Tag Archives: Stanely Williams

Brain-inspired electronics with organic memristors for wearable computing

I went down a rabbit hole while trying to figure out the difference between ‘organic’ memristors and standard memristors. I have put the results of my investigation at the end of this post. First, there’s the news.

An April 21, 2020 news item on ScienceDaily explains why researchers are so focused on memristors and brainlike computing,

The advent of artificial intelligence, machine learning and the internet of things is expected to change modern electronics and bring forth the fourth Industrial Revolution. The pressing question for many researchers is how to handle this technological revolution.

“It is important for us to understand that the computing platforms of today will not be able to sustain at-scale implementations of AI algorithms on massive datasets,” said Thirumalai Venkatesan, one of the authors of a paper published in Applied Physics Reviews, from AIP Publishing.

“Today’s computing is way too energy-intensive to handle big data. We need to rethink our approaches to computation on all levels: materials, devices and architecture that can enable ultralow energy computing.”

An April 21, 2020 American Institute of Physics (AIP) news release (also on EurekAlert), which originated the news item, describes the authors’ approach to the problems with organic memristors,

Brain-inspired electronics with organic memristors could offer a functionally promising and cost- effective platform, according to Venkatesan. Memristive devices are electronic devices with an inherent memory that are capable of both storing data and performing computation. Since memristors are functionally analogous to the operation of neurons, the computing units in the brain, they are optimal candidates for brain-inspired computing platforms.

Until now, oxides have been the leading candidate as the optimum material for memristors. Different material systems have been proposed but none have been successful so far.

“Over the last 20 years, there have been several attempts to come up with organic memristors, but none of those have shown any promise,” said Sreetosh Goswami, lead author on the paper. “The primary reason behind this failure is their lack of stability, reproducibility and ambiguity in mechanistic understanding. At a device level, we are now able to solve most of these problems,”

This new generation of organic memristors is developed based on metal azo complex devices, which are the brainchild of Sreebata Goswami, a professor at the Indian Association for the Cultivation of Science in Kolkata and another author on the paper.

“In thin films, the molecules are so robust and stable that these devices can eventually be the right choice for many wearable and implantable technologies or a body net, because these could be bendable and stretchable,” said Sreebata Goswami. A body net is a series of wireless sensors that stick to the skin and track health.

The next challenge will be to produce these organic memristors at scale, said Venkatesan.

“Now we are making individual devices in the laboratory. We need to make circuits for large-scale functional implementation of these devices.”

Caption: The device structure at a molecular level. The gold nanoparticles on the bottom electrode enhance the field enabling an ultra-low energy operation of the molecular device. Credit Sreetosh Goswami, Sreebrata Goswami and Thirumalai Venky Venkatesan

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

An organic approach to low energy memory and brain inspired electronics by Sreetosh Goswami, Sreebrata Goswami, and T. Venkatesan. Applied Physics Reviews 7, 021303 (2020) DOI: https://doi.org/10.1063/1.5124155

This paper is open access.

Basics about memristors and organic memristors

This undated article on Nanowerk provides a relatively complete and technical description of memristors in general (Note: A link has been removed),

A memristor (named as a portmanteau of memory and resistor) is a non-volatile electronic memory device that was first theorized by Leon Ong Chua in 1971 as the fourth fundamental two-terminal circuit element following the resistor, the capacitor, and the inductor (IEEE Transactions on Circuit Theory, “Memristor-The missing circuit element”).

Its special property is that its resistance can be programmed (resistor function) and subsequently remains stored (memory function). Unlike other memories that exist today in modern electronics, memristors are stable and remember their state even if the device loses power.

However, it was only almost 40 years later that the first practical device was fabricated. This was in 2008, when a group led by Stanley Williams at HP Research Labs realized that switching of the resistance between a conducting and less conducting state in metal-oxide thin-film devices was showing Leon Chua’s memristor behavior. …

The article on Nanowerk includes an embedded video presentation on memristors given by Stanley Williams (also known as R. Stanley Williams).

Mention of an ‘organic’memristor can be found in an October 31, 2017 article by Ryan Whitwam,

The memristor is composed of the transition metal ruthenium complexed with “azo-aromatic ligands.” [emphasis mine] The theoretical work enabling this material was performed at Yale, and the organic molecules were synthesized at the Indian Association for the Cultivation of Sciences. …

I highlighted ‘ligands’ because that appears to be the difference. However, there is more than one type of ligand on Wikipedia.

First, there’s the Ligand (biochemistry) entry (Note: Links have been removed),

In biochemistry and pharmacology, a ligand is a substance that forms a complex with a biomolecule to serve a biological purpose. …

Then, there’s the Ligand entry,

In coordination chemistry, a ligand[help 1] is an ion or molecule (functional group) that binds to a central metal atom to form a coordination complex …

Finally, there’s the Ligand (disambiguation) entry (Note: Links have been removed),

  • Ligand, an atom, ion, or functional group that donates one or more of its electrons through a coordinate covalent bond to one or more central atoms or ions
  • Ligand (biochemistry), a substance that binds to a protein
  • a ‘guest’ in host–guest chemistry

I did take a look at the paper and did not see any references to proteins or other biomolecules that I could recognize as such. I’m not sure why the researchers are describing their device as an ‘organic’ memristor but this may reflect a shortcoming in the definitions I have found or shortcomings in my reading of the paper rather than an error on their parts.

Hopefully, more research will be forthcoming and it will be possible to better understand the terminology.

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.