IIT Kanpur-incubated startup inks pact for India’s first 100 pc electric compact tractor

IANS Photo

New Delhi, (IANS): An SIIC IIT Kanpur-incubated startup, ScaNxt Scientific Technologies, entered into an agreement with two institutions under the Ministry of Science and Technology for the technology transfer of India’s first indigenously developed 100 per cent electric compact tractor, a statement has said.

The electric compact tractor, developed with over 90 per cent indigenous components, has been specifically designed for India’s small and marginal farmers.

Conventional diesel-based mechanisation models have historically remained economically inaccessible for small land holders, creating a structural productivity gap across rural India.

India’s agricultural economy remains heavily dependent on smallholder farmers, with over 86 per cent of farming households operating on less than 2 hectares of land.

The tractor integrates a fully electric drivetrain, Vehicle-to-Load (V2L) functionality capable of powering irrigation pumps and farm equipment, compact operational architecture suited for smaller farms, and simplified controls designed to improve accessibility for women farmers.

“Our Smart Compact EV Tractor will dramatically cut cultivation costs, generate green jobs in rural India, and usher in a new era of precision and prosperous farming,” the ScaNxt team said in the statement.

The development also signalled the emergence of a new category within India’s farm mechanisation landscape.

With electric agricultural equipment still at an early stage nationally, the initiative opens opportunities for manufacturing, distribution, servicing, and ecosystem development around sustainable rural mobility solutions.

SIIC IIT Kanpur signed the Memorandum of Understanding (MoU) with CSIR-CMERI and the National Research Development Corporation (NRDC) during the Vigyan Tech 2026 exhibition in New Delhi.

Under the agreement, ScaNxt Scientific Technologies will commercialise the technology under its own brand identity, with a focus on creating an affordable, energy-efficient, and scalable mechanisation solution for India’s rural economy."The agreement reflects the growing maturity of India’s translational innovation ecosystem — where publicly funded research, startup entrepreneurship, and institutional incubation are converging to solve large-scale national challenges through indigenous technologies," the statement noted. IIT Kanpur-incubated startup inks pact for India’s first 100 pc electric compact tractor | MorungExpress | morungexpress.com
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New Solar Method Turns Ocean Into Drinking Water, While Extracting Valuable Lithium Without Waste

Vials of (left to right) seawater, salt water, nickel sulfate, copper chloride wastewater, and desalinated water with recovered salts – Credit: University of Rochester / J. Adam Fenster

A new energy-efficient desalination system produces fresh water without chemical additives and transforms leftover salts into useful materials.

Communities from California to the Middle East currently rely on desalination plants to convert ocean water to fresh water. But, common desalination techniques—such as reverse osmosis and thermal distillation—are energy-intensive, require chemical water treatment, and leave behind a concentrated saltwater byproduct called brine, which wreaks havoc on sea life if it’s deposited back into the ocean by raising the salt content and lowering oxygen levels.

Now, a novel approach developed at the University of Rochester offers a way to overcome these drawbacks. Their new solar-thermal desalination process does not leave behind brine and requires no chemical additives to pre-treat the water, according to the paper published in Light: Science & Applications.

The technology uses solar panels made of black metal etched with femtosecond lasers to make the surface super light-absorbing and super-wicking, extremely attractive to water.

The panels have a laser-treated active region that pulls a thin layer of water across the surface, absorbs nearly all solar radiation, distills the water, and deposits the leftover salts and minerals into the panel’s untreated sides, leaving the active region unclogged for continuous desalination.

A team led by senior scientist Chunlei Guo, a professor of optics and physics at the university, says other researchers have developed solar-thermal desalination techniques that only work well in lab experiments—using simulated seawater made of only water and sodium chloride. The real ocean is much more complex, and these systems tend to encounter problems when used in the field.

Unlike sodium chloride, many other components in seawater, such as magnesium- and calcium-based materials, crystallize in a crusty and non-porous fashion on the solar panel’s surface—and water can’t seep through anymore. This is the same phenomenon as your shower head clogging over time, except that seawater contains hundreds of times more salts than your tap water.
The ‘coffee ring effect’ makes it self-cleaning

To keep their solar panel surface from gumming up, Guo’s team etched the black metal’s grooves so the various salts and minerals in ocean water would simply slough off. They also leveraged a physical phenomenon java-lovers have encountered for centuries: the coffee ring effect.

“If you drop coffee on a surface, eventually the water evaporates, and there’s a ring left at the outer edge that is the concentrated coffee particles,” says Prof. Guo. “We use that same principle to advance the salts to the passive region.”

Testing their solar-thermal desalination technique using samples of water from the Pacific, Atlantic, and Indian Oceans, Guo and his team were able to make the surface self-cleaning.

Old and new desalination systems – Credit University of Rochester / J. Adam Fenster

It extracted freshwater and directed the remaining salts to where they could be collected without reducing the panel’s efficiency.
Turning waste into resources – like lithium

Another distinct advantage is that instead of leaving behind brine that must be disposed of or processed, it extracts nearly 100 percent of the salts in solid form. This could not only produce an abundant supply of table salt, but it could also be used to extract more precious minerals, including lithium, which helps power electric vehicles and electronics.

“Mining lithium from the earth has proven to be very taxing from an energy and environmental standpoint, so pulling lithium directly from saltwater could be a very important future route,” says Guo.

In a related paper in the Journal of Materials Chemistry, Guo and his colleagues showed how they can use the same super-wicking solar panels to separate lithium from the rest of other salts in desalination.

Embedding nanoparticles made of hydrogen titanate in the tiny grooves of the black metal surface isolates the lithium from other salts and minerals.

Using water samples from Great Salt Lake, the researchers extracted about 50 percent of the lithium from the salts left behind by the desalination process.

Guo sees the technology as inherently scalable, capable of improving global access to drinking water while building a more sustainable supply of precious minerals.“Mining lithium from the earth has proven to be very taxing from an energy and environmental standpoint, so pulling lithium directly from saltwater could be a very important future route.” New Solar Method Turns Ocean Into Drinking Water, While Extracting Valuable Lithium Without Waste:
(The work was funded by the National Science Foundation, the Bill & Melinda Gates Foundation, and Worldwide Universities Network.)
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World’s first AI‑designed vaccine explained

Neil Mabbott, University of Edinburgh

Researchers at the University of Cambridge have developed what they describe as a fundamentally new type of vaccine using artificial intelligence (AI). The vaccine’s key component was designed entirely by AI and has now been tested in people for the first time.

The goal is ambitious: a single vaccine that works not just against all known human coronavirus variants, but against related bat viruses that could jump from animals to humans and cause future pandemics.

Traditional vaccines train our immune system to recognise one specific virus. The problem is that viruses mutate. When they change enough, the vaccine stops working, which is why we need a new flu shot every year and why COVID vaccines have been updated repeatedly since 2021.

AI offers a way around this. By analysing genetic data from thousands of related viruses, it can identify the parts that stay the same across different strains and that are unlikely to change over time. Target those stable features, and you have a vaccine that should work against the whole family, not just the strain you started with.

This is exactly what the Cambridge team did. They used AI to scan viruses from the sarbecovirus family, which includes the viruses that cause both SARS and COVID, as well as a range of animal coronaviruses – looking for shared features that evolution has left largely untouched. Those features became the basis of the vaccine.

DNA vaccines

While many people are familiar with the mRNA shots used during the pandemic, this new vaccine uses DNA. DNA vaccines are generally more stable than mRNA vaccines, making them easier to store and transport. A significant advantage in lower-income countries where “cold-chain” infrastructure is limited.

They can also be administered without needles. A high-pressure stream of liquid delivers the vaccine through the skin, making administration less painful and easier to scale up during an outbreak.

DNA and RNA viruses explained.

Could it protect against future pandemics?

These practical advantages matter most if the vaccine itself can do something no existing jab can: protect against viruses we haven’t encountered yet.

Broad-spectrum vaccines could change the way the world responds to emerging infectious diseases. By offering much wider protection than traditional vaccines, they could provide rapid immunity against new and emerging viral threats. This would equip public health officials with tools to stop future outbreaks in their tracks before they have a chance to turn into global pandemics.

They could also transform our approach to more familiar diseases. Influenza is a prime target because it exists in many different strains and evolves so rapidly. Scientists have to predict which strains will dominate each flu season, and they guess wrong, vaccine effectiveness can suffer. A universal flu vaccine that targets features shared across multiple strains could eventually end the annual race to keep up with the virus.

And the Ebola virus shows why this matters right now. The recent outbreak in the Democratic Republic of the Congo and Uganda is driven by the Bundibugyo strain, which bypasses existing vaccines. While researchers rush to create a new vaccine specifically for this strain, local communities remain at high risk. A broad-spectrum vaccine designed to cover an entire virus family could transform that picture.

What the trial found

This is the first human trial of an AI-designed vaccine. The results showed that this DNA vaccine was able to stimulate the immune system to produce antibodies that can recognise different types of sarbecoviruses. The technology was found to be safe and well tolerated.

This is an exciting advance because it demonstrates how AI has the potential to design variant-proof vaccines against future pandemic threats. The needle-free delivery system could also make the vaccine easier to administer and distribute worldwide.

However, there is more work to do. Although the results in this study are encouraging, the immune responses following vaccination were modest. It was also uncertain how long the protection lasts and whether further boosters will be required. Larger trials are also needed to determine whether the vaccine can prevent or reduce virus infections in the real world.

A universal vaccine remains a few years away. And any new vaccine must still pass larger trials to prove it is safe, effective and provides lasting protection. But this study shows the goal is getting closer – and AI may help us get there faster.The Conversation

Neil Mabbott, Personal Chair of Immunopathology, University of Edinburgh

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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UN report warns AI could soon use 3% of world’s electricity and more water than we need to drink

Amanda Turnbull-McRae, University of Waikato

One argument often used to quell concerns about the rising energy and resource demand of data centres is that artificial intelligence (AI) models will need less in the future as they improve and become more efficient.

But this seemingly logical thinking is a trap, according to a new United Nations report that quantifies the environmental costs of AI.

The report estimates that by 2030, AI’s energy use could double to consume 3% of the world’s electricity, produce emissions to equal the UK and deplete more water for cooling than the annual drinking water need of the global population.

It also anticipates the use of AI will follow an economic principle known as the “Jevons paradox”, which predicts that when technological improvements increase the efficiency of a resource, it leads to a rise, rather than a fall, in the total consumption of that resource.

The paradox is named after economist William Stanley Jevons who observed this effect with the use of coal in 19th-century England. Efficiency gains did not reduce overall consumption. Instead, the lower costs resulted in expanded use and higher overall demand.

As AI models become cheaper and more attractive, the report expects this to encourage new uses and higher volumes of use, eroding and possibly erasing any savings from efficiency advances.

To avoid falling into this trap, it lays out a roadmap for responsible AI use based on guiding principles of transparency, efficiency by design, equity and justice, lifecycle responsibility, global cooperation and sustainable use.

The scale of the problem

Last year, data centres already consumed as much electricity as Saudi Arabia, which ranks as the world’s 11th largest electricity consumer.

If electricity use doubles as projected by 2030, the associated carbon footprint would require 6.7 billion trees grown over ten years to offset this demand.

Data centres would also require 9.3 trillion litres of water and land nearly ten times the size of Mexico City.

Beyond resource use, the report also underscores the structural inequity at the heart of the AI boom, with only 32 nations hosting AI-specific cloud infrastructure and 90% of that capacity located in the US and China.

It warns of a widening digital divide between nations that build and control AI systems and those that consume them, with the latter often bearing a disproportionate environmental burden caused by mineral extraction and e-waste.

Responsible AI use

Two main forces shape AI’s operational footprint: how much we use it and how we use it.

This involves all tasks AI models perform, from text and code generation to image and video. Each of these tasks requires different levels of computational effort.

The model choice also matters as each AI system performs these task with distinct energy and environmental costs.

The report argues responsible AI requires full value-chain governance, from mineral sourcing to recycling and safe disposal.

It calls for a twinning of capability and environmental stewardship – thinking about both what AI can do for us and the protection of the natural environment.

This would mean making environmental disclosures a routine part of AI development, at both the model and task level, and incorporating projected AI demand in climate and energy planning.

Responsible AI is crucial as countries are promoting and adopting AI across government and the public sector.

In Aotearoa New Zealand, the government has launched a national AI strategy and a public service AI framework.

While the framework was informed by the OECD’s values-based AI principles, including inclusive and sustainable development, there is no requirement for environmental disclosures and no regulator compiling energy use or emissions.

Likewise in Australia, improving public services is part of the national AI plan. For example, the National Film and Sound Archive of Australia has created Bowerbird, a machine learning-enabled mass audio and video transcription engine, to document material. The Department of Veteran’s Affairs has developed a proof-of-concept tool to see whether AI can help speed up the processing of claims.

Both countries take a deliberate “light touch” and principles-based regulatory approach to AI. But this approach risks overlooking the growing environmental cost of AI that can’t be solved by improving it.

The natural environment is foundational to the economy, culture and wellbeing. It should be at the centre of our thinking. It’s time to rethink the AI innovation playbook and shift focus toward a sustainable tech future.The Conversation

Amanda Turnbull-McRae, Senior Lecturer in Law, University of Waikato

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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New AI Glasses for Dementia ‘Sees’ Objects With Labels Projected on Lenses to ‘Significantly’ Improve Lives

Carole Grieg testing the CrossSense AI glasses – SWNS

New AI glasses for people with dementia are able to project visual prompts onto the lenses to help folks live more independently—and they could be available in the UK in 2027.

The latest news comes after the glasses wowed both test patients in their homes and a panel of outside judges.

They can guide people living with early-stage dementia through daily activities by identifying common objects and providing audio commentary or answer questions while projecting visual prompts onto the lenses.

By asking gentle questions, the glasses’ AI companion, called ‘Wispy’, understands and learns a person’s unique way of doing things, with the AI adapting to each user’s needs as their dementia progresses.

Wispy will even talk through what to do when a person cannot remember a particular step in a process.

In test trials, three out of four patients reported a significant improvement to their quality of life, thanks to the glasses and Wispy’s tips developed from UK company CrossSense.

Warning appears on the lenses of the CrossSense AI glasses (GNN screenshot of SWNS/CrossSense video)

Spending over a decade creating and tweaking prototypes of the app and gadget, a team of AI engineers trained the glasses with dozens of everyday activities including getting dressed, managing household chores safely, making a cup of tea and interacting with loved ones.

The specs, which work with people’s prescription lens inserts and hearing aids, also capture the environment of the person living with dementia and the AI interprets that information to help the user to do the things that define independence.

“This includes feeling confident in their own home, taking good care of themselves, planning the day ahead, completing planned activities and hosting friends and family,” said the creators.

Screenshot of Wispy AI in the midst of interacting with user of theCrossSense AI glasses, discussing care of a houseplant (Still from SWNS video)

With a release date set for early 2027 in the UK, the inventors hope the specs, which weigh less than 3 ounces (75g), will be used by local authorities, care providers, and NHS hospital memory clinics.

Last week, the London-based team behind the technology, CrossSense, won the Longitude Prize on Dementia with its million dollar prize funded by the Alzheimer’s Society and Innovate UK.

The panel of international expert judges agreed that the winning solution was a genuine breakthrough technology with revolutionary potential for people living with dementia and their families.

CrossSense says the gadget includes a built-in battery that lasts for one hour, but also a portable power bank that can keep the glasses running all day long.

70-year-old Carole Grieg from London (pictured above), who founded a dementia support group called ForgetMeNots, tried the new glasses and is convinced they could help her fellow dementia patients maintain their independence.

“I thought it was an amazing concept, with the potential to provide real, reliable support for people like me, helping to compensate for the cognitive skills we gradually lose as dementia progresses.”

“For many of us, our world slowly becomes smaller as the condition progresses. Innovations like this offer real hope, and I know that as my own circumstances change, I will certainly be relying on them.”

Professor Fiona Carragher, chief research officer at Alzheimer’s Society admires the way the technology can develop its ‘intuitive personal support’.

“By anticipating people’s needs as their condition progresses, easing daily living challenges, and providing reassurance to families, this revolutionary tech will allow people with dementia to maintain their independence for longer, within the familiar environment of home.” New AI Glasses for Dementia ‘Sees’ Objects With Labels Projected on Lenses to ‘Significantly’ Improve Lives
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AI-powered digital stethoscopes show promise in bridging screening gaps

(Photo: Eko Health, US) IANS

New Delhi, As tuberculosis (TB) continues as the deadliest infectious cause of deaths globally, a new study has shown that artificial intelligence (AI)-enabled digital stethoscopes can help fill critical screening gaps, especially in hard-to-reach areas.

In a commentary published in the journal Med (Cell Press), global experts contended that stethoscopes combined with digital technology and AI can be a better option against the challenges faced in screening programmes, such as under-detection, high cost, and inequitable access.

“AI-enabled digital stethoscopes have demonstrated promising accuracy and feasibility for detecting lung and cardiovascular abnormalities, with promising results in early TB studies. Training and validation in diverse, high-burden settings are essential to explore the potential of this tool further,” said corresponding author Madhukar Pai from McGill University, Canada, along with researchers from the UAE, Germany, and Switzerland.

Despite advancements in screening and diagnostic tools, an estimated 2.7 million people with TB were missed by current screening programmes, as per data from the World Health Organization (WHO). Routine symptom screening is also likely to miss people with asymptomatic or subclinical TB.

While the WHO recently recommended several AI-powered computer-aided detection (CAD) software, as well as ultra-portable radiography hardware, higher operating costs and upfront hardware act as a deterrent.

This particularly appeared difficult in primary care settings and or among pregnant women due to radiation concerns.

At the same time, AI showed significant potential for screening, including applications beyond CAD of TB from radiographs, said the researchers.

“One application of AI for disease screening is to interpret acoustic (sound) biomarkers of disease, with potential to identify sounds that appear nonspecific or are inaudible to the human ear,” they added, while highlighting the potential of AI in detecting and interpreting cough biomarkers and lung auscultation to analyse breath sounds.

Studies from high-TB burden countries, including India, Peru, South Africa, Uganda, and Vietnam, highlighted that AI-enabled auscultation could hold promise as a TB screening and triage tool.

"AI digital stethoscopes may become useful alternatives to imaging-based approaches for TB screening, with the potential to democratise access to care for populations underserved by radiography," the researchers said."Importantly, AI digital stethoscopes offer a scalable, low-cost, and person-centered tool that could bring us closer to reaching TB case finding goals," they added. AI-powered digital stethoscopes show promise in bridging screening gaps | MorungExpress | morungexpress.com
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Quantum computers are coming to break our codes faster than anyone expected

Craig Costello, Queensland University of Technology

Online data is generally pretty secure. Assuming everyone is careful with passwords and other protections, you can think of it as being locked in a vault so strong that even all the world’s supercomputers, working together for 10,000 years, could not crack it.

But last month, Google and others released results suggesting a new kind of computer – a quantum computer – might be able to open the vault with significantly less resources than previously thought.

The changes are coming on two fronts. On one, tech giants such as IBM and Google are racing to build ever-larger quantum computers: IBM hopes to achieve a genuine advantage over classical computers in some special cases this year, and an even more powerful “fault-tolerant” system by 2029.

On the other front, theorists are refining quantum algorithms: recent work shows the resources needed to break today’s cryptography may be far lower than earlier estimates.

The net result? The day quantum computers can break widely used cryptography – portentously dubbed “Q Day” – may be approaching faster than expected.

The quantum hardware race

Quantum computers are built from quantum bits, or qubits, which use the counterintuitive properties of very tiny objects to carry out computations in a different and sometimes far more efficient way from traditional computers.

So far the technology is in its infancy, with the major goal to increase the number of qubits that can be connected to work as a single computer. Bigger quantum computers should be much better at some things than their traditional counterparts – they will have a “quantum advantage”.

Late last year, IBM unveiled a 120-qubit chip which it hopes will demonstrate a quantum advantage for some tasks.

Google also recently announced it planned to speed up its move to adopt encryption techniques that should be safe against quantum computers, known as post-quantum cryptography.

Alongside these tech giants, newer approaches are also flourishing. PsiQuantum is using light-based qubits and traditional chip-manufacturing technology. Experimental platforms such as neutral-atom systems have demonstrated control over thousands of qubits in laboratory settings.

In response, standards bodies and national agencies are setting increasingly concrete timelines for moving away from common encryption systems that are vulnerable to quantum attack.

In the United States, the National Institute of Standards and Technology (NIST) has proposed a transition away from quantum-vulnerable cryptography, with migration largely completed by 2035. In Australia, the Australian Signals Directorate has issued similar guidance, urging organisations to begin planning immediately and transition to post-quantum cryptography by 2030.

Algorithms make the lock-picking faster

Hardware is only half the story. Equally important are advances in quantum algorithms – ways to use quantum computers to attack encryption.

Much interest in quantum computer development was spurred by Peter Shor’s 1994 discovery of an algorithm that showed how quantum computers could efficiently find the prime factors of very large numbers. This mathematical trick is precisely what you need to break the common RSA encryption method.

For decades, it was believed a quantum computer would need millions of physical qubits to pose a threat to real-world encryption. This is far bigger than current systems, so the threat felt comfortably distant.

That picture is now changing.

In March 2026, Google’s Quantum AI team released a detailed study showing that far fewer resources may be needed to attack a different kind of encryption which uses mathematical objects called elliptic curves. This is what systems including Bitcoin and Ethereum use – and the study shows how a quantum computer with fewer than half a million physical qubits may be able to crack it in minutes.

That’s still a long way beyond current quantum computers, but around ten times less than earlier estimates.

At the same time, a March 2026 preprint from a Caltech–Berkeley–Oratomic collaboration explores what might be possible using neutral-atom quantum computers. The researchers estimate that Shor’s algorithm could be implemented with as few as 10,000–20,000 atomic qubits. In one design they propose, a system with around 26,000 qubits could crack Bitcoin’s encryption in a few days, while tougher problems like the RSA method with a 2048-bit key would need more time and resources.

In plain terms: the codebreakers are becoming more efficient. Advances in algorithms and design are steadily lowering the bar for quantum attacks, even before large-scale hardware exists.

What now?

So what does this mean in practice?

First, there is no immediate catastrophe – today’s cryptography won’t be broken overnight. But the direction of travel is clear. Each improvement in hardware or algorithms reduces the gap between current capabilities and useful quantum cracking machines.

Second, viable defences already exist. NIST has standardised several post-quantum cryptographic algorithms which are believed to be resistant to quantum attacks.

Technology companies have begun deploying these in hybrid modes: Google Chrome and Cloudflare, for example, already support post-quantum protections in some protocols and services.

Systems that rely heavily on elliptic-curve cryptography – including cryptocurrencies and many secure communication protocols – will need particular attention. Google’s recent work explicitly highlights the need to migrate blockchain systems to post-quantum schemes.

Finally, this is a two-front race. It is not enough to track progress in quantum hardware alone. Advances in algorithms and error correction can be just as important, and recent results show these improvements can significantly reduce the estimated cost of attacks.

Every new headline about reduced qubit counts or faster quantum algorithms should be understood for what it is: another step toward a future where today’s cryptographic assumptions no longer hold.

The only reliable defence is to move – deliberately but decisively – toward quantum-safe cryptography.The Conversation

Craig Costello, Professor, School of Computer Science, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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EV Charging Answer: Quantum Technology Will Cut Time it Takes to Charge Electric Cars to Just 9 Seconds

Institute for Basic Science

Scientists in South Korea have proven that a new technology will cut the time it takes to charge electric cars to just nine seconds, allowing EV owners to ‘fill up’ faster than their gasoline counterparts.

And even those plugging-in at home will have the time slashed from 10 hours to three minutes.

The new device uses the laws of quantum physics to power all of a battery’s cells at once—instead of one at a time—so recharging takes no longer than filling up at the pump.

Electric cars were rarely seen on the roads 10 years ago, but millions are now being sold every year and it has become one of the fastest growing industries, but even the fastest superchargers need around 20 to 40 minutes to power their car.

Scientists at the Institute for Basic Science (IBS) in South Korea have come up with a solution. Co-author Dr. Dario Rosa said the consequences could be far-reaching.

“Quantum charging could go well beyond electric cars and consumer electronics. For example, it may find key uses in future fusion power plants, which require large amounts of energy to be charged and discharged in an instant.”

The concept of a “quantum battery” was first proposed in a seminal paper published by Alicki and Fannes in 2012. It was theorized that quantum resources, such as entanglement, can be used to vastly speed up battery charging.

The researchers used quantum mechanics to model their super fast charging station with calculations of the charging speed showing that a typical electric vehicle with a battery containing around 200 cells would recharge 200 times faster.

Current collective charging is not possible in classical batteries, where the cells are charged in parallel, independently of one another.

“This is particularly exciting as modern large-capacity batteries can contain numerous cells.”

The group went further to provide an explicit way of designing such batteries.

This means charging times could be cut from 10 hours to three minutes at home and from around 30 minutes to just a few seconds at stations.

Co-author Dr Dominik Å afránek said, “Of course, quantum technologies are still in their infancy and there is a long way to go before these methods can be implemented in practice.”

“Research findings such as these, however, create a promising direction and can incentivize the funding agencies and businesses to further invest in these technologies.

“If employed, it is believed that quantum batteries would completely revolutionize the way we use energy and take us a step closer to our sustainable future.”

The findings were published in the February 8 edition of the journal Physical Review Letters. [GNN updated the earlier broken link.] EV Charging Answer: Quantum Technology Will Cut Time it Takes to Charge Electric Cars to Just 9 Seconds
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Multiple Types of Plastic Are Turned into Vinegar Using Sunlight-Powered Process Without Emissions

Waterloo PhD student Wei Wei, who led the research – credit, University of Waterloo, released

Researchers at the University of Waterloo have discovered a way to turn plastic waste into acetic acid, the main ingredient of vinegar, using sunlight.

The breakthrough offers a promising new approach to reducing plastic pollution through photocatalysis, while simultaneously creating a useful, value-added chemical product through a process inspired by nature.

“Our goal was to solve the plastic pollution challenge by converting microplastic waste into high-value products using sunlight,” said Dr. Yimin Wu, a professor of mechanical and mechatronics engineering at the University of Waterloo, Canada.

Plastic waste, notably microplastics, has been found across many of the planet’s ecosystems, raising concerns about threats to terrestrial and marine life as well as human health. Plastic recycling rates remain low around the globe.

To tackle this problem, the team developed a bio-inspired photocatalysis process using iron atoms embedded in carbon nitride, a way that certain types of fungi break down organic matter using enzymes.

When exposed to sunlight, the material drives a series of chemical reactions that transform plastic polymers into acetic acid with high selectivity. The reaction takes place in water, making it particularly relevant for addressing plastic pollution in aquatic environments.

Acetic acid is widely used in food production, chemical manufacturing and energy applications. The study shows it can be produced from common plastic wastes, including PVC, PP, PE and PET, and remains effective across mixed plastic compositions.

This makes the approach well suited to real-world waste streams, offering a promising alternative to plastic incineration, and could support more circular approaches to material use while providing a new strategy for upcycling plastics.

“Both from a business and societal perspective, the financial and economic benefits associated with this innovation seem promising,” said Roy Brouwer, executive director of the Water Institute and a coauthor of the article supporting the techno-economic analysis.

“This method allows abundant and free solar energy to break down plastic pollution without adding extra carbon dioxide to the atmosphere,” Wu adds.

The findings also point to new possibilities for addressing microplastics directly. Because the process degrades plastics at the chemical level, it could help prevent the accumulation of microplastics in water systems.While still at the laboratory stage, the team envisions that this approach could be adapted for scalable, solar-driven recycling and environmental cleanup and the photocatalytic upcycling system can be further enhanced through strategic engineering of the materials and manufacturing processes. Multiple Types of Plastic Are Turned into Vinegar Using Sunlight-Powered Process Without Emissions
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AI could help us more accurately screen for breast cancer – new research

At least 20,000 Australian women are diagnosed with breast cancer each year. And more than 3,300 die from the disease.

To save women’s lives, we need to detect breast cancer early. Breast screening, which halves women’s risk of dying from breast cancer, is key to that.

A new Australian study published today in The Lancet Digital Health suggests AI could help improve how we screen for breast cancer.

How do we currently screen for breast cancer?

Since 1992, Australia has offered free breast X-rays, known as mammograms, every two years to women aged between 50 and 74. Just over half of eligible women participate.

Of the women found to have cancer, about 25% are diagnosed between the biennial screens. These “interval cancers” are often aggressive and, unfortunately, more likely to be fatal.

In some cases, a more sensitive screening test may have detected them earlier.

The role of AI

Australia’s BreastScreen program was established in response to several major clinical trials conducted between the 1960s and 1980s. The screening technology used by the program has not substantially changed since then.

Researchers are now exploring risk-adjusted screening, which tailors screening to women based on their risk, as a way to detect more cancers earlier. This may include programs offering different technologies for women at higher risk of developing breast cancer.

Currently, we generally assess cancer risk via questionnaires that help identify if a woman has any risk factors associated with breast cancer.

One risk factor is breast density which refers to how much glandular tissue is in the breast. As well as being a risk factor for breast cancer, the higher a woman’s breast density, the harder it is to detect cancer on a mammogram.

We can also use one-off genetic testing to identify women with a higher lifetime risk of developing breast cancer. This involves looking for high-risk gene mutations such as BRCA1 and BRCA2, which are associated with increased breast and ovarian cancer risk. Genetic testing can also help us estimate a person’s lifetime risk of developing breast cancer.

More recently, researchers have been investigating artificial intelligence (AI) as a new approach to assess breast cancer risk. A new Australian study, published in The Lancet Digital Health today, focused on a specific AI tool known as BRAIx.

What did the study involve? And what did it find?

This study used an AI tool, known as BRAIx, trained using BreastScreen Australia data to help radiologists assess mammograms.

The study assessed how well BRAIx predicted women’s risk of developing breast cancer in the next four years, among women who had a clear mammogram.

Of the 95,823 Australian women assessed, 1.1% (1,098) had developed breast cancer in the four years after they received a clear mammogram. Of the 4,430 Swedish women assessed, 6.9% had developed breast cancer within two years of a clear screen.

The study findings show that BRAIx scores were very useful for identifying women who were more likely to develop cancer one to two years after having a clear screen. Findings from the Australian dataset suggest BRAIx scores identified cancers found three to four years later, but with less accuracy.

These findings suggest BRAIx could help identify women who might benefit from additional tests. This may include an MRI (which uses a magnetic field to produce images of organs and tissue) or contrast-enhanced mammography (which uses an iodine dye to improve the visibility of a regular mammogram).

These findings reinforce a 2024 Swedish study that used an AI-based risk assessment to select women for additional testing. The researchers referred 7% of women to have a follow-up MRI, and 6.5% of were found to have cancers missed by mammograms.

Does the study have any limitations?

As with most studies, yes. Here are two.

  • it’s difficult to compare BRAIx to genetic testing. This is because BRAIx is trained to find missed or emerging cancers over a four year period. In contrast, genetic testing identifies a person’s risk of developing cancer over their lifetime

  • it might not use the best breast density data. This study found BRAIx more accurately predicts breast cancer risk compared to assessments based on breast density. But this breast density data was collected using a different tool to those used by the Breastscreen program. So this finding should be interpreted carefully.

So, where to from here?

The study adds to a growing body of evidence that AI risk assessment could help breast screening programs find cancers earlier.

BRAIx is now being trialled as part of the BreastScreen Victoria program, to help read mammograms. And other states are already using and evaluating different AI tools for reading mammograms.

So it may be time for Australia to conduct a national, independent review of these new tools. As part of a more risk-adjusted approach to breast screening, they could save lives.The Conversation

Carolyn Nickson, Principal Research Fellow, Cancer Elimination Collaboration, University of Sydney; The University of Melbourne and Bruce Mann, Professor of Surgery, Specialist Breast Surgeon, The University of Melbourne

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Wildlife Poachers to Be Targeted Using State of the Art AI Listening Technology

A photo of a male forest elephant captured near the site where some of the gunshot recordings were taken – credit, Anahita Verahrami / SWNS

Wildlife poachers can now be located and arrested across the central African forests thanks to state-of-the-art AI listening technology.

A network of microphones has been deployed across the rainforests to detect gunshots from illegal poaching of elephants and other animals, and American scientists are using AI to ensure the network can distinguish gunshots over the din of the jungle environment.

The web of acoustic sensors was deployed in Gabon, Congo, and Cameroon, creating the possibility of real-time alerts to the sounds of gun-based poaching.

But the belly of the rainforest is loud, and scientists say sorting through a constant influx of sound data is computationally demanding. Detectors can distinguish a loud bang from the whistles, chirps, and rasps of birds and bugs, but they often confuse the sounds of branches cracking or trees falling with gunshot noises, resulting in a high percentage of false positives.

Project leader Naveen Dhar at Center for Conservation Bioacoustics at Cornell University aimed to develop a lightweight gunshot detection neural network that can accompany sensors and process signals in real-time to minimize false positives.

He worked alongside colleagues at the Elephant Listening Project to create a model that will work through autonomous recording units (ARUs), which are power-efficient microphones that capture continuous, long-term soundscapes.

“The proposed system utilizes a web of ARUs deployed across the forest, each performing real-time detection, with a central hub that handles more complex processing.”

An initial scan filters all audio for “gunshot likely” signals and sends them to the ARU’s microprocessor, where the lightweight gunshot detection model lives.

If confirmed as a gunshot by the microprocessor, the ARU passes the information to the central hub, initiating data collection from other devices in the web.


By determining if other sensors also hear a “gunshot likely” noise, the central hub then decides whether the event was a true gunshot or a potential false positive.

If it determines a true positive, the central hub collates audio files from each sensor, allowing it to pinpoint the location of the gunshot and alert rangers on the ground with coordinates for immediate poaching intervention.

“Down the road, the device can be used as a tool for rangers and conservation managers, providing accurate and verifiable alerts for on-the-ground intervention along with low-latency data on the spatiotemporal trends of poachers,” Dhar said.

He plans to expand the model to detect the type of gun that fires each gunshot and other human activities, such as chainsaws or trucks, before field-testing the system, which is currently under development.

“I hope the device can coalesce with Internet of Things infrastructure innovations and cost reduction of materials to produce a low-cost, open-source framework for real-time detection usable in any part of the globe.”He is due to present his findings at a joint meeting of the Acoustical Society of America and Acoustical Society of Japan, in Honolulu, Hawaii. Wildlife Poachers to Be Targeted Using State of the Art AI Listening Technology:
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Scientists Develop Biodegradable Smart Textile–A Big Leap Forward for Eco-Friendly Wearable Technology

Flexible inkjet printed E-textile – Credit: Marzia Dulal

Wearable electronic textiles can be both sustainable and biodegradable, shows a new study.

A research team led by the University of Southampton and UWE Bristol in the UK tested a new sustainable approach for fully inkjet-printed, eco-friendly e-textiles.

Named SWEET—for Smart, Wearable, and Eco-friendly Electronic Textiles—the new ‘fabric’ was described in findings published in the journal Energy and Environmental Materials.


E-textiles are those with embedded electrical components, such as sensors, batteries or lights. They might be used in fashion, for performance sportswear, or for medical purposes as garments that monitor people’s vital signs.

Such textiles need to be durable, safe to wear and comfortable, but also, in an industry which is increasingly concerned with clothing waste, they need to be kind to the environment when no longer required.

“Integrating electrical components into conventional textiles complicates the recycling of the material because it often contains metals, such as silver, that don’t easily biodegrade,” explained Professor Nazmul Karim at the University of Southampton.


“Our eco-friendly approach for selecting sustainable materials and manufacturing overcomes this, enabling the fabric to decompose when it is disposed of.”

The team’s design has three layers, a sensing layer, a layer to interface with the sensors and a base fabric. It uses a textile called Tencel for the base, which is made from renewable wood and is biodegradable.

The active electronics in the design are made from graphene, along with a polymer called PEDOT: PSS. These conductive materials are precision inkjet-printed onto the fabric.

The research team, which included members from the universities of Exeter, Cambridge, Leeds, and Bath, tested samples of the material for continuous monitoring of heart rates. Five volunteers were connected to monitoring equipment, attached to gloves worn by the participants. Results confirmed the material can effectively and reliably measure both heart rate and temperature at the industry standard level.

Gloves with e-textile sensors monitoring heart rate – Credit: Marzia Dulal

“Achieving reliable, industry-standard monitoring with eco-friendly materials is a significant milestone,” said Dr. Shaila Afroj, an Associate Professor of Sustainable Materials from the University of Exeter and a co-author of the study. “It demonstrates that sustainability doesn’t have to come at the cost of functionality, especially in critical applications like healthcare.”

The project team then buried the e-textiles in soil to measure its biodegradable properties.

After four months, the fabric had lost 48 percent of its weight and 98 percent of its strength, suggesting relatively rapid and also effective decomposition.

Furthermore, a life cycle assessment revealed the graphene-based electrodes had up to 40 times less impact on the environment than standard electrodes.

Four strips in a variety of decomposed states, during four months of decomposition – Credit: Marzia Dulal

Marzia Dulal from UWE Bristol, the first author of the study, highlighted the environmental impact: “Our life cycle analysis shows that graphene-based e-textiles have a fraction of the environmental footprint compared to traditional electronics. This makes them a more responsible choice for industries looking to reduce their ecological impact.”

The ink-jet printing process is also a more sustainable approach for e-textile fabrications, depositing exact numbers of functional materials on textiles as needed, with almost no material waste and less use of water and energy than conventional screen printing.“These materials will become increasingly more important in our lives,” concluded Prof. Karim, who hopes to move forward with the team to design wearable garments made from SWEET, particularly in the area of early detection and prevention of heart diseases. Scientists Develop Biodegradable Smart Textile–A Big Leap Forward for Eco-Friendly Wearable Technology
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Samsung's 600-Mile-Range Batteries That Charge in 9 Minutes Ready for Production/Sale Next Year

A mock-up design of Samsung SDI’s solid-state battery – credit, Samsung, released

In late October, Samsung announced that it was preparing to take its long-anticipated solid-state batteries to market with a trilateral agreement between itself, BMW, and American battery expert Solid Power.

It was January of last year that industry outlets began to get some of the promises that all-solid-state batteries (ASSBs) developed by Samsung SDI would bring. With an energy density of 500 watt-hours per kilogram, they’re twice as dense as conventional lithium-ion batteries.

Samsung claimed they were smaller, lighter, and safer, capable of driving 600 miles, and charging with
in 9 minutes. Typically, a lithium-ion battery pack in a modern EV charges from 10% to 80% in around 45 minutes, and has a limit of around 300 miles of range.

“Samsung SDI’s preparations for mass-producing next-generation products of various form factors such as an all-solid-state battery are well underway as we are set to lead the global battery market with our unrivaled ‘super-gap’ technology,” said Samsung SDI CEO Yoon-ho Choi.

ASSB cells use solid electrolyte instead of liquid electrolyte found in a lithium-ion battery. They offer superior safety, as they aren’t flammable, and last for 20 years, or 2,000 charge-discharges, equating to 1.2 million miles.

Under the trilateral agreement, Samsung will supply ASSB cells featuring the solid electrolyte developed by Solid Power to the German automotive group BMW, which will then develop modules and packs for ASSB cells to fit into their next-generation evaluation vehicles, expected in late 2026.

Metal Tech News reported in January that ASSBs will also debut in some smaller Samsung devices during 2026, including the Galaxy Ring fitness tracker, as a way of testing the new power supplies in the real world before incorporating them into smartphones, laptops, and other devices.Samsung’s ASSBs use a silver-carbon layer as the anode and a nickel-manganese-cobalt material for the cathode. Silver is not only the most electrically conductive metal available, it’s also substantially more plentiful in the Earth’s crust than lithium. Samsung's 600-Mile-Range Batteries That Charge in 9 Minutes Ready for Production/Sale Next Year
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AI tool can simulate complex fusion plasma in seconds

(Image: UKAEA)

A team of scientists from the UK Atomic Energy Authority, the Johannes Kepler University Linz, and Emmi AI, have developed an artificial intelligence tool - named GyroSwin - which can create simulations up to 1,000 times faster than traditional computational methods.

Magnetic nuclear fusion is considered a promising technology for sustainable and emission-free energy supply. However, to achieve fusion, machines need to confine plasma at extreme temperatures using powerful magnets. Managing turbulence within the plasma is a key fusion challenge so it needs to be accurately modelled.

Plasma scientists rely on state-of-the-art numerical simulations, using five-dimensional (5D) gyrokinetics, which includes three spatial dimensions plus two additional dimensions which account for parallel and perpendicular velocity of particles within the plasma. This 5D approach requires immense supercomputing power. Traditional simulations are extremely slow and computationally expensive, significantly lengthening design and development cycles. Previously, computation methods simulated a plasma by actively calculating the complex plasma dynamics.

GyroSwin uses the latest AI methods to learn the 5D simulation dynamics and the resulting surrogate models can run in seconds, in contrast to the hours or even days for conventional simulations. It was trained on six terabytes of data. This speed allows for much faster, more agile prediction of plasma turbulence, crucial for optimising fusion machine designs.

"Designing, developing, and operating a fusion power plant will involve millions of plasma simulations," said Rob Akers, Director of Computing Programmes at UKAEA. "Reducing runtimes from hours or days to minutes or seconds - whilst preserving sufficient accuracy - will be essential for making this challenge manageable. Pioneering AI-based tools like GyroSwin therefore show great promise for being genuinely transformative around time-to-solution and cost."

Processing 5D data has never previously been tackled by an AI surrogate model, and GyroSwin outperforms other AI methods it's been compared against, UKAEA noted. This increased performance is made possible because GyroSwin preserves key physical information from a fusion plasma, including the length scale of fluctuations, and the sheared flows that can reduce turbulence - all crucial to the physical interpretability of plasma simulations.

"We love scientific challenges, and building AI models that accelerate 5D gyrokinetic simulations is definitely one of the toughest challenges out there," said Johannes Brandstetter, Professor at JKU, co-founder and Chief Scientist at Emmi. "We are very proud of how far we got in this great collaboration, but we know that we have just scratched the surface."

UKAEA will now research how GyroSwin's advanced capability can be applied to next generation power plants such as the UK's Spherical Tokamak for Energy Production (STEP), where millions of simulations will potentially be required to optimise plasma scenario designs with uncertainty quantification. As more complex physics is included for power plant conditions, simulations become even more lengthy, making faster plasma modelling essential.This GyroSwin project was part-funded by the International Computing element of the UK Government's Fusion Futures Programme. AI tool can simulate complex fusion plasma in seconds
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New Ultrasonic Imaging System Can Detect Deadly Defects in All Types of Concrete

– credit Fujikawa et al. with background / SWNS

If a physician needs to see what’s gone wrong inside a human body, it’s easy enough to order an ultrasound scan. But if the structural engineer wants to do the same in a block of concrete, his options are of limited effectiveness.

The range of materials that concrete contains, such as stone, clay, chalk, slate, iron ore, and sand, scatters normal sound waves, making clear images difficult to obtain.

Now, Japanese and American scientists have teamed up to develop a system that can identify interior defects in concrete buildings and bridges without destroying their structure.

Team members explain in a news release that their method sends sound waves into the material and captures the waves that echo back to create images of what’s inside, just like an ultrasound.

“In our approach, the ultrasonic wave is broadband, using a wide range of ultrasonic frequencies rather than operating around a single, fixed frequency,” said Professor Yoshikazu Ohara from Tohoku University in Japan.

“The receiver is capable of accepting an even broader range of frequencies. By automatically adapting the frequency to the material, our system improves the contrast between defects and background material in concrete.”

Tohoku and his colleagues joined the Los Alamos National Laboratory in New Mexico, and Texas A&M University to create the system.

A chief challenge is that it’s hard to know which frequencies of sound waves will survive traveling through concrete, as different material therein may interfere with different wavelengths.

To accommodate the uncertainty, the team used two devices: one to generate a wide range of frequencies to send into the material and another, called a vibrometer, to capture the outcoming waves.

The system, described in the journal Applied Physics Letters, can handle a wide range of frequencies, which means that even if ultrasonic waves are scattered by materials in the concrete, those that do make it through are still detected, regardless of what frequency they are.

“As the concrete filters out certain frequencies, the laser Doppler vibrometer simply captures whatever frequencies remain,” said Professor Ohara. “Unlike conventional systems, we don’t have to swap transducers or adjust the frequency beforehand. The system adapts automatically.”

The result is a high-resolution 3D image of the defect and its location in the concrete.For a repair planner or field technician, this provides ‘concrete’ information: how deep the defect is from the surface, how large it is, and how it extends in three dimensions, making it possible to plan repairs more efficiently. New Ultrasonic Imaging System Can Detect Deadly Defects in All Types of Concrete
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Nanotechnology breakthrough may boost treatment for aggressive breast cancer: Study

IANS Photo

Sydney, (IANS): Researchers in Australia are developing next-generation nanoparticles to supercharge current treatments for triple-negative breast cancer (TNBC) -- one of the most aggressive and deadly forms of the disease.

The researchers are designing innovative iron-based nanoparticles, or "nano-adjuvants," small enough to fit thousands on a single strand of hair, to strengthen the body's immune response against TNBC, according to the University of Queensland's Australian Institute for Bioengineering and Nanotechnology (AIBN) on Monday, Xinhua news agency reported.

Unlike other breast cancers, TNBC lacks the proteins targeted by some of the conventional treatments used against other cancers, making effective therapy a significant challenge, according to Prof. Yu Chengzhong from the AIBN.

"Despite the promise of immunotherapy, its effectiveness against triple-negative breast cancer is extremely limited, which is leaving too many women without options -- and that's what our research is trying to change," Yu said.

The nanoparticles are designed to enhance the activity of T-cells, the white blood cells used by the immune system to fight disease, within the tumour microenvironment, improving the immune system's ability to recognise and attack cancer cells, according to Yu.

Supported by a 3 million Australian dollar ($1.89 million) National Health and Medical Research Council grant, the five-year research project aims to bridge a critical treatment gap, and could pave the way for clinical applications, not only for TNBC but also for other hard-to-treat cancers like ovarian cancer.

With over two decades of experience in nanotechnology and nanomedicine, Yu hopes this breakthrough will transform cancer treatment by making immunotherapy more effective for patients with aggressive solid tumours."This research will push the boundaries of science to find innovative treatments that change the way we fight this cancer, offering hope for women facing devastating outcomes," said AIBN Director Alan Rowan. Nanotechnology breakthrough may boost treatment for aggressive breast cancer: Study | MorungExpress | morungexpress.com
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ICRISAT develops portable technology for testing crops' nutrition level



The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) on Thursday announced that its researchers are leading a transformation in crop testing, combining AI-driven models and pocket-size near-infrared spectroscopy (NIRS) devices.

These portable sensors allow for quick evaluation of nutrition levels in indigenous food grains right at the farmer's gate or in research fields.

ICRISAT Director General, Dr Jacqueline d'Arros Hughes, championed the integration of this disruptive technology into breeding pipelines and key points of relevant value chains.

Aligned with the UN Food and Agriculture Organisation (FAO) strategy, she foresees the tool as a catalyst for the production of nutrient-dense crops, both in breeding programmes and in farmers' fields, a crucial element in the global fight against malnutrition.

"This technology is poised to expedite the breeding of nutrient-dense crops while facilitating their integration into the value chain. Our goal with this intervention is to provide quality assurance for the distribution of nutritionally fortified crops, so that they reach those who need them most," she added.

Traditionally, assessing the nutritional quality of grains and feedstock could take a number of weeks, involving manual or partially automated processes and laboratory instruments.

In contrast, mobile NIRS devices are more cost-effective and can assess over 150 samples per day per person, ICRISAT said.

These non-destructive and robust grain quality measuring devices provide timely information on grain composition and can be used to promote quality-based payments in the market—benefiting food producers, grain processing industries, and farmers alike.

"We see the adoption of portable technology for assessing grain quality as an important step in decentralising and democratising market systems, essential to promote the consumption of nutri-cereals. This transition can facilitate quality-driven payments for farmers, while providing quality assurance to health-conscious households moving forward," noted Dr Sean Mayes, Global Research Director of the Accelerated Crop Improvement Program at ICRISAT.

In Anantapur in Andhra Pradesh, ICRISAT recommends its Girnar 4 groundnut variety to ensure premium prices for farmers and to differentiate the crop from lower-value varieties. ICRISAT's Girnar 4 and Girnar 5 groundnut varieties boast oleic acid levels of 75-80 per cent, far surpassing that of the standard variety at 40-50 per cent.

Oleic acid is a heart-healthy monounsaturated fatty acid, which holds considerable importance for the groundnut market, as it provides new end-uses for the crop. Growing consumer awareness of its advantages spurred market demand for high oleic acid content in oils and related products.

This pioneering approach, initially applied in peanut breeding, could be replicated across other crops, offering efficient and cost-effective solutions to address poor nutrition.

ICRISAT's Facility for Exploratory Research on Nutrition (FERN laboratory) is expanding its prediction models to encompass various traits and crops beyond groundnuts."We are currently focusing on developing methods to assess oil, oleic acid, linoleic acid, carotenoids, starch, moisture, and phosphorus in various cereals and legumes, such as finger millet, foxtail millet, pearl millet, sorghum, maize, wheat, chickpea, mungbean, common bean, pigeon pea, cowpea, soybean, groundnut, and mustard," said Dr Jana Kholova, Cluster Leader. Crop Physiology and Modelling, ICRISAT. ICRISAT develops portable technology for testing crops' nutrition level | MorungExpress | morungexpress.com
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Cement Supercapacitors Could Turn the Concrete Around Us into Massive Energy Storage Systems

credit – MIT Sustainable Concrete Lab

Scientists from MIT have created a conductive “nanonetwork” inside a unique concrete mixture that could enable everyday structures like walls, sidewalks, and bridges to store and release electrical energy.

It’s perhaps the most ubiquitous man-made material on Earth by weight, but every square foot of it could, with the addition of some extra materials, power the world that it has grown to cover.

Known as e c-cubed (ec3) the electron-conductive carbon concrete is made by adding an ultra-fine paracrystalline form of carbon known as carbon black, with electrolytes and carbon nanoscales.

Not a new technology, MIT reported in 2023 that 45 cubic meters of ec3, roughly the amount of concrete used in a typical basement, could power the whole home, but advancements in materials sciences and manufacturing processes has improved the efficiency by orders of magnitude.

Now, just 5 cubic meters can do the job thanks to an improved electrolyte.

“A key to the sustainability of concrete is the development of ‘multifunctional concrete,’ which integrates functionalities like this energy storage, self-healing, and carbon sequestration,” said Admir Masic, lead author of the new study and associate professor of civil and environmental engineering at MIT.

“Concrete is already the world’s most-used construction material, so why not take advantage of that scale to create other benefits?”

The improved energy density was made possible by a deeper understanding of how the nanocarbon black network inside ec3 functions and interacts with electrolytes. Using focused ion beams for the sequential removal of thin layers of the ec3 material, followed by high-resolution imaging of each slice with a scanning electron microscope.

The team across the EC³ Hub and MIT Concrete Sustainability Hub was able to reconstruct the conductive nanonetwork at the highest resolution yet. This approach allowed the team to discover that the network is essentially a fractal-like “web” that surrounds ec3 pores, which is what allows the electrolyte to infiltrate and for current to flow through the system.

“Understanding how these materials ‘assemble’ themselves at the nanoscale is key to achieving these new functionalities,” adds Masic.

Equipped with their new understanding of the nanonetwork, the team experimented with different electrolytes and their concentrations to see how they impacted energy storage density. As Damian Stefaniuk, first author and EC³ Hub research scientist, highlights, “we found that there is a wide range of electrolytes that could be viable candidates for ec3. This even includes seawater, which could make this a good material for use in coastal and marine applications, perhaps as support structures for offshore wind farms.”

At the same time, the team streamlined the way they added electrolytes to the mix. Rather than curing ec3 electrodes and then soaking them in electrolyte, they added the electrolyte directly into the mixing water. Since electrolyte penetration was no longer a limitation, the team could cast thicker electrodes that stored more energy.

The team achieved the greatest performance when they switched to organic electrolytes, especially those that combined quaternary ammonium salts — found in everyday products like disinfectants — with acetonitrile, a clear, conductive liquid often used in industry. A cubic meter of this version of ec3—about the size of a refrigerator—can store over 2 kilowatt-hours of energy. That’s about enough to power an actual refrigerator for a day.

While batteries maintain a higher energy density, ec3 can in principle be incorporated directly into a wide range of architectural elements—from slabs and walls to domes and vaults—and last as long as the structure itself.

“The Ancient Romans made great advances in concrete construction. Massive structures like the Pantheon stand to this day without reinforcement. If we keep up their spirit of combining material science with architectural vision, we could be at the brink of a new architectural revolution with multifunctional concretes like ec3,” proposes Masic.

Taking inspiration from Roman architecture, the team built a miniature ec3 arch to show how structural form and energy storage can work together. Operating at 9 volts, the arch supported its own weight and additional load while powering an LED light.

The latest developments in ec³ technology bring it a step closer to real-world scalability. It’s already been used to heat sidewalk slabs in Sapporo, Japan, due to its thermally conductive properties, representing a potential alternative to salting.

“What excites us most is that we’ve taken a material as ancient as concrete and shown that it can do something entirely new,” says James Weaver, a co-author on the paper who is an associate professor of design technology and materials science and engineering at Cornell University, as well as a former EC³ Hub researcher. “By combining modern nanoscience with an ancient building block of civilization, we’re opening a door to infrastructure that doesn’t just support our lives, it powers them.” Cement Supercapacitors Could Turn the Concrete Around Us into Massive Energy Storage Systems
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