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Jo Napolitano


Argonne Scientists Help Explain Phenomenon in Hardware That Could Revolutionize AI

Scientists developed a device that can sort information similarly to how the human brain does

Published: Thursday, April 15, 2021 - 11:02

Artificial intelligence, or AI, requires a huge amount of computing power and versatile hardware to support that power. But most AI-supportive hardware is built around the same decades-old technology, and still a long way from emulating the neural activity in the human brain.

In an effort to solve this problem, a group of scientists from around the country, led by Shriram Ramanathan of Purdue University, has discovered a way to make the hardware more efficient and sustainable.

“We’re creating hardware that is smart enough to keep up [with advancements in AI] and also doesn’t use too much energy. In fact, the energy demand will be cut significantly using this technology.”—Argonne physicist Hua Zhou

Ramanathan and his team used quantum materials—those whose properties operate outside the bounds of classical physics—to develop a device that can sort information quickly and efficiently. Scientists at the Department of Energy’s (DOE) Argonne National Laboratory, DOE’s Brookhaven Laboratory (BNL), and the University of California at San Diego helped him learn exactly how it works.

Ramanathan and his team began their experiment by introducing a proton into a quantum material called neodymium nickel oxide (NdNiO3).

The collaborative research team utilized the powerful X-ray nanoprobe imaging tool to study the NdNiO₃ device showing neuron tree-like memory. A scanning electron microscope image of the NdNiO₃ device is shown at the bottom. The red rectangle shows the scanned area of the X-ray imaging. (Image by Argonne National Laboratory.)

They soon discovered that applying an electric pulse to the material moved the proton. They further learned that each new position of the proton created a different resistance state, which generated an information storage site called a memory state. Multiple electric pulses created a branch made up of memory states, mimicking the ​“tree-like” memory process of the human brain.

“This discovery opens up new frontiers for AI that have been largely ignored because the ability to implement this kind of intelligence into electronic hardware has not existed,” says Ramanathan.

He and his team chose to work with NdNiO3 because it exhibits unique electronic and magnetic properties. One of its most intriguing behaviors is its metal-to-insulator transition (MIT), for which the properties change dramatically from enabling free-flowing energy (like metal) to blocking the current (like ceramic or plastic) by changing temperature.

This unique MIT behavior has tremendous potential in electronic devices for computing and memory. In the current research, Ramanathan demonstrated the MIT process in NdNiO3 by doping protons into the material rather than by changing the temperature.

He and his team are the first to do this. Prior to the discovery, this kind of neuron ​“tree-like” network had only been observed in hardware operated at temperatures far too low for practical applications, somewhere between dry ice and liquid nitrogen.

After Ramanathan’s team made the device, scientists at the Advanced Photon Source (APS) and Center for Nanoscale Materials (CNM)—both DOE Office of Science User Facilities at Argonne—investigated the structural and electronic evolution in the material used to build it. Characterizations of the material and its working mechanism were conducted at APS beamlines 26-ID and 33-ID-D.

High-performance computing and AI applications based on current electronics consume a good deal of energy. This new artificially intelligent hardware will take some of that energy load off of those AI applications.

“We’re creating a hardware that could provide smarter algorithms for brain-like computing,” says co-author and physicist Hua Zhou of Argonne’s X-ray Science Division, who worked on this experiment at the APS. ​“In fact, the energy demand will be cut significantly using this technology.”

Potential applications include those related to neuromorphic computing systems, those that can learn and perform tasks on their own by interacting with their surroundings, and artificial synapses, which emulate biological synaptic signals in neuromorphic systems to attain brain-like computation and autonomous learning behaviors. Neuromorphic memory systems and artificial synapses could help make more energy efficient and smarter AI chips, which are used in both consumer and industrial electronics.

Findings in this area could also improve biosensing, which is critical to medical diagnostics.

Researchers at the University of California at San Diego characterized the device at the microscopic scale utilizing hard X-ray nanoprobe tools at both APS and the National Synchrotron Light Source II (NSLS-II), a DOE Office of Science User Facility at BNL.

The team used CNM’s high-performance computing cluster to investigate the atomistic mechanisms behind the tree-like behavior in nickelates.

“Using the high-performance computing cluster at CNM, we showed how the presence of an electric field can dramatically alter the barrier associated with proton migration in nickelates,” says Sukriti Manna, lead computational author and a postdoctoral researcher at the University of Illinois at Chicago (UIC) and Argonne. Manna performed the quantum calculations needed to unravel the mystery behind this phenomenon.

“An important aspect of the tree is to understand the atomistic mechanisms that enable branching,” says Subramanian Sankaranarayanan, associate professor at UIC and theory group leader at CNM. ​“In simple terms, each branch of the tree is likely a different proton migration pathway controlled by electric fields.”

Sankaranarayanan said the sharing of intelligence features between hardware and software will be particularly useful in advanced applications, such as those related to self-driving cars or in the discovery of life-saving drugs.

“We are incredibly proud of our role in unlocking the potential of this critical discovery,” he said.

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

About Argonne’s Center for Nanoscale Materials

The Center for Nanoscale Materials is one of the five DOE Nanoscale Science Research Centers, premier national user facilities for interdisciplinary research at the nanoscale supported by the DOE Office of Science. Together the NSRCs comprise a suite of complementary facilities that provide researchers with state-of-the-art capabilities to fabricate, process, characterize, and model nanoscale materials, and constitute the largest infrastructure investment of the National Nanotechnology Initiative. The NSRCs are located at DOE’s Argonne, Brookhaven, Lawrence Berkeley, Oak Ridge, Sandia, and Los Alamos National Laboratories. For more information about the DOE NSRCs, visit https://​sci​ence​.osti​.gov/​U​s​e​r​-​F​a​c​i​l​i​t​i​e​s​/​U​s​e​r​-​F​a​c​i​l​i​t​i​e​s​-​a​t​-​a​-​G​lance.

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 more than 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.

First published March 2, 2021, on Argonne National Laboratory’s website.


About The Author

Jo Napolitano’s picture

Jo Napolitano

Jo Napolitano spent nearly two decades reporting for The New York Times, Chicago Tribune, and Newsday before winning a Spencer Education Fellowship to Columbia University in 2016 in support of her reporting on immigrant youth. Her first book, The School I Deserve: Six Young Refugees and Their Fight for Equality in America, published by Beacon Press, will be released April 20, 2021.