Category Archives: electronics

Everlasting dirt-powered sensors for agriculture?

Caption: The fuel cell’s 3D printed cap peeks above the ground. The cap keeps debris out of the device while enabling air flow. Credit: Bill Yen/Northwestern University

A January 12, 2024 Northwestern University news release (also received via email and also on EurekAlert both published January 15, 2024) describes this dirt-powered research from the US, Note: Links have been removed,

*New fuel cell harnesses naturally occurring microbes to generate electricity

*Soil-powered sensors to successfully monitor soil moisture and detect touch

*New tech was robust enough to withstand drier soil conditions and flooding

*Fuel cell could replace batteries in sensors used for precision agriculture

EVANSTON, Ill. — A Northwestern University-led team of researchers has developed a new fuel cell that harvests energy from microbes living in dirt. 

About the size of a standard paperback book, the completely soil-powered technology could fuel underground sensors used in precision agriculture and green infrastructure. This potentially could offer a sustainable, renewable alternative to batteries, which hold toxic, flammable chemicals that leach into the ground, are fraught with conflict-filled supply chains and contribute to the ever-growing problem of electronic waste.

To test the new fuel cell, the researchers used it to power sensors measuring soil moisture and detecting touch, a capability that could be valuable for tracking passing animals. To enable wireless communications, the researchers also equipped the soil-powered sensor with a tiny antenna to transmit data to a neighboring base station by reflecting existing radio frequency signals.

Not only did the fuel cell work in both wet and dry conditions, but its power also outlasted similar technologies by 120%.

The research will be published today (Jan. 12 [2024]) in the Proceedings of the Association for Computing Machinery on Interactive, Mobile, Wearable and Ubiquitous Technologies. The study authors also are releasing all designs, tutorials and simulation tools to the public, so others may use and build upon the research.

“The number of devices in the Internet of Things (IoT) is constantly growing,” said Northwestern alumnus Bill Yen, who led the work. “If we imagine a future with trillions of these devices, we cannot build every one of them out of lithium, heavy metals and toxins that are dangerous to the environment. We need to find alternatives that can provide low amounts of energy to power a decentralized network of devices. In a search for solutions, we looked to soil microbial fuel cells, which use special microbes to break down soil and use that low amount of energy to power sensors. As long as there is organic carbon in the soil for the microbes to break down, the fuel cell can potentially last forever.”

“These microbes are ubiquitous; they already live in soil everywhere,” said Northwestern’s George Wells, a senior author on the study. “We can use very simple engineered systems to capture their electricity. We’re not going to power entire cities with this energy. But we can capture minute amounts of energy to fuel practical, low-power applications.”

Wells is an associate professor of civil and environmental engineering at Northwestern’s McCormick School of Engineering. Now a Ph.D. student at Stanford University, Yen started this project when he was an undergraduate researcher in Wells’ laboratory.

Solutions for a dirty job

In recent years, farmers worldwide increasingly have adopted precision agriculture as a strategy to improve crop yields. The tech-driven approach relies on measuring precise levels of moisture, nutrients and contaminants in soil to make decisions that enhance crop health. This requires a widespread, dispersed network of electronic devices to continuously collect environmental data.

“If you want to put a sensor out in the wild, in a farm or in a wetland, you are constrained to putting a battery in it or harvesting solar energy,” Yen said. “Solar panels don’t work well in dirty environments because they get covered with dirt, do not work when the sun isn’t out and take up a lot of space. Batteries also are challenging because they run out of power. Farmers are not going to go around a 100-acre farm to regularly swap out batteries or dust off solar panels.”

To overcome these challenges, Wells, Yen and their collaborators wondered if they could instead harvest energy from the existing environment. “We could harvest energy from the soil that farmers are monitoring anyway,” Yen said.

‘Stymied efforts’

Making their first appearance in 1911, soil-based microbial fuel cells (MFCs) operate like a battery — with an anode, cathode and electrolyte. But instead of using chemicals to generate electricity, MFCs harvest electricity from bacteria that naturally donate electrons to nearby conductors. When these electrons flow from the anode to the cathode, it creates an electric circuit.

But in order for microbial fuel cells to operate without disruption, they need to stay hydrated and oxygenated — which is tricky when buried underground within dry dirt.

“Although MFCs have existed as a concept for more than a century, their unreliable performance and low output power have stymied efforts to make practical use of them, especially in low-moisture conditions,” Yen said.

Winning geometry

With these challenges in mind, Yen and his team embarked on a two-year journey to develop a practical, reliable soil-based MFC. His expedition included creating — and comparing — four different versions. First, the researchers collected a combined nine months of data on the performance of each design. Then, they tested their final version in an outdoor garden.

The best-performing prototype worked well in dry conditions as well as within a water-logged environment. The secret behind its success: Its geometry. Instead of using a traditional design, in which the anode and cathode are parallel to one another, the winning fuel cell leveraged a perpendicular design.

Made of carbon felt (an inexpensive, abundant conductor to capture the microbes’ electrons), the anode is horizontal to the ground’s surface. Made of an inert, conductive metal, the cathode sits vertically atop the anode. 

Although the entire device is buried, the vertical design ensures that the top end is flush with the ground’s surface. A 3D-printed cap rests on top of the device to prevent debris from falling inside. And a hole on top and an empty air chamber running alongside the cathode enable consistent airflow.  

The lower end of the cathode remains nestled deep beneath the surface, ensuring that it stays hydrated from the moist, surrounding soil — even when the surface soil dries out in the sunlight. The researchers also coated part of the cathode with waterproofing material to allow it to breathe during a flood. And, after a potential flood, the vertical design enables the cathode to dry out gradually rather than all at once.

On average, the resulting fuel cell generated 68 times more power than needed to operate its sensors. It also was robust enough to withstand large changes in soil moisture — from somewhat dry (41% water by volume) to completely underwater.

Making computing accessible

The researchers say all components for their soil-based MFC can be purchased at a local hardware store. Next, they plan to develop a soil-based MFC made from fully biodegradable materials. Both designs bypass complicated supply chains and avoid using conflict minerals.

“With the COVID-19 pandemic, we all became familiar with how a crisis can disrupt the global supply chain for electronics,” said study co-author Josiah Hester, a former Northwestern faculty member who is now at the Georgia Institute of Technology. “We want to build devices that use local supply chains and low-cost materials so that computing is accessible for all communities.”

The study, “Soil-powered computing: The engineer’s guide to practical soil microbial fuel cell design,” was supported by the National Science Foundation (award number CNS-2038853), the Agricultural and Food Research Initiative (award number 2023-67021-40628) from the USDA National Institute of Food and Agriculture, the Alfred P. Sloan Foundation, VMware Research and 3M.

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

Soil-Powered Computing: The Engineer’s Guide to Practical Soil Microbial Fuel Cell Design by Bill Yen, Laura Jaliff, Louis Gutierrez, Philothei Sahinidis, Sadie Bernstein, John Madden, Stephen Taylor, Colleen Josephson, Pat Pannuto, Weitao Shuai, George Wells, Nivedita Arora, Josiah Hester. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 7 Issue 4 Article No.: 196 pp 1–40 DOI: https://doi.org/10.1145/3631410 Published: 12 January 2024

This paper is open access.

Physical neural network based on nanowires can learn and remember ‘on the fly’

A November 1, 2023 news item on Nanowerk announced new work on neuromorphic engineering from Australia,

For the first time, a physical neural network has successfully been shown to learn and remember ‘on the fly’, in a way inspired by and similar to how the brain’s neurons work.

The result opens a pathway for developing efficient and low-energy machine intelligence for more complex, real-world learning and memory tasks.

Key Takeaways
*The nanowire-based system can learn and remember ‘on the fly,’ processing dynamic, streaming data for complex learning and memory tasks.

*This advancement overcomes the challenge of heavy memory and energy usage commonly associated with conventional machine learning models.

*The technology achieved a 93.4% accuracy rate in image recognition tasks, using real-time data from the MNIST database of handwritten digits.

*The findings promise a new direction for creating efficient, low-energy machine intelligence applications, such as real-time sensor data processing.

Nanowire neural network
Caption: Electron microscope image of the nanowire neural network that arranges itself like ‘Pick Up Sticks’. The junctions where the nanowires overlap act in a way similar to how our brain’s synapses operate, responding to electric current. Credit: The University of Sydney

A November 1, 2023 University of Sydney news release (also on EurekAlert), which originated the news item, elaborates on the research,

Published today [November 1, 2023] in Nature Communications, the research is a collaboration between scientists at the University of Sydney and University of California at Los Angeles.

Lead author Ruomin Zhu, a PhD student from the University of Sydney Nano Institute and School of Physics, said: “The findings demonstrate how brain-inspired learning and memory functions using nanowire networks can be harnessed to process dynamic, streaming data.”

Nanowire networks are made up of tiny wires that are just billionths of a metre in diameter. The wires arrange themselves into patterns reminiscent of the children’s game ‘Pick Up Sticks’, mimicking neural networks, like those in our brains. These networks can be used to perform specific information processing tasks.

Memory and learning tasks are achieved using simple algorithms that respond to changes in electronic resistance at junctions where the nanowires overlap. Known as ‘resistive memory switching’, this function is created when electrical inputs encounter changes in conductivity, similar to what happens with synapses in our brain.

In this study, researchers used the network to recognise and remember sequences of electrical pulses corresponding to images, inspired by the way the human brain processes information.

Supervising researcher Professor Zdenka Kuncic said the memory task was similar to remembering a phone number. The network was also used to perform a benchmark image recognition task, accessing images in the MNIST database of handwritten digits, a collection of 70,000 small greyscale images used in machine learning.

“Our previous research established the ability of nanowire networks to remember simple tasks. This work has extended these findings by showing tasks can be performed using dynamic data accessed online,” she said.

“This is a significant step forward as achieving an online learning capability is challenging when dealing with large amounts of data that can be continuously changing. A standard approach would be to store data in memory and then train a machine learning model using that stored information. But this would chew up too much energy for widespread application.

“Our novel approach allows the nanowire neural network to learn and remember ‘on the fly’, sample by sample, extracting data online, thus avoiding heavy memory and energy usage.”

Mr Zhu said there were other advantages when processing information online.

“If the data is being streamed continuously, such as it would be from a sensor for instance, machine learning that relied on artificial neural networks would need to have the ability to adapt in real-time, which they are currently not optimised for,” he said.

In this study, the nanowire neural network displayed a benchmark machine learning capability, scoring 93.4 percent in correctly identifying test images. The memory task involved recalling sequences of up to eight digits. For both tasks, data was streamed into the network to demonstrate its capacity for online learning and to show how memory enhances that learning.

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

Online dynamical learning and sequence memory with neuromorphic nanowire networks by Ruomin Zhu, Sam Lilak, Alon Loeffler, Joseph Lizier, Adam Stieg, James Gimzewski & Zdenka Kuncic. Nature Communications volume 14, Article number: 6697 (2023) DOI: https://doi.org/10.1038/s41467-023-42470-5 Published: 01 November 2023

This paper is open access.

You’ll notice a number of this team’s members are also listed in the citation in my June 21, 2023 posting “Learning and remembering like a human brain: nanowire networks” and you’ll see some familiar names in the citation in my June 17, 2020 posting “A tangle of silver nanowires for brain-like action.”

“Injectable tissue prosthesis coupled with closed-loop bioelectronic system” for damaged muscle/nerve regeneration and robot-assisted rehabilitation

A fascinating new use for hyaluronic acid (usually discussed in relation to cosmetic wrinkle-reduction) has been found according to a November 1, 2023 news item on ScienceDaily.

In a recent publication in the journal Nature, researchers from the Institute of Basic Science (IBS) in South Korea have made significant strides in biomaterial technology and rehabilitation medicine. They’ve developed a novel approach to healing muscle injury by employing “injectable tissue prosthesis” in the form of conductive hydrogels and combining it with a robot-assisted rehabilitation system.

Let’s imagine you are swimming in the ocean. A giant shark approaches and bites a huge chunk of meat out of your thigh, resulting in a complete loss of motor/sensor function in your leg.

If left untreated, such severe muscle damage would result in permanent loss of function and disability.

How on Earth will you be able to recover from this kind of injury?

Traditional rehabilitation methods for these kinds of muscle injuries have long sought an efficient closed-loop gait rehabilitation system that merges lightweight exoskeletons and wearable/implantable devices.

Such assistive prosthetic system is required to aid the patients through the process of recovering sensory and motor functions linked to nerve and muscle damage.

Unfortunately, the mechanical properties and rigid nature of existing electronic materials render them incompatible with soft tissues.

This leads to friction and potential inflammation, stalling patient rehabilitation.

To overcome these limitations, the IBS researchers turned to a material commonly used as a wrinkle-smoothing filler, called hyaluronic acid.

A November 2, 2023 Institute of Basic Science (IBS) press release (also on EurekAlert but published November 1, 2023), which originated the news item, explains how hyaluronic acid helps in tissue rehabilitation and regeneration,

Using this substance [hyaluronic acid], an injectable hydrogel was developed for “tissue prostheses”, which can temporarily fill the gap of the missing muscle/nerve tissues while it regenerates. The injectable nature of this material gives it a significant advantage over traditional bioelectronic devices, which are unsuitable for narrow, deep, or small areas, and necessitate invasive surgeries.

Thanks to its highly “tissue-like” properties, this hydrogel seamlessly interfaces with biological tissues and can be easily administered to hard-to-reach body areas without surgery. The reversible and irreversible crosslinks within the hydrogel adapt to high shear stress during injection, ensuring excellent mechanical stability. This hydrogel also incorporates gold nanoparticles, which gives it decent electrical properties. Its conductive nature allows for the effective transmission of electrophysiological signals between the two ends of injured tissues. In addition, the hydrogel is biodegrdable, meaning that the patients do not need to get surgery again.

With mechanical properties akin to natural tissues, exceptional tissue adhesion, and injectable characteristics, researchers believe this material offers a novel approach to rehabilitation.

Next, the researchers put this novel idea to the test in rodent models. To simulate volumetric muscle loss injury, a large chunk of muscle has been removed from the hind legs of these animals. By injecting the hydrogel and implanting the two kinds of stretchable tissue-interfacing devices for electrical sensing and stimulation, the researchers were able to improve the gait in the “injured” rodents. The hydrogel prosthetics were combined with robot assistance, guided by muscle electromyography signals. Together, the two helped enhance the animal’s gait without nerve stimulation. Furthermore, muscle tissue regeneration was effectively improved over the long term after the conductive hydrogel was used to fill muscle damage.

The injectable conductive hydrogel developed in this study excels in electrophysiological signal recording and stimulation performance, offering the potential to expand its applications. It presents a fresh approach to the field of bioelectronic devices and holds promise as a soft tissue prosthesis for rehabilitation support.

Emphasizing the significance of the research, Professor SHIN Mikyung notes, “We’ve created an injectable, mechanically tough, and electrically conductive soft tissue prosthesis ideal for addressing severe muscle damage requiring neuromusculoskeletal rehabilitation. The development of this injectable hydrogel, utilizing a novel cross-linking method, is a notable achievement. We believe it will be applicable not only in muscles and peripheral nerves but also in various organs like the brain and heart.”

Professor SON Donghee added, “In this study, the closed-loop gait rehabilitation system entailing tough injectable hydrogel and stretchable and self-healing sensors could significantly enhance the rehabilitation prospects for patients with neurological and musculoskeletal challenges. It could also play a vital role in precise diagnosis and treatment across various organs in the human body.”

The research team is currently pursuing further studies to develop new materials for nerve and muscle tissue regeneration that can be implanted in a minimally invasive manner. They are also exploring the potential for recovery in various tissue damages through the injection of the conductive hydrogel, eliminating the need for open surgery.

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

Injectable tissue prosthesis for instantaneous closed-loop rehabilitation by Subin Jin, Heewon Choi, Duhwan Seong, Chang-Lim You, Jong-Sun Kang, Seunghyok Rho, Won Bo Lee, Donghee Son & Mikyung Shin. Nature volume 623, pages 58–65 (2023) DOI: https://doi.org/10.1038/s41586-023-06628-x Published: 01 November 2023 Issue Date: 02 November 2023

This paper is behind a paywall.

Pressure-cooking birch leaves to produce nanoscale carbon particles for organic semiconductors

By pressure cooking birch leaves picked on campus the scientists produced carbon particles that can be used as raw material for the production of organic semiconductors. Image: Mattias Pettersson

A November 28, 2023 news item on phys.org announces work on an organic semiconductor,

Today, petrochemical compounds and rare metals such as platinum and iridium are used to produce semiconductors for optoelectronics, such as organic LEDs for super-thin TV and mobile phone screens. Physicists at Umeå University in collaboration with researchers in Denmark and China, have discovered a more sustainable alternative. By pressure-cooking birch leaves picked on the Umeå University campus, they have produced a nanosized carbon particle with desired optical properties.

A January 28, 2023 Umeå University press release by Anna-Lena Lindskog, which originated the news item, provides more information about the research,

“The essence of our research is to harness nearby renewable resources for producing organic semiconductor materials” says Jia Wang, research fellow at the Department of Physics, Umeå University, and one of the authors of the study that has been published in the Green Chemistry.

Organic semiconductors are one of the most important functional materials in optoelectronic applications. One example is the organic light-emitting diodes, OLEDs, which enable ultra-thin and bright TV and mobile phone screens. Sharply increasing demand for this advanced technology is driving massive production of organic semiconductor materials.

Unfortunately, these semiconductors are currently produced mainly from petrochemical compounds and rare elements, obtained through environmentally harmful mining. Moreover, these materials often contain so-called ‘critical raw materials’ that are in short supply, such as Platinum, Indium and Phosphorus.

From a sustainability point of view, it would be ideal if we can use biomass from plants, animals and waste to produce organic semiconductor materials. These starting materials are renewable and abundantly available. Research fellow Jia Wang and her colleagues at the Department of Physics, together with international partners, have succeeded in producing such a bio-based semiconductor material.

Birch leaves in pressure cooker

The synthesis process is simple: they picked birch leaves on the Umeå campus and cooked them in a pressure cooker. That produced a kind of ‘carbon dots’ about two nanometers in size, which emit a narrow-band, deep red light when dissolved in ethanol. Some of the optical properties of these birch leaf carbon dots are comparable to commercial quantum dots currently used in semiconductor materials, but unlike them, they contain no heavy metals or critical raw materials.

”It is important to note that our method is not limited to birch leaves” explains Jia Wang. “We tested different plant leaves with the same pressure cooking method, and all of them produced similar red-emitting carbon dots. This versatility suggests that the transformation process can be used in different locations.”

Using the carbon dots in a light-emitting electrochemical cell device, the researchers were able to show that the brightness generated was 100 cd/m2, which is comparable to the light intensity from a computer screen.

“It is important to note that our method is not limited to birch leaves.”

”This result shows that it is possible to transition from depleting petroleum compounds to regenerating biomass as a raw material for organic semiconductors” says Jia Wang.

She emphasises the broader potential of carbon dots beyond just light-emitting devices.

“Carbon dots are promising across various applications, from bioimaging and sensing to anti-counterfeiting. We’re open to collaborations and eager to explore more exciting uses for these emissive and sustainable carbon dots” says Jia Wang.

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

Fluorescent carbon dots from birch leaves for sustainable electroluminescent devices by Shi Tang, Yongfeng Liu, Henry Opoku, Märta Gregorsson, Peijuan Zhang, Etienne Auroux, Dongfeng Dang, Anja-Verena Mudring, Thomas Wågberg, Ludvig Edman, and Jia Wang. Green Chem., 2023, 25, 9884-9895 DOI: https://doi.org/10.1039/D3GC03827K First published: 01 Nov 2023

This paper is open access.

Adaptive neural connectivity with an event-based architecture using photonic processors

On first glance it looked like a set of matches. If there were more dimension, this could also have been a set pencils but no,

Caption: The chip contains almost 8,400 functioning artificial neurons from waveguide-coupled phase-change material. The researchers trained this neural network to distinguish between German and English texts on the basis of vowel frequency. Credit: Jonas Schütte / Pernice Group Courtesy: University of Münster

An October 23, 2023 news item on Nanowerk introduces research into a new approach to optical neural networks

A team of researchers headed by physicists Prof. Wolfram Pernice and Prof. Martin Salinga and computer specialist Prof. Benjamin Risse, all from the University of Münster, has developed a so-called event-based architecture, using photonic processors. In a similar way to the brain, this makes possible the continuous adaptation of the connections within the neural network.

Key Takeaways

Researchers have created a new computing architecture that mimics biological neural networks, using photonic processors for data transportation and processing.

The new system enables continuous adaptation of connections within the neural network, crucial for learning processes. This is known as both synaptic and structural plasticity.

Unlike traditional studies, the connections or synapses in this photonic neural network are not hardware-based but are coded based on optical pulse properties, allowing for a single chip to hold several thousand neurons.

Light-based processors in this system offer a much higher bandwidth and lower energy consumption compared to traditional electronic processors.

The researchers successfully tested the system using an evolutionary algorithm to differentiate between German and English texts based on vowel count, highlighting its potential for rapid and energy-efficient AI applications.

The Research

Modern computer models – for example for complex, potent AI applications – push traditional digital computer processes to their limits.

The person who edited the original press release, which is included in the news item in the above, is not credited.

Here’s the unedited original October 23, 2023 University of Münster press release (also on EurekAlert)

Modern computer models – for example for complex, potent AI applications – push traditional digital computer processes to their limits. New types of computing architecture, which emulate the working principles of biological neural networks, hold the promise of faster, more energy-efficient data processing. A team of researchers has now developed a so-called event-based architecture, using photonic processors with which data are transported and processed by means of light. In a similar way to the brain, this makes possible the continuous adaptation of the connections within the neural network. This changeable connections are the basis for learning processes. For the purposes of the study, a team working at Collaborative Research Centre 1459 (“Intelligent Matter”) – headed by physicists Prof. Wolfram Pernice and Prof. Martin Salinga and computer specialist Prof. Benjamin Risse, all from the University of Münster – joined forces with researchers from the Universities of Exeter and Oxford in the UK. The study has been published in the journal “Science Advances”.

What is needed for a neural network in machine learning are artificial neurons which are activated by external excitatory signals, and which have connections to other neurons. The connections between these artificial neurons are called synapses – just like the biological original. For their study, the team of researchers in Münster used a network consisting of almost 8,400 optical neurons made of waveguide-coupled phase-change material, and the team showed that the connection between two each of these neurons can indeed become stronger or weaker (synaptic plasticity), and that new connections can be formed, or existing ones eliminated (structural plasticity). In contrast to other similar studies, the synapses were not hardware elements but were coded as a result of the properties of the optical pulses – in other words, as a result of the respective wavelength and of the intensity of the optical pulse. This made it possible to integrate several thousand neurons on one single chip and connect them optically.

In comparison with traditional electronic processors, light-based processors offer a significantly higher bandwidth, making it possible to carry out complex computing tasks, and with lower energy consumption. This new approach consists of basic research. “Our aim is to develop an optical computing architecture which in the long term will make it possible to compute AI applications in a rapid and energy-efficient way,” says Frank Brückerhoff-Plückelmann, one of the lead authors.

Methodology: The non-volatile phase-change material can be switched between an amorphous structure and a crystalline structure with a highly ordered atomic lattice. This feature allows permanent data storage even without an energy supply. The researchers tested the performance of the neural network by using an evolutionary algorithm to train it to distinguish between German and English texts. The recognition parameter they used was the number of vowels in the text.

The researchers received financial support from the German Research Association, the European Commission and “UK Research and Innovation”.

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

Event-driven adaptive optical neural network by Frank Brückerhoff-Plückelmann, Ivonne Bente, Marlon Becker, Niklas Vollmar, Nikolaos Farmakidis, Emma Lomonte, Francesco Lenzini, C. David Wright, Harish Bhaskaran, Martin Salinga, Benjamin Risse, and Wolfram H. P. Pernice. Science Advances 20 Oct 2023 Vol 9, Issue 42 DOI: 10.1126/sciadv.adi9127

This paper is open access.

Living technology possibilities

Before launching into the possibilities, here are two descriptions of ‘living technology’ from the European Centre for Living Technology’s (ECLT) homepage,

Goals

Promote, carry out and coordinate research activities and the diffusion of scientific results in the field of living technology. The scientific areas for living technology are the nano-bio-technologies, self-organizing and evolving information and production technologies, and adaptive complex systems.

History

Founded in 2004 the European Centre for Living Technology is an international and interdisciplinary research centre established as an inter-university consortium, currently involving 18 European and extra-European institutional affiliates.

The Centre is devoted to the study of technologies that exhibit life-like properties including self-organization, adaptability and the capacity to evolve.

Despite the reference to “nano-bio-technologies,” this October 11, 2023 news item on ScienceDaily focuses on microscale living technology,

It is noIn a recent article in the high-profile journal “Advanced Materials,” researchers in Chemnitz show just how close and necessary the transition to sustainable living technology is, based on the morphogenesis of self-assembling microelectronic modules, strengthening the recent membership of Chemnitz University of Technology with the European Centre for Living Technology (ECLT) in Venice.

An October 11, 2023 Chemnitz University of Technology (Technische Universität Chemnitz; TU Chemnitz) press release (also on EurekAlert), which originated the news item, delves further into the topic, Note: Links have been removed,

It is now apparent that the mass-produced artefacts of technology in our increasingly densely populated world – whether electronic devices, cars, batteries, phones, household appliances, or industrial robots – are increasingly at odds with the sustainable bounded ecosystems achieved by living organisms based on cells over millions of years. Cells provide organisms with soft and sustainable environmental interactions with complete recycling of material components, except in a few notable cases like the creation of oxygen in the atmosphere, and of the fossil fuel reserves of oil and coal (as a result of missing biocatalysts). However, the fantastic information content of biological cells (gigabits of information in DNA alone) and the complexities of protein biochemistry for metabolism seem to place a cellular approach well beyond the current capabilities of technology, and prevent the development of intrinsically sustainable technology.

SMARTLETs: tiny shape-changing modules that collectively self-organize to larger more complex systems

A recent perspective review published in the very high impact journal Advanced Materials this month [October 2023] by researchers at the Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN) of Chemnitz University of Technology, shows how a novel form of high-information-content Living Technology is now within reach, based on microrobotic electronic modules called SMARTLETs, which will soon be capable of self-assembling into complex artificial organisms. The research belongs to the new field of Microelectronic Morphogenesis, the creation of form under microelectronic control, and builds on work over the previous years at Chemnitz University of Technology to construct self-folding and self-locomoting thin film electronic modules, now carrying tiny silicon chiplets between the folds, for a massive increase in information processing capabilities. Sufficient information can now be stored in each module to encode not only complex functions but fabrication recipes (electronic genomes) for clean rooms to allow the modules to be copied and evolved like cells, but safely because of the gating of reproduction through human operated clean room facilities.

Electrical self-awareness during self-assembly

In addition, the chiplets can provide neuromorphic learning capabilities allowing them to improve performance during operation. A further key feature of the specific self-assembly of these modules, based on matching physical bar codes, is that electrical and fluidic connections can be achieved between modules. These can then be employed, to make the electronic chiplets on board “aware” of the state of assembly, and of potential errors, allowing them to direct repair, correct mis-assembly, induce disassembly and form collective functions spanning many modules. Such functions include extended communication (antennae), power harvesting and redistribution, remote sensing, material redistribution etc.

So why is this technology vital for sustainability?

The complete digital fab description for modules, for which actually only a limited number of types are required even for complex organisms, allows their material content, responsible originator and environmentally relevant exposure all to be read out. Prof. Dagmar Nuissl-Gesmann from the Law Department at Chemnitz University of Technology observes that “this fine-grained documentation of responsibility intrinsic down to microscopic scales will be a game changer in allowing legal assignment of environmental and social responsibility for our technical artefacts”.

Furthermore, the self-locomotion and self-assembly-disassembly capabilities allows the modules to self-sort for recycling. Modules can be regained, reused, reconfigured, and redeployed in different artificial organisms. If they are damaged, then their limited and documented types facilitate efficient custom recycling of materials with established and optimized protocols for these sorted and now identical entities. These capabilities complement the other more obvious advantages in terms of design development and reuse in this novel reconfigurable media. As Prof. Marlen Arnold, an expert in Sustainability of the Faculty of Economics and Business Administration observes, “Even at high volumes of deployment use, these properties could provide this technology with a hitherto unprecedented level of sustainability which would set the bar for future technologies to share our planet safely with us.”

Contribution to European Living Technology

This research is a first contribution of MAIN/Chemnitz University of Technology, as a new member of the European Centre for Living Technology ECLT, based in Venice,” says Prof. Oliver G. Schmidt, Scientific Director of the Research Center MAIN and adds that “It’s fantastic to see that our deep collaboration with ECLT is paying off so quickly with immediate transdisciplinary benefit for several scientific communities.” “Theoretical research at the ECLT has been urgently in need of novel technology systems able to implement the core properties of living systems.” comments Prof. John McCaskill, coauthor of the paper, and a grounding director of the ECLT in 2004.

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

Microelectronic Morphogenesis: Smart Materials with Electronics Assembling into Artificial Organisms by John S. McCaskill, Daniil Karnaushenko, Minshen Zhu, Oliver G. Schmidt. Advanced Materials DOI: https://doi.org/10.1002/adma.202306344 First published: 09 October 2023

This paper is open access.

A formal theory for neuromorphic (brainlike) computing hardware needed

This is one my older pieces as the information dates back to October 2023 but neuromorphic computing is one of my key interests and I’m particularly interested to see the upsurge in the discussion of hardware, here goes. From an October 17, 2023 news item on Nanowerk,

There is an intense, worldwide search for novel materials to build computer microchips with that are not based on classic transistors but on much more energy-saving, brain-like components. However, whereas the theoretical basis for classic transistor-based digital computers is solid, there are no real theoretical guidelines for the creation of brain-like computers.

Such a theory would be absolutely necessary to put the efforts that go into engineering new kinds of microchips on solid ground, argues Herbert Jaeger, Professor of Computing in Cognitive Materials at the University of Groningen [Netherlands].

Key Takeaways
Scientists worldwide are searching for new materials to build energy-saving, brain-like computer microchips as classic transistor miniaturization reaches its physical limit.

Theoretical guidelines for brain-like computers are lacking, making it crucial for advancements in the field.

The brain’s versatility and robustness serve as an inspiration, despite limited knowledge about its exact workings.

A recent paper suggests that a theory for non-digital computers should focus on continuous, analogue signals and consider the characteristics of new materials.

Bridging gaps between diverse scientific fields is vital for developing a foundational theory for neuromorphic computing..

An October 17, 2023 University of Groningen press release (also on EurekAlert), which originated the news item, provides more context for this proposal,

Computers have, so far, relied on stable switches that can be off or on, usually transistors. These digital computers are logical machines and their programming is also based on logical reasoning. For decades, computers have become more powerful by further miniaturization of the transistors, but this process is now approaching a physical limit. That is why scientists are working to find new materials to make more versatile switches, which could use more values than just the digitals 0 or 1.

Dangerous pitfall

Jaeger is part of the Groningen Cognitive Systems and Materials Center (CogniGron), which aims to develop neuromorphic (i.e. brain-like) computers. CogniGron is bringing together scientists who have very different approaches: experimental materials scientists and theoretical modelers from fields as diverse as mathematics, computer science, and AI. Working closely with materials scientists has given Jaeger a good idea of the challenges that they face when trying to come up with new computational materials, while it has also made him aware of a dangerous pitfall: there is no established theory for the use of non-digital physical effects in computing systems.

Our brain is not a logical system. We can reason logically, but that is only a small part of what our brain does. Most of the time, it must work out how to bring a hand to a teacup or wave to a colleague on passing them in a corridor. ‘A lot of the information-processing that our brain does is this non-logical stuff, which is continuous and dynamic. It is difficult to formalize this in a digital computer,’ explains Jaeger. Furthermore, our brains keep working despite fluctuations in blood pressure, external temperature, or hormone balance, and so on. How is it possible to create a computer that is as versatile and robust? Jaeger is optimistic: ‘The simple answer is: the brain is proof of principle that it can be done.’

Neurons

The brain is, therefore, an inspiration for materials scientists. Jaeger: ‘They might produce something that is made from a few hundred atoms and that will oscillate, or something that will show bursts of activity. And they will say: “That looks like how neurons work, so let’s build a neural network”.’ But they are missing a vital bit of knowledge here. ‘Even neuroscientists don’t know exactly how the brain works. This is where the lack of a theory for neuromorphic computers is problematic. Yet, the field doesn’t appear to see this.’

In a paper published in Nature Communications on 16 August, Jaeger and his colleagues Beatriz Noheda (scientific director of CogniGron) and Wilfred G. van der Wiel (University of Twente) present a sketch of what a theory for non-digital computers might look like. They propose that instead of stable 0/1 switches, the theory should work with continuous, analogue signals. It should also accommodate the wealth of non-standard nanoscale physical effects that the materials scientists are investigating.

Sub-theories

Something else that Jaeger has learned from listening to materials scientists is that devices from these new materials are difficult to construct. Jaeger: ‘If you make a hundred of them, they will not all be identical.’ This is actually very brain-like, as our neurons are not all exactly identical either. Another possible issue is that the devices are often brittle and temperature-sensitive, continues Jaeger. ‘Any theory for neuromorphic computing should take such characteristics into account.’

Importantly, a theory underpinning neuromorphic computing will not be a single theory but will be constructed from many sub-theories (see image below). Jaeger: ‘This is in fact how digital computer theory works as well, it is a layered system of connected sub-theories.’ Creating such a theoretical description of neuromorphic computers will require close collaboration of experimental materials scientists and formal theoretical modellers. Jaeger: ‘Computer scientists must be aware of the physics of all these new materials [emphasis mine] and materials scientists should be aware of the fundamental concepts in computing.’

Blind spots

Bridging this divide between materials science, neuroscience, computing science, and engineering is exactly why CogniGron was founded at the University of Groningen: it brings these different groups together. ‘We all have our blind spots,’ concludes Jaeger. ‘And the biggest gap in our knowledge is a foundational theory for neuromorphic computing. Our paper is a first attempt at pointing out how such a theory could be constructed and how we can create a common language.’

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

Toward a formal theory for computing machines made out of whatever physics offers by Herbert Jaeger, Beatriz Noheda & Wilfred G. van der Wiel. Nature Communications volume 14, Article number: 4911 (2023) DOI: https://doi.org/10.1038/s41467-023-40533-1 Published: 16 August 2023

This paper is open access and there’s a 76 pp. version, “Toward a formal theory for computing machines made out of whatever physics offers: extended version” (emphasis mine) available on arXchiv.

Caption: A general theory of physical computing systems would comprise existing theories as special cases. Figure taken from an extended version of the Nature Comm paper on arXiv. Credit: Jaeger et al. / University of Groningen

With regard to new materials for neuromorphic computing, my January 4, 2024 posting highlights a proposed quantum material for this purpose.

A hardware (neuromorphic and quantum) proposal for handling increased AI workload

It’s been a while since I’ve featured anything from Purdue University (Indiana, US). From a November 7, 2023 news item on Nanowerk, Note Links have been removed,

Technology is edging closer and closer to the super-speed world of computing with artificial intelligence. But is the world equipped with the proper hardware to be able to handle the workload of new AI technological breakthroughs?

Key Takeaways
Current AI technologies are strained by the limitations of silicon-based computing hardware, necessitating new solutions.

Research led by Erica Carlson [Purdue University] suggests that neuromorphic [brainlike] architectures, which replicate the brain’s neurons and synapses, could revolutionize computing efficiency and power.

Vanadium oxides have been identified as a promising material for creating artificial neurons and synapses, crucial for neuromorphic computing.

Innovative non-volatile memory, observed in vanadium oxides, could be the key to more energy-efficient and capable AI hardware.

Future research will explore how to optimize the synaptic behavior of neuromorphic materials by controlling their memory properties.

The colored landscape above shows a transition temperature map of VO2 (pink surface) as measured by optical microscopy. This reveals the unique way that this neuromorphic quantum material [emphasis mine] stores memory like a synapse. Image credit: Erica Carlson, Alexandre Zimmers, and Adobe Stock

An October 13, 2023 Purdue University news release (also on EurekAlert but published November 6, 2023) by Cheryl Pierce, which originated the news item, provides more detail about the work, Note: A link has been removed,

“The brain-inspired codes of the AI revolution are largely being run on conventional silicon computer architectures which were not designed for it,” explains Erica Carlson, 150th Anniversary Professor of Physics and Astronomy at Purdue University.

A joint effort between Physicists from Purdue University, University of California San Diego (USCD) and École Supérieure de Physique et de Chimie Industrielles (ESPCI) in Paris, France, believe they may have discovered a way to rework the hardware…. [sic] By mimicking the synapses of the human brain.  They published their findings, “Spatially Distributed Ramp Reversal Memory in VO2” in Advanced Electronic Materials which is featured on the back cover of the October 2023 edition.

New paradigms in hardware will be necessary to handle the complexity of tomorrow’s computational advances. According to Carlson, lead theoretical scientist of this research, “neuromorphic architectures hold promise for lower energy consumption processors, enhanced computation, fundamentally different computational modes, native learning and enhanced pattern recognition.”

Neuromorphic architecture basically boils down to computer chips mimicking brain behavior.  Neurons are cells in the brain that transmit information. Neurons have small gaps at their ends that allow signals to pass from one neuron to the next which are called synapses. In biological brains, these synapses encode memory. This team of scientists concludes that vanadium oxides show tremendous promise for neuromorphic computing because they can be used to make both artificial neurons and synapses.

“The dissonance between hardware and software is the origin of the enormously high energy cost of training, for example, large language models like ChatGPT,” explains Carlson. “By contrast, neuromorphic architectures hold promise for lower energy consumption by mimicking the basic components of a brain: neurons and synapses. Whereas silicon is good at memory storage, the material does not easily lend itself to neuron-like behavior. Ultimately, to provide efficient, feasible neuromorphic hardware solutions requires research into materials with radically different behavior from silicon – ones that can naturally mimic synapses and neurons. Unfortunately, the competing design needs of artificial synapses and neurons mean that most materials that make good synaptors fail as neuristors, and vice versa. Only a handful of materials, most of them quantum materials, have the demonstrated ability to do both.”

The team relied on a recently discovered type of non-volatile memory which is driven by repeated partial temperature cycling through the insulator-to-metal transition. This memory was discovered in vanadium oxides.

Alexandre Zimmers, lead experimental scientist from Sorbonne University and École Supérieure de Physique et de Chimie Industrielles, Paris, explains, “Only a few quantum materials are good candidates for future neuromorphic devices, i.e., mimicking artificial synapses and neurons. For the first time, in one of them, vanadium dioxide, we can see optically what is changing in the material as it operates as an artificial synapse. We find that memory accumulates throughout the entirety of the sample, opening new opportunities on how and where to control this property.”

“The microscopic videos show that, surprisingly, the repeated advance and retreat of metal and insulator domains causes memory to be accumulated throughout the entirety of the sample, rather than only at the boundaries of domains,” explains Carlson. “The memory appears as shifts in the local temperature at which the material transitions from insulator to metal upon heating, or from metal to insulator upon cooling. We propose that these changes in the local transition temperature accumulate due to the preferential diffusion of point defects into the metallic domains that are interwoven through the insulator as the material is cycled partway through the transition.”

Now that the team has established that vanadium oxides are possible candidates for future neuromorphic devices, they plan to move forward in the next phase of their research.

“Now that we have established a way to see inside this neuromorphic material, we can locally tweak and observe the effects of, for example, ion bombardment on the material’s surface,” explains Zimmers. “This could allow us to guide the electrical current through specific regions in the sample where the memory effect is at its maximum. This has the potential to significantly enhance the synaptic behavior of this neuromorphic material.”

There’s a very interesting 16 mins. 52 secs. video embedded in the October 13, 2023 Purdue University news release. In an interview with Dr. Erica Carlson who hosts The Quantum Age website and video interviews on its YouTube Channel, Alexandre Zimmers takes you from an amusing phenomenon observed by 19th century scientists through the 20th century where it becomes of more interest as the nanscale phenonenon can be exploited (sonar, scanning tunneling microscopes, singing birthday cards, etc.) to the 21st century where we are integrating this new information into a quantum* material for neuromorphic hardware.

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

Spatially Distributed Ramp Reversal Memory in VO2 by Sayan Basak, Yuxin Sun, Melissa Alzate Banguero, Pavel Salev, Ivan K. Schuller, Lionel Aigouy, Erica W. Carlson, Alexandre Zimmers. Advanced Electronic Materials Volume 9, Issue 10 October 2023 2300085 DOI: https://doi.org/10.1002/aelm.202300085 First published: 10 July 2023

This paper is open access.

There’s a lot of research into neuromorphic hardware, here’s a sampling of some of my most recent posts on the topic,

There’s more, just use ‘neuromorphic hardware’ for your search term.

*’meta’ changed to ‘quantum’ on January 8, 2024.

Powered with salt water

Apparently, salt water can be used both in the production of fusion energy (a form of nuclear energy) and, according to new research from the University of Illinois into a nanofluidic device, electricity. From a September 22, 2023 University of Illinois news release (also on EurekAlert),

There is a largely untapped energy source along the world’s coastlines: the difference in salinity between seawater and freshwater. A new nanodevice can harness this difference to generate power.

A team of researchers at the University of Illinois Urbana-Champaign has reported a design for a nanofluidic device capable of converting ionic flow into usable electric power in the journal Nano Energy. The team believes that their device could be used to extract power from the natural ionic flows at seawater-freshwater boundaries.

“While our design is still a concept at this stage, it is quite versatile and already shows strong potential for energy applications,” said Jean-Pierre Leburton, a U. of I. professor of electrical & computer engineering and the project lead. “It began with an academic question – ‘Can a nanoscale solid-state device extract energy from ionic flow?’ – but our design exceeded our expectations and surprised us in many ways.”

When two bodies of water with different salinity meet, such as where a river empties into an ocean, salt molecules naturally flow from higher concentration to lower concentration. The energy of these flows can be harvested because they consist of electrically charged particles called ions that form from the dissolved salt.

Leburton’s group designed a nanoscale semiconductor device that takes advantage of a phenomenon called “Coulomb drag” between flowing ions and electric charges in the device. When the ions flow through a narrow channel in the device, electric forces cause the device charges to move from one side to the other creating voltage and electric current.

The researchers found two surprising behaviors when they simulated their device. First, while they expected that Coulomb drag would primarily occur through the attractive force between opposite electric charges, the simulations indicated that the device works equally well if the electric forces are repulsive. Both positively and negatively charged ions contribute to drag.

“Just as noteworthy, our study indicates that there is an amplification effect” said Mingye Xiong, a graduate student in Leburton’s group and the study’s lead author. “Since the moving ions are so massive compared to the device charges, the ions impart large amounts of momentum to the charges, amplifying the underlying current.”

The researchers also found that these effects are independent of the specific channel configuration as well as the choice of materials, provided the channel diameter is narrow enough to ensure proximity between the ions and the charges.

The researchers are in the process of patenting their findings, and they are studying how arrays of these devices could scale for practical power generation.

“We believe that the power density of a device array could meet or exceed that of solar cells,” Leburton said. “And that’s not to mention the potential applications in other fields like biomedical sensing and nanofluidics.”

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

Ionic coulomb drag in nanofluidic semiconductor channels for energy harvest by Mingye Xiong, Kewei Song, Jean-Pierre Leburton. Nano Energy Volume 117, 1 December 2023, 108860 DOI: https://doi.org/10.1016/j.nanoen.2023.108860

This paper is behind a paywall.

Shape-changing speaker (aka acoustic swarms) for sound control

To alleviate any concerns, these swarms are not kin to Michael Crichton’s swarms in his 2002 novel, Prey or his 2011 novel, Micro (published after his death).

A September 21, 2023 news item on ScienceDaily announces this ‘acoustic swarm’ research,

In virtual meetings, it’s easy to keep people from talking over each other. Someone just hits mute. But for the most part, this ability doesn’t translate easily to recording in-person gatherings. In a bustling cafe, there are no buttons to silence the table beside you.

The ability to locate and control sound — isolating one person talking from a specific location in a crowded room, for instance — has challenged researchers, especially without visual cues from cameras.

A team led by researchers at the University of Washington has developed a shape-changing smart speaker, which uses self-deploying microphones to divide rooms into speech zones and track the positions of individual speakers. With the help of the team’s deep-learning algorithms, the system lets users mute certain areas or separate simultaneous conversations, even if two adjacent people have similar voices. Like a fleet of Roombas, each about an inch in diameter, the microphones automatically deploy from, and then return to, a charging station. This allows the system to be moved between environments and set up automatically. In a conference room meeting, for instance, such a system might be deployed instead of a central microphone, allowing better control of in-room audio.

The team published its findings Sept. 21 [2023] in Nature Communications.

A September 21, 2023 University of Washington (state) news release (also on EurekAlert), which originated the news item, delves further into the work, Note: Links have been removed,

“If I close my eyes and there are 10 people talking in a room, I have no idea who’s saying what and where they are in the room exactly. That’s extremely hard for the human brain to process. Until now, it’s also been difficult for technology,” said co-lead author Malek Itani, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “For the first time, using what we’re calling a robotic ‘acoustic swarm,’ we’re able to track the positions of multiple people talking in a room and separate their speech.”

Previous research on robot swarms has required using overhead or on-device cameras, projectors or special surfaces. The UW team’s system is the first to accurately distribute a robot swarm using only sound.

The team’s prototype consists of seven small robots that spread themselves across tables of various sizes. As they move from their charger, each robot emits a high frequency sound, like a bat navigating, using this frequency and other sensors to avoid obstacles and move around without falling off the table. The automatic deployment allows the robots to place themselves for maximum accuracy, permitting greater sound control than if a person set them. The robots disperse as far from each other as possible since greater distances make differentiating and locating people speaking easier. Today’s consumer smart speakers have multiple microphones, but clustered on the same device, they’re too close to allow for this system’s mute and active zones.

“If I have one microphone a foot away from me, and another microphone two feet away, my voice will arrive at the microphone that’s a foot away first. If someone else is closer to the microphone that’s two feet away, their voice will arrive there first,” said co-lead author Tuochao Chen, a UW doctoral student in the Allen School. “We developed neural networks that use these time-delayed signals to separate what each person is saying and track their positions in a space. So you can have four people having two conversations and isolate any of the four voices and locate each of the voices in a room.”

The team tested the robots in offices, living rooms and kitchens with groups of three to five people speaking. Across all these environments, the system could discern different voices within 1.6 feet (50 centimeters) of each other 90% of the time, without prior information about the number of speakers. The system was able to process three seconds of audio in 1.82 seconds on average — fast enough for live streaming, though a bit too long for real-time communications such as video calls.

As the technology progresses, researchers say, acoustic swarms might be deployed in smart homes to better differentiate people talking with smart speakers. That could potentially allow only people sitting on a couch, in an “active zone,” to vocally control a TV, for example.

Researchers plan to eventually make microphone robots that can move around rooms, instead of being limited to tables. The team is also investigating whether the speakers can emit sounds that allow for real-world mute and active zones, so people in different parts of a room can hear different audio. The current study is another step toward science fiction technologies, such as the “cone of silence” in “Get Smart” and“Dune,” the authors write.

Of course, any technology that evokes comparison to fictional spy tools will raise questions of privacy. Researchers acknowledge the potential for misuse, so they have included guards against this: The microphones navigate with sound, not an onboard camera like other similar systems. The robots are easily visible and their lights blink when they’re active. Instead of processing the audio in the cloud, as most smart speakers do, the acoustic swarms process all the audio locally, as a privacy constraint. And even though some people’s first thoughts may be about surveillance, the system can be used for the opposite, the team says.

“It has the potential to actually benefit privacy, beyond what current smart speakers allow,” Itani said. “I can say, ‘Don’t record anything around my desk,’ and our system will create a bubble 3 feet around me. Nothing in this bubble would be recorded. Or if two groups are speaking beside each other and one group is having a private conversation, while the other group is recording, one conversation can be in a mute zone, and it will remain private.”

Takuya Yoshioka, a principal research manager at Microsoft, is a co-author on this paper, and Shyam Gollakota, a professor in the Allen School, is a senior author. The research was funded by a Moore Inventor Fellow award.

Two of the paper`s authors, Malek Itani and Tuochao Chen, have written a ‘Behind the Paper’ article for Nature.com’s Electrical and Electronic Engineering Community, from their September 21, 2023 posting,

Sound is a versatile medium. In addition to being one of the primary means of communication for us humans, it serves numerous purposes for organisms across the animal kingdom. Particularly, many animals use sound to localize themselves and navigate in their environment. Bats, for example, emit ultrasonic sound pulses to move around and find food in the dark. Similar behavior can be observed in Beluga whales to avoid obstacles and locate one other.

Various animals also have a tendency to cluster together into swarms, forming a unit greater than the sum of its parts. Famously, bees agglomerate into swarms to more efficiently search for a new colony. Birds flock to evade predators. These behaviors have caught the attention of scientists for quite some time, inspiring a handful of models for crowd control, optimization and even robotics. 

A key challenge in building robot swarms for practical purposes is the ability for the robots to localize themselves, not just within the swarm, but also relative to other important landmarks. …

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

Creating speech zones with self-distributing acoustic swarms by Malek Itani, Tuochao Chen, Takuya Yoshioka & Shyamnath Gollakota. Nature Communications volume 14, Article number: 5684 (2023) DOI: https://doi.org/10.1038/s41467-023-40869-8 Published: 21 September 2023

This paper is open access.