Tag Archives: Purdue University

Neuromorphic (brainlike) computing inspired by sea slugs

The sea slug has taught neuroscientists the intelligence features that any creature in the animal kingdom needs to survive. Now, the sea slug is teaching artificial intelligence how to use those strategies. Pictured: Aplysia californica. (Image by NOAA Monterey Bay National Marine Sanctuary/Chad King.)

I don’t think I’ve ever seen a picture of a sea slug before. Its appearance reminds me of its terrestrial cousin.

As for some of the latest news on brainlike computing, a December 7, 2021 news item on Nanowerk makes an announcement from the Argonne National Laboratory (a US Department of Energy laboratory; Note: Links have been removed),

A team of scientists has discovered a new material that points the way toward more efficient artificial intelligence hardware for everything from self-driving cars to surgical robots.

For artificial intelligence (AI) to get any smarter, it needs first to be as intelligent as one of the simplest creatures in the animal kingdom: the sea slug.

A new study has found that a material can mimic the sea slug’s most essential intelligence features. The discovery is a step toward building hardware that could help make AI more efficient and reliable for technology ranging from self-driving cars and surgical robots to social media algorithms.

The study, published in the Proceedings of the National Academy of Sciences [PNAS] (“Neuromorphic learning with Mott insulator NiO”), was conducted by a team of researchers from Purdue University, Rutgers University, the University of Georgia and the U.S. Department of Energy’s (DOE) Argonne National Laboratory. The team used the resources of the Advanced Photon Source (APS), a DOE Office of Science user facility at Argonne.

A December 6, 2021 Argonne National Laboratory news release (also on EurekAlert) by Kayla Wiles and Andre Salles, which originated the news item, provides more detail,

“Through studying sea slugs, neuroscientists discovered the hallmarks of intelligence that are fundamental to any organism’s survival,” said Shriram Ramanathan, a Purdue professor of Materials Engineering. ​“We want to take advantage of that mature intelligence in animals to accelerate the development of AI.”

Two main signs of intelligence that neuroscientists have learned from sea slugs are habituation and sensitization. Habituation is getting used to a stimulus over time, such as tuning out noises when driving the same route to work every day. Sensitization is the opposite — it’s reacting strongly to a new stimulus, like avoiding bad food from a restaurant.

AI has a really hard time learning and storing new information without overwriting information it has already learned and stored, a problem that researchers studying brain-inspired computing call the ​“stability-plasticity dilemma.” Habituation would allow AI to ​“forget” unneeded information (achieving more stability) while sensitization could help with retaining new and important information (enabling plasticity).

In this study, the researchers found a way to demonstrate both habituation and sensitization in nickel oxide, a quantum material. Quantum materials are engineered to take advantage of features available only at nature’s smallest scales, and useful for information processing. If a quantum material could reliably mimic these forms of learning, then it may be possible to build AI directly into hardware. And if AI could operate both through hardware and software, it might be able to perform more complex tasks using less energy.

“We basically emulated experiments done on sea slugs in quantum materials toward understanding how these materials can be of interest for AI,” Ramanathan said.

Neuroscience studies have shown that the sea slug demonstrates habituation when it stops withdrawing its gill as much in response to tapping. But an electric shock to its tail causes its gill to withdraw much more dramatically, showing sensitization.

For nickel oxide, the equivalent of a ​“gill withdrawal” is an increased change in electrical resistance. The researchers found that repeatedly exposing the material to hydrogen gas causes nickel oxide’s change in electrical resistance to decrease over time, but introducing a new stimulus like ozone greatly increases the change in electrical resistance.

Ramanathan and his colleagues used two experimental stations at the APS to test this theory, using X-ray absorption spectroscopy. A sample of nickel oxide was exposed to hydrogen and oxygen, and the ultrabright X-rays of the APS were used to see changes in the material at the atomic level over time.

“Nickel oxide is a relatively simple material,” said Argonne physicist Hua Zhou, a co-author on the paper who worked with the team at beamline 33-ID. ​“The goal was to use something easy to manufacture, and see if it would mimic this behavior. We looked at whether the material gained or lost a single electron after exposure to the gas.”

The research team also conducted scans at beamline 29-ID, which uses softer X-rays to probe different energy ranges. While the harder X-rays of 33-ID are more sensitive to the ​“core” electrons, those closer to the nucleus of the nickel oxide’s atoms, the softer X-rays can more readily observe the electrons on the outer shell. These are the electrons that define whether a material is conductive or resistive to electricity.

“We’re very sensitive to the change of resistivity in these samples,” said Argonne physicist Fanny Rodolakis, a co-author on the paper who led the work at beamline 29-ID. ​“We can directly probe how the electronic states of oxygen and nickel evolve under different treatments.”

Physicist Zhan Zhang and postdoctoral researcher Hui Cao, both of Argonne, contributed to the work, and are listed as co-authors on the paper. Zhang said the APS is well suited for research like this, due to its bright beam that can be tuned over different energy ranges.

For practical use of quantum materials as AI hardware, researchers will need to figure out how to apply habituation and sensitization in large-scale systems. They also would have to determine how a material could respond to stimuli while integrated into a computer chip.

This study is a starting place for guiding those next steps, the researchers said. Meanwhile, the APS is undergoing a massive upgrade that will not only increase the brightness of its beams by up to 500 times, but will allow for those beams to be focused much smaller than they are today. And this, Zhou said, will prove useful once this technology does find its way into electronic devices.

“If we want to test the properties of microelectronics,” he said, ​“the smaller beam that the upgraded APS will give us will be essential.”

In addition to the experiments performed at Purdue and Argonne, a team at Rutgers University performed detailed theory calculations to understand what was happening within nickel oxide at a microscopic level to mimic the sea slug’s intelligence features. The University of Georgia measured conductivity to further analyze the material’s behavior.

A version of this story was originally published by Purdue University

About the Advanced Photon Source

The U. S. Department of Energy Office of Science’s Advanced Photon Source (APS) at Argonne National Laboratory is one of the world’s most productive X-ray light source facilities. The APS provides high-brightness X-ray beams to a diverse community of researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. These X-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. Each year, more than 5,000 researchers use the APS to produce over 2,000 publications detailing impactful discoveries, and solve more vital biological protein structures than users of any other X-ray light source research facility. APS scientists and engineers innovate technology that is at the heart of advancing accelerator and light-source operations. This includes the insertion devices that produce extreme-brightness X-rays prized by researchers, lenses that focus the X-rays down to a few nanometers, instrumentation that maximizes the way the X-rays interact with samples being studied, and software that gathers and manages the massive quantity of data resulting from discovery research at the APS.

This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.

Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.

The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://​ener​gy​.gov/​s​c​ience.

You can find the September 24, 2021 Purdue University story, Taking lessons from a sea slug, study points to better hardware for artificial intelligence here.

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

Neuromorphic learning with Mott insulator NiO by Zhen Zhang, Sandip Mondal, Subhasish Mandal, Jason M. Allred, Neda Alsadat Aghamiri, Alireza Fali, Zhan Zhang, Hua Zhou, Hui Cao, Fanny Rodolakis, Jessica L. McChesney, Qi Wang, Yifei Sun, Yohannes Abate, Kaushik Roy, Karin M. Rabe, and Shriram Ramanathan. PNAS September 28, 2021 118 (39) e2017239118 DOI: https://doi.org/10.1073/pnas.2017239118

This paper is behind a paywall.

Pandemic science breakthroughs: combining supercomputing materials with specialized oxides to mimic brain function

This breakthrough in neuromorphic (brainlike) computing is being attributed to the pandemic (COVID-19) according to a September 3, 2021 news item on phys.org,

Isaac Newton’s groundbreaking scientific productivity while isolated from the spread of bubonic plague is legendary. University of California San Diego physicists can now claim a stake in the annals of pandemic-driven science.

A team of UC San Diego [University of California San Diego] researchers and colleagues at Purdue University have now simulated the foundation of new types of artificial intelligence computing devices that mimic brain functions, an achievement that resulted from the COVID-19 pandemic lockdown. By combining new supercomputing materials with specialized oxides, the researchers successfully demonstrated the backbone of networks of circuits and devices that mirror the connectivity of neurons and synapses in biologically based neural networks.

A September 3, 2021 UC San Diego news release by Mario Aguilera, which originated the news item, delves further into the topic of neuromorphic computing,

As bandwidth demands on today’s computers and other devices reach their technological limit, scientists are working towards a future in which new materials can be orchestrated to mimic the speed and precision of animal-like nervous systems. Neuromorphic computing based on quantum materials, which display quantum-mechanics-based properties, allow scientists the ability to move beyond the limits of traditional semiconductor materials. This advanced versatility opens the door to new-age devices that are far more flexible with lower energy demands than today’s devices. Some of these efforts are being led by Department of Physics Assistant Professor Alex Frañó and other researchers in UC San Diego’s Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C), a Department of Energy-supported Energy Frontier Research Center.

“In the past 50 years we’ve seen incredible technological achievements that resulted in computers that were progressively smaller and faster—but even these devices have limits for data storage and energy consumption,” said Frañó, who served as one of the PNAS paper’s authors, along with former UC San Diego chancellor, UC president and physicist Robert Dynes. “Neuromorphic computing is inspired by the emergent processes of the millions of neurons, axons and dendrites that are connected all over our body in an extremely complex nervous system.”

As experimental physicists, Frañó and Dynes are typically busy in their laboratories using state-of-the-art instruments to explore new materials. But with the onset of the pandemic, Frañó and his colleagues were forced into isolation with concerns about how they would keep their research moving forward. They eventually came to the realization that they could advance their science from the perspective of simulations of quantum materials.

“This is a pandemic paper,” said Frañó. “My co-authors and I decided to study this issue from a more theoretical perspective so we sat down and started having weekly (Zoom-based) meetings. Eventually the idea developed and took off.”

The researchers’ innovation was based on joining two types of quantum substances—superconducting materials based on copper oxide and metal insulator transition materials that are based on nickel oxide. They created basic “loop devices” that could be precisely controlled at the nano-scale with helium and hydrogen, reflecting the way neurons and synapses are connected. Adding more of these devices that link and exchange information with each other, the simulations showed that eventually they would allow the creation of an array of networked devices that display emergent properties like an animal’s brain.

Like the brain, neuromorphic devices are being designed to enhance connections that are more important than others, similar to the way synapses weigh more important messages than others.

“It’s surprising that when you start to put in more loops, you start to see behavior that you did not expect,” said Frañó. “From this paper we can imagine doing this with six, 20 or a hundred of these devices—then it gets exponentially rich from there. Ultimately the goal is to create a very large and complex network of these devices that will have the ability to learn and adapt.”

With eased pandemic restrictions, Frañó and his colleagues are back in the laboratory, testing the theoretical simulations described in the PNAS [Proceedings of the National Academy of Sciences] paper with real-world instruments.

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

Low-temperature emergent neuromorphic networks with correlated oxide devices by Uday S. Goteti, Ivan A. Zaluzhnyy, Shriram Ramanathan, Robert C. Dynes, and Alex Frano. PNAS August 31, 2021 118 (35) e2103934118; DOI: https://doi.org/10.1073/pnas.2103934118

This paper is open access.

The coolest paint

It’s the ‘est’ of it all. The coolest, the whitest, the blackest … Scientists and artists are both pursuing the ‘est’. (More about the pursuit later in this posting.)

In this case, scientists have developed the coolest, whitest paint yet. From an April 16, 2021 news item on Nanowerk,

In an effort to curb global warming, Purdue University engineers have created the whitest paint yet. Coating buildings with this paint may one day cool them off enough to reduce the need for air conditioning, the researchers say.

In October [2020], the team created an ultra-white paint that pushed limits on how white paint can be. Now they’ve outdone that. The newer paint not only is whiter but also can keep surfaces cooler than the formulation that the researchers had previously demonstrated.

“If you were to use this paint to cover a roof area of about 1,000 square feet, we estimate that you could get a cooling power of 10 kilowatts. That’s more powerful than the central air conditioners used by most houses,” said Xiulin Ruan, a Purdue professor of mechanical engineering.

Caption: Xiulin Ruan, a Purdue University professor of mechanical engineering, holds up his lab’s sample of the whitest paint on record. Credit: Purdue University/Jared Pike

This is nicely done. Researcher Xiulin Ruan is standing close to a structure that could be said to resemble the sun while in shirtsleeves and sunglasses and holding up a sample of his whitest paint in April (not usually a warm month in Indiana).

An April 15, 2021 Purdue University news release (also on EurkeAlert), which originated the news item, provides more detail about the work and hints about its commercial applications both civilian and military,

The researchers believe that this white may be the closest equivalent of the blackest black, “Vantablack,” [emphasis mine; see comments later in this post] which absorbs up to 99.9% of visible light. The new whitest paint formulation reflects up to 98.1% of sunlight – compared with the 95.5% of sunlight reflected by the researchers’ previous ultra-white paint – and sends infrared heat away from a surface at the same time.

Typical commercial white paint gets warmer rather than cooler. Paints on the market that are designed to reject heat reflect only 80%-90% of sunlight and can’t make surfaces cooler than their surroundings.

The team’s research paper showing how the paint works publishes Thursday (April 15 [2021]) as the cover of the journal ACS Applied Materials & Interfaces.

What makes the whitest paint so white

Two features give the paint its extreme whiteness. One is the paint’s very high concentration of a chemical compound called barium sulfate [emphasis mine] which is also used to make photo paper and cosmetics white.

“We looked at various commercial products, basically anything that’s white,” said Xiangyu Li, a postdoctoral researcher at the Massachusetts Institute of Technology who worked on this project as a Purdue Ph.D. student in Ruan’s lab. “We found that using barium sulfate, you can theoretically make things really, really reflective, which means that they’re really, really white.”

The second feature is that the barium sulfate particles are all different sizes in the paint. How much each particle scatters light depends on its size, so a wider range of particle sizes allows the paint to scatter more of the light spectrum from the sun.

“A high concentration of particles that are also different sizes gives the paint the broadest spectral scattering, which contributes to the highest reflectance,” said Joseph Peoples, a Purdue Ph.D. student in mechanical engineering.

There is a little bit of room to make the paint whiter, but not much without compromising the paint.”Although a higher particle concentration is better for making something white, you can’t increase the concentration too much. The higher the concentration, the easier it is for the paint to break or peel off,” Li said.

How the whitest paint is also the coolest

The paint’s whiteness also means that the paint is the coolest on record. Using high-accuracy temperature reading equipment called thermocouples, the researchers demonstrated outdoors that the paint can keep surfaces 19 degrees Fahrenheit cooler than their ambient surroundings at night. It can also cool surfaces 8 degrees Fahrenheit below their surroundings under strong sunlight during noon hours.

The paint’s solar reflectance is so effective, it even worked in the middle of winter. During an outdoor test with an ambient temperature of 43 degrees Fahrenheit, the paint still managed to lower the sample temperature by 18 degrees Fahrenheit.

This white paint is the result of six years of research building on attempts going back to the 1970s to develop radiative cooling paint as a feasible alternative to traditional air conditioners.

Ruan’s lab had considered over 100 different materials, narrowed them down to 10 and tested about 50 different formulations for each material. Their previous whitest paint was a formulation made of calcium carbonate, an earth-abundant compound commonly found in rocks and seashells.

The researchers showed in their study that like commercial paint, their barium sulfate-based paint can potentially handle outdoor conditions. The technique that the researchers used to create the paint also is compatible with the commercial paint fabrication process.

Patent applications for this paint formulation have been filed through the Purdue Research Foundation Office of Technology Commercialization. This research was supported by the Cooling Technologies Research Center at Purdue University and the Air Force Office of Scientific Research [emphasis mine] through the Defense University Research Instrumentation Program (Grant No.427 FA9550-17-1-0368). The research was performed at Purdue’s FLEX Lab and Ray W. Herrick Laboratories and the Birck Nanotechnology Center of Purdue’s Discovery Park.

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

Ultrawhite BaSO4 Paints and Films for Remarkable Daytime Subambient Radiative Cooling by Xiangyu Li, Joseph Peoples, Peiyan Yao, and Xiulin Ruan. ACS Appl. Mater. Interfaces 2021, XXXX, XXX, XXX-XXX DOI: https://doi.org/10.1021/acsami.1c02368 Publication Date:April 15, 2021 © 2021 American Chemical Society

This paper is behind a paywall.

Vantablack and the ongoing ‘est’ of blackest

Vantablack’s 99.9% light absorption no longer qualifies it for the ‘blackest black’. A newer standard for the ‘blackest black’ was set by the US National Institute of Standards and Technology at 99.99% light absorption with its N.I.S.T. ultra-black in 2019, although that too seems to have been bested.

I have three postings covering the Vantablack and blackest black story,

The third posting (December 2019) provides a brief summary of the story along with what was the latest from the US National Institute of Standards and Technology. There’s also a little bit about the ‘The Redemption of Vanity’ an art piece demonstrating the blackest black material from the Massachusetts Institute of Technology, which they state has 99.995% (at least) absorption of light.

From a science perspective, the blackest black would be useful for space exploration.

I am surprised there doesn’t seem to have been an artistic rush to work with the whitest white. That impression may be due to the fact that the feuds get more attention than quiet work.

Dark side to the whitest white?

Andrew Parnell, research fellow in physics and astronomy at the University of Sheffield (UK), mentions a downside to obtaining the material needed to produce this cooling white paint in a June 10, 2021 essay on The Conversation (h/t Fast Company), Note: Links have been removed,

… this whiter-than-white paint has a darker side. The energy required to dig up raw barite ore to produce and process the barium sulphite that makes up nearly 60% of the paint means it has a huge carbon footprint. And using the paint widely would mean a dramatic increase in the mining of barium.

Parnell ends his essay with this (Note: Links have been removed),

Barium sulphite-based paint is just one way to improve the reflectivity of buildings. I’ve spent the last few years researching the colour white in the natural world, from white surfaces to white animals. Animal hairs, feathers and butterfly wings provide different examples of how nature regulates temperature within a structure. Mimicking these natural techniques could help to keep our cities cooler with less cost to the environment.

The wings of one intensely white beetle species called Lepidiota stigma appear a strikingly bright white thanks to nanostructures in their scales, which are very good at scattering incoming light. This natural light-scattering property can be used to design even better paints: for example, by using recycled plastic to create white paint containing similar nanostructures with a far lower carbon footprint. When it comes to taking inspiration from nature, the sky’s the limit.

Spider web-like electronics with graphene

A spiderweb-inspired fractal design is used for hemispherical 3D photodetection to replicate the vision system of arthropods. (Sena Huh image)

This image is pretty and I’m pretty sure it’s an illustration and not a real photodetection system. Regardless, an Oct. 21, 2020 news item on Nanowerk describes the research into producing a real 3D hemispheric photodetector for biomedical imaging (Note: A link has been removed),

Purdue University innovators are taking cues from nature to develop 3D photodetectors for biomedical imaging.

The researchers used some architectural features from spider webs to develop the technology. Spider webs typically provide excellent mechanical adaptability and damage-tolerance against various mechanical loads such as storms.

“We employed the unique fractal design of a spider web for the development of deformable and reliable electronics that can seamlessly interface with any 3D curvilinear surface,” said Chi Hwan Lee, a Purdue assistant professor of biomedical engineering and mechanical engineering. “For example, we demonstrated a hemispherical, or dome-shaped, photodetector array that can detect both direction and intensity of incident light at the same time, like the vision system of arthropods such as insects and crustaceans.”

The Purdue technology uses the structural architecture of a spider web that exhibits a repeating pattern. This work is published in Advanced Materials (“Fractal Web Design of a Hemispherical Photodetector Array with Organic-Dye-Sensitized Graphene Hybrid Composites”).

An Oct. 21, 2020 Purdue University news release by Chris Adam, which originated the news item, delves further into the work,

Lee said this provides unique capabilities to distribute externally induced stress throughout the threads according to the effective ratio of spiral and radial dimensions and provides greater extensibility to better dissipate force under stretching. Lee said it also can tolerate minor cuts of the threads while maintaining overall strength and function of the entire web architecture.

“The resulting 3D optoelectronic architectures are particularly attractive for photodetection systems that require a large field of view and wide-angle antireflection, which will be useful for many biomedical and military imaging purposes,” said Muhammad Ashraful Alam, the Jai N. Gupta Professor of Electrical and Computer Engineering.

Alam said the work establishes a platform technology that can integrate a fractal web design with system-level hemispherical electronics and sensors, thereby offering several excellent mechanical adaptability and damage-tolerance against various mechanical loads.

“The assembly technique presented in this work enables deploying 2D deformable electronics in 3D architectures, which may foreshadow new opportunities to better advance the field of 3D electronic and optoelectronic devices,” Lee said.

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

Fractal Web Design of a Hemispherical Photodetector Array with Organic‐Dye‐Sensitized Graphene Hybrid Composites by Eun Kwang Lee, Ratul Kumar Baruah, Jung Woo Leem, Woohyun Park, Bong Hoon Kim, Augustine Urbas, Zahyun Ku, Young L. Kim, Muhammad Ashraful Alam, Chi Hwan Lee. Advanced Materials Volume 32, Issue 46 November 19, 2020 2004456 DOI: https://doi.org/10.1002/adma.202004456 First published online: 12 October 2020

This paper is behind a paywall.

Artificial intelligence (AI) consumes a lot of energy but tree-like memory may help conserve it

A simulation of a quantum material’s properties reveals its ability to learn numbers, a test of artificial intelligence. (Purdue University image/Shakti Wadekar)

A May 7, 2020 Purdue University news release (also on EurekAlert) describes a new approach for energy-efficient hardware in support of artificial intelligence (AI) systems,

To just solve a puzzle or play a game, artificial intelligence can require software running on thousands of computers. That could be the energy that three nuclear plants produce in one hour.

A team of engineers has created hardware that can learn skills using a type of AI that currently runs on software platforms. Sharing intelligence features between hardware and software would offset the energy needed for using AI in more advanced applications such as self-driving cars or discovering drugs.

“Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circuit components in addition to what is happening in software, you could do things that simply cannot be done today,” said Shriram Ramanathan, a professor of materials engineering at Purdue University.

AI hardware development is still in early research stages. Researchers have demonstrated AI in pieces of potential hardware, but haven’t yet addressed AI’s large energy demand.

As AI penetrates more of daily life, a heavy reliance on software with massive energy needs is not sustainable, Ramanathan said. If hardware and software could share intelligence features, an area of silicon might be able to achieve more with a given input of energy.

Ramanathan’s team is the first to demonstrate artificial “tree-like” memory in a piece of potential hardware at room temperature. Researchers in the past have only been able to observe this kind of memory in hardware at temperatures that are too low for electronic devices.

The results of this study are published in the journal Nature Communications.

The hardware that Ramanathan’s team developed is made of a so-called quantum material. These materials are known for having properties that cannot be explained by classical physics. Ramanathan’s lab has been working to better understand these materials and how they might be used to solve problems in electronics.

Software uses tree-like memory to organize information into various “branches,” making that information easier to retrieve when learning new skills or tasks.

The strategy is inspired by how the human brain categorizes information and makes decisions.

“Humans memorize things in a tree structure of categories. We memorize ‘apple’ under the category of ‘fruit’ and ‘elephant’ under the category of ‘animal,’ for example,” said Hai-Tian Zhang, a Lillian Gilbreth postdoctoral fellow in Purdue’s College of Engineering. “Mimicking these features in hardware is potentially interesting for brain-inspired computing.”

The team introduced a proton to a quantum material called neodymium nickel oxide. They discovered that applying an electric pulse to the material moves around the proton. Each new position of the proton creates a different resistance state, which creates an information storage site called a memory state. Multiple electric pulses create a branch made up of memory states.

“We can build up many thousands of memory states in the material by taking advantage of quantum mechanical effects. The material stays the same. We are simply shuffling around protons,” Ramanathan said.

Through simulations of the properties discovered in this material, the team showed that the material is capable of learning the numbers 0 through 9. The ability to learn numbers is a baseline test of artificial intelligence.

The demonstration of these trees at room temperature in a material is a step toward showing that hardware could offload tasks from software.

“This discovery opens up new frontiers for AI that have been largely ignored because implementing this kind of intelligence into electronic hardware didn’t exist,” Ramanathan said.

The material might also help create a way for humans to more naturally communicate with AI.

“Protons also are natural information transporters in human beings. A device enabled by proton transport may be a key component for eventually achieving direct communication with organisms, such as through a brain implant,” Zhang said.

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

Perovskite neural trees by Hai-Tian Zhang, Tae Joon Park, Shriram Ramanathan. Nature Communications volume 11, Article number: 2245 (2020) DOI: https://doi.org/10.1038/s41467-020-16105-y Published: 07 May 2020

This paper is open access.

Control your electronics devices with your clothing while protecting yourself from bacteria

Purdue University researchers have developed a new fabric innovation that allows the wearer to control electronic devices through the clothing. Courtesy: Purdue University

I like the image but do they really want someone pressing a cufflink? Anyway, being able to turn on your house lights and music system with your clothing would certainly be convenient. From an August 8, 2019 Purdue University (Indiana, US) news release (also on EurekAlert) by Chris Adam,

A new addition to your wardrobe may soon help you turn on the lights and music – while also keeping you fresh, dry, fashionable, clean and safe from the latest virus that’s going around.

Purdue University researchers have developed a new fabric innovation that allows wearers to control electronic devices through clothing.

“It is the first time there is a technique capable to transform any existing cloth item or textile into a self-powered e-textile containing sensors, music players or simple illumination displays using simple embroidery without the need for expensive fabrication processes requiring complex steps or expensive equipment,” said Ramses Martinez, an assistant professor in the School of Industrial Engineering and in the Weldon School of Biomedical Engineering in Purdue’s College of Engineering.

The technology is featured in the July 25 [2019] edition of Advanced Functional Materials.

“For the first time, it is possible to fabricate textiles that can protect you from rain, stains, and bacteria while they harvest the energy of the user to power textile-based electronics,” Martinez said. “These self-powered e-textiles also constitute an important advancement in the development of wearable machine-human interfaces, which now can be washed many times in a conventional washing machine without apparent degradation.

Martinez said the Purdue waterproof, breathable and antibacterial self-powered clothing is based on omniphobic triboelectric nanogeneragtors (RF-TENGs) – which use simple embroidery and fluorinated molecules to embed small electronic components and turn a piece of clothing into a mechanism for powering devices. The Purdue team says the RF-TENG technology is like having a wearable remote control that also keeps odors, rain, stains and bacteria away from the user.

“While fashion has evolved significantly during the last centuries and has easily adopted recently developed high-performance materials, there are very few examples of clothes on the market that interact with the user,” Martinez said. “Having an interface with a machine that we are constantly wearing sounds like the most convenient approach for a seamless communication with machines and the Internet of Things.”

The technology is being patented through the Purdue Research Foundation Office of Technology Commercialization. The researchers are looking for partners to test and commercialize their technology.

Their work aligns with Purdue’s Giant Leaps celebration of the university’s global advancements in artificial intelligence and health as part of Purdue’s 150th anniversary. It is one of the four themes of the yearlong celebration’s Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world issues.

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

Waterproof, Breathable, and Antibacterial Self‐Powered e‐Textiles Based on Omniphobic Triboelectric Nanogenerators by Marina Sala de Medeiros, Daniela Chanci, Carolina Moreno, Debkalpa Goswami, Ramses V. Martinez. Advanced Functional Materials DOI: https://doi.org/10.1002/adfm.201904350 First published online: 25 July 2019

This paper is behind a paywall.

New ingredient for computers: water!

A July 25, 2019 news item on Nanowerk provides a description of Moore`s Law and some ‘watery’ research that may upend it,

Moore’s law – which says the number of components that could be etched onto the surface of a silicon wafer would double every two years – has been the subject of recent debate. The quicker pace of computing advancements in the past decade have led some experts to say Moore’s law, the brainchild of Intel co-founder Gordon Moore in the 1960s, no longer applies. Particularly of concern, next-generation computing devices require features smaller than 10 nanometers – driving unsustainable increases in fabrication costs.

Biology creates features at sub-10nm scales routinely, but they are often structured in ways that are not useful for applications like computing. A Purdue University group has found ways of transforming structures that occur naturally in cell membranes to create other architectures, like parallel 1nm-wide line segments, more applicable to computing.

Inspired by biological cell membranes, Purdue researchers in the Claridge Research Group have developed surfaces that act as molecular-scale blueprints for unpacking and aligning nanoscale components for next-generation computers. The secret ingredient? Water, in tiny amounts.

A July 25, 2019 Purdue University news release (also on EurekAlert), expands on the theme,

“Biology has an amazing tool kit for embedding chemical information in a surface,” said Shelley Claridge, a recently tenured faculty member in chemistry and biomedical engineering at Purdue, who leads a group of nanomaterials researchers. “What we’re finding is that these instructions can become even more powerful in nonbiological settings, where water is scarce.”

In work just published in Chem, sister journal to Cell, the group has found that stripes of lipids can unpack and order flexible gold nanowires with diameters of just 2 nm, over areas corresponding to many millions of molecules in the template surface.

“The real surprise was the importance of water,” Claridge said. “Your body is mostly water, so the molecules in your cell membranes depend on it to function. Even after we transform the membrane structure in a way that’s very nonbiological and dry it out, these molecules can pull enough water out of dry winter air to do their job.”

Their work aligns with Purdue’s Giant Leaps celebration, celebrating the global advancements in sustainability as part of Purdue’s 150th anniversary. Sustainability is one of the four themes of the yearlong celebration’s Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world issues.

The research team is working with the Purdue Research Foundation Office of Technology Commercialization to patent their work. They are looking for partners for continued research and to take the technology to market. [emphasis mine]

I wonder how close they are to taking this work to market. Usually they say it will be five to 10 years but perhaps we’ll see water-based computers in the near future. In the meantime, here’s a link to and a citation for the paper,

1-nm-Wide Hydrated Dipole Arrays Regulate AuNW Assembly on Striped Monolayers in Nonpolar Solvent by Ashlin G. Porter, Tianhong Ouyang, Tyler R. Hayes, John Biechele-Speziale, Shane R. Russell, Shelley A. Claridge. Chem DOI: DOI:https://doi.org/10.1016/j.chempr.2019.07.002 Published online:July 25, 2019

This paper is behind a paywall.

AI (artificial intelligence) and a hummingbird robot

Every once in a while I stumble across a hummingbird robot story (my August 12, 2011 posting and my August 1, 2014 posting). Here’s what the hummingbird robot looks like now (hint: there’s a significant reduction in size),

Caption: Purdue University researchers are building robotic hummingbirds that learn from computer simulations how to fly like a real hummingbird does. The robot is encased in a decorative shell. Credit: Purdue University photo/Jared Pike

I think this is the first time I’ve seen one of these projects not being funded by the military, which explains why the researchers are more interested in using these hummingbird robots for observing wildlife and for rescue efforts in emergency situations. Still, they do acknowledge theses robots could also be used in covert operations.

From a May 9, 2019 news item on ScienceDaily,

What can fly like a bird and hover like an insect?

Your friendly neighborhood hummingbirds. If drones had this combo, they would be able to maneuver better through collapsed buildings and other cluttered spaces to find trapped victims.

Purdue University researchers have engineered flying robots that behave like hummingbirds, trained by machine learning algorithms based on various techniques the bird uses naturally every day.

This means that after learning from a simulation, the robot “knows” how to move around on its own like a hummingbird would, such as discerning when to perform an escape maneuver.

Artificial intelligence, combined with flexible flapping wings, also allows the robot to teach itself new tricks. Even though the robot can’t see yet, for example, it senses by touching surfaces. Each touch alters an electrical current, which the researchers realized they could track.

“The robot can essentially create a map without seeing its surroundings. This could be helpful in a situation when the robot might be searching for victims in a dark place — and it means one less sensor to add when we do give the robot the ability to see,” said Xinyan Deng, an associate professor of mechanical engineering at Purdue.

The researchers even have a video,

A May 9, 2019 Purdue University news release (also on EurekAlert), which originated the news item, provides more detail,


The researchers [presented] their work on May 20 at the 2019 IEEE International Conference on Robotics and Automation in Montreal. A YouTube video is available at https://www.youtube.com/watch?v=hl892dHqfA&feature=youtu.be. [it’s the video I’ve embedded in the above]

Drones can’t be made infinitely smaller, due to the way conventional aerodynamics work. They wouldn’t be able to generate enough lift to support their weight.

But hummingbirds don’t use conventional aerodynamics – and their wings are resilient. “The physics is simply different; the aerodynamics is inherently unsteady, with high angles of attack and high lift. This makes it possible for smaller, flying animals to exist, and also possible for us to scale down flapping wing robots,” Deng said.

Researchers have been trying for years to decode hummingbird flight so that robots can fly where larger aircraft can’t. In 2011, the company AeroVironment, commissioned by DARPA, an agency within the U.S. Department of Defense, built a robotic hummingbird that was heavier than a real one but not as fast, with helicopter-like flight controls and limited maneuverability. It required a human to be behind a remote control at all times.

Deng’s group and her collaborators studied hummingbirds themselves for multiple summers in Montana. They documented key hummingbird maneuvers, such as making a rapid 180-degree turn, and translated them to computer algorithms that the robot could learn from when hooked up to a simulation.

Further study on the physics of insects and hummingbirds allowed Purdue researchers to build robots smaller than hummingbirds – and even as small as insects – without compromising the way they fly. The smaller the size, the greater the wing flapping frequency, and the more efficiently they fly, Deng says.

The robots have 3D-printed bodies, wings made of carbon fiber and laser-cut membranes. The researchers have built one hummingbird robot weighing 12 grams – the weight of the average adult Magnificent Hummingbird – and another insect-sized robot weighing 1 gram. The hummingbird robot can lift more than its own weight, up to 27 grams.

Designing their robots with higher lift gives the researchers more wiggle room to eventually add a battery and sensing technology, such as a camera or GPS. Currently, the robot needs to be tethered to an energy source while it flies – but that won’t be for much longer, the researchers say.

The robots could fly silently just as a real hummingbird does, making them more ideal for covert operations. And they stay steady through turbulence, which the researchers demonstrated by testing the dynamically scaled wings in an oil tank.

The robot requires only two motors and can control each wing independently of the other, which is how flying animals perform highly agile maneuvers in nature.

“An actual hummingbird has multiple groups of muscles to do power and steering strokes, but a robot should be as light as possible, so that you have maximum performance on minimal weight,” Deng said.

Robotic hummingbirds wouldn’t only help with search-and-rescue missions, but also allow biologists to more reliably study hummingbirds in their natural environment through the senses of a realistic robot.

“We learned from biology to build the robot, and now biological discoveries can happen with extra help from robots,” Deng said.
Simulations of the technology are available open-source at https://github.com/
purdue-biorobotics/flappy
.

Early stages of the work, including the Montana hummingbird experiments in collaboration with Bret Tobalske’s group at the University of Montana, were financially supported by the National Science Foundation.

The researchers have three paper on arxiv.org for open access peer review,

Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots
Fan Fei, Zhan Tu, Jian Zhang, and Xinyan Deng
Purdue University, West Lafayette, IN, USA
https://arxiv.org/abs/1902.0962

Biological studies show that hummingbirds can perform extreme aerobatic maneuvers during fast escape. Given a sudden looming visual stimulus at hover, a hummingbird initiates a fast backward translation coupled with a 180-degree yaw turn, which is followed by instant posture stabilization in just under 10 wingbeats. Consider the wingbeat frequency of 40Hz, this aggressive maneuver is carried out in just 0.2 seconds. Inspired by the hummingbirds’ near-maximal performance during such extreme maneuvers, we developed a flight control strategy and experimentally demonstrated that such maneuverability can be achieved by an at-scale 12- gram hummingbird robot equipped with just two actuators. The proposed hybrid control policy combines model-based nonlinear control with model-free reinforcement learning. We use model-based nonlinear control for nominal flight control, as the dynamic model is relatively accurate for these conditions. However, during extreme maneuver, the modeling error becomes unmanageable. A model-free reinforcement learning policy trained in simulation was optimized to ‘destabilize’ the system and maximize the performance during maneuvering. The hybrid policy manifests a maneuver that is close to that observed in hummingbirds. Direct simulation-to-real transfer is achieved, demonstrating the hummingbird-like fast evasive maneuvers on the at-scale hummingbird robot.

Acting is Seeing: Navigating Tight Space Using Flapping Wings
Zhan Tu, Fan Fei, Jian Zhang, and Xinyan Deng
Purdue University, West Lafayette, IN, USA
https://arxiv.org/abs/1902.0868

Wings of flying animals can not only generate lift and control torques but also can sense their surroundings. Such dual functions of sensing and actuation coupled in one element are particularly useful for small sized bio-inspired robotic flyers, whose weight, size, and power are under stringent constraint. In this work, we present the first flapping-wing robot using its flapping wings for environmental perception and navigation in tight space, without the need for any visual feedback. As the test platform, we introduce the Purdue Hummingbird, a flapping-wing robot with 17cm wingspan and 12 grams weight, with a pair of 30-40Hz flapping wings driven by only two actuators. By interpreting the wing loading feedback and its variations, the vehicle can detect the presence of environmental changes such as grounds, walls, stairs, obstacles and wind gust. The instantaneous wing loading can be obtained through the measurements and interpretation of the current feedback by the motors that actuate the wings. The effectiveness of the proposed approach is experimentally demonstrated on several challenging flight tasks without vision: terrain following, wall following and going through a narrow corridor. To ensure flight stability, a robust controller was designed for handling unforeseen disturbances during the flight. Sensing and navigating one’s environment through actuator loading is a promising method for mobile robots, and it can serve as an alternative or complementary method to visual perception.

Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals
Fan Fei, Zhan Tu, Yilun Yang, Jian Zhang, and Xinyan Deng
Purdue University, West Lafayette, IN, USA
https://arxiv.org/abs/1902.0962

Insects and hummingbirds exhibit extraordinary flight capabilities and can simultaneously master seemingly conflicting goals: stable hovering and aggressive maneuvering, unmatched by small scale man-made vehicles. Flapping Wing Micro Air Vehicles (FWMAVs) hold great promise for closing this performance gap. However, design and control of such systems remain challenging due to various constraints. Here, we present an open source high fidelity dynamic simulation for FWMAVs to serve as a testbed for the design, optimization and flight control of FWMAVs. For simulation validation, we recreated the hummingbird-scale robot developed in our lab in the simulation. System identification was performed to obtain the model parameters. The force generation, open- loop and closed-loop dynamic response between simulated and experimental flights were compared and validated. The unsteady aerodynamics and the highly nonlinear flight dynamics present challenging control problems for conventional and learning control algorithms such as Reinforcement Learning. The interface of the simulation is fully compatible with OpenAI Gym environment. As a benchmark study, we present a linear controller for hovering stabilization and a Deep Reinforcement Learning control policy for goal-directed maneuvering. Finally, we demonstrate direct simulation-to-real transfer of both control policies onto the physical robot, further demonstrating the fidelity of the simulation.

Enjoy!

Two-dimensional material stacks into multiple layers to build a memory cell for longer lasting batteries

This research comes from Purdue University (US) and the December announcement seemed particularly timely since battery-powered gifts are popular at Christmas but since it could be many years before this work is commercialized, you may want to tuck it away for future reference.  Also, readers familiar with memristors might see a resemblance to the memory cells mentioned in the following excerpt. From a December 13, 2018 news item on Nanowerk,

The more objects we make “smart,” from watches to entire buildings, the greater the need for these devices to store and retrieve massive amounts of data quickly without consuming too much power.

Millions of new memory cells could be part of a computer chip and provide that speed and energy savings, thanks to the discovery of a previously unobserved functionality in a material called molybdenum ditelluride.

The two-dimensional material stacks into multiple layers to build a memory cell. Researchers at Purdue University engineered this device in collaboration with the National Institute of Standards and Technology (NIST) and Theiss Research Inc.

A December 13, 2018 Purdue University news release by Kayla Wiles, which originated the news item,  describes the work in more detail,

Chip-maker companies have long called for better memory technologies to enable a growing network of smart devices. One of these next-generation possibilities is resistive random access memory, or RRAM for short.

In RRAM, an electrical current is typically driven through a memory cell made up of stacked materials, creating a change in resistance that records data as 0s and 1s in memory. The sequence of 0s and 1s among memory cells identifies pieces of information that a computer reads to perform a function and then store into memory again.

A material would need to be robust enough for storing and retrieving data at least trillions of times, but materials currently used have been too unreliable. So RRAM hasn’t been available yet for widescale use on computer chips.

Molybdenum ditelluride could potentially last through all those cycles.
“We haven’t yet explored system fatigue using this new material, but our hope is that it is both faster and more reliable than other approaches due to the unique switching mechanism we’ve observed,” Joerg Appenzeller, Purdue University’s Barry M. and Patricia L. Epstein Professor of Electrical and Computer Engineering and the scientific director of nanoelectronics at the Birck Nanotechnology Center.

Molybdenum ditelluride allows a system to switch more quickly between 0 and 1, potentially increasing the rate of storing and retrieving information. This is because when an electric field is applied to the cell, atoms are displaced by a tiny distance, resulting in a state of high resistance, noted as 0, or a state of low resistance, noted as 1, which can occur much faster than switching in conventional RRAM devices.

“Because less power is needed for these resistive states to change, a battery could last longer,” Appenzeller said.

In a computer chip, each memory cell would be located at the intersection of wires, forming a memory array called cross-point RRAM.

Appenzeller’s lab wants to explore building a stacked memory cell that also incorporates the other main components of a computer chip: “logic,” which processes data, and “interconnects,” wires that transfer electrical signals, by utilizing a library of novel electronic materials fabricated at NIST.

“Logic and interconnects drain battery too, so the advantage of an entirely two-dimensional architecture is more functionality within a small space and better communication between memory and logic,” Appenzeller said.

Two U.S. patent applications have been filed for this technology through the Purdue Office of Technology Commercialization.

The work received financial support from the Semiconductor Research Corporation through the NEW LIMITS Center (led by Purdue University), NIST, the U.S. Department of Commerce and the Material Genome Initiative.

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

Electric-field induced structural transition in vertical MoTe2- and Mo1–xWxTe2-based resistive memories by Feng Zhang, Huairuo Zhang, Sergiy Krylyuk, Cory A. Milligan, Yuqi Zhu, Dmitry Y. Zemlyanov, Leonid A. Bendersky, Benjamin P. Burton, Albert V. Davydov, & Joerg Appenzeller. Nature Materials volume 18, pages 55–61 (2019) Published: 10 December 2018 DOI: https://doi.org/10.1038/s41563-018-0234-y

This paper is behind a paywall.

Thin-film electronic stickers for the Internet of Things (IoT)

This research is from Purdue University (Indiana, US) and the University of Virginia (US) increases and improves the interactivity between objects in what’s called the Internet of Things (IoT).

Caption: Electronic stickers can turn ordinary toy blocks into high-tech sensors within the ‘internet of things.’ Credit: Purdue University image/Chi Hwan Lee

From a July 16, 2018 news item on ScienceDaily,

Billions of objects ranging from smartphones and watches to buildings, machine parts and medical devices have become wireless sensors of their environments, expanding a network called the “internet of things.”

As society moves toward connecting all objects to the internet — even furniture and office supplies — the technology that enables these objects to communicate and sense each other will need to scale up.

Researchers at Purdue University and the University of Virginia have developed a new fabrication method that makes tiny, thin-film electronic circuits peelable from a surface. The technique not only eliminates several manufacturing steps and the associated costs, but also allows any object to sense its environment or be controlled through the application of a high-tech sticker.

Eventually, these stickers could also facilitate wireless communication. …

A July 16, 2018 University of Purdue news release (also on EurekAlert), which originated the news item, explains more,

“We could customize a sensor, stick it onto a drone, and send the drone to dangerous areas to detect gas leaks, for example,” said Chi Hwan Lee, Purdue assistant professor of biomedical engineering and mechanical engineering.

Most of today’s electronic circuits are individually built on their own silicon “wafer,” a flat and rigid substrate. The silicon wafer can then withstand the high temperatures and chemical etching that are used to remove the circuits from the wafer.

But high temperatures and etching damage the silicon wafer, forcing the manufacturing process to accommodate an entirely new wafer each time.

Lee’s new fabrication technique, called “transfer printing,” cuts down manufacturing costs by using a single wafer to build a nearly infinite number of thin films holding electronic circuits. Instead of high temperatures and chemicals, the film can peel off at room temperature with the energy-saving help of simply water.

“It’s like the red paint on San Francisco’s Golden Gate Bridge – paint peels because the environment is very wet,” Lee said. “So in our case, submerging the wafer and completed circuit in water significantly reduces the mechanical peeling stress and is environmentally-friendly.”

A ductile metal layer, such as nickel, inserted between the electronic film and the silicon wafer, makes the peeling possible in water. These thin-film electronics can then be trimmed and pasted onto any surface, granting that object electronic features.

Putting one of the stickers on a flower pot, for example, made that flower pot capable of sensing temperature changes that could affect the plant’s growth.

Lee’s lab also demonstrated that the components of electronic integrated circuits work just as well before and after they were made into a thin film peeled from a silicon wafer. The researchers used one film to turn on and off an LED light display.

“We’ve optimized this process so that we can delaminate electronic films from wafers in a defect-free manner,” Lee said.

This technology holds a non-provisional U.S. patent. The work was supported by the Purdue Research Foundation, the Air Force Research Laboratory (AFRL-S-114-054-002), the National Science Foundation (NSF-CMMI-1728149) and the University of Virginia.

The researchers have provided a video,

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

Wafer-recyclable, environment-friendly transfer printing for large-scale thin-film nanoelectronics by Dae Seung Wie, Yue Zhang, Min Ku Kim, Bongjoong Kim, Sangwook Park, Young-Joon Kim, Pedro P. Irazoqui, Xiaolin Zheng, Baoxing Xu, and Chi Hwan Lee.
PNAS July 16, 2018 201806640 DOI: https://doi.org/10.1073/pnas.1806640115
published ahead of print July 16, 2018

This paper is behind a paywall.

Dexter Johnson provides some context in his July 25, 2018 posting on the Nanoclast blog (on the IEEE [Institute of Electronic and Electrical Engineers] website), Note: A link has been removed,

The Internet of Things (IoT), the interconnection of billions of objects and devices that will be communicating with each other, has been the topic of many futurists’ projections. However, getting the engineering sorted out with the aim of fully realizing the myriad visions for IoT is another story. One key issue to address: How do you get the electronics onto these devices efficiently and economically?

A team of researchers from Purdue University and the University of Virginia has developed a new manufacturing process that could make equipping a device with all the sensors and other electronics that will make it Internet capable as easily as putting a piece of tape on it.

… this new approach makes use of a water environment at room temperature to control the interfacial debonding process. This allows clean, intact delamination of prefabricated thin film devices when they’re pulled away from the original wafer.

The use of mechanical peeling in water rather than etching solution provides a number of benefits in the manufacturing scheme. Among them are simplicity, controllability, and cost effectiveness, says Chi Hwan Lee, assistant professor at Purdue University and coauthor of the paper chronicling the research.

If you have the time, do read Dexter’s piece. He always adds something that seems obvious in retrospect but wasn’t until he wrote it.