Tag Archives: Subramanian K. R. S. Sankaranarayanan

An ‘artificial brain’ and life-long learning

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Talk of artificial brains (also known as, brainlike computing or neuromorphic computing) usually turns to memory fairly quickly. This February 3, 2022 news item on ScienceDaily does too although the focus is on how memory and forgetting affect the ability to learn,

When the human brain learns something new, it adapts. But when artificial intelligence learns something new, it tends to forget information it already learned.

As companies use more and more data to improve how AI recognizes images, learns languages and carries out other complex tasks, a paper publishing in Science this week shows a way that computer chips could dynamically rewire themselves to take in new data like the brain does, helping AI to keep learning over time.

“The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan,” said Shriram Ramanathan, a professor in Purdue University’s [Indiana, US] School of Materials Engineering who specializes in discovering how materials could mimic the brain to improve computing.

Unlike the brain, which constantly forms new connections between neurons to enable learning, the circuits on a computer chip don’t change. A circuit that a machine has been using for years isn’t any different than the circuit that was originally built for the machine in a factory.

This is a problem for making AI more portable, such as for autonomous vehicles or robots in space that would have to make decisions on their own in isolated environments. If AI could be embedded directly into hardware rather than just running on software as AI typically does, these machines would be able to operate more efficiently.

A February 3, 2022 Purdue University news release (also on EurekAlert), which originated the news item, provides more technical detail about the work (Note: Links have been removed),

In this study, Ramanathan and his team built a new piece of hardware that can be reprogrammed on demand through electrical pulses. Ramanathan believes that this adaptability would allow the device to take on all of the functions that are necessary to build a brain-inspired computer.

“If we want to build a computer or a machine that is inspired by the brain, then correspondingly, we want to have the ability to continuously program, reprogram and change the chip,” Ramanathan said.

Toward building a brain in chip form

The hardware is a small, rectangular device made of a material called perovskite nickelate,  which is very sensitive to hydrogen. Applying electrical pulses at different voltages allows the device to shuffle a concentration of hydrogen ions in a matter of nanoseconds, creating states that the researchers found could be mapped out to corresponding functions in the brain.

When the device has more hydrogen near its center, for example, it can act as a neuron, a single nerve cell. With less hydrogen at that location, the device serves as a synapse, a connection between neurons, which is what the brain uses to store memory in complex neural circuits.

Through simulations of the experimental data, the Purdue team’s collaborators at Santa Clara University and Portland State University showed that the internal physics of this device creates a dynamic structure for an artificial neural network that is able to more efficiently recognize electrocardiogram patterns and digits compared to static networks. This neural network uses “reservoir computing,” which explains how different parts of a brain communicate and transfer information.

Researchers from The Pennsylvania State University also demonstrated in this study that as new problems are presented, a dynamic network can “pick and choose” which circuits are the best fit for addressing those problems.

Since the team was able to build the device using standard semiconductor-compatible fabrication techniques and operate the device at room temperature, Ramanathan believes that this technique can be readily adopted by the semiconductor industry.

“We demonstrated that this device is very robust,” said Michael Park, a Purdue Ph.D. student in materials engineering. “After programming the device over a million cycles, the reconfiguration of all functions is remarkably reproducible.”

The researchers are working to demonstrate these concepts on large-scale test chips that would be used to build a brain-inspired computer.

Experiments at Purdue were conducted at the FLEX Lab and Birck Nanotechnology Center of Purdue’s Discovery Park. The team’s collaborators at Argonne National Laboratory, the University of Illinois, Brookhaven National Laboratory and the University of Georgia conducted measurements of the device’s properties.

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

Reconfigurable perovskite nickelate electronics for artificial intelligence by Hai-Tian Zhang, Tae Joon Park, A. N. M. Nafiul Islam, Dat S. J. Tran, Sukriti Manna, Qi Wang, Sandip Mondal, Haoming Yu, Suvo Banik, Shaobo Cheng, Hua Zhou, Sampath Gamage, Sayantan Mahapatra, Yimei Zhu, Yohannes Abate, Nan Jiang, Subramanian K. R. S. Sankaranarayanan, Abhronil Sengupta, Christof Teuscher, Shriram Ramanathan. Science • 3 Feb 2022 • Vol 375, Issue 6580 • pp. 533-539 • DOI: 10.1126/science.abj7943

This paper is behind a paywall.

Organismic learning—learning to forget

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This approach to mimicking the human brain differs from the memristor. (You can find several pieces about memrisors here including this August 24, 2017 post about a derivative, a neuristor).  This approach comes from scientists at Purdue University and employs a quantum material. From an Aug. 15, 2017 news item on phys.org,

A new computing technology called “organismoids” mimics some aspects of human thought by learning how to forget unimportant memories while retaining more vital ones.

“The human brain is capable of continuous lifelong learning,” said Kaushik Roy, Purdue University’s Edward G. Tiedemann Jr. Distinguished Professor of Electrical and Computer Engineering. “And it does this partially by forgetting some information that is not critical. I learn slowly, but I keep forgetting other things along the way, so there is a graceful degradation in my accuracy of detecting things that are old. What we are trying to do is mimic that behavior of the brain to a certain extent, to create computers that not only learn new information but that also learn what to forget.”

The work was performed by researchers at Purdue, Rutgers University, the Massachusetts Institute of Technology, Brookhaven National Laboratory and Argonne National Laboratory.

Central to the research is a ceramic “quantum material” called samarium nickelate, which was used to create devices called organismoids, said Shriram Ramanathan, a Purdue professor of materials engineering.

A video describing the work has been produced,

An August 14, 2017 Purdue University news release by Emil Venere, which originated the news item,  details the work,

“These devices possess certain characteristics of living beings and enable us to advance new learning algorithms that mimic some aspects of the human brain,” Roy said. “The results have far reaching implications for the fields of quantum materials as well as brain-inspired computing.”

…

When exposed to hydrogen gas, the material undergoes a massive resistance change, as its crystal lattice is “doped” by hydrogen atoms. The material is said to breathe, expanding when hydrogen is added and contracting when the hydrogen is removed.

“The main thing about the material is that when this breathes in hydrogen there is a spectacular quantum mechanical effect that allows the resistance to change by orders of magnitude,” Ramanathan said. “This is very unusual, and the effect is reversible because this dopant can be weakly attached to the lattice, so if you remove the hydrogen from the environment you can change the electrical resistance.”

…

When hydrogen is exposed to the material, it splits into a proton and an electron, and the electron attaches to the nickel, temporarily causing the material to become an insulator.

“Then, when the hydrogen comes out, this material becomes conducting again,” Ramanathan said. “What we show in this paper is the extent of conduction and insulation can be very carefully tuned.”

This changing conductance and the “decay of that conductance over time” is similar to a key animal behavior called habituation.

“Many animals, even organisms that don’t have a brain, possess this fundamental survival skill,” Roy said. “And that’s why we call this organismic behavior. If I see certain information on a regular basis, I get habituated, retaining memory of it. But if I haven’t seen such information over a long time, then it slowly starts decaying. So, the behavior of conductance going up and down in exponential fashion can be used to create a new computing model that will incrementally learn and at same time forget things in a proper way.”

The researchers have developed a “neural learning model” they have termed adaptive synaptic plasticity.

“This could be really important because it’s one of the first examples of using quantum materials directly for solving a major problem in neural learning,” Ramanathan said.

The researchers used the organismoids to implement the new model for synaptic plasticity.

“Using this effect we are able to model something that is a real problem in neuromorphic computing,” Roy said. “For example, if I have learned your facial features I can still go out and learn someone else’s features without really forgetting yours. However, this is difficult for computing models to do. When learning your features, they can forget the features of the original person, a problem called catastrophic forgetting.”

Neuromorphic computing is not intended to replace conventional general-purpose computer hardware, based on complementary metal-oxide-semiconductor transistors, or CMOS. Instead, it is expected to work in conjunction with CMOS-based computing. Whereas CMOS technology is especially adept at performing complex mathematical computations, neuromorphic computing might be able to perform roles such as facial recognition, reasoning and human-like decision making.

Roy’s team performed the research work on the plasticity model, and other collaborators concentrated on the physics of how to explain the process of doping-driven change in conductance central to the paper. The multidisciplinary team includes experts in materials, electrical engineering, physics, and algorithms.

“It’s not often that a materials science person can talk to a circuits person like professor Roy and come up with something meaningful,” Ramanathan said.

Organismoids might have applications in the emerging field of spintronics. Conventional computers use the presence and absence of an electric charge to represent ones and zeroes in a binary code needed to carry out computations. Spintronics, however, uses the “spin state” of electrons to represent ones and zeros.

It could bring circuits that resemble biological neurons and synapses in a compact design not possible with CMOS circuits. Whereas it would take many CMOS devices to mimic a neuron or synapse, it might take only a single spintronic device.

In future work, the researchers may demonstrate how to achieve habituation in an integrated circuit instead of exposing the material to hydrogen gas.

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

Habituation based synaptic plasticity and organismic learning in a quantum perovskite by Fan Zuo, Priyadarshini Panda, Michele Kotiuga, Jiarui Li, Mingu Kang, Claudio Mazzoli, Hua Zhou, Andi Barbour, Stuart Wilkins, Badri Narayanan, Mathew Cherukara, Zhen Zhang, Subramanian K. R. S. Sankaranarayanan, Riccardo Comin, Karin M. Rabe, Kaushik Roy, & Shriram Ramanathan. Nature Communications 8, Article number: 240 (2017) doi:10.1038/s41467-017-00248-6 Published online: 14 August 2017

This paper is open access.

Self-healing diamond-like carbon from the Argonne Lab (US)

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Argonne researchers, from left, Subramanian Sankaranarayanan, Badri Narayanan, Ali Erdemir, Giovanni Ramirez and Osman Levent Eryilmaz show off metal engine parts that have been treated with a diamond-like carbon coating similar to one developed and explored by the team. The catalytic coating interacts with engine oil to create a self-healing diamond-like film that could have profound implications for the efficiency and durability of future engines. (photo by Wes Agresta)

Argonne researchers, from left, Subramanian Sankaranarayanan, Badri Narayanan, Ali Erdemir, Giovanni Ramirez and Osman Levent Eryilmaz show off metal engine parts that have been treated with a diamond-like carbon coating similar to one developed and explored by the team. The catalytic coating interacts with engine oil to create a self-healing diamond-like film that could have profound implications for the efficiency and durability of future engines. (photo by Wes Agresta)

An Aug. 5, 2016 news item on ScienceDaily makes the announcement,

Fans of Superman surely recall how the Man of Steel used immense heat and pressure generated by his bare hands to form a diamond out of a lump of coal.

The tribologists — scientists who study friction, wear, and lubrication — and computational materials scientists at the U.S. Department of Energy’s (DOE’s) Argonne National Laboratory will probably never be mistaken for superheroes. However, they recently applied the same principles and discovered a revolutionary diamond-like film of their own that is generated by the heat and pressure of an automotive engine.

An Aug. 5, 2016 Argonne National Laboratory news release (also on EurekAlert) by Greg Cunningham, which originated the news item, explains further,

The discovery of this ultra-durable, self-lubricating tribofilm – a film that forms between moving surfaces — was first reported yesterday in the journal Nature. It could have profound implications for the efficiency and durability of future engines and other moving metal parts that can be made to develop self-healing, diamond-like carbon (DLC) tribofilms.

“This is a very unique discovery, and one that was a little unexpected,” said Ali Erdemir, the Argonne Distinguished Fellow who leads the team. “We have developed many types of diamond-like carbon coatings of our own, but we’ve never found one that generates itself by breaking down the molecules of the lubricating oil and can actually regenerate the tribofilm as it is worn away.”

The phenomenon was first discovered several years ago by Erdemir and his colleague Osman Levent Eryilmaz in the Tribology and Thermal-Mechanics Department in Argonne’s Center for Transportation Research. But it took theoretical insight enhanced by the massive computing resources available at Argonne to fully understand what was happening at the molecular level in the experiments. The theoretical understanding was provided by lead theoretical researcher Subramanian Sankaranarayanan and postdoctoral researcher Badri Narayanan from the Center for Nanoscale Materials (CNM), while the computing power was provided by the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. CNM, ALCF and NERSC are all DOE Office of Science User Facilities.

The original discovery occurred when Erdemir and Eryilmaz decided to see what would happen when a small steel ring was coated with a catalytically active nanocoating – tiny molecules of metals that promote chemical reactions to break down other materials – then subjected to high pressure and heat using a base oil without the complex additives of modern lubricants. When they looked at the ring after the endurance test, they didn’t see the expected rust and surface damage, but an intact ring with an odd blackish deposit on the contact area.

“This test creates extreme contact pressure and temperatures, which are supposed to cause the ring to wear and eventually seize,” said Eryilmaz. “But this ring didn’t significantly wear and this blackish deposit was visible. We said, ‘This material is strange. Maybe this is what is causing this unusual effect.'”

Looking at the deposit using high-powered optical and laser Raman microscopes, the experimentalists realized the deposit was a tribofilm of diamond-like carbon, similar to several other DLCs developed at Argonne in the past. But it worked even better. Tests revealed the DLC tribofilm reduced friction by 25 to 40 percent and that wear was reduced to unmeasurable values.

Further experiments, led by postdoctoral researcher Giovanni Ramirez, revealed that multiple types of catalytic coatings can yield DLC tribofilms. The experiments showed the coatings interact with the oil molecules to create the DLC film, which adheres to the metal surfaces. When the tribofilm is worn away, the catalyst in the coating is re-exposed to the oil, causing the catalysis to restart and develop new layers of tribofilm. The process is self-regulating, keeping the film at consistent thickness. The scientists realized the film was developing spontaneously between the sliding surfaces and was replenishing itself, but they needed to understand why and how.

To provide the theoretical understanding of what the tribology team was seeing in its experiments, they turned to Sankaranarayanan and Narayanan, who used the immense computing power of ALCF’s 10-petaflop supercomputer, Mira. They ran large-scale simulations to understand what was happening at the atomic level, and determined that the catalyst metals in the nanocomposite coatings were stripping hydrogen atoms from the hydrocarbon chains of the lubricating oil, then breaking the chains down into smaller segments. The smaller chains joined together under pressure to create the highly durable DLC tribofilm.

“This is an example of catalysis under extreme conditions created by friction. It is opening up a new field where you are merging catalysis and tribology, which has never been done before,” said Sankaranarayanan. “This new field of tribocatalysis has the potential to change the way we look at lubrication.”

The theorists explored the origins of the catalytic activity to understand how catalysis operates under the extreme heat and pressure in an engine. By gaining this understanding, they were able to predict which catalysts would work, and which would create the most advantageous tribofilms.

“Interestingly, we found several metals or composites that we didn’t think would be catalytically active, but under these circumstances, they performed quite well,” said Narayanan. “This opens up new pathways for scientists to use extreme conditions to enhance catalytic activity.”

The implications of the new tribofilm for efficiency and reliability of engines are huge. Manufacturers already use many different types of coatings — some developed at Argonne — for metal parts in engines and other applications. The problem is those coatings are expensive and difficult to apply, and once they are in use, they only last until the coating wears through. The new catalyst allows the tribofilm to be continually renewed during operation.

Additionally, because the tribofilm develops in the presence of base oil, it could allow manufacturers to reduce, or possibly eliminate, some of the modern anti-friction and anti-wear additives in oil. These additives can decrease the efficiency of vehicle catalytic converters and can be harmful to the environment because of their heavy metal content.

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

Carbon-based tribofilms from lubricating oils by Ali Erdemir, Giovanni Ramirez, Osman L. Eryilmaz, Badri Narayanan, Yifeng Liao, Ganesh Kamath, & Subramanian K. R. S. Sankaranarayanan. Nature 536, 67–71 (04 August 2016) doi:10.1038/nature18948 Published online 03 August 2016

This paper is behind a paywall.

Heat, evolution, and the shape of gold nanorods

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A Feb. 23, 2015 news item on Azonano features gold nanorods and their shapeshifting ways when releasing heat,

Researchers at the U.S. Department of Energy’s Argonne National Laboratory have revealed previously unobserved behaviors that show how details of the transfer of heat at the nanoscale cause nanoparticles to change shape in ensembles.

The new findings depict three distinct stages of evolution in groups of gold nanorods, from the initial rod shape to the intermediate shape to a sphere-shaped nanoparticle. The research suggests new rules for the behavior of nanorod ensembles, providing insights into how to increase heat transfer efficiency in a nanoscale system.

A Feb. 18, 2015 Argonne National Laboratory news release by Justin H. S. Breaux, which originated the news item, provides more details about the work,

At the nanoscale, individual gold nanorods have unique electronic, thermal and optical properties. Understanding these properties and managing how collections of these elongated nanoparticles absorb and release this energy as heat will drive new research towards next-generation technologies such as water purification systems, battery materials and cancer research.

A good deal is known about how single nanorods behave—but little is known about how nanorods behave in ensembles of millions. Understanding how the individual behavior of each nanorod, including how its orientation and rate of transition differ from those around it, impacts the collective kinetics of the ensemble and is critical to using nanorods in future technologies.

“We started with a lot of questions,” said Argonne physicist Yuelin Li, “like ‘How much power can the particles sustain before losing functionality? How do individual changes at the nanoscale affect the overall functionality? How much heat is released to the surrounding area?’ Each nanorod is continuously undergoing a change in shape when heated beyond melting temperature, which means a change in the surface area and thus a change in its thermal and hydrodynamic properties.”

The researchers used a laser to heat the nanoparticles and X-rays to analyze their changing shapes. Generally, nanorods transition into nanospheres more quickly when supplied with a higher intensity of laser power. In this case, completely different ensemble behaviors were observed when this intensity increased incrementally. The intensity of the heat applied changes not only the nanoparticles’ shape at various rates but also affects their ability to efficiently absorb and release heat.

“For us, the key was to understand just how efficient the nanorods were at transferring light into heat in many different scenarios,” said nanoscientist Subramanian Sankaranarayanan of Argonne’s Center for Nanoscale Materials. “Then we had to determine the physics behind how heat was transferred and all the different ways these nanorods could transition into nanospheres.”

To observe how the rod makes this transition, researchers first shine a laser pulse at the nanorod suspended in a water solution at Argonne’s Advanced Photon Source. The laser lasts for less than a hundred femtoseconds, nearly one trillion times faster than a blink of the eye. What follows is a series of focused and rapid X-ray bursts using a technique called small angle X-ray scattering. The resulting data is used to determine the average shape of the particle as it changes over time.

In this way, scientists can reconstruct the minute changes occurring in the shape of the nanorod. However, to understand the physics underlying this phenomenon, the researchers needed to look deeper at how individual atoms vibrate and move during the transition. For this, they turned to the field of molecular dynamics using the supercomputing power of the 10-petaflop Mira supercomputer at the Argonne Leadership Computing Facility.

Mira used mathematical equations to pinpoint the individual movements of nearly two million of the nanorods’ atoms in the water. Using factors such as the shape, temperature and rate of change, the researchers built simulations of the nanorod in many different scenarios to see how the structure changes over time.

“In the end,” said Sankaranarayanan, “we discovered the heat transfer rates for shorter but wider nanospheres are lower than for their rod-shaped predecessors. This decrease in heat transfer efficiency at the nanoscale plays a key role in accelerating the transition from rod to sphere when heated beyond the melting temperature.”

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

Femtosecond Laser Pulse Driven Melting in Gold Nanorod Aqueous Colloidal Suspension: Identification of a Transition from Stretched to Exponential Kinetics by Yuelin Li, Zhang Jiang, Xiao-Min Lin, Haidan Wen, Donald A. Walko, Sanket A. Deshmukh, Ram Subbaraman, Subramanian K. R. S. Sankaranarayanan, Stephen K. Gray, & Phay Ho. Scientific Reports 5, Article number: 8146 doi:10.1038/srep08146 Published 30 January 2015

This article is open access.

Single layer graphene as a solid lubricant

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Graphite (from which graphene springs) has been used as a solid lubricant for many years but it has limitations which researchers at the US Dept. of Energy’s Argonne National Laboratory are attempting to overcome by possibly replacing it with graphene. An Oct. 14, 2014 news item on phys.org describes the research (Note: A link has been removed),

Nanoscientist Anirudha Sumant and his colleagues at Argonne’s Center for Nanoscale Materials and Argonne’s Energy Systems division applied a one-atom-thick layer of graphene, a two-dimensional form of carbon, in between a steel ball and a steel disk. They found that just the single layer of graphene lasted for more than 6,500 “wear cycles,” a dramatic improvement over conventional lubricants like graphite or molybdenum disulfide.

An Oct. 13, 2014 Argonne National Laboratory news release by Jared Sagoff, which originated the news item, provides more information about this research (Note: A link has been removed),

“For comparison,” Sumant said, “conventional lubricants would need about 1,000 layers to last for 1,000 wear cycles. That’s a huge advantage in terms of cost savings with much better performance.”

Graphite has been used as an industrial lubricant for more than 40 years, but not without certain drawbacks, Sumant explained.  “Graphite is limited by the fact that it really works only in humid environments. If you have a dry setting, it’s not going to be nearly as effective,” he said.

This limitation arises from the fact that graphite – unlike graphene – has a three-dimensional structure.  The water molecules in the moist air create slipperiness by weaving themselves in between graphite’s carbon sheets. When there are not enough water molecules in the air, the material loses its slickness.

Molybdenum disulfide, another common lubricant, has the reverse problem, Sumant said. It works in dry environments but not well in wet ones. “Essentially the challenge is to find a single all-purpose lubricant that works well for mechanical systems, no matter where they are,” he said.

Graphene’s two-dimensional structure gives it a significant advantage. “The material is able to bond directly to the surface of the stainless steel ball, making it so perfectly even that even hydrogen atoms are not able to penetrate it,” said Argonne materials scientist Ali Erdemir, a collaborator on the study who tested graphene-coated steel surfaces in his lab.

In a previous study in Materials Today, Sumant and his colleagues showed that a few layers of graphene works equally well in humid and dry environments as a solid lubricant, solving the 40-year-old puzzle of finding a flawless solid lubricant. However, the team wanted to go further and test just a single graphene layer.

While doing so in an environment containing molecules of pure hydrogen, they observed a dramatic improvement in graphene’s operational lifetime. When the graphene monolayer eventually starts to wear away, hydrogen atoms leap in to repair the lattice, like stitching a quilt back together. “Hydrogen can only get into the fabric where there is already an opening,” said Subramanian Sankaranarayanan, an Argonne computational scientist and co-author in this study. This means the graphene layer stays intact longer.

Researchers had previously done experiments to understand the mechanical strength of a single sheet of graphene, but the Argonne study is the first to explain the extraordinary wear resistance of one-atom-thick graphene.

Here’s a link to and a citation for the August 2014 study,

Extraordinary Macroscale Wear Resistance of One Atom Thick Graphene Layer by Diana Berman, Sanket A. Deshmukh, Subramanian K. R. S. Sankaranarayanan, Ali Erdemir, and Anirudha V. Sumant. Advanced Funtional Materials DOI: 10.1002/adfm.201401755 Article first published online: 26 AUG 2014

© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

This article is behind a paywall.

Studying corrosion from the other side

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Corrosion can be beautiful as well as destructive,

Typically, the process of corrosion has been studied from the metal side of the equation - See more at: http://www.anl.gov/articles/core-corrosion#sthash.ZPqFF13I.dpuf. Courtesy of the Argonne National Laboratory

Typically, the process of corrosion has been studied from the metal side of the equation – See more at: http://www.anl.gov/articles/core-corrosion#sthash.ZPqFF13I.dpuf. Courtesy of the Argonne National Laboratory

A Feb. 18, 2014 news item on Nanowerk expands on the theme of corrosion as destruction (Note: Links have been removed),

Anyone who has ever owned a car in a snowy town – or a boat in a salty sea – can tell you just how expensive corrosion can be.

One of the world’s most common and costly chemical reactions, corrosion happens frequently at the boundaries between water and metal surfaces. In the past, the process of corrosion has mostly been studied from the metal side of the equation.

However, in a new study (“Chloride ions induce order-disorder transition at water-oxide interfaces”), scientists at the Center for Nanoscale Materials at the U.S. Department of Energy’s Argonne National Laboratory investigated the problem from the other side, looking at the dynamics of water containing dissolved ions located in the regions near a metal surface.

The Feb. 14, 2014 Argonne National Laboratory news release by Jared Sagoff, which originated the news item, describes how the scientists conducted their research,

A team of researchers led by Argonne materials scientist Subramanian Sankaranarayanan simulated the physical and chemical dynamics of dissolved ions in water at the atomic level as it corrodes metal oxide surfaces. “Water-based solutions behave quite differently near a metal or oxide surface than they do by themselves,” Sankaranarayanan said. “But just how the chemical ions in the water interact with a surface has been an area of intense debate.”

Under low-chlorine conditions, water tends to form two-dimensional ordered layers near solid interfaces because of the influence of its strong hydrogen bonds. However, the researchers found that increasing the proportion of chlorine ions above a certain threshold causes a change in which the solution loses its ordered nature near the surface and begins to act similar to water away from the surface. This transition, in turn, can increase the rate at which materials corrode as well as the freezing temperature of the solution.

This switch between an ordered and a disordered structure near the metal surface happens incredibly quickly, in just fractions of a nanosecond. The speed of the chemical reaction necessitates the use of high-performance computers like Argonne’s Blue/Gene Q supercomputer, Mira.

To further explore these electrochemical oxide interfaces with high-performance computers, Sankaranarayanan and his colleagues from Argonne, Harvard University and the University of Missouri have also been awarded 40 million processor-hours of time on Mira.

“Having the ability to look at these reactions in a more powerful simulation will give us the opportunity to make a more educated guess of the rates of corrosion for different scenarios,” Sankaranarayanan said. Such studies will open up for the first time fundamental studies of corrosion behavior and will allow scientists to tailor materials surfaces to improve the stability and lifetime of materials.

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

Chloride ions induce order-disorder transition at water-oxide interfaces by Sanket Deshmukh, Ganesh Kamath, Shriram Ramanathan, and Subramanian K. R. S. Sankaranarayanan. Phys. Rev. E 88 (6), 062119 (2013) [5 pages]

This article is behind a paywall on both the primary site and the beta site (the American Physical Society is testing a new website for its publications).