Data centres have existed for decades. So why are they so controversial now?

 

The Conversation, CC BY-SA

Johanna Lim, University of Sydney

Until recently, data centres attracted relatively little public attention. They were largely treated as invisible pieces of digital infrastructure: essential but rarely discussed outside technical and industry circles.

But over the past 12 months across Australia, data centres have become the subject of intense political debate, community opposition, planning disputes and parliamentary inquiries.

Questions are being raised about how much electricity and water they use, where they should be built, who should pay for the infrastructure needed to support them, and whether Australia benefits from their continued expansion.

These questions are feeding into government policy. Following Prime Minister Anthony Albanese’s speech at the University of Sydney in July, a National Cabinet meeting in August reaffirmed plans to legislate nationally consistent mandatory standards for large data centres by early next year. These will include requirements around their energy, water and land use.

So how did a piece of digital infrastructure that once attracted relatively little public attention become such a prominent policy issue? Data centres themselves are not new. What has changed is their scale, purpose and the resources required to support their growth.

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Data centres have existed for decades. But something has changed, and this essential infrastructure is now at the centre of a major policy debate.

This article is part of The Conversation’s series on data centres – what they are, why we need them, and why they’re suddenly so controversial.

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The evolution of data centres

Data centres are specialised physical facilities that house servers, networking equipment and data storage systems. They are foundational infrastructure for the modern digital economy, supporting a wide range of services such as streaming, social media, banking, emergency response systems, and artificial intelligence (AI).

The origins of data centres can be traced to the 1940s, when early computers were so large they needed dedicated spaces to house them. As computers became smaller, more powerful and more accessible, governments and businesses increasingly adopted their own IT infrastructure. They often operated on-premises server rooms to manage email, file storage and other internal systems.

The internet then drove a shift towards larger co-location data centres in the 1990s, where multiple customers could rent space for their servers in a single shared facility.

Then came cloud computing. This provided customers with on-demand access to computing resources over the internet, and further accelerated the growth of data centres. In 2006, Google opened its first hyperscale data centre. Amazon Web Services also launched its first cloud computing services in the same year. Cloud service providers subsequently built increasingly large facilities to meet growing demand for these services.

What was once a room or floor serving a single organisation evolved into massive dedicated facilities – often called hyperscale data centres – capable of supporting millions of users. Today, the scale of a data centre is often measured by its power capacity, in megawatts or gigawatts. This reflects how much electricity the facility can draw at any one time.

Australia’s data centre boom

Australia’s own data centre market reflects this shift in scale.

Australia currently has over 160 operational data centres, with most located in New South Wales and Victoria. There are at least another 90 facilities in the development pipeline.

The data centres now being proposed are also considerably larger than many existing data centres.

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For example, the proposed 1.2 gigawatt Mamre Road Data Centre in Sydney would cover an area equivalent to the size of 52 rugby fields.

If built to its maximum capacity, it would become Australia’s largest single electricity user.

Why AI is driving bigger data centres

Hyperscale data centres typically contain at least 5,000 servers, occupy at least 10,000 square feet of physical space, and can draw over 100 megawatts of power. That’s enough to meet the annual electricity needs of more than 50,000 households.

In 2025, hyperscale operators accounted for 48% of global data centre capacity.

Cloud computing and the growth of everyday digital activity initially drove the expansion of these large, centralised facilities. But since OpenAI launched ChatGPT in late 2022, AI has rapidly accelerated this growth.

AI workloads are far more computationally intensive than traditional digital services. They are expected to account for approximately 70% of data centre demand by 2030.

Training advanced AI models requires dense arrangements of specialised chips working simultaneously to process large volumes of data. This can run continuously for weeks or months.

Once trained, AI models also require computing power to respond to users. This process is known as inference. While a single interaction requires considerably less computing power than training a model, that demand adds up across millions of users.

Inference represents an increasing share of AI’s energy demands. This will continue to increase alongside AI adoption.

A 2025 survey found 88% of organisations reported regularly using AI in at least one business function – an increase from 78% a year earlier.

The shift toward large-scale data centres is also about efficiency.

Larger facilities tend to be more efficient. They benefit from economies of scale and advances in facility design, such as optimising power distribution and using higher-performance chips and servers.

In Australia, on-premises servers are estimated to consume over seven times more electricity to perform the same computation as hyperscale and co-location data centres.

But while hyperscale data centres can use energy more efficiently for the computing they perform, the sheer scale and growth of demand mean their overall electricity consumption is still significant.

Data centres accounted for around 3% of electricity supplied through Australia’s main grid in 2025–26. This share is projected to reach 13% by 2035–36.

What comes next for Australia?

The growth of Australia’s data centre market is unlikely to slow anytime soon.

Australia remains a competitive destination for data centre investment, with strong government support, continued interest from major technology companies and an estimated A$150 billion in data centre buildouts by 2030.

But community opposition is emerging as a significant risk for new developments. This opposition is, in part, because of the land, power and water data centres consume.

But it’s also because there is uncertainty over whether the significant investment in AI infrastructure will truly generate sufficient economic returns – and who will benefit from those returns.

The future growth of Australia’s data centre sector may therefore depend less on whether there is demand or capital to build them, and more on where they can be built, who bears the costs, and whether communities benefit from hosting them.

Johanna Lim, Research Associate, Strategic Technologies, University of Sydney

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

Read More........→September 16, 2026

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 Šafránek 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

Read More........→September 16, 2026

The evolution of science and technology: How humanity evolved with it?

Photo Courtesy: Image by Syed Ali Mehdi from Pixabay | For representational purpose only

Saanvi Singh

Was it a moment or a day or perhaps a bright morning once upon a time, or a fine evening in the past? How do we trace the origins of science and technology? It is an ongoing journey that started even before the beginning of our own species and is seen to be constantly developing and becoming more efficient over time.

Do we start with the prehistoric and early human era? Somewhat 2 million years ago, when people used stone tools for survival. The era when clothing was invented, and people could then live in cool climates. Then came the ancient civilizations, where humanity explored through the ideas of betterment in agriculture and medicine. The discovery of metallurgy led to stronger and more versatile tools and weapons. Post this came the classical period of history of science and technology.

Famous scientists like Archimedes proposed his principle of buoyancy. Europe and the Middle East saw watermills and windmills being used for power. The 13th century brought with it the Late Medieval Period, where mechanical clocks regulated time, and printing presses helped in mass communication. Modern science instruments like the microscope and barometer were invented in the 1600s – 1700s. Then in the 1750s, the world saw an industrial revolution.

The period before the Industrial Revolution was all about survival, discovery, and laid the base for the foundations of scientific thought. The transformation of the traditional approach and the adoption of more efficient solutions helped in several ways. The introduction of fire, somewhat 1.5 million years ago, led to the betterment of necessities of life like cooking, protection. The introduction of the concept of wheel revolutionized transportation, made it easier, helped in the easy flow of goods and people, and helped new industries such as pottery, spinning, and weaving flourish. The innovation of the printing press enhanced the ways knowledge was spread back then, prepared people and society for the large-scale exchange of knowledge.

In Greek mythology, the Titan Prometheus, God of fire, is often portrayed as a champion of humanity, considering fire a divine gift to mankind, which symbolized knowledge and progress. At the same time, another god, named Zeus in Greek Mythology, punished him, fearing that fire would make humans rebellious. Fire was seen as a double-edged sword; on one hand, it improved the way of living, but at the same time, it was capable of uncontrollable destruction. Martin Luther praised the printing press as “the latest and greatest gift, by which God intends the work of true religion to be known throughout the world and translated into every tongue". He called it God’s highest and most extreme act of grace. But, at the same time, a 20th-century thinker, Marshall McLuhan, thought that the press gave way to propaganda, censorship, and misinformation.

The early 18th and 19th centuries saw the rise of the Industrial Revolution with the introduction of machines and mass production that brought major changes in people’s lives. This period observed a shift from traditional economic practices and became more centered on mass production and the machine system. Mechanization, implying the invention of new machines like the steam engine and power looms, resulted in a faster pace at which work was being done than before. Industries like iron and steel and textiles saw major hikes in their production rates with the introduction of these machines into the market.

For instance, with the adoption of machinery in the iron and steel industry, coal production in the UK boosted from 100 million tons to 265 million tons during 1870 – 1910. With the onset of the Industrial Revolution, some were sparked with happiness, while others had deep concerns about the situation.

People like Dadabhai Naoroji were in favor of the usage of modern machinery and technology; however, they had concerns about the ‘drain of wealth’ to Britain during the colonization period that affected India’s economic growth. Jawaharlal Nehru believed that industrialization was an essential factor that contributed to the building of an independent nation and a beneficial economy. However, people like Rabindranath Tagore laid his belief in the fact that true progress can be achieved with nature, culture, and rural life, not with modernization techniques. People like R.C Dutt and Bal Gangadhar Tilak believed that industrialization was exploitative for India as it impacted the Indian economy under colonial control and turned India into a raw material supplier.

Post this, the 20th and 21st centuries brought with them the scientific revolutions and a digital era.

The early 1900s saw Max Planck, a German Physicist, come up with his Quantum Theory, followed by Albert Einstein, the renowned scientist, bringing up the theory of relativity. The mid-1900s saw advances in medicine with the mass production of vaccines, and the invention of transistors, computers sparked the field of electronics and computing. The late 1900s brought with it the era of the internet. From 2000 onwards, the world saw a rapid rise in technological advancements across fields. People from diverse backgrounds, fell under the huge umbrella of science and technology.

The journey of mobile communication from 1G to 5G expanded global communication, enhancing speed and efficiency. With the introduction of platforms like Linkedin in 2003, Facebook in 2004, YouTube in 2005, and Twitter in 2006, the world was taken over by this hike in social media services and impacted people across the globe.

Anand Mahindra, Chairman of the Mahindra Group, sees social media as “an amazing business tool”. In his words, “I get feedback from 11 million people.” Famous actress Priyanka Chopra Jonas believes that social media is a way to connect and support. At the same time, Lily Allen, a Pop Star, despite building her career through the social networking site Myspace where her vocal recordings got published, confessed that the internet felt “damaging on mental health, actual health and our relationships.”

Followed by this, multiple developments were observed in fascinating areas like space and astronomy, physics and energy and then came the masters of all, “Computing and Artificial Intelligence”. It changed the way the world operated, it changed the way humans processed material. The concepts, for example, machine learning, artificial intelligence, robotics, not only made the digital world turn into a reality but also made it smarter and more intelligent than humankind.

Among some people, it changed their lifestyles, brought comfort in daily lives, improved health, education, and business. However, among others, it turned into a nightmare and made people face challenges like loss of jobs in a flash, privacy issues, and other ethical concerns.

At a developer conference in Bengaluru, Microsoft CEO Satya Nadella advocated for the utilization of AI tools to empower millions of Indian developers across the nation. Nicolas Cage, a renowned Hollywood actor, addressing his own field, asserted that AI could assist filmmakers in visual effects, cost reduction, and the better portrayal of ideas. However, he simultaneously expressed his concerns regarding the excessive dependency on AI in films that threatened the idea of emotional authenticity.

Kamal Haasan, a famous film star, in 2025 said, “I like AI, but not sure if AI will like me.” He drew attention to the plight of deceased musicians and emphasized his preference for authentic human expression over digital replicas of human art and creativity. Similarly, another celebrated actor, Tom Cruise, highlighted AI’s potential to undermine originality and emotional authenticity.

The evolution of science and technology reflects humanity’s constant search to survive, adapt, and progress—from stone tools and fire to telescopes and electricity. Each breakthrough reshaped societies, improved lifestyle, and expanded human imagination far beyond. Today, artificial intelligence is writing destinies much like past revolutions did, influencing jobs, education, health, and connections, while continuing to guide humans into an ever-unfolding future. This era of AI is never ending and will continue to bring inevitable changes and introduce even smarter and newer ideologies to the world. Saanvi Singh is a first year student at Plaksha University The evolution of science and technology: How humanity evolved with it? | MorungExpress | morungexpress.com

Read More........→September 10, 2026

Drones are Saving Hundreds of Fawns From Mower Deaths in Germany (WATCH)

Credit: Erika Fletcher

A Bavarian wildlife rescue organization is using thermal imaging drones to locate and rescue vulnerable fawns hidden in tall meadow grass ahead of the annual mowing season.

Every spring, thousands of fawns are killed by mowing machinery across Germany. Baby deer instinctively freeze when threatened, a natural defense mechanism that protects them from predators but leaves them vulnerable to farm equipment.

Traditionally, this work was done on foot—with volunteers walking through the meadows in lines—an extremely labor-intensive task for this volunteer rescue group founded in 2020.

Now, with the thermal imaging of DJI drones, the rescue group, Rehkitz-Rettung Mangfalltal, can locate these hidden animals more quickly and efficiently before mowing begins, especially with the drone’s AI technology features that help pilots reliably spot fawns, baby hares, and ground-nesting birds.

Since integrating drone technology into their workflow, the group’s annual count of rescued fawns has ballooned from 10-15 in previous years to between 300 and 350 fawns today.

In a case study, operators used the Matrice 4 Series’ precision positioning controls to spot heat signatures in vegetation, verify them visually, and direct ground teams to the exact location. (See the video below…)

Whenever the thermal camera detects a heat source, its location is pinned with centimeter-level accuracy using the drone’s GPS and shared instantly with the ground team.

The German case study also provides a video step-by-step guide on the rescue process, including drone operations from an altitude of 80–100 meters and how to handle fawns once they are found.Thanks to the Rehkitz-Rettung Mangfalltal volunteers and drone pilots, farmers are able to happily proceed with mowing—confident that fields have been safely cleared of hidden animals. WATCH the Reuters news video below… Drones are Saving Hundreds of Fawns From Mower Deaths in Germany (WATCH)

Read More........→August 08, 2026

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

Read More........→June 19, 2026

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.)

Read More........→June 17, 2026

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.

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.

Read More........→June 11, 2026

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.

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.

Read More........→June 05, 2026

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

Read More........→April 23, 2026

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

Read More........→April 12, 2026

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.

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.

Read More........→April 10, 2026

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

Read More........→March 11, 2026

AI could help us more accurately screen for breast cancer – new research

Sasun Bughdaryan/Unsplash Carolyn Nickson, University of Sydney; The University of Melbourne and Bruce Mann, The University of Melbourne

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.

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.

Read More........→March 10, 2026

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:

Read More........→February 26, 2026

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

Read More........→February 19, 2026