Monthly Archives: June 2025

‘Super-Turing AI’ uses less energy to mimic brain

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Neuromorphic (brainlike) engineering and neuromorphic computing being long time interests here, this March 26, 2025 new item on ScienceDaily caught my eye,

Artificial Intelligence (AI) can perform complex calculations and analyze data faster than any human, but to do so requires enormous amounts of energy. The human brain is also an incredibly powerful computer, yet it consumes very little energy.

As technology companies increasingly expand, a new approach to AI’s “thinking,” developed by researchers including Texas A&M University engineers, mimics the human brain and has the potential to revolutionize the AI industry.

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A March 25, 2025 Texas A&M University news release (also on EurekAlert) by Lesley Henton, which originated the news item, delves further into the creation of a “Super-Turing AI,” Note: Links have been removed,

As technology companies increasingly expand, a new approach to AI’s “thinking,” developed by researchers including Texas A&M University engineers, mimics the human brain and has the potential to revolutionize the AI industry.

Dr. Suin Yi, assistant professor of electrical and computer engineering at Texas A&M’s College of Engineering, is on a team of researchers that developed “Super-Turing AI,” which operates more like the human brain. This new AI integrates certain processes instead of separating them and then migrating huge amounts of data like current systems do.

The Energy Crisis In AI

Today’s AI systems, including large language models [LLM] such as OpenAI [a company not an LLM] and ChatGPT [an LLM produced by OpenAI], require immense computing power and are housed in expansive data centers that consume vast amounts of electricity.

“These data centers are consuming power in gigawatts, whereas our brain consumes 20 watts,” Suin explained. “That’s 1 billion watts compared to just 20. Data centers that are consuming this energy are not sustainable with current computing methods. So while AI’s abilities are remarkable, the hardware and power generation needed to sustain it is still needed.”

The substantial energy demands not only escalate operational costs but also raise environmental concerns, given the carbon footprint associated with large-scale data centers. As AI becomes more integrated, addressing its sustainability becomes increasingly critical.

Emulating The Brain

Yi and team believe the key to solving this problem lies in nature — specifically, the human brain’s neural processes.

In the brain, the functions of learning and memory are not separated, they are integrated. Learning and memory rely on connections between neurons, called “synapses,” where signals are transmitted. Learning strengthens or weakens synaptic connections through a process called “synaptic plasticity,” forming new circuits and altering existing ones to store and retrieve information. 

By contrast, in current computing systems, training (how the AI is taught) and memory (data storage) happen in two separate places within the computer hardware. Super-Turing AI is revolutionary because it bridges this efficiency gap, so the computer doesn’t have to migrate enormous amounts of data from one part of its hardware to another.

“Traditional AI models rely heavily on backpropagation — a method used to adjust neural networks during training,” Yi said. “While effective, backpropagation is not biologically plausible and is computationally intensive.

“What we did in that paper is troubleshoot the biological implausibility present in prevailing machine learning algorithms,” he said. “Our team explores mechanisms like Hebbian learning and spike-timing-dependent plasticity — processes that help neurons strengthen connections in a way that mimics how real brains learn.”

Hebbian learning principles are often summarized as “cells that fire together, wire together.” This approach aligns more closely with how neurons in the brain strengthen their connections based on activity patterns. By integrating such biologically inspired mechanisms, the team aims to develop AI systems that require less computational power without compromising performance.

In a test, a circuit using these components helped a drone navigate a complex environment — without prior training — learning and adapting on the fly. This approach was faster, more efficient and used less energy than traditional AI.

Why This Matters For The Future Of AI

This research could be a game-changer for the AI industry. Companies are racing to build larger and more powerful AI models, but their ability to scale is limited by hardware and energy constraints. In some cases, new AI applications require building entire new data centers, further increasing environmental and economic costs.

Yi emphasizes that innovation in hardware is just as crucial as advancements in AI systems themselves. “Many people say AI is just a software thing, but without computing hardware, AI cannot exist,” he said.

Looking Ahead: Sustainable AI Development

Super-Turing AI represents a pivotal step toward sustainable AI development. By reimagining AI architectures to mirror the efficiency of the human brain, the industry can address both economic and environmental challenges.

Yi and his team hope that their research will lead to a new generation of AI that is both smarter and more efficient.

“Modern AI like ChatGPT is awesome, but it’s too expensive. We’re going to make sustainable AI,” Yi said. “Super-Turing AI could reshape how AI is built and used, ensuring that as it continues to advance, it does so in a way that benefits both people and the planet.”

There’s no mention of a memristor but there is a ‘synaptic resistor’, which I find puzzling. Is a synaptic resistor something different? In a search with these search terms “synaptic resistor memristor” I found this,

The term “memristive synapses” signifies the amalgamation of memristor functionality with synaptic characteristics, resulting in a novel approach to neuromorphic computing.

I’m guessing memristive synapses can also be called synaptic resistors or, at the least, are related concepts.

I pulled the definition from,

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications by Rajwali Khan, Naveed Ur Rehman, Shahid Iqbal, Sherzod Abdullaev, and Haila M. Aldosari. ACS Applied Electronic Materials Vol 6/ Issue 1 pp. 73–119 DOI: https://doi.org/10.1021/acsaelm.3c01323 Published December 29, 2023 Copyright © 2023 The Authors. Published by American Chemical Society. This publication is licensed under
CC-BY 4.0

Getting back to this latest work from Texas A&M University, here’s a link to and a citation for Dr. Suin Yi and his team’s paper,

HfZrO-based synaptic resistor circuit for a Super-Turing intelligent system by Jungmin Lee, Rahul Shenoy, Atharva Deo, Suin Yi, Dawei Gao, David Qiao, Mingjie Xu, Shiva Asapu, Zixuan Rong, Dhruva Nathan, Yong Hei, Dharma Paladugu, Jian-Guo Zheng, J. Joshua Yang, R. Stanley Williams, Qing Wu, and Yong Chen. Science Advances 28 Feb 2025 Vol 11, Issue 9 DOI: 10.1126/sciadv.adr2082

This paper is open access.

Notice that one of the Super Turing paper’s authors is R. Stanley Williams who ‘discovered’ the memristor in 2008. You can read his November 28, 2008 article “How We Found the Missing Memristor; The memristor—the functional equivalent of a synapse—could revolutionize circuit design” in the IEEE Spectrum online,

It’s time to stop shrinking. Moore’s Law, the semiconductor industry’s obsession with the shrinking of transistors and their commensurate steady doubling on a chip about every two years, has been the source of a 50-year technical and economic revolution. Whether this scaling paradigm lasts for five more years or 15, it will eventually come to an end. The emphasis in electronics design will have to shift to devices that are not just increasingly infinitesimal but increasingly capable.

Earlier this year, I and my colleagues at Hewlett-Packard Labs, in Palo Alto, Calif., surprised the electronics community with a fascinating candidate for such a device: the memristor. It had been theorized nearly 40 years ago, but because no one had managed to build one, it had long since become an esoteric curiosity. That all changed on 1 May [2008], when my group published the details of the memristor in Nature.

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For anyone interested in a trip down memory road, I have a few comments from the theorist (Leon Chua) mentioned in his 2008 article in this April 13, 2010 posting (scroll down to the ‘More on memristors’ subhead).

3D nanotech blankets for clean drinking water?

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A March 24, 2025 news item on ScienceDaily announces a new technique for removing pollutants from water (aka, water remediation),

Researchers have developed a new material that, by harnessing the power of sunlight, can clear water of dangerous pollutants.

Created through a combination of soft chemistry gels and electrospinning — a technique where electrical force is applied to liquid to craft small fibers — the team constructed thin fiber-like strips of titanium dioxide (TiO₂), a compound often utilized in solar cells, gas sensors and various self-cleaning technologies.

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A March 24, 2025 Ohio State University (OSU) news release (also on EurekAlert), which originated the news item, delves further into the topic, Note: Links have been removed,

Despite being a great alternative energy source, solar fuel systems that utilize TiO₂ nanoparticles are often power-limited because they can only undergo photocatalysis, or create chemical reactions, by absorbing non-visible UV light. This can cause significant challenges to implementation, including low efficiency and the need for complex filtration systems. 

Yet when researchers added copper to the material to improve this process, their new structures, called nanomats, were able to absorb enough light energy to break down harmful pollutants in air and water, said Pelagia-Irene Gouma, lead author of the study and a professor of materials science and engineering at The Ohio State University. 

“There hasn’t been an easy way to create something like a blanket that you can lay on water and start creating energy,” she said. “But we are the only ones who have made these structures and the only ones to demonstrate that they actually work.”

The study was recently published in the journal Advanced Science. 

When titanium dioxide absorbs light, electrons are formed that oxidize water and attack pollutants, slowly destroying them until they become benign. When copper is added, that process is supercharged, making it even more effective. 

To determine this, researchers worked to characterize the nanomat’s updated properties to understand how it behaved and what made it different from other self-cleaning nanoparticles, said Gouma. Surprisingly, researchers found that compared to traditional solar cells, these nanomats can be more successful at power generation when placed under natural sunlight, she said.

“These nanomats can be used as a power generator, or as water remediation tools,” she said. “In both ways, you have a catalyst with the highest efficiency reported to date.”

These lightweight, easy-to-remove fiber mats can float and operate atop any body of water and are even reusable through multiple cleaning cycles. Because nanomats are so effective, researchers envision that they could be used to rid water of industrial pollutants in developing countries, turning otherwise contaminated rivers and lakes into sources of clean drinking water. 

Additionally, because this technology doesn’t generate any toxic byproducts like some solar cell systems, nanomats are extremely environmentally friendly. “It’s a safe material, it won’t hurt anything, and it’s as clean as it can be,” said Gouma. 

Still, although this team’s technology is incredibly efficient, how long it will take to scale up commercially depends on how quickly industries take notice of the product. “We have the tools to make them in large quantities and translate them to various industries,” said Gouma. “The only limitation is that it needs someone to take advantage of these abundant resources.”

Overall, the study’s findings suggest that nanomats could be a promising tool in many future photocatalytic applications, including long-term sustainability efforts like environmental remediation as well as solar-driven hydrogen production. 

In the meantime, the team plans to examine ways to optimize the material further. 

“This material is completely novel in terms of a new form of nanotechnology,” said Gouma. “It’s really impressive and something that we are very excited about.”

Other Ohio State co-authors include Fateh Mikaeilia and Mohammad Mahafuzur Rahaman. This study was supported by the National Science Foundation. 

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

3D Self-Supported Visible Light Photochemical Nanocatalysts by Fateh Mikaeili, Mohammad Mahafuzur Rahaman, Pelagia-Irene (Perena) Gouma. Advanced Science Online Version of Record before inclusion in an issue 2502981 DOI: https://doi.org/10.1002/advs.202502981 First published: 24 March 2025

This paper is open access.

“Does Anything Ever Come Out of a Black Hole?” hybrid event: Perimeter Institute (PI) free tickets available on Monday, June 16, 2025 at 9 am ET

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As is their practice, the Perimeter Institute (PI) for Theoretical Physics, the “Does Anything …” event itself won’t take place until sometime June 26, 2025 but, if you can attend in person. here are the details for getting a ticket or two this coming Monday morning, from a June 13, 2025 PI announcement (received via email),

Does Anything Ever Come Out of a Black Hole?

 Netta Engelhardt

Wednesday, June 25 [2025] at 7:00 pm ET

Join us for a public lecture with Professor Netta Engelhardt, one of today’s leading voices in the study of black holes and quantum gravity.

Stephen Hawking made a number of memorable contributions to physics, but perhaps his greatest was a puzzle: is information that falls into a black hole destroyed, in contradiction with the laws of quantum mechanics? The question sits squarely at the overlap of the quantum world and gravitation, a frontier of physics where direct experimental input is hard to come by. Recent progress has been revealing how subtle effects relate the radiation leaving a black hole to what happens inside. In this lecture, we will dive into the black hole information puzzle: what it is, what we have learned about it, and where it all might lead.

Don’t miss out! Free tickets to attend this event in person will become available on Monday, June 16, [2025] at 9 am ET. 

In-Person Tickets

If you didn’t get tickets for the lecture, not to worry – you can always catch the livestream on our website or watch it on YouTube after the fact.

Watch Online

I have more from the event registration page,

Location

Perimeter Institute for Theoretical Physics 31 Caroline Street North Waterloo, ON N2L 2Y5

Agenda

6:00 p.m.

Doors Open

Perimeter’s main floor Atrium will be open for ticket holders, with researchers available to answer science questions until the talk begins.

6:45 p.m. – 6:45 p.m.

Doors Close

Theater doors close to ensure all guests have enough time to enter and be seated by our ushers.

7:00 p.m. – 8:00 p.m.

Public Talk

The talk will begin at 7:00 PM, offering a live stream for virtual attendees. This will include a full presentation in the Theatre as well as a Q&A session.

8:00 p.m. – 8:30 p.m.

Atrium (Optional)

After the talk, head to the Atrium to mingle with other attendees and meet the speaker.

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About the Speaker

Netta Engelhardt works on quantum gravity, primarily within the framework of the AdS/CFT correspondence. Her research focuses on understanding the dynamics of black holes in quantum gravity, leveraging insights from the interplay between gravity and quantum information via holography. Her current primary interests revolve around the black hole information paradox, the thermodynamic behavior of black holes, and the cosmic censorship hypothesis (which conjectures that singularities are always hidden behind event horizons). Professor Engelhardt received her BSc in physics and mathematics from Brandeis University and her PhD in physics from the University of California, Santa Barbara. She was a postdoctoral fellow at Princeton University and a member of the Princeton Gravity Initiative prior to joining the physics faculty at MIT i[Massachusetts Institute of Technology] n July 2019.

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Good luck getting a ticket or “The talk will also be live-streamed on our YouTube channel: https://www.youtube.com/@PIOutreach.”

For anyone who’d like more information about Englehardt’s work, MIT issued an April 9, 2024 news release by Jennifer Chu. Note: The MIT news releases are quite good and Chu has been writing for them for years; they’re not so technical that you need a PhD in the field or so simplified that a five-year-old might find them irritating.

Faster identification of fish sounds from recordings (‘fishial recognition’) could improve research & conservation efforts

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I do love a pun. Thank you to whoever came up with the fishial/facial recognition pun. This March 11, 2025 news item on ScienceDaily announces research into fish sounds (bioacoustics) and coral reefs,

Researchers combine acoustic monitoring with a neural network to identify fish activity on coral reefs by sound. They trained the network to sort through the deluge of acoustic data automatically, analyzing audio recordings in real time. Their algorithm can match the accuracy of human experts in deciphering acoustical trends on a reef, but it can do so more than 25 times faster, and it could change the way ocean monitoring and research is conducted.

In JASA [The Journal of the Acoustical Society of America], published on behalf of the Acoustical Society of America by AIP [American Institute of Physics] Publishing, researchers from Woods Hole Oceanographic Institution combined acoustic monitoring with a neural network to identify fish activity on coral reefs by sound.

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A March 11, 2025 American Institute of Physics news release (also on the Woods Hole Oceanographic Institution website and on the EurekAlert website), which originated the news item, further describes how a neural network has benefited research into fish sounds,

For years, researchers have used passive acoustic monitoring to track coral reef activity. Typically, an acoustic recorder would be deployed underwater, where it would spend months recording audio from a reef. Existing signal processing tools can be used to analyze large batches of acoustic data at a time, but they cannot be used to find specific sounds — to do that, scientists usually need to go through all that data by hand.

“But for the people that are doing that, it’s awful work, to be quite honest,” said author Seth McCammon. “It’s incredibly tedious work. It’s miserable.”

Equally as important, this type of manual analysis is too slow for practical use. With many of the world’s coral reefs under threat from climate change and human activity, being able to rapidly identify and track changes in reef populations is crucial for conservation efforts.

“It takes years to analyze data to that level with humans,” said McCammon. “The analysis of the data in this way is not useful at scale.”

As an alternative, the researchers trained a neural network to sort through the deluge of acoustic data automatically, analyzing audio recordings in real time. Their algorithm can match the accuracy of human experts in deciphering acoustical trends on a reef, but it can do so more than 25 times faster, and it could change the way ocean monitoring and research is conducted.

“Now that we no longer need to have a human in the loop, what other sorts of devices — moving beyond just recorders — could we use?” said McCammon. “Some work that my co-author Aran Mooney is doing involves integrating this type of neural network onto a floating mooring that’s broadcasting real-time updates of fish call counts. We are also working on putting our neural network onto our autonomous underwater vehicle, CUREE, so that it can listen for fish and map out hot spots of biological activity.”

This technology also has the potential to solve a long-standing problem in marine acoustic studies: matching each unique sound to a fish.

“For the vast majority of species, we haven’t gotten to the point yet where we can say with certainty that a call came from a particular species of fish,” said McCammon. “That’s, at least in my mind, the holy grail we’re looking for. By being able to do fish call detection in real time, we can start to build devices that are able to automatically hear a call and then see what fish are nearby.”

Eventually, McCammon hopes that this neural network will provide researchers with the ability to monitor fish populations in real time, identify species in trouble, and respond to disasters. This technology will help conservationists gain a clearer picture of the health of coral reefs, in an era where reefs need all the help they can get.

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

Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural network by Seth McCammon, Nathan Formel, Sierra Jarriel, T. Aran Mooney. J. Acoust. Soc. Am. (JASA) Volume 157 Issue 3 March 2025 1665–1683 DOI: https://doi.org/10.1121/10.0035829

This paper appears to be open access.

Caption: CUREE, an autonomous underwater robot, is used by the researchers to collect acoustic data for analysis. Credit: Austin Greene, Woods Hole Oceanographic Institution

Another fishial (more information about this and other fish projects)

I found fishial.ai, which is unrelated to the research published by the AIP. From the About Us webpage,

ABOUT US

Our Project Goal

Fishial.AI is a project sponsored by “The Wye Foundation” with the goal of making highly accurate fish identification possible by building the largest open-source fish species image library labeled for AI machine learning and then creating an open-source AI based fish Identification model.

I haven’t found more than a LinkedIn page for The Wye Foundation, which seems to be located in Florida. The founders of fishial.ai, Jane Wye and Tom Wye have informative bios as members on the Board of Directors for the Celebration of the Sea organization,

Tom & Jane Wye are passionate about the oceans and are the founders of both Fishial.AI and FishAngler. Fishial.AI is being built to create the largest open-source fish specials image library labeled for AI cache learning and seeking the development of ah highly accurate open-source AI model that can identify fish specials worldwide.

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The Wye’s also are the founders of FishAngler which began with idea to advance the sport’s fishing industry into the mobile tech space and it has now evolved into a cross-device platform that answers the call for a technological update in the sport fishing industry. From beginners to avid professionals, FishAngler provides features for all anglers to capture fishing’s finest moments.

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Sports fishers, eh?

One last item, The Wye and Usk Foundation is an unrelated effort. It is a registered UK charity dedicated to “… restoring the habitat, water quality and fisheries of the rivers Wye and Usk in Wales.

As for more information about bioacoustic, specifically fish, projects, I have a pretty exhaustive description of what was then recent research and marine sound libraries in my March 4, 2022 posting “Fishes ‘talk’ and ‘sing’, which featured a video from The Guardian newspaper with fish sounds from a coral reef.

Nanomaterials used to measure nuclear reaction in radioactive nuclei produced in neutron star collisions

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There seems to be renewed interest in nuclear science as measured by the frequency of the research I’m stumbling across and as evidenced by this March 18, 2025 news item on phys.org,

Physicists have measured a nuclear reaction that can occur in neutron star collisions, providing direct experimental data for a process that had previously only been theorized. The study, led by the University of Surrey, provides new insight into how the universe’s heaviest elements are forged—and could even drive advancements in nuclear reactor physics.

Working in collaboration with the University of York, the University of Seville, and TRIUMF, Canada’s national particle accelerator centre, the breakthrough marks the first-ever measurement of a weak r-process reaction cross-section using a radioactive ion beam, in this case studying the 94Sr(α,n)97Zr reaction. This is where a radioactive form of strontium (strontium-94) absorbs an alpha particle (a helium nucleus), then emits a neutron and transforms into zirconium-97.

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I’ve highlighted the mention of nanomaterials in the March 18, 2025 University of Surrey press release (also on EurekAlert), which originated the news item,

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Dr Matthew Williams, lead author of the study from the University of Surrey, said: 

“The weak r-process plays a crucial role in the formation of heavy elements, which astronomers have observed in ancient stars – celestial fossils that carry the chemical fingerprints of perhaps only one prior cataclysmic event, like a supernovae or neutron star merger. Until now, our understanding of how these elements form has relied on theoretical predictions, but this experiment provides the first real-world data to test those models that involve radioactive nuclei.” 

The experiment was enabled by the use of novel helium targets. Since helium is a noble gas, meaning it is neither reactive nor solid, researchers at the University of Seville developed an innovative nano-material target, embedding helium inside ultra-thin silicon films to form billions of microscopic helium bubbles, each only a few 10s of nanometres across. 

Using TRIUMF’s advanced radioactive ion beam technology, the team accelerated short-lived strontium-94 isotopes into these targets, allowing them to measure the nuclear reaction under conditions similar to those found in extreme cosmic environments.  

Dr Williams said: 

“This is a major achievement for astrophysics and nuclear physics, and the first-time nanomaterials have been used in this way, opening exciting new possibilities for nuclear research.  

“Beyond astrophysics, understanding how radioactive nuclei behave is crucial for improving nuclear reactor design. These types of nuclei are constantly produced in nuclear reactors, but until recently, studying their reactions has been extremely difficult. Reactor physics depends on this kind of data to predict how often components need replacing, how long they’ll last and how to design more efficient, modern systems.” 

The next phase of research will apply the findings to astrophysical models, helping scientists to better understand the origins of the heaviest known elements. As researchers continue to explore these processes, their work could deepen our understanding of both the extreme physics of neutron star collisions and practical applications in nuclear technology. 

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

First Measurement of a Weak 𝑟-Process Reaction on a Radioactive Nucleus by M. Williams, C. Angus, A. M. Laird, B. Davids, C. Aa. Diget, A. Fernandez, E. J. Williams, A. N. Andreye, H. Asch, A. A. Avaa, G. Bartram, S. Chakraborty, I. Dillmann, K. Directo, D. T. Doherty, E. Geerlof, C. J. Griffin, A. Grimes, G. Hackman, J. Henderson, K. Hudson, D. Hufschmidt, J. Jeong, M. C. Jiménez de Haro, V. Karayonchev,, A. Katrusiak, A. Lennarz, G. Lotay, B. Marlow, M. S. Martin, S. Molló, F. Montes, J. R. Murias, J. O’Neill, K. Pak6, C. Paxman, L. Pedro-Botet, A. Psaltis, E. Raleigh-Smith, D. Rhodes, J. S. Rojo, M. Satrazani, T. Sauvage, C. Shenton, C. E. Svensson, D. Tam, L. Wagner, and D. Yates. Phys. Rev. Lett. 134, 112701– Published 17 March, 2025 Vol. 134, Iss. 11 — 21 March 2025. DOI: https://doi.org/10.1103/PhysRevLett.134.112701

This paper is behind a paywall.

New magnetic state, ‘Vortion,’ able to mimic neuronal synapses

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A March 3, 2025 news item on phys.org announces a new magnetic state,

Researchers from the Department of Physics [at the Autonomous University of Barcelona] have managed to experimentally develop a new magnetic state: a magneto-ionic vortex or “vortion.” The research, published in Nature Communications, allows for an unprecedented level of control of magnetic properties at the nanoscale and at room temperature, and opens new horizons for the development of advanced magnetic devices.

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A March 3, 2025 Universitat Autonoma de Barcelona [Autonomous University of Barcelona] press release on EurekAlert, which originated the news item, describes the impetus for this research,

The use of Big Data has multiplied the energy demand in information technologies. Generally, to store information, systems utilize electric currents to write data, which dissipates power by heating the devices. Controlling magnetic memories with voltage, instead of electric currents, can minimise this energy expenditure. One way to achieve this is by using magneto-ionic materials, which allow for the manipulation of their magnetic properties by adding or removing ions through changes in the polarity of the applied voltage. So far, most studies in this area have focused on continuous films, rather than on controlling properties at the nanometric scale in discrete “bits”, essential for high-density data storage. Moreover, it is known that new magnetic phenomena can emerge at the sub-micrometre scale, that do not exist at the macroscopic level, such as magnetic vortices – small swirl-like magnetic structures. These vortices have applications in the way magnetic data are currently recorded and read, as well as in biomedicine. Nevertheless, changing the vortex state in already prepared materials is often impossible or requires large amounts of energy.

Researchers from the UAB Department of Physics, in collaboration with scientists from the ICMAB-CSIC, the ALBA Synchrotron and research institutions in Italy and the United States, propose a new solution that combines magneto-ionics and magnetic vortices. Researchers experimentally developed a new magnetic state that they have named magneto-ionic vortex, or “vortion”. This new object allows “on-demand” control of the magnetic properties of a nanodot (a dot of nanometric dimensions) with high precision. This is achieved by extracting nitrogen ions through the application of voltage, thus allowing for efficient control with very low energy consumption.

“This is a so far unexplored object at the nanoscale,” explains ICREA [Catalan Institution for Research and Advanced Studies] researcher in the UAB Department of Physics Jordi Sort, director of the research. “There is a great demand for controlling magnetic states at the nanoscale but, surprisingly, most of the research in magneto-ionics has so far focused on the study of films of continuous materials. If we look at the effects of ion displacement in discrete structures of nanometre dimensions, the ‘nanodots’ we have analysed, we see that very interesting dynamically evolving spin configurations appear, which are unique to these types of structures”. These spin configurations and the magnetic properties of the vortices vary as a function of the duration of the applied voltage. Thus, different magnetic states (e.g., vortices with different properties or states with uniform magnetic orientation) can be generated from nanodots of an initially non-magnetic material by the gradual extraction of ions through the application of voltage.

“With the ‘vortions’ we developed, we can have unprecedented control of magnetic properties such as magnetisation, coercivity, remanence, anisotropy or the critical fields at which vortions are formed or annihilated. These are fundamental properties for storing information in magnetic memories, which we are now able to control and tune in an analogue and reversible manner by a voltage-activated process with very low energy consumption,” explains Irena Spasojević, postdoctoral researcher in the UAB Department of Physics and first author of the paper. “The voltage actuation procedure, instead of using electric current, prevents heating in devices such as laptops, servers and data centres, and it drastically reduces energy loss.”

Researchers have shown that by precisely controlling the thickness of the voltage-generated magnetic layer, the magnetic state of the material can be varied at will, in a controlled and reversible manner, between a non-magnetic state, a state with a uniform magnetic orientation (such as that found in a magnet), and the new magneto-ionic vortex state.

Ability to mimic the behaviour of neuronal synapses

This unprecedented level of control of magnetic properties at the nanoscale and at room temperature opens new horizons for the development of advanced magnetic devices with functionalities that can be tailored once the material has been synthesised. This provides greater flexibility which is needed to meet specific technological demands. “We envision, for example, the integration of reconfigurable magneto-ionic vortices in neural networks as dynamic synapses, capable of mimicking the behaviour of biological synapses”, says Jordi Sort. In the brain, the connections between neurons, the synapses, have different weights (intensities) that adapt dynamically according to the activity and learning process. Similarly, “vortions” could provide tuneable neuronal synaptic weights, reflected in reconfigurable magnetisation or anisotropy values, for neuromorphic (brain-inspired) spintronic devices. In fact, “the activity of biological neurons and synapses is also controlled by electrical signals and ion migration, analogous to our magneto-ionic units,” comments Irena Spasojević.

Researchers believe that, besides their impact in brain-inspired devices, analogue computing or multi-state data storage systems, vortions may have other potential applications, including medical therapy techniques such as theragnostics, data security, magnetic spin computing devices (spin logics), and the generation of spin waves (magnonics).

The research, led by ICREA professor of the UAB Department of Physics Jordi Sort, and postdoctoral researcher of the UAB Department of Physics Irena Spasojević as the first author of the publication, also included Zheng Ma, from the same department, Aleix Barrera and Anna Palau, from the Institute of Materials Science of Barcelona (ICMAB-CSIC), and researchers from the ALBA Synchrotron, the Istituto Nazionale di Ricerca Metrologica (INRiM) of Turin, Italy, and Colorado State University, USA. The study was published in the latest issue of the journal Nature Communications. This study was financed by the REMINDS project from the European Research Council.

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

Magneto-ionic vortices: voltage-reconfigurable swirling-spin analog-memory nanomagnets by Irena Spasojevic, Zheng Ma, Aleix Barrera, Federica Celegato, Alessandro Magni, Sandra Ruiz-Gómez, Michael Foerster, Anna Palau, Paola Tiberto, Kristen S. Buchanan & Jordi Sort. Nature Communications volume 16, Article number: 1990 (2025) DOI: https://doi.org/10.1038/s41467-025-57321-8 Published: 26 February 2025

This paper is open access.

Memristor-based brain-computer interfaces (BCIs)

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Brief digression: For anyone unfamiliar with memristors, they are, for want of better terms, devices or elements that have memory in addition to their resistive properties. (For more see: R Jagan Mohan Rao’s undated article ‘What is a Memristor? Principle, Advantages, Applications” on InsstrumentalTools.com)

A March 27,2025 news item on ScienceDaily announces a memristor-enhanced brain-computer interface (BCI),

Summary: Researchers have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). This research presents an innovative approach for implementing energy-efficient adaptive neuromorphic decoders in BCIs that can effectively co-evolve [emphasis mine] with changing brain signals.

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So, the decoder in the BCI will ‘co-evolve’ with your brain? hmmm Also, where is this ‘memristor chip’? The video demo (https://assets-eu.researchsquare.com/files/rs-3966063/v1/7a84dc7037b11bad96ae0378.mp4) shows a volunteer wearing cap attached by cable to an intermediary device (an enlarged chip with a brain on it?) which is in turn attached to a screen. I believe some artistic licence has been taken with regard to the brain on the chip..

Caption: Researchers propose an adaptive neuromorphic decoder supporting brain-machine co-evolution. Credit: The University of Hong Kong

A March 25, 2025 University of Hong Kong (HKU) press release (also on EurekAlert but published on March 26, 2025), which originated the news item, explains more about memristors, BCIs, and co-evolution,

Professor Ngai Wong and Dr Zhengwu Liu from the Department of Electrical and Electronic Engineering at the Faculty of Engineering at the University of Hong Kong (HKU), in collaboration with research teams at Tsinghua University and Tianjin University, have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). Published in Nature Electronics, this research presents an innovative approach for implementing energy-efficient adaptive neuromorphic decoders in BCIs that can effectively co-evolve with changing brain signals.

A brain-computer interface (BCI) is a computer-based system that creates a direct communication pathway between the brain and external devices, such as computers, allowing individuals to control these devices or applications purely through brain activity, bypassing the need for traditional muscle movements or the nervous system. This technology holds immense potential across a wide range of fields, from assistive technologies to neurological rehabilitation. However, traditional BCIs still face challenges.

“The brain is a complex dynamic system with signals that constantly evolve and fluctuate. This poses significant challenges for BCIs to maintain stable performance over time,” said Professor Wong and Dr Liu. “Additionally, as brain-machine links grow in complexity, traditional computing architectures struggle with real-time processing demands.”

The collaborative research addressed these challenges by developing a 128K-cell memristor chip that serves as an adaptive brain signal decoder. The team introduced a hardware-efficient one-step memristor decoding strategy that significantly reduces computational complexity while maintaining high accuracy. Dr Liu, a Research Assistant Professor in the Department of Electrical and Electronic Engineering at HKU, contributed as a co-first author to this groundbreaking work.

In real-world testing, the system demonstrated impressive capabilities in a four-degree-of-freedom drone flight control task, achieving 85.17% decoding accuracy—equivalent to software-based methods—while consuming 1,643 times less energy and offering 216 times higher normalised speed than conventional CPU-based systems.

Most significantly, the researchers developed an interactive update framework that enables the memristor decoder and brain signals to adapt to each other naturally. This co-evolution, demonstrated in experiments involving ten participants over six-hour sessions, resulted in approximately 20% higher accuracy compared to systems without co-evolution capability.

“Our work on optimising the computational models and error mitigation techniques was crucial to ensure that the theoretical advantages of memristor technology could be realised in practical BCI applications,” explained Dr Liu. “The one-step decoding approach we developed together significantly reduces both computational complexity and hardware costs, making the technology more accessible for a wide range of practical scenarios.”

Professor Wong further emphasised, “More importantly, our interactive updating framework enables co-evolution between the memristor decoder and brain signals, addressing the long-term stability issues faced by traditional BCIs. This co-evolution mechanism allows the system to adapt to natural changes in brain signals over time, greatly enhancing decoding stability and accuracy during prolonged use.”

Building on the success of this research, the team is now expanding their work through a new collaboration with HKU Li Ka Shing Faculty of Medicine and Queen Mary Hospital to develop a multimodal large language model for epilepsy data analysis.

“This new collaboration aims to extend our work on brain signal processing to the critical area of epilepsy diagnosis and treatment,” said Professor Wong and Dr Liu. “By combining our expertise in advanced algorithms and neuromorphic computing with clinical data and expertise, we hope to develop more accurate and efficient models to assist epilepsy patients.”

The research represents a significant step forward in human-centred hybrid intelligence, which combines biological brains with neuromorphic computing systems, opening new possibilities for medical applications, rehabilitation technologies, and human-machine interaction.

The project received support from the RGC Theme-based Research Scheme (TRS) project T45-701/22-R, the STI 2030-Major Projects, the National Natural Science Foundation of China, and the XPLORER Prize.

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

A memristor-based adaptive neuromorphic decoder for brain–computer interfaces by Zhengwu Liu, Jie Mei, Jianshi Tang, Minpeng Xu, Bin Gao, Kun Wang, Sanchuang Ding, Qi Liu, Qi Qin, Weize Chen, Yue Xi, Yijun Li, Peng Yao, Han Zhao, Ngai Wong, He Qian, Bo Hong, Tzyy-Ping Jung, Dong Ming & Huaqiang Wu. Nature Electronics volume 8, pages 362–372 (2025) DOI: https://doi.org/10.1038/s41928-025-01340-2 Published online: 17 February 2025 Issue Date: April 2025

This paper is behind a paywall.

Words from the press release like “… human-centred hybrid intelligence, which combines biological brains with neuromorphic computing systems …” put me in mind of cyborgs.

Citizen science app (iNaturalist) may play a role in Australian mushroom murder trial

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Caption: Death cap mushrooms (Amanita phalloides) Credit: Jolanda Aalbers/Shutterstock [downloaded from https://theconversation.com/what-is-inaturalist-the-citizen-science-app-playing-an-unlikely-role-in-erin-pattersons-mushroom-murder-trial-255714]

The woman’s trial is still ongoing and my interest is in the citizen science aspect of it all. Here’s a precis of the murder trial and a discussion of iNaturalist from a May 2, 2025 essay by Caitlyn Forster, associate lecturer, University of Sydney, and Melissa Humphries, senior lecturer, University of Adelaide, for The Conversation, Note: Links have been removed,

The world has been gripped by the case of Australian woman Erin Patterson, who was charged with the murder of three people after allegedly serving them a lunch of beef wellington containing poisonous death cap mushrooms (Amanita phalloides).

A new element of the sensational story emerged in court this week, when prosecutors reportedly alleged Patterson used iNaturalist to locate and visit places where death cap mushrooms were known to grow.

So what exactly is iNaturalist? And how is this 17-year-old citizen science project being used to better understand our world?

More than 240 million observations worldwide

iNaturalist is an app that allows users to take photos of plants, fungi, animals and any piece of nature. The photos are uploaded, and identified using a combination of crowd-sourcing and artificial intelligence.

When a user uploads an image, they can also choose to make the location public, so others can see where it was found. iNaturalist’s database holds more than 240 million observations wordlwide. More than 10.6 million of these are in Australia.

All of this data is extremely important for scientists to understand the ecology of different species. iNaturalist has played a key role in the discovery of new species as well as sightings of species that have previously not been seen for decades.

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Finding the unusual

Real people usually collect images for iNaturalist as part of their everyday life, rather than systematically as part of their job. That means there are patterns to the data that is collected.

Observations tend to be recorded on weekends and in good weather, and to involve life forms people find strange, unusual or interesting.

For example, at the time of writing, iNaturalist had recorded 1,382 sightings of domestic cats in Australia, compared with 29,660 koalas. But cataloguing the rare and wonderful can be useful.

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In 2011, iNaturalist added more features to protect geoprivacy – which allows locations of observations to be obscured. Rare and exciting pets, and collectable insects could be found by looking at location data on iNaturalist.

There is previous evidence this has occurred. Nowadays, species of concern for poaching automatically have their locations obscured, preventing them from being illegally poached or collected. This can also be helpful to prevent people crowding popular endangered animals when they have been sighted.

Typically, anything listed as endangered will automatically have an obscured location on iNaturalist.

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Observing nature has huge benefits to understanding our natural world. But these observations do collect a lot of personal data in terms of where and when the observation occurred.

Although iNaturalist doesn’t sell users’ information, and users can obscure their precise location, the pictures a person shares can still contain enough information to figure out where they are.

This could be used for forensic intelligence to locate plants and animals of interest, and to place people with them at the time the photo was taken.

If you’re lucky enough to see a rare or threatened species, consider taking a photo that has little background information that can give away the precise details of the locations, particularly when observing immobile organisms like such as plants and fungi.

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iNaturalist is a fantastic resource for observing nature. More data points to understand where plants, animals, and mushrooms can be found is vital for understanding their ecology, and potentially conserving species.

It also has huge ramifications for biosecurity, forensics, and even understanding movements that may have occurred during an alleged crime. So it’s really worth getting out in nature and taking photos of interesting things you see!

For anyone curious about the trial, Ms. Patterson is currently testifying on her own behalf, there’s the Australian Broadcasting Corporation’s (ABC) “Erin Patterson Mushroom Murder Trial” blog with live updates or the British Broadcasting Corporation’s (BBC) “Deadly mushroom cook calculated fatal dose on kitchen scales, prosecution alleges” live blog.

I have few comments, it’s well known that some varieties of mushrooms can be fatal and they have been inadvertently or purposefully implicated in more than one death. It’s up to a jury to decide Ms. Patterson’s guilt or innocence and I imagine the folks at iNaturalist are making some adjustments to what geolocation information is being shared on their site.

Getting back to citizen science and iNaturalist, there’s this from their homepage, Note: A link has been removed,

Contribute to Science

Every observation can contribute to biodiversity science, from the rarest butterfly to the most common backyard weed. We share your findings with scientific data repositories like the Global Biodiversity Information Facility to help scientists find and use your data. All you have to do is observe.

On that note, let’s contribute to science.

With a wave of your finger you can control your electronic fabric

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A March 6, 2025 news item on ScienceDaily announces a durable electronic textile that can be washed,

A team of researchers from Nottingham Trent University (UK), Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and Free University of Bozen-Bolzano (Italy) has created washable and durable magnetic field sensing electronic textiles — thought to be the first of their kind — which they say paves the way to transform use in clothing, as they report in the journal Communications Engineering. This technology will allow users to interact with everyday textiles or specialized clothing by simply pointing their finger above a sensor.

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A March 5, 2025 Helmholtz-Zentrum Dresden-Rossendorf press release (also on EurekAlert but published March 6, 2025), which originated the news item, describes some possibilities that, until now, have been the province of science fiction,

The researchers show how they placed tiny flexible and highly responsive magnetoresistive sensors within braided textile yarns compatible with conventional textile manufacturing. The garment can be operated by the user across a variety of functions through the use of a ring or glove which would require a miniature magnet. The sensors are seamlessly integrated within the textile, allowing the position of the sensors to be indicated using dyeing or embroidering, acting as touchless controls or ‘buttons’.

The technology, which could even be in the form of a textile-based keyboard, can be integrated into clothing and other textiles and can work underwater and across different weather conditions. Importantly, the researchers argue, it is not prone to accidental activation unlike some capacitive sensors in textiles and textile-based switches. “By integrating the technology into everyday clothing people would be able to interact with computers, smart phones, watches and other smart devices, transforming their clothes into a wearable human-computer interface”, summarizes Dr. Denys Makarov from the Institute of Ion Beam Physics and Materials Research at HZDR.

Washable fashion for human-computer interaction

The technology could be applied to areas such as temperature or safety controls for specialized clothing, gaming, or interactive fashion – such as allowing its users to employ simple gestures to control LEDs or other illuminating devices embedded in the textiles. Furthermore, the research team demonstrates the technology on a variety of uses, including a functional armband allowing navigational control in a virtual reality environment, and a self-monitoring safety strap for a motorcycle helmet. “It is the first time that washable magnetic sensors have been unobtrusively integrated within textiles to be used for human-computer interactions”, emphasizes Prof. Niko Münzenrieder from Free University of Bozen-Bolzano.

“Our design could revolutionize electronic textiles for both specialized and everyday clothing,” said lead researcher Dr. Pasindu Lugoda, who is based in Nottingham Trent University’s Department of Engineering. He further remarks: “Tactile sensors on textiles vary in usefulness as accidental activation occurs when they rub or brush against surfaces. Touchless interaction reduces wear and tear. Importantly, our technology is designed for everyday use. It is machine washable and durable and does not impact the drape, or overall aesthetic appeal of the textile.”

Electronic textiles are becoming increasingly popular with wide-ranging uses, but the fusion of electronic functionality and textile fabrics can be very challenging. Such textiles have evolved and now rely on soft and flexible materials which are robust enough to endure washing and bending, but which are intuitive and reliable.

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

Submersible touchless interactivity in conformable textiles enabled by highly selective overbraided magnetoresistive sensors by Pasindu Lugoda, Eduardo Sergio Oliveros-Mata, Kalana Marasinghe, Rahul Bhaumik, Niccolò Pretto, Carlos Oliveira, Tilak Dias, Theodore Hughes-Riley, Michael Haller, Niko Münzenrieder & Denys Makarov. Communications Engineering volume 4, Article number: 33 (2025) DOI: https://doi.org/10.1038/s44172-025-00373-x Published: 25 February 2025

This paper is open access.