Computers Math

Jonathan Boreyko, an associate professor in mechanical engineering, has developed an aircraft thermal management technology that stands ready for adaptation into other areas.
The research was published in Advanced Functional Materials on Aug. 18, 2020.
Boreyko was the recipient of a Young Investigator Research Program award in 2016, given by the Air Force Office of Scientific Research. This award funded the development of planar bridging-droplet thermal diodes, a novel approach to thermal management. Boreyko’s research has shown this new approach to be both highly efficient and extremely versatile.
“We are hopeful that the one-way heat transfer of our bridging-droplet diode will enable the smart thermal management of electronics, aircraft, and spacecraft,” said Boreyko.
Diodes are a special kind of device that allow heat to conduct in only one direction by use of engineered materials. For management of heat, diodes are attractive because they enable the dumping of heat entering one side, while resisting heat on the opposite side. In the case of aircraft (the focus of Boreyko’s funding), heat is absorbed from an overheated plane, but resisted from the outside environment.
Boreyko’s team created a diode using two copper plates in a sealed environment, separated by a microscopic gap. The first plate is engineered with a wick structure to hold water, while the opposite plate is coated with a water-repelling (hydrophobic) layer. The water on the wicking surface receives heat, causing evaporation into steam. As the steam moves across the narrow gap, it cools and condenses into dew droplets on the hydrophobic side. These dew droplets grow large enough to “bridge” the gap and get sucked back into the wick, starting the process again.
If the source of heat were instead applied the hydrophobic side, no steam can be produced because the water remains trapped in the wick. This is why the device can only conduct heat in one direction.
What does this look like in practice? An object producing heat, like a CPU chip, overheats if this heat is not continually removed. Boreyko’s invention is affixed to this heat source. Generated heat is transferred through the conducting plate, into the water. Water turns to steam and moves away from the source of the heat. The hydrophobic, nonconducting side prevents heat from entering via the air or other heat sources that may be near, allowing the diode to manage the heat only from its main subject.
Boreyko’s team measured a nearly 100-fold increase in heat conduction when the wicked side was heated, compared to the hydrophobic side. This is a significant improvement to existing thermal diodes. According to Boreyko, current diodes are either not very effective, only conducting a few times more heat in one direction, or require gravity. This new bridging-droplet thermal diode can be used upright, sideways, or even upside-down, and would even work in space where gravity is negligible.
The team has filed a provisional patent and is in search of industry partners to carry on the work.

Story Source:
Materials provided by Virginia Tech. Note: Content may be edited for style and length. More

Patients who need surgery to fix major bone fractures use fewer opioid pills after their procedure if they’re reminded of their values — and those reminders don’t necessarily need to come from a doctor, according to a new study published in the Journal of Medical Internet Research.
“We showed that opioid medication utilization could be decreased by more than a third in an at-risk patient population by delivering psychotherapy via a chatbot,” said the study’s lead author, Christopher Anthony, MD, the associate director of Hip Preservation at Penn Medicine and an assistant professor of Orthopaedic Surgery. “While it must be tested with future investigations, we believe our findings are likely transferrable to other patient populations.”
Although opioids can be appropriate to treat the pain that results from an injury like a broken leg or arm, there is a concern that a large prescription of opioids might be an on-ramp to dependence for many. The researchers — who included Edward Octavio Rojas, MD, a resident in Orthopaedic Surgery at the University of Iowa Hospitals & Clinics — believe a low-effort, patient-centered approach to reducing the number of opioids taken can be a valuable method for cutting into the opioid epidemic.
To test this approach, 76 patients who went to a Level 1 Trauma Center at the University of Iowa Hospitals & Clinics for fractures that required a surgery to fix were randomly divided into two groups. Although each group received the same prescription of an opioid medication for pain, just one group was enrolled in a daily text-messaging program. That group received two daily text messages to their phones for two weeks after their procedure from an automated “chatbot” — a computer that uses artificial intelligence to send messages — starting the day after their surgery. The goal of each message was to help focus patients and hone their coping skills for the inevitable pain after such a procedure.
While they don’t expressly discourage using opioid pills, the messages, designed by a pain psychologist who specialized in acceptance and commitment therapy (ACT), are designed to direct thoughts away from taking a painkiller.
Each message fell under one of six “core principles”: Values, Acceptance, Present Moment Awareness, Self-As-Context, Committed Action, and Diffusion.
So, for example, a message a patient could receive under the Acceptance principle could be: “Feelings of pain and feelings about your experience of pain are normal after surgery. Acknowledge and accept these feelings as part of the recovery process. Remember how you feel now is temporary and your healing process will continue. Call to mind pleasant feelings or thoughts that you experienced today.” Or a Committed Action message might urge a patient to work toward a life goal, even if some pain might be present.
Overall, the patients who didn’t receive the messages took 41 opioid tablets after their surgeries, on average. The group who were regularly contacted by the chatbot averaged just 26, a 37 percent difference. Moreover, they reported less pain, overall, just two weeks after their procedure.
Importantly, the messages each patient received were not curated for their individual personality. This type of effectiveness was seen without the messages needing to be overly personalized. Combined with the using a chatbot instead of a human-intensive effort, this could be a low-cost, low-effort for orthopaedic and other procedures that provides significant protection from opioid dependence.
“A realistic goal for this type of work is to decrease opioid utilization to as few tablets as possible, with the ultimate goal being to eliminate the need for opioid medication in the setting of fracture care,” Anthony said.
This study was funded by a grant from the Orthopaedic Trauma Association.
Co-authors included Valerie Keffala, PhD; Natalie Ann Glass, PhD; Benjamin J. Miller, MD; Mathew Hogue, MD; Michael Wiley, MD; Matthew Karam, MD; and John Lawrence Marsh, MD, all of the University of Iowa, as well as Apurva Shah, MD, of the Children’s Hospital of Philadelphia. More

COMPUTER SCIENCE Researchers from the University of Copenhagen and the Technical University of Denmark (DTU) thought that they were five years away from solving a math riddle from the 1980’s. In reality, and without knowing, they had nearly cracked the problem and had just given away much of the solution in a research article. The solution could be used to improve tomorrow’s phones and computers.
Jacob Holm and Eva Rotenberg
The two computer scientists, Assistant Professor Jacob Holm of UCPH and Associate Professor Eva Rotenberg of DTU almost gave their solution away in the summer of 2019, after submitting a research article that became the precursor to the article in which they finally solved the math riddle.
A veritable brain teaser. That’s how one can safely describe this mathematical problem in the discipline of graph theory. Two mathematicians from the University of Copenhagen’s Department of Computer Science and DTU have now solved a problem that the world’s quickest and most clever have been struggling with since the 1980’s.
The two computer scientists, Assistant Professor Jacob Holm of UCPH and Associate Professor Eva Rotenberg of DTU almost gave their solution away in the summer of 2019, after submitting a research article that became the precursor to the article in which they finally solved the math riddle.
“We had nearly given up on getting the last piece and solving the riddle. We thought we had a minor result, one that was interesting, but in no way solved the problem. We guessed that there would be another five years of work, at best, before we would be able to solve the puzzle,” explains Jacob Holm, who is a part of BARC, the algorithm section at UCPH’s Department of Computer Science.

advertisement

The three utilities problem
In 1913, a precursor to the now solved mathematical conundrum was published in “The Strand Magazine” as “The Three Utilities Problem”. It caused the magazine’s readers to scratch their heads and ponder. In the problem, each of three cottages must have water, gas and electricity, while the “lines” between the houses and water, electricity and gas may not cross each other — which is not possible.
A solution between the lines
Simply put, the puzzle is about how to connect a number of points in a graph without allowing the lines connecting them to cross. And how, with a mathematical calculation — an algorithm — you can make changes to an extensive “graph network” to ensure that no lines intersect without having to start all over again. Properties that can be used for, among other things, building immense road networks or the tiny innards of computers, where electrical circuitry on circuit boards may not cross.
Jacob Holm has been interested in the mathematical conundrum since 1998, but the answer was only revealed while the two researchers were reading through their already submitted research article. In the meantime, the researchers heard about a novel mathematical technique that they realized could be applied to the problem.

advertisement

“While reading our research article, we suddenly realized that the solution was before our eyes. Our next reaction was ‘oh no – we’ve shot ourselves in the foot and given away the solution,’ says Associate Professor Eva Rotenberg of DTU.
About graph theory
A GRAPH is a very simple construction used to model things that can be described as objects and the connections between them. Graph theory is both an area of mathematics and an important tool in computer science.
In this context, a graph can be illustrated by a diagram consisting of a number of points (nodes, vertices) associated with a number of lines (edges). Each edge is illustrated as a line (or curved piece) with nodes as its two endpoints.
About the solution
There are two kinds of updates in dynamic graphs: One can delete an edge and you can insert a new edge. These two operations must be made by the user, while an algorithm keeps track of the network’s drawing at all times. This is the algorithm that the researchers have found the recipe for.
Read the research article: https://arxiv.org/abs/1911.03449
Could be used for computer electronics
This is when the two researchers got busy writing the research paper and tying up loose ends to solve the conundrum that Holm had been working on intermittently since 1998.
“We worked on the article non-stop, for five to six weeks. And, it ended up filling more than 80 pages,” says Eva Rotenberg.
Fortunately, no one beat them to the solution and the two researchers were able to present their results at the main theoretical computer science conferences, which were meant to be held in Chicago, but ended up being held virtually.
So, what can the solution to this mathematical conundrum be used for? The two researchers don’t know for sure, but they have a few suggestions.
“Our research is basic research, so we rarely know what it will end up being used for. Even from the start, we find applications difficult to imagine,” says Jacob Holm, who adds:
“the design of microchips and circuit boards, found in all electronics, could be an area where our result ends up being used. When drawing wires on a circuit board, they must never intersect. Otherwise, short circuits will occur. The same applies to microchips, which contain millions of transistors and for which one must have a graph drawing.”
### More

Like electronic devices, biological cells send and receive messages, but they communicate through very different mechanisms. Now, scientists report progress on tiny communication networks that overcome this language barrier, allowing electronics to eavesdrop on cells and alter their behavior — and vice versa. These systems could enable applications including a wearable device that could diagnose and treat a bacterial infection or a capsule that could be swallowed to track blood sugar and make insulin when needed.
The researchers will present their results today at the American Chemical Society (ACS) Fall 2020 Virtual Meeting & Expo.
“We want to expand electronic information processing to include biology,” says principal investigator William E. Bentley, Ph.D. “Our goal is to incorporate biological cells in the computational decision-making process.”
The new technology Bentley’s team developed relies on redox mediators, which move electrons around cells. These small molecules carry out cellular activities by accepting or giving up electrons through reduction or oxidation reactions. Because they can also exchange electrons with electrodes, thereby producing a current, redox mediators can bridge the gap between hardware and living tissue. In ongoing work, the team, which includes co-principal investigator Gregory F. Payne, Ph.D., is developing interfaces to enable this information exchange, opening the way for electronic control of cellular behavior, as well as cellular feedback that could operate electronics.
“In one project that we are reporting on at the meeting, we engineered cells to receive electronically generated information and transmit it as molecular cues,” says Eric VanArsdale, a graduate student in Bentley’s lab at the University of Maryland, who is presenting the latest results at the meeting. The cells were designed to detect and respond to hydrogen peroxide. When placed near a charged electrode that generated this redox mediator, the cells produced a corresponding amount of a quorum sensing molecule that bacteria use to signal to each other and modulate behavior by altering gene expression.
In another recent project, the team engineered two types of cells to receive molecular information from the pathogenic bacteria Pseudomonas aeruginosa and convert it into an electronic signal for diagnostic and other applications. One group of cells produced the amino acid tyrosine, and another group made tyrosinase, which converts tyrosine into a molecule called L-DOPA. The cells were engineered so this redox mediator would be produced only if the bacteria released both a quorum sensing molecule and a toxin associated with a virulent stage of P. aeruginosa growth. The size of the resulting current generated by L-DOPA indicated the amount of bacteria and toxin present in a sample. If used in a blood test, the technique could reveal an infection and also gauge its severity. Because this information would be in electronic form, it could be wirelessly transmitted to a doctor’s office and a patient’s cell phone to inform them about the infection, Bentley says. “Ultimately, we could engineer it so that a wearable device would be triggered to give the patient a therapeutic after an infection is detected.”
The researchers envision eventually integrating the communication networks into autonomous systems in the body. For instance, a diabetes patient could swallow a capsule containing cells that monitor blood sugar. The device would store this blood sugar data and periodically send it to a cell phone, which would interpret the data and send back an electronic signal directing other cells in the capsule to make insulin as needed. As a step toward this goal, VanArsdale developed a biological analog of computer memory that uses the natural pigment melanin to store information and direct cellular signaling.
In other work, Bentley’s team and collaborators including Reza Ghodssi, Ph.D., recently designed a system to monitor conditions inside industrial bioreactors that hold thousands of gallons of cell culture for drug production. Currently, manufacturers track oxygen levels, which are vital to cells’ productivity, with a single probe in the side of each vessel. That probe can’t confirm conditions are uniform everywhere in the bioreactor, so the researchers developed “smart marbles” that will circulate throughout the vessel measuring oxygen. The marbles transmit data via Bluetooth to a cell phone that could adjust operating conditions. In the future, these smart marbles could serve as a communication interface to detect chemical signals within a bioreactor, send that information to a computer, and then transmit electronic signals to direct the behavior of engineered cells in the bioreactor. The team is working with instrument makers interested in commercializing the design, which could be adapted for environmental monitoring and other uses.

Story Source:
Materials provided by American Chemical Society. Note: Content may be edited for style and length. More

Although true “cyborgs” — part human, part robotic beings — are science fiction, researchers are taking steps toward integrating electronics with the body. Such devices could monitor for tumor development or stand in for damaged tissues. But connecting electronics directly to human tissues in the body is a huge challenge. Now, a team is reporting new coatings for components that could help them more easily fit into this environment.
The researchers will present their results today at the American Chemical Society (ACS) Fall 2020 Virtual Meeting & Expo. 
“We got the idea for this project because we were trying to interface rigid, inorganic microelectrodes with the brain, but brains are made out of organic, salty, live materials,” says David Martin, Ph.D., who led the study. “It wasn’t working well, so we thought there must be a better way.”
Traditional microelectronic materials, such as silicon, gold, stainless steel and iridium, cause scarring when implanted. For applications in muscle or brain tissue, electrical signals need to flow for them to operate properly, but scars interrupt this activity. The researchers reasoned that a coating could help.
“We started looking at organic electronic materials like conjugated polymers that were being used in non-biological devices,” says Martin, who is at the University of Delaware. “We found a chemically stable example that was sold commercially as an antistatic coating for electronic displays.” After testing, the researchers found that the polymer had the properties necessary for interfacing hardware and human tissue.
“These conjugated polymers are electrically active, but they are also ionically active,” Martin says. “Counter ions give them the charge they need so when they are in operation, both electrons and ions are moving around.” The polymer, known as poly(3,4-ethylenedioxythiophene) or PEDOT, dramatically improved the performance of medical implants by lowering their impedance two to three orders of magnitude, thus increasing signal quality and battery lifetime in patients.
Martin has since determined how to specialize the polymer, putting different functional groups on PEDOT. Adding a carboxylic acid, aldehyde or maleimide substituent to the ethylenedioxythiophene (EDOT) monomer gives the researchers the versatility to create polymers with a variety of functions.
“The maleimide is particularly powerful because we can do click chemistry substitutions to make functionalized polymers and biopolymers,” Martin says. Mixing unsubstituted monomer with the maleimide-substituted version results in a material with many locations where the team can attach peptides, antibodies or DNA. “Name your favorite biomolecule, and you can in principle make a PEDOT film that has whatever biofunctional group you might be interested in,” he says.
Most recently, Martin’s group created a PEDOT film with an antibody for vascular endothelial growth factor (VEGF) attached. VEGF stimulates blood vessel growth after injury, and tumors hijack this protein to increase their blood supply. The polymer that the team developed could act as a sensor to detect overexpression of VEGF and thus early stages of disease, among other potential applications.
Other functionalized polymers have neurotransmitters on them, and these films could help sense or treat brain or nervous system disorders. So far, the team has made a polymer with dopamine, which plays a role in addictive behaviors, as well as dopamine-functionalized variants of the EDOT monomer. Martin says these biological-synthetic hybrid materials might someday be useful in merging artificial intelligence with the human brain.
Ultimately, Martin says, his dream is to be able to tailor how these materials deposit on a surface and then to put them in tissue in a living organism. “The ability to do the polymerization in a controlled way inside a living organism would be fascinating.” More

Imagine if every time you looked at a face, one side of the face always appeared distorted as if it were melting, resembling a painting by Salvador Dalí. This is the case for people who have a rare condition known as hemi-prosopometamophosia (hemi-PMO), which makes looking at faces discomforting. According to a new study published in Current Biology, some people with hemi-PMO see distortions to the same half of a person’s face regardless of how the face is viewed. The results demonstrate that our visual system standardizes all the faces we perceive using the same process so they can be better compared to faces we have seen before.
“Every time we see a face, the brain adjusts our representation of that face so its size, viewpoint, and orientation is matched to faces stored in memory, just like computer face recognition systems such as those used by Facebook and Google,” explains co-author Brad Duchaine, a professor of psychological and brain sciences and the principal investigator of the Social Perception Lab at Dartmouth College. “By aligning the perceived face with faces stored in memory, it’s much easier for us to determine whether the face is one we’ve seen before,” he added.
Hemi-PMO is a rare disorder that may occur after brain damage. When a person with this condition looks at a face, facial features on one side of the face appear distorted. The existence of hemi-PMO suggests the two halves of the face are processed separately. The condition usually dissipates over time, which makes it difficult to study. As a result, little is known about the condition or what it reveals about how human face processing normally works.
The current study focused on a right-handed man in his early sixties (“Patient A.D.”) with hemi-PMO whose symptoms have persisted for years. Like many with this condition, his distortions were caused by damage to a fiber bundle called the splenium that connects visual areas in the left hemisphere and right hemisphere of his brain. Five years ago while A.D. was watching television, he noticed that the right halves of people’s faces looked like they had melted. Yet, the left sides of their faces looked normal. He looked in the mirror at his own face and noticed that the right side of his reflection was also distorted. In contrast, A.D. sees no distortions in other body parts or objects.
The study involved two experiments. In the first, A.D. was presented with images of human faces and non-face images such as objects, houses and cars, and asked to report on distortions. For 17 of the 20 faces, he saw distortions. The distortions were always on the right side of the face and facial features usually appeared to drooped. For example, in one of the faces, A.D. reported that the right eye looked a lot bigger than the left eye while the right eyebrow, right side of the nose, and right side of the lips all hung down unnaturally. Two of the face photographs that did not elicit a distortion showed right profile views in which the right side of the face was not visible. Consistent with his daily experiences, A.D. did not see distortions in any of the non-face images. These results show that his condition affects brain processes specialized for faces.
For the second part of the study, A.D. reported on distortions that he saw in 15 different faces that were presented in a variety of ways: in the left and right visual field, at different in-depth rotations, and at four picture plane rotations — 0 degrees or upright, 90 degrees, 180 degrees or upside down, and 270 degrees. Regardless of how the faces were presented, A.D. continued to report that the distortions affected the same facial features. For example, even when a face was presented upside down, A.D. still saw the facial features distorted on the right side of the face even though the distortion now appeared on the left-hand side of the stimulus. The consistency of the location of A.D.’s distortion demonstrates that faces, regardless of viewpoint or orientation, are aligned to the same template similar to what computer face recognition systems do. In A.D.’s case, the output from that process is disrupted as it is passed from one brain hemisphere to the other due to his splenium lesion.

Story Source:
Materials provided by Dartmouth College. Note: Content may be edited for style and length. More

Most of modern medicine has physical tests or objective techniques to define much of what ails us. Yet, there is currently no blood or genetic test, or impartial procedure that can definitively diagnose a mental illness, and certainly none to distinguish between different psychiatric disorders with similar symptoms. Experts at the University of Tokyo are combining machine learning with brain imaging tools to redefine the standard for diagnosing mental illnesses.
“Psychiatrists, including me, often talk about symptoms and behaviors with patients and their teachers, friends and parents. We only meet patients in the hospital or clinic, not out in their daily lives. We have to make medical conclusions using subjective, secondhand information,” explained Dr. Shinsuke Koike, M.D., Ph.D., an associate professor at the University of Tokyo and a senior author of the study recently published in Translational Psychiatry.
“Frankly, we need objective measures,” said Koike.
Challenge of overlapping symptoms
Other researchers have designed machine learning algorithms to distinguish between those with a mental health condition and nonpatients who volunteer as “controls” for such experiments.
“It’s easy to tell who is a patient and who is a control, but it is not so easy to tell the difference between different types of patients,” said Koike.

advertisement

The UTokyo research team says theirs is the first study to differentiate between multiple psychiatric diagnoses, including autism spectrum disorder and schizophrenia. Although depicted very differently in popular culture, scientists have long suspected autism and schizophrenia are somehow linked.
“Autism spectrum disorder patients have a 10-times higher risk of schizophrenia than the general population. Social support is needed for autism, but generally the psychosis of schizophrenia requires medication, so distinguishing between the two conditions or knowing when they co-occur is very important,” said Koike.
Computer converts brain images into a world of numbers
A multidisciplinary team of medical and machine learning experts trained their computer algorithm using MRI (magnetic resonance imaging) brain scans of 206 Japanese adults, a combination of patients already diagnosed with autism spectrum disorder or schizophrenia, individuals considered high risk for schizophrenia and those who experienced their first instance of psychosis, as well as neurotypical people with no mental health concerns. All of the volunteers with autism were men, but there was a roughly equal number of male and female volunteers in the other groups.
Machine learning uses statistics to find patterns in large amounts of data. These programs find similarities within groups and differences between groups that occur too often to be easily dismissed as coincidence. This study used six different algorithms to distinguish between the different MRI images of the patient groups.

advertisement

The algorithm used in this study learned to associate different psychiatric diagnoses with variations in the thickness, surface area or volume of areas of the brain in MRI images. It is not yet known why any physical difference in the brain is often found with a specific mental health condition.
Broadening the thin line between diagnoses
After the training period, the algorithm was tested with brain scans from 43 additional patients. The machine’s diagnosis matched the psychiatrists’ assessments with high reliability and up to 85 percent accuracy.
Importantly, the machine learning algorithm could distinguish between nonpatients, patients with autism spectrum disorder, and patients with either schizophrenia or schizophrenia risk factors.
Machines help shape the future of psychiatry
The research team notes that the success of distinguishing between the brains of nonpatients and individuals at risk for schizophrenia may reveal that the physical differences in the brain that cause schizophrenia are present even before symptoms arise and then remain consistent over time.
The research team also noted that the thickness of the cerebral cortex, the top 1.5 to 5 centimeters of the brain, was the most useful feature for correctly distinguishing between individuals with autism spectrum disorder, schizophrenia and typical individuals. This unravels an important aspect of the role thickness of the cortex plays in distinguishing between different psychiatric disorders and may direct future studies to understand the causes of mental illness.
Although the research team trained their machine learning algorithm using brain scans from approximately 200 individuals, all of the data were collected between 2010 to 2013 on one MRI machine, which ensured the images were consistent.
“If you take a photo with an iPhone or Android camera phone, the images will be slightly different. MRI machines are also like this — each MRI takes slightly different images, so when designing new machine learning protocols like ours, we use the same MRI machine and the exact same MRI procedure,” said Koike.
Now that their machine learning algorithm has proven its value, the researchers plan to begin using larger datasets and hopefully coordinate multisite studies to train the program to work regardless of the MRI differences. More

The human brain efficiently executes highly sophisticated tasks, such as image and speech recognition, with an exceptionally lower energy budget than today’s computers can. The development of energy-efficient and tunable artificial neurons capable of emulating brain-inspired processes has, therefore, been a major research goal for decades.
Researchers at the University of Gothenburg and Tohoku University jointly reported on an important experimental advance in this direction, demonstrating a novel voltage-controlled spintronic microwave oscillator capable of closely imitating the non-linear oscillatory neural networks of the human brain.
The research team developed a voltage-controlled spintronic oscillator, whose properties can be strongly tuned, with negligible energy consumption. “This is an important breakthrough as these so-called spin Hall nano-oscillators (SHNOs) can act as interacting oscillator-based neurons but have so far lacked an energy-efficient tuning scheme — an essential prerequisite to train the neural networks for cognitive neuromorphic tasks,” proclaimed Shunsuke Fukami, co-author of the study. “The expansion of the developed technology can also drive the tuning of the synaptic interactions between each pair of spintronic neurons in a large complex oscillatory neural network.”
Earlier this year, the Johan Åkerman group at the University of Gothenburg demonstrated, for the first time, 2D mutually synchronized arrays accommodating 100 SHNOs while occupying an area of less than a square micron. The network can mimic neuron interactions in our brain and carry out cognitive tasks. However, a major bottleneck in training such artificial neurons to produce different responses to different inputs has been the lack of the scheme to control individual oscillator inside such networks.
The Johan Åkerman group teamed up with Hideo Ohno and Shunsuke Fukami at Tohoku University to develop a bow tie-shaped spin Hall nano-oscillator made from an ultrathin W/CoFeB/MgO material stack with an added functionality of a voltage controlled gate over the oscillating region. Using an effect called voltage-controlled magnetic anisotropy (VCMA), the magnetic and magnetodynamic properties of CoFeB ferromagnet, consisting of a few atomic layers, can be directly controlled to modify the microwave frequency, amplitude, damping, and, thus, the threshold current of the SHNO.
The researchers also found a giant modulation of SHNO damping up to 42% using voltages from -3 to +1 V in the bow-tied geometry. The demonstrated approach is, therefore, capable of independently turning individual oscillators on/off within a large synchronized oscillatory network driven by a single global drive current. The findings are also valuable since they reveal a new mechanism of energy relaxation in patterned magnetic nanostructures.
Fukami notes that “With readily available energy-efficient independent control of the dynamical state of individual spintronic neurons, we hope to efficiently train large SHNO networks to carry out complex neuromorphic tasks and scale up oscillator-based neuromorphic computing schemes to much larger network sizes.”

Story Source:
Materials provided by Tohoku University. Note: Content may be edited for style and length. More