ago, another European project named FACETS (Fast Analog Computing with Emergent Transient States) completed an exhaustive study of neurons to find out exactly how they work, how they connect to each other and how the network can ‘learn’ to do new things. One of the outcomes of the project was PyNN, a simulator-independent language for building neuronal network models.

Scientists have great expectations that nanotechnologies will bring them closer to the goal of creating computer systems that can simulate and emulate the brain’s abilities for sensation, perception, action, interaction and cognition while rivaling its low power consumption and compact size – basically a brain-on-a-chip. Already, scientists are working hard on laying the foundations for what is called neuromorphic engineering – a new interdisciplinary discipline that includes nanotechnologies and whose goal is to design artificial neural systems with physical architectures similar to biological nervous systems.

Several research projects funded with millions of dollars are at work with the goal of developing brain-inspired computer architectures or virtual brains: DARPA’s SyNAPSE, the EU’s BrainScaleS (a successor to FACETS), or the Blue Brain project (one of the predecessors of the Human Brain Project) at Switzerland’s EPFL [École Polytechnique Fédérale de Lausanne].

Berger goes on to describe the raison d’être for neuromorphic engineering (attempts to mimic biological brains),

Programmable machines are limited not only by their computational capacity, but also by an architecture requiring (human-derived) algorithms to both describe and process information from their environment. In contrast, biological neural systems (e.g., brains) autonomously process information in complex environments by automatically learning relevant and probabilistically stable features and associations. Since real world systems are always many body problems with infinite combinatorial complexity, neuromorphic electronic machines would be preferable in a host of applications – but useful and practical implementations do not yet exist.

Researchers are mostly interested in emulating neural plasticity (aka synaptic plasticity), from Berger’s April 4, 2014 article,

Independent from military-inspired research like DARPA’s, nanotechnology researchers in France have developed a hybrid nanoparticle-organic transistor that can mimic the main functionalities of a synapse. This organic transistor, based on pentacene and gold nanoparticles and termed NOMFET (Nanoparticle Organic Memory Field-Effect Transistor), has opened the way to new generations of neuro-inspired computers, capable of responding in a manner similar to the nervous system  (read more: “Scientists use nanotechnology to try building computers modeled after the brain”).

One of the key components of any neuromorphic effort, and its starting point, is the design of artificial synapses. Synapses dominate the architecture of the brain and are responsible for massive parallelism, structural plasticity, and robustness of the brain. They are also crucial to biological computations that underlie perception and learning. Therefore, a compact nanoelectronic device emulating the functions and plasticity of biological synapses will be the most important building block of brain-inspired computational systems.

In 2011, a team at Stanford University demonstrates a new single element nanoscale device, based on the successfully commercialized phase change material technology, emulating the functionality and the plasticity of biological synapses. In their work, the Stanford team demonstrated a single element electronic synapse with the capability of both the modulation of the time constant and the realization of the different synaptic plasticity forms while consuming picojoule level energy for its operation (read more: “Brain-inspired computing with nanoelectronic programmable synapses”).

Berger does mention memristors but not in any great detail in this article,

Researchers have also suggested that memristor devices are capable of emulating the biological synapses with properly designed CMOS neuron components. A memristor is a two-terminal electronic device whose conductance can be precisely modulated by charge or flux through it. It has the special property that its resistance can be programmed (resistor) and subsequently remains stored (memory).

One research project already demonstrated that a memristor can connect conventional circuits and support a process that is the basis for memory and learning in biological systems (read more: “Nanotechnology’s road to artificial brains”).

You can find a number of memristor articles here including these: Memristors have always been with us from June 14, 2013; How to use a memristor to create an artificial brain from Feb. 26, 2013; Electrochemistry of memristors in a critique of the 2008 discovery from Sept. 6, 2012; and many more (type ‘memristor’ into the blog search box and you should receive many postings or alternatively, you can try ‘artificial brains’ if you want everything I have on artificial brains).

Getting back to Berger’s April 4, 2014 article, he mentions one more approach and this one stands out,

A completely different – and revolutionary – human brain model has been designed by researchers in Japan who introduced the concept of a new class of computer which does not use any circuit or logic gate. This artificial brain-building project differs from all others in the world. It does not use logic-gate based computing within the framework of Turing. The decision-making protocol is not a logical reduction of decision rather projection of frequency fractal operations in a real space, it is an engineering perspective of Gödel’s incompleteness theorem.

Berger wrote about this work in much more detail in a Feb. 10, 2014 Nanowerk Spotlight article titled: Brain jelly – design and construction of an organic, brain-like computer, (Note: Links have been removed),

In a previous Nanowerk Spotlight we reported on the concept of a full-fledged massively parallel organic computer at the nanoscale that uses extremely low power (“Will brain-like evolutionary circuit lead to intelligent computers?”). In this work, the researchers created a process of circuit evolution similar to the human brain in an organic molecular layer. This was the first time that such a brain-like ‘evolutionary’ circuit had been realized.

The research team, led by Dr. Anirban Bandyopadhyay, a senior researcher at the Advanced Nano Characterization Center at the National Institute of Materials Science (NIMS) in Tsukuba, Japan, has now finalized their human brain model and introduced the concept of a new class of computer which does not use any circuit or logic gate.

In a new open-access paper published online on January 27, 2014, in Information (“Design and Construction of a Brain-Like Computer: A New Class of Frequency-Fractal Computing Using Wireless Communication in a Supramolecular Organic, Inorganic System”), Bandyopadhyay and his team now describe the fundamental computing principle of a frequency fractal brain like computer.

“Our artificial brain-building project differs from all others in the world for several reasons,” Bandyopadhyay explains to Nanowerk. He lists the four major distinctions:
1) We do not use logic gate based computing within the framework of Turing, our decision-making protocol is not a logical reduction of decision rather projection of frequency fractal operations in a real space, it is an engineering perspective of Gödel’s incompleteness theorem.
2) We do not need to write any software, the argument and basic phase transition for decision-making, ‘if-then’ arguments and the transformation of one set of arguments into another self-assemble and expand spontaneously, the system holds an astronomically large number of ‘if’ arguments and its associative ‘then’ situations.
3) We use ‘spontaneous reply back’, via wireless communication using a unique resonance band coupling mode, not conventional antenna-receiver model, since fractal based non-radiative power management is used, the power expense is negligible.
4) We have carried out our own single DNA, single protein molecule and single brain microtubule neurophysiological study to develop our own Human brain model.

I encourage people to read Berger’s articles on this topic as they provide excellent information and links to much more. Curiously (mind you, it is easy to miss something), he does not mention James Gimzewski’s work at the University of California at Los Angeles (UCLA). Working with colleagues from the National Institute for Materials Science in Japan, Gimzewski published a paper about “two-, three-terminal WO3-x-based nanoionic devices capable of a broad range of neuromorphic and electrical functions”. You can find out more about the paper in my Dec. 24, 2012 posting titled: Synaptic electronics.

As for the ‘brain jelly’ paper, here’s a link to and a citation for it,

Design and Construction of a Brain-Like Computer: A New Class of Frequency-Fractal Computing Using Wireless Communication in a Supramolecular Organic, Inorganic System by Subrata Ghoshemail, Krishna Aswaniemail, Surabhi Singhemail, Satyajit Sahuemail, Daisuke Fujitaemail and Anirban Bandyopadhyay. Information 2014, 5(1), 28-100; doi:10.3390/info5010028

It’s an open access paper.

As for anyone who’s curious about why the US BRAIN initiative ((Brain Research through Advancing Innovative Neurotechnologies, also referred to as the Brain Activity Map Project) is not mentioned, I believe that’s because it’s focussed on biological brains exclusively at this point (you can check its Wikipedia entry to confirm).

Anirban Bandyopadhyay was last mentioned here in a January 16, 2014 posting titled: Controversial theory of consciousness confirmed (maybe) in  the context of a presentation in Amsterdam, Netherlands.

Resistive memory from University of California Riverside (replacing flash memory in mobile devices) and Boise State University (neuron chips)

Today, (Aug. 19, 2 013)I have two items on memristors. First, Dexter Johnson provides some context for understanding why a University of California Riverside research team’s approach to creating memristors is exciting some interest in his Aug. 17, 2013 posting (Nanoclast blog on the IEEE [Institute of Electrical and Electronics Engineers] website), Note: Links have been removed,

The heralding of the memristor, or resistive memory, and the long-anticipated demise of flash memory have both been tracking on opposite trajectories with resistive memory expected to displace flash ever since the memristor was first discovered by Stanley Williams’ group at Hewlett Packard in 2008.

The memristor has been on a rapid development track ever since and has been promised to be commercially available as early as 2014, enabling 10 times greater embedded memory for mobile devices than currently available.

The obsolescence of flash memory at the hands of the latest nanotechnology has been predicted for longer than the commercial introduction of the memristor. But just at the moment it appears it’s going to reach its limits in storage capacity along comes a new way to push its capabilities to new heights, sometimes thanks to a nanomaterial like graphene.

In addition to the graphene promise, Dexter goes on to discuss another development,  which could push memory capabilities and which is mentioned in an Aug. 14, 2013 news item on ScienceDaily (and elsewhere),

A team at the University of California, Riverside Bourns College of Engineering has developed a novel way to build what many see as the next generation memory storage devices for portable electronic devices including smart phones, tablets, laptops and digital cameras.

The device is based on the principles of resistive memory [memristor], which can be used to create memory cells that are smaller, operate at a higher speed and offer more storage capacity than flash memory cells, the current industry standard. Terabytes, not gigbytes, will be the norm with resistive memory.

The key advancement in the UC Riverside research is the creation of a zinc oxide nano-island on silicon. It eliminates the need for a second element called a selector device, which is often a diode.

The Aug. 13, 2013 University of California Riverside news release by Sean Nealon, which originated the news item, further describes the limitations of flash memory and reinforces the importance of being able to eliminate a component (selector device),

Flash memory has been the standard in the electronics industry for decades. But, as flash continues to get smaller and users want higher storage capacity, it appears to reaching the end of its lifespan, Liu [Jianlin Liu, a professor of electrical engineering] said.

With that in mind, resistive memory is receiving significant attention from academia and the electronics industry because it has a simple structure, high-density integration, fast operation and long endurance.

Researchers have also found that resistive memory can be scaled down in the sub 10-nanometer scale. (A nanometer is one-billionth of a meter.) Current flash memory devices are roughly using a feature size twice as large.

Resistive memory usually has a metal-oxide-metal structure in connection with a selector device. The UC Riverside team has demonstrated a novel alternative way by forming self-assembled zinc oxide nano-islands on silicon. Using a conductive atomic force microscope, the researchers observed three operation modes from the same device structure, essentially eliminating the need for a separate selector device.

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

Multimode Resistive Switching in Single ZnO Nanoisland System by Jing Qi, Mario Olmedo, Jian-Guo Zheng, & Jianlin Liu. Scientific Reports 3, Article number: 2405 doi:10.1038/srep02405 Published 12 August 2013

This study is open access.

Meanwhile, Boise State University (Idaho, US) is celebrating a new project, CIF: Small: Realizing Chip-scale Bio-inspired Spiking Neural Networks with Monolithically Integrated Nano-scale Memristors, which was announced in an Aug. 17, 2013 news item on Azonano,

Electrical and computer engineering faculty Elisa Barney Smith, Kris Campbell and Vishal Saxena are joining forces on a project titled “CIF: Small: Realizing Chip-scale Bio-inspired Spiking Neural Networks with Monolithically Integrated Nano-scale Memristors.”

Team members are experts in machine learning (artificial intelligence), integrated circuit design and memristor devices. Funded by a three-year, $500,000 National Science Foundation grant, they have taken on the challenge of developing a new kind of computing architecture that works more like a brain than a traditional digital computer.

“By mimicking the brain’s billions of interconnections and pattern recognition capabilities, we may ultimately introduce a new paradigm in speed and power, and potentially enable systems that include the ability to learn, adapt and respond to their environment,” said Barney Smith, who is the principal investigator on the grant.

The Aug. 14, 2013 Boise State University news release by Kathleen Tuck, which originated the news item, describes the team’s focus on mimicking the brain’s capabilities ,

One of the first memristors was built in Campbell’s Boise State lab, which has the distinction of being one of only five or six labs worldwide that are up to the task.

The team’s research builds on recent work from scientists who have derived mathematical algorithms to explain the electrical interaction between brain synapses and neurons.

“By employing these models in combination with a new device technology that exhibits similar electrical response to the neural synapses, we will design entirely new computing chips that mimic how the brain processes information,” said Barney Smith.

Even better, these new chips will consume power at an order of magnitude lower than current computing processors, despite the fact that they match existing chips in physical dimensions. This will open the door for ultra low-power electronics intended for applications with scarce energy resources, such as in space, environmental sensors or biomedical implants.

Once the team has successfully built an artificial neural network, they will look to engage neurobiologists in parallel to what they are doing now. A proposal for that could be written in the coming year.

Barney Smith said they hope to send the first of the new neuron chips out for fabrication within weeks.

With the possibility that HP Labs will make its ‘memristor chips‘ commercially available in 2014 and neuron chips fabricated for the Boise State University researchers within weeks of this Aug. 19, 2013 date, it seems that memristors have been developed at a lightning fast pace. It’s been a fascinating process to observe.

Memristors have always been with us

Sprightly, a word not often used in conjunction with technology of any kind,  is the best of way describing the approach that researchers Varun Aggarwal and Gaurav Gandhi, along with Dr. Leon Chua, have taken towards their discovery that memristors are all around us. ( For anyone not familiar with the concept, I suggest reading the Wikipedia essay on memristors as it includes information about the various critiques of the memristor definition, as well as, the definition.)

It was Dexter Johnson in his June 6, 2013 post on the IEEE (Institute of Electrical and Electronics Engineers) Nanoclast blog who alerted me to this latest memristor work (Note: Links have been removed),

Two researchers from mLabs in India, along with Prof. Leon Chua at the University of California Berkeley, who first postulated the memristor in a paper back in 1971, have discovered the simplest physical implementation for the memristor, which can be built by anyone and everyone.

In two separate papers, one published in arXiv (“Bipolar electrical switching in metal-metal contacts”) and the other in the IEEE’s own Circuits and Systems Magazine (“The First Radios Were Made Using Memristors!”), Chua and the researchers, Varun Aggarwal and Gaurav Gandhi, discovered that simple imperfect point contacts all around us act as memristors.

“Our arXiv paper talks about the coherer, which comprises an imperfect metal-metal contact in embodiments such as a point contact between two metallic balls, granular media or a metal-mercury interface,” Gandhi explained to me via e-email. “On the other hand, the CAS paper comprises an imperfect metal-semiconductor contact (Cat’s Whisker) which was also the first solid-state diode. Both the systems have as their signature an imperfect point contact between two conducting/partially-conducting elements. Both act like memristor.”

I’ll get to the articles in a minutes, first let’s look at the researchers’ website, Mlabs home page (splash page). BTW, I have a soft spot for websites that are easy to navigate and don’t irritate me with movement or pop-ups (thank you mLabs). I think this description of the researchers (Aggarwal and Gandhi) and how they came to develop mLabs (excerpted from the About us page) explains why I described their approach as sprightly,

As they say, anything can happen over a cup of coffee and this story is no different! Gaurav and Varun were friends for over a decade, and one fine day they were sitting at a coffee house discussing Gaurav’s trip to the Second Memristor and Memristive Symposium at Berkeley. Gaurav shared the exciting work around memristor that he witnessed at Berkeley. Varun, who has been an evangelist of Jagadish Chandra Bose’s work thought there was some correlation between the research work of Bose and memristor. He convinced Gaurav to look deeper into these aspects. Soon, a plan was put forth, they wore their engineering gloves and mLabs was born. Gaurav quit his job for full time involvement at mLabs, while Varun assisted and advised throughout.

Three years of curiosity, experimentation, discussions and support from various researchers and professors from different parts of the world, led us to where we are today.

We are also sincerely grateful to Prof. Leon Chua for his continuous support, mentorship and indispensable contribution to our work.

As Dexter notes, Aggarwal and Gandhi have written papers about two different ways to create memristors, the arXiv paper, Bipolar electrical switching in metal-metal contacts, describes how corherers could be used to create simple memristors for research purposes. This paper also makes the argument that the memristor is a fundamental circuit (a claim which is a matter of considerable debate as the Wikipedia Memristor essay notes briefly),

Our new results show that bipolar switching can be observed in a large class of metals by a simple construction in form of a point-contact or granular media. It does not require complex construction, particular materials or small geometries. The signature of all our devices is an imperfect metal-metal contact and the physical mechanism for the observed behavior needs to be further studied. That the electrical behavior of these simple, naturally-occurring physical constructs can be modeled by a memristor, but not the other three passive elements, is an indication of its fundamental nature. By providing the canonic physical implementation for memristor, the present work not only lls an important gap in the study of switching devices, but also brings them into the realm of immediate practical use and implementation.

Due to the fact that the second article, the one in the IEEE published Circuits and Systems magazine, is behind a paywall, I can’t do much more than offer the title and the first paragraph,

The First Radios Were Made Using Memristors!

In 2008, Williams et al. reported the discovery of the fourth fundamental passive circuit element, memristor, which exhibits electrically controllable state-dependent resistance [1]. We show that one of the first wireless radio detector, called cat?s whisker, also the world?s first solid-state diode, had memristive properties. We have identified the state variable governing the resistance state of the device and can program it to switch between multiple stable resistance states. Our observations and results are valid for a larger class of devices called coherers, which include the cat?s whisker. These devices constitute the missing canonical physical implementations for a memristor (ref. Fig. 1).

It’s fascinating when you consider that up until now researching memristors meant having high tech equipment. I wonder how many backyard memristor labs are going to spring up?

On a somewhat related note, Dexter mentions that HP Labs ‘memristor’ products will be available in 2014. This latest date represents two postponements. Originally meant to be on the market in the summer of 2013, the new products were then supposed to brought to market in late 2013 as per my Feb. 7, 2013 posting; scroll down about 75% of the way).

Extending memristive theory

This is kind of fascinating. A German research team based at JARA (Jülich Aachen Research Alliance) is suggesting that memristive theory be extended beyond passive components in their paper about Resistive Memory Cells (ReRAM) which was recently published in Nature Communications. From the Apr. 26, 2013 news item on Azonano,

Resistive memory cells (ReRAM) are regarded as a promising solution for future generations of computer memories. They will dramatically reduce the energy consumption of modern IT systems while significantly increasing their performance.

Unlike the building blocks of conventional hard disk drives and memories, these novel memory cells are not purely passive components but must be regarded as tiny batteries. This has been demonstrated by researchers of Jülich Aachen Research Alliance (JARA), whose findings have now been published in the prestigious journal Nature Communications. The new finding radically revises the current theory and opens up possibilities for further applications. The research group has already filed a patent application for their first idea on how to improve data readout with the aid of battery voltage.

The Apr. 23, 2013 JARA news release, which originated the news item, provides some background information about data memory before going on to discuss the ReRAMs,

Conventional data memory works on the basis of electrons that are moved around and stored. However, even by atomic standards, electrons are extremely small. It is very difficult to control them, for example by means of relatively thick insulator walls, so that information will not be lost over time. This does not only limit storage density, it also costs a great deal of energy. For this reason, researchers are working feverishly all over the world on nanoelectronic components that make use of ions, i.e. charged atoms, for storing data. Ions are some thousands of times heavier that electrons and are therefore much easier to ‘hold down’. In this way, the individual storage elements can almost be reduced to atomic dimensions, which enormously improves the storage density.

Here’s how the ions behave in ReRAMs (from the news release),

In resistive switching memory cells (ReRAMs), ions behave on the nanometre scale in a similar manner to a battery. The cells have two electrodes, for example made of silver and platinum, at which the ions dissolve and then precipitate again. This changes the electrical resistance, which can be exploited for data storage. Furthermore, the reduction and oxidation processes also have another effect. They generate electric voltage. ReRAM cells are therefore not purely passive systems – they are also active electrochemical components. Consequently, they can be regarded as tiny batteries whose properties provide the key to the correct modelling and development of future data storage.

In complex experiments, the scientists from Forschungszentrum Jülich and RWTH Aachen University determined the battery voltage of typical representatives of ReRAM cells and compared them with theoretical values. This comparison revealed other properties (such as ionic resistance) that were previously neither known nor accessible. “Looking back, the presence of a battery voltage in ReRAMs is self-evident. But during the nine-month review process of the paper now published we had to do a lot of persuading, since the battery voltage in ReRAM cells can have three different basic causes, and the assignment of the correct cause is anything but trivial,” says Dr. Ilia Valov, the electrochemist in Prof. Rainer Waser’s research group.

This discovery could lead to optimizing ReRAMs and exploiting them in new applications (from the news release),

“The new findings will help to solve a central puzzle of international ReRAM research,” says Prof. Rainer Waser, deputy spokesman of the collaborative research centre SFB 917 ‘Nanoswitches’ established in 2011. In recent years, these puzzling aspects include unexplained long-term drift phenomena or systematic parameter deviations, which had been attributed to fabrication methods. “In the light of this new knowledge, it is possible to specifically optimize the design of the ReRAM cells, and it may be possible to discover new ways of exploiting the cells’ battery voltage for completely new applications, which were previously beyond the reach of technical possibilities,” adds Waser, whose group has been collaborating for years with companies such as Intel and Samsung Electronics in the field of ReRAM elements.

The part I found most interesting, given my interest in memristors, is this bit about extending the memristor theory, from the news release,

The new finding is of central significance, in particular, for the theoretical description of the memory components. To date, ReRAM cells have been described with the aid of the concept of memristors – a portmanteau word composed of “memory” and “resistor”. The theoretical concept of memristors can be traced back to Leon Chua in the 1970s. It was first applied to ReRAM cells by the IT company Hewlett-Packard in 2008. It aims at the permanent storage of information by changing the electrical resistance. The memristor theory leads to an important restriction. It is limited to passive components. “The demonstrated internal battery voltage of ReRAM elements clearly violates the mathematical construct of the memristor theory. This theory must be expanded to a whole new theory – to properly describe the ReRAM elements,” says Dr. Eike Linn, the specialist for circuit concepts in the group of authors. [emphases mine] This also places the development of all micro- and nanoelectronic chips on a completely new footing.

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

Nanobatteries in redox-based resistive switches require extension of memristor theory by I. Valov,  E. Linn, S. Tappertzhofen,  S. Schmelzer,  J. van den Hurk,  F. Lentz,  & R. Waser. Nature Communications 4, Article number: 1771 doi:10.1038/ncomms2784 Published 23 April 2013

This paper is open access (as of this writing).

Here’s a list of my 2013 postings on memristors and memristive devices,

2.5M Euros for Ireland’s John Boland and his memristive nanowires (Apr. 4, 2013 posting)

How to use a memristor to create an artificial brain (Feb. 26, 2013 posting)

CeNSE (Central Nervous System of the Earth) and billions of tiny sensors from HP plus a memristor update (Feb. 7, 2013 posting)

For anyone who cares to search the blog, there are several more.

2.5M Euros for Ireland’s John Boland and his memristive nanowires

The announcement makes no mention of the memristor or neuromorphic engineering but those are the areas in which  John Boland works and the reason for his 2.5M Euro research award. From the Ap. 3, 2013 news item on Nanowerk,

Professor John Boland, Director of CRANN, the SFI-funded [Science Foundation of Ireland] nanoscience institute based at Trinity College Dublin, and a Professor in the School of Chemistry has been awarded a €2.5 million research grant by the European Research Council (ERC). This is the second only Advanced ERC grant ever awarded in Physical Sciences in Ireland.

The Award will see Professor Boland and his team continue world-leading research into how nanowire networks can lead to a range of smart materials, sensors and digital memory applications. The research could result in computer networks that mimic the functions of the human brain and vastly improve on current computer capabilities such as facial recognition.

The University of Dublin’s Trinity College CRANN (Centre for Research on Adaptive Nanostructures and Nanodevices) April 3, 2013 news release, which originated the news item,  provides details about Boland’s proposed nanowire network,

Nanowires are spaghetti like structures, made of materials such as copper or silicon. They are just a few atoms thick and can be readily engineered into tangled networks of nanowires. Researchers worldwide are investigating the possibility that nanowires hold the future of energy production (solar cells) and could deliver the next generation of computers.

Professor Boland has discovered that exposing a random network of nanowires to stimuli like electricity, light and chemicals, generates chemical reaction at the junctions where the nanowires cross. By controlling the stimuli, it is possible to harness these reactions to manipulate the connectivity within the network. This could eventually allow computations that mimic the functions of the nerves in the human brain – particularly the development of associative memory functions which could lead to significant advances in areas such as facial recognition.

Commenting Professor John Boland said, “This funding from the European Research Council allows me to continue my work to deliver the next generation of computing, which differs from the traditional digital approach.  The human brain is neurologically advanced and exploits connectivity that is controlled by electrical and chemical signals. My research will create nanowire networks that have the potential to mimic aspects of the neurological functions of the human brain, which may revolutionise the performance of current day computers.   It could be truly ground-breaking.”

It’s only in the news release’s accompanying video that the memristor and neuromorphic engineering are mentioned,

I have written many times about the memristor, most recently in a Feb. 26, 2013 posting titled, How to use a memristor to create an artificial brain, where I noted a proposed ‘blueprint’ for an artificial brain. A contested concept, the memristor has attracted critical commentary as noted in a Mar. 19, 2013 comment added to the ‘blueprint’  post,

A Sceptic says:

….

Before talking about blueprints, one has to consider that the dynamic state equations describing so-called non-volatile memristors are in conflict with fundamentals of physics. These problems are discussed in:

“Fundamental Issues and Problems in the Realization of Memristors” by P. Meuffels and R. Soni (http://arxiv.org/abs/1207.7319)

“On the physical properties of memristive, memcapacitive, and meminductive systems” by M. Di Ventra and Y. V. Pershin (http://arxiv.org/abs/1302.7063)

How to use a memristor to create an artificial brain

Dr. Andy Thomas of Bielefeld University’s (Germany) Faculty of Physics has developed a ‘blueprint’ for an artificial brain based on memristors. From the Feb. 26, 2013, news item on phys.org,

Scientists have long been dreaming about building a computer that would work like a brain. This is because a brain is far more energy-saving than a computer, it can learn by itself, and it doesn’t need any programming. Privatdozent [senior lecturer] Dr. Andy Thomas from Bielefeld University’s Faculty of Physics is experimenting with memristors – electronic microcomponents that imitate natural nerves. Thomas and his colleagues proved that they could do this a year ago. They constructed a memristor that is capable of learning. Andy Thomas is now using his memristors as key components in a blueprint for an artificial brain. He will be presenting his results at the beginning of March in the print edition of the Journal of Physics D: Applied Physics.

The Feb. 26, 2013 University of Bielefeld news release, which originated the news item, describes why memristors are the foundation for Thomas’s proposed artificial brain,

Memristors are made of fine nanolayers and can be used to connect electric circuits. For several years now, the memristor has been considered to be the electronic equivalent of the synapse. Synapses are, so to speak, the bridges across which nerve cells (neurons) contact each other. Their connections increase in strength the more often they are used. Usually, one nerve cell is connected to other nerve cells across thousands of synapses.

Like synapses, memristors learn from earlier impulses. In their case, these are electrical impulses that (as yet) do not come from nerve cells but from the electric circuits to which they are connected. The amount of current a memristor allows to pass depends on how strong the current was that flowed through it in the past and how long it was exposed to it.

Andy Thomas explains that because of their similarity to synapses, memristors are particularly suitable for building an artificial brain – a new generation of computers. ‘They allow us to construct extremely energy-efficient and robust processors that are able to learn by themselves.’ Based on his own experiments and research findings from biology and physics, his article is the first to summarize which principles taken from nature need to be transferred to technological systems if such a neuromorphic (nerve like) computer is to function. Such principles are that memristors, just like synapses, have to ‘note’ earlier impulses, and that neurons react to an impulse only when it passes a certain threshold.

‘… a memristor can store information more precisely than the bits on which previous computer processors have been based,’ says Thomas. Both a memristor and a bit work with electrical impulses. However, a bit does not allow any fine adjustment – it can only work with ‘on’ and ‘off’. In contrast, a memristor can raise or lower its resistance continuously. ‘This is how memristors deliver a basis for the gradual learning and forgetting of an artificial brain,’ explains Thomas.

A nanocomponent that is capable of learning: The Bielefeld memristor built into a chip here is 600 times thinner than a human hair. [ downloaded from http://ekvv.uni-bielefeld.de/blog/uninews/entry/blueprint_for_an_artificial_brain]

A nanocomponent that is capable of learning: The Bielefeld memristor built into a chip here is 600 times thinner than a human hair. [ downloaded from http://ekvv.uni-bielefeld.de/blog/uninews/entry/blueprint_for_an_artificial_brain]

Here’s a citation for and link to the paper (from the university news release),

Andy Thomas, ‘Memristor-based neural networks’, Journal of Physics D: Applied Physics, http://dx.doi.org/10.1088/0022-3727/46/9/093001, released online on 5 February 2013, published in print on 6 March 2013.

This paper is available until March 5, 2013 as IOP Science (publisher of Journal Physics D: Applied Physics), makes their papers freely available (with some provisos) for the first 30 days after online publication, from the Access Options page for Memristor-based neural networks,

As a service to the community, IOP is pleased to make papers in its journals freely available for 30 days from date of online publication – but only fair use of the content is permitted.

Under fair use, IOP content may only be used by individuals for the sole purpose of their own private study or research. Such individuals may access, download, store, search and print hard copies of the text. Copying should be limited to making single printed or electronic copies.

Other use is not considered fair use. In particular, use by persons other than for the purpose of their own private study or research is not fair use. Nor is altering, recompiling, reselling, systematic or programmatic copying, redistributing or republishing. Regular/systematic downloading of content or the downloading of a substantial proportion of the content is not fair use either.

Getting back to the memristor, I’ve been writing about it for some years, it was most recently mentioned here  in a Feb.7, 2013 posting and I mentioned in a Dec. 24, 2012 posting nanoionic nanodevices  also described as resembling synapses.

FrogHeart at the 2012 S.NET conference, part 5: informal public dialogue/science education and transhuman narratives

Anne Dijkstra’s presentation (at the 2012 S.NET [Society for the Study of Nanoscience and Emerging Technologies] conference on “Science Cafés and scientific citizens. The Nanotrail project as a case” provided a contrast to the local (Vancouver, Canada) science café scene I wasn’t expecting. The Dutch science cafés Dijkstra described were formal both in tone and organization.  She featured five science cafés focussed on discussions of nanotechnology. The most striking image in Dijkstra’s presentation was of someone taking notes at one of the meetings. By contrast, the Vancouver café scientifique get togethers take place in a local bar/pub (The Railway Club) and are organized by members of the local science community. (There are some life science café scientifique Vancouver meetings which may be more formal as they take place at the University of British Columbia.)

I was quite fascinated to hear about the Dutch children’s science cafés that have been organized by the parents featuring presentations by children to their peers. It’s a grassroots effort/community-based initiative.

The next and final presentation set was when I presented my work on ‘Zombies, brains, collapsing boundaries, and entanglements’. (People at the conference kept laughing when I told them when my presentation was scheduled.) Briefly, my area of interest is in neuromorphic engineering (artificial brains), memristors and other devices which can mimic synaptic plasticity, pop culture (zombies), and something I’ve termed ‘cognitive entanglement’. My basic question is: what does it mean to be human at a time when notions about what constitutes life and nonlife are being obliterated? In addition, although I didn’t do this deliberately, this passage from my Oct. 31, 2012 posting (Part 1 of this series) touches on a related issue,

His [Chris Groves' plenary] quote from Hannah Arendt, “What we make remakes us” brought home the notion that there is a feedback loop and that science and invention are not unidirectional pursuits, i.e., we do not create the world and stand apart from it; the world we create, in turn, recreates us.

I have more about this ‘conversation’ regarding artificial brains taking place in business, pop culture, philosophy, advertising, science, engineering, and elsewhere but I think I need to write up a paper. Once I do that I”ll post it. As for the response from the conference goers, there were no questions but there were a few comments (I’m not the only one interested in zombies and the living dead) and a suggestion to me for further reading (Andrew Pickering, The cybernetic brain: sketches of another future).

Memristors and transparent electronics in Oregon

The Sept. 14, 2012 news release from Oregon State University (OSU) features some very careful wording around the concept of a memristor.  First, here’s the big picture news,

The transparent electronics that were pioneered at Oregon State University may find one of their newest applications as a next-generation replacement for some uses of non-volatile flash memory, a multi-billion dollar technology nearing its limit of small size and information storage capacity.

Researchers at OSU have confirmed that zinc tin oxide, an inexpensive and environmentally benign compound, has significant potential for use in this field, and could provide a new, transparent technology where computer memory is based on resistance, instead of an electron charge.

Here’s where it starts to get interesting,

This resistive random access memory, or RRAM, is referred to by some researchers as a “memristor.”  [emphasis mine] Products using this approach could become even smaller, faster and cheaper than the silicon transistors that have revolutionized modern electronics – and transparent as well.

Transparent electronics offer potential for innovative products that don’t yet exist, like information displayed on an automobile windshield, or surfing the web on the glass top of a coffee table.

“Flash memory has taken us a long way with its very small size and low price,” said John Conley, a professor in the OSU School of Electrical Engineering and Computer Science. “But it’s nearing the end of its potential, and memristors are a leading candidate to continue performance improvements.”

Memristors have a simple structure, are able to program and erase information rapidly, and consume little power. They accomplish a function similar to transistor-based flash memory, but with a different approach. Whereas traditional flash memory stores information with an electrical charge, RRAM accomplishes this with electrical resistance. Like flash, it can store information as long as it’s needed.

Flash memory computer chips are ubiquitous in almost all modern electronic products, ranging from cell phones and computers to video games and flat panel televisions.

I like how they note that some scientists call these devices memristors thereby sidestepping at least some of the controversy as to what exactly constitute a memristor (my latest piece which mentions a critique of the memristor concept was posted Sept. 6, 2012).

The news release gets a little confusing here,

Some of the best opportunities for these new amorphous oxide semiconductors are not so much for memory chips, but with thin-film, flat panel displays, researchers say. [emphasis mine] Private industry has already shown considerable interest in using them for the thin-film transistors that control liquid crystal displays, and one compound approaching commercialization is indium gallium zinc oxide.

But indium and gallium are getting increasingly expensive, and zinc tin oxide – also a transparent compound – appears to offer good performance with lower cost materials. The new research also shows that zinc tin oxide can be used not only for thin-film transistors, but also for memristive memory, Conley said, an important factor in its commercial application.

More work is needed to understand the basic physics and electrical properties of the new compounds, researchers said.

There was no mention of amorphous oxide semiconductors until the portion I’ve highlighted . If I’ve understood what follows correctly, there’s a new class of semiconductor for use in thin film applications (transparent electronics): an amorphous oxide semiconductor and the most promising material for commercial purposes is indium gallium zinc oxide. The other oxide mentioned in the excerpt, zinc tin oxide, can be used both for thin film applications and memristive applications.

This memristor story has certainly moved some interesting directions as it continues to develop.

Memristors: they are older than you think

I got an email this morning (May 22, 2012) informing me that an article, Two centuries of memristors by Themistoklis Prodromakis, Christofer Toumazou and Leon Chua, had just been published in the journal Nature Materials. The article situates memristors in an historical context stretching back to the 19th century. Sadly, the article is behind a paywall so I won’t be copying too much material but I will attempt to give you the flavour of the piece.

The focus is on 19th century scientists and their work with what we are now calling ‘memristors’.  Before moving on to the article, here’s a good definition of a memristor, from the Wikipedia essay (note: I have removed links and footnotes),

Memristor (…  a portmanteau of “memory resistor”) is a passive two-terminal electrical component envisioned as a fundamental non-linear circuit element relating charge and magnetic flux linkage. The memristor is currently under development by a team at Hewlett-Packard.

When current flows in one direction through the device, the electrical resistance increases; and when current flows in the opposite direction, the resistance decreases. When the current is stopped, the component retains the last resistance that it had, and when the flow of charge starts again, the resistance of the circuit will be what it was when it was last active. It has a regime of operation with an approximately linear charge-resistance relationship as long as the time-integral of the current stays within certain bounds.

This Wikipedia essay also offers an historical timeline, which starts in 1960 with Bernard Widrow and his memistor, adding very nicely to the discussion in the Nature Materials article which focuses on such 19th luminaries as Sir Michael Faraday, Hertha Ayrton, Alessandro Volta, and Humphry Davy, amongst others.  Here’s a helpful description of hysteresis and how it relates to the memristor from the article (note: I have removed footnotes),

The functional properties of memristors were first documented by Chua and later on by Chua and Kang, with their main fingerprint being a pinched-hysteresis loop when subjected to a bipolar periodic signal. This particular signature has been explicitly observed in a number of devices for more than one century, while it can be extrapolated for devices that appeared as early as the dawn of the nineteenth century.

Hysteresis is typically noticed in systems and devices that possess certain inertia, causing the value of a physical property to lag behind changes in the mechanism causing it, manifesting memory.

The authors go on to outline the various  scientists who have grappled with the ‘memristive effect’ dating back to two centuries ago.  They finish their essay with this (note:  I’ve removed footnotes),

The memristor is not an invention. Rather it is a description of a basic phenomenon of nature that manifests itself in various dissipative devices, made from different materials, internal structures and architectures. We end this historical narrative by noting that even though the memristor has seen its light of joy only recently in 2008, and has been recognized as the fourth circuit element along with the resistor, capacitor and inductor, it actually predates the resistor, which was formally published by Ohm in 1827, and the inductor, which was formally published by Faraday in 1831.

If you are at all interested in memristors and have access behind the paywall, I strongly recommend reading this paper not only for the historical context but for how the authors support their contention that the memristor is a fourth circuit element.

A contrasting perspective is offered by Blaise Mouttet (discussed in my Jan. 27, 2012 posting) who contends that the what we are now calling a ‘memristor’ is part of a larger class of variable resistance systems.

Whose Electric Brain? the video

After a few fits and starts, the video of my March 15, 2012 presentation to the Canadian Academy of Independent Scholars at Simon Fraser University has been uploaded to Vimeo. Unfortunately the original recording was fuzzy (camera issues) so we (camera operator, director, and editor, Sama Shodjai [[email protected]]) and I rerecorded the presentation and this second version is the one we’ve uploaded.

Whose Electric Brain? (Presentation) from Maryse de la Giroday on Vimeo.

I’ve come across a few errors; at one point, I refer to Buckminster Fuller as Buckminster Fullerene and I state that the opening image visualizes a neuron from someone with Parkinson’s disease, I should have said Huntingdon’s disease. Perhaps, you’ll come across more, please do let me know. If this should become a viral sensation (no doubt feeding a pent up demand for grey-haired women talking about memristors and brains), it’s important that corrections be added.

Finally, a big thank you to Mark Dwor who provides my introduction at the beginning, the Canadian Academy of Independent Scholars whose grant made the video possible, and Simon Fraser University.

ETA March 29, 2012: This is an updated version of the presentation I was hoping to give at ISEA (International Symposium on Electronic Arts) 2011 in Istanbul. Sadly, I was never able to raise all of the funds I needed for that venture. The funds I raised separately from the CAIS grant are being held until I can find another suitable opportunity to present my work.