For decades, tritium has remained the one radioactive contaminant that nuclear engineers could not efficiently remove from wastewater. Unlike other radioactive elements, tritium becomes part of the water molecule itself, making it nearly impossible to separate using conventional treatment methods. Instead, facilities have relied on energy-intensive distillation or, in some cases, the controlled dilution and release of treated water that still contains tritium within regulatory safety limits.

Now, researchers in China report a possible solution. In a study published in Environmental Science & Technology, they developed a metal-organic framework (MOF)-coated material that significantly improves tritium separation during distillation. This study builds on work that won the Nobel Prize in Chemistry last year. If the technology performs similarly outside the laboratory, it could make treating radioactive wastewater far more efficient.

The problem Hidden Inside a Water Molecule

Most radioactive contaminants can be removed using filters or chemical treatment. Tritium is different because it replaces one of the hydrogen atoms in the water molecule itself. That means the contaminated water looks and behaves almost exactly like clean water.

For decades, the only practical way to separate the two has been distillation. Since tritiated water boils at a slightly different temperature, the process eventually works. But the difference is so tiny that it requires enormous distillation towers and a great deal of energy.

The difficulty came into public focus in 2023 when Japan began releasing treated wastewater from the Fukushima Daiichi nuclear power plant into the Pacific Ocean. Although most radioactive substances had been removed, tritium remained because no practical technology existed to separate it at such a large scale. Instead, the water was diluted before being released under international safety standards.

A Sponge at the Molecular Level

Inside every distillation tower are materials called packings, which create surfaces where water vapour and liquid interact. Traditionally, these packings simply help the process along. The researchers turned them into active participants.

They coated a stainless-steel mesh with a metal-organic framework (MOF) called NH₂-MIL-101(Cr). MOFs are often described as molecular sponges because they contain countless microscopic pores packed into a tiny space. But this sponge does more than hold water. Its chemical structure encourages tritium atoms to exchange places with ordinary hydrogen atoms, making them easier to separate during distillation.

In laboratory tests, the material achieved a separation efficiency of 42.5 theoretical plates per metre, the highest reported for this type of distillation system. The team estimates that a 10-metre distillation column fitted with the new material could outperform the best previously reported packing by 134 times. Compared with the commercial packing materials used today, its overall separation performance could be up to one million times greater under similar industrial conditions.

Those figures still need to be validated outside the laboratory, but they suggest that future treatment systems may no longer need the massive, energy-hungry towers used today.

India has become the world’s fourth-largest market for liquefied natural gas (LNG) regasification capacity after expanding its import infrastructure in 2025, according to the International Gas Union’s (IGU) World LNG Report 2026.

The report says India’s total LNG regasification capacity reached 52.5 million tonnes per annum (mtpa) by the end of 2025, after adding 7.1 mtpa during the year. The increase helped India overtake Spain in global rankings.

The additional capacity came from two projects: the 5 mtpa Chhara LNG terminal in Gujarat and the completion of a breakwater at the Dabhol LNG terminal in Maharashtra, which added 2.1 mtpa by allowing the terminal to operate throughout the year.

LNG is natural gas that is cooled into a liquid so it can be transported by ship. Once it reaches India, it is converted back into gas at regasification terminals and supplied to industries, fertiliser plants, refineries and city gas networks.

Supporting India’s growing energy needs

India’s demand for energy is rising as industries expand and cities grow. Since domestic natural gas production is not enough to meet demand, the country imports a large share of its gas as LNG.

More regasification capacity means India can import larger volumes of LNG from different countries, improving energy security and reducing the risk of supply disruptions. It also gives industries access to a more reliable fuel supply.

The IGU report notes that global LNG trade reached a record 436.98 million tonnes in 2025, with Asia remaining the largest market for LNG.

India has also been working towards increasing the share of natural gas in its energy mix from around 6% to 15%. The government sees natural gas as a fuel that can help reduce dependence on coal while supporting sectors where cleaner alternatives are still developing.

A transition fuel with challenges

Although natural gas burns cleaner than coal, it is still a fossil fuel. Many experts describe it as a transition fuel because it can help lower emissions in the short term while renewable energy continues to expand.

However, natural gas also has environmental concerns. Methane, the main component of natural gas, is a powerful greenhouse gas, and leaks during production and transport can reduce its climate benefits.

India is therefore following a dual approach: expanding gas infrastructure to meet current energy needs while continuing to invest in solar, wind, green hydrogen and battery storage to achieve its long-term climate goals.

The IGU report shows that India’s latest investments are aimed at balancing energy security, economic growth and the transition to cleaner energy, even as the country continues to expand its renewable energy capacity.

Data center energy use could become cheaper and more efficient if AI facilities shift electricity consumption to off-peak hours, according to a new MIT study that highlights both economic and environmental trade-offs.

As artificial intelligence fuels a rapid expansion of data centres around the world, concerns are growing over how much electricity these facilities will consume—and whether power grids can keep up.

A new study by researchers at the Massachusetts Institute of Technology (MIT) suggests there may be a way to ease the pressure. Rather than consuming electricity around the clock at fixed rates, data centres could shift a significant portion of their energy use to off-peak hours, lowering electricity costs while making better use of existing grid capacity.

The findings, published in the journal iScience, indicate that if data centres adopt more flexible electricity consumption patterns, average power system costs could fall by as much as 5 per cent in Texas, 4 per cent in the Mid-Atlantic region and 2 per cent across western U.S. states.

Data Center Energy Use: Flexible Data Centers Could Reduce Energy Costs

The researchers modelled how expanding data centres would affect electricity grids in three regions that are expected to host about 82 per cent of U.S. data centres by 2030: Texas, the Mid-Atlantic and the Western Interconnect, which covers 11 western states.

Their simulations found that shifting at least one-fifth of a data centre’s electricity use away from peak-demand periods could reduce overall system costs. In some cases, as much as half of a facility’s energy demand would need to be moved to quieter periods of the day.

“The key with data centers is: How can we add them to the network without adding a lot to our peak usage?” said Christopher Knittel, economist at the MIT Sloan School of Management and co-author of the study, in a media statement.

“One way for data centers to do that — to add to average usage but not the peak usage — is if they provide some grid flexibility during those high-cost periods. And that’s what we’ve been interested in understanding.”

The researchers note that most data centres already have some operational flexibility because they typically run below full capacity. Instead of carrying out energy-intensive computing tasks during periods of peak electricity demand, many could shift those operations to midday, when solar power generation is often highest and overall demand is lower.

AI Growth Is Putting Pressure on Power Grids

The rapid expansion of AI has dramatically increased demand for computing infrastructure, raising questions about whether electricity grids can support hundreds of new data centres without driving up costs or emissions.

The study suggests that adding more data centres does not automatically translate into higher electricity prices. Because much of the cost of running a power grid comes from fixed infrastructure such as transmission lines, increasing electricity use can spread those costs across a larger customer base—provided peak demand does not rise at the same pace.

“It’s really just math,” Knittel said.

“There are two dimensions that data centers have to make decisions about. One is how much of their load in any one time period is flexible. And two, how many hours, plus or minus, can they move that computation?”

Flexible Data Centers May Have Different Climate Impacts

The environmental picture is more complex.

The researchers found that the projected growth in data centres by 2030 could significantly increase carbon dioxide emissions if electricity demand is met through fossil fuels. Compared with a scenario without new data centres, emissions could rise by 58 per cent in Texas, 20 per cent in the Mid-Atlantic region and 24 per cent in the western United States.

However, the impact varies depending on how regional electricity systems generate power.

In Texas, where wind energy accounts for a large share of electricity generation, shifting data-centre operations to times when renewable energy is abundant could reduce carbon emissions by as much as 40 per cent.

In contrast, the Mid-Atlantic region presents a different picture. There, flexible electricity use could unintentionally keep coal-fired power plants operating for longer periods.

“When data centers provide some flexibility in that latter scenario, the data centers actually move hours to when sun and wind energy production is slowing, and that allows a coal plant to stay on,” Knittel observed. “So it doesn’t necessarily attract more renewable investment. It attracts more coal investment.”

Policy Could Shape the Future of AI Infrastructure

The researchers argue that flexibility alone is unlikely to become common unless governments and grid operators create incentives for companies.

“That’s why we have policy,” Knittel said.

One option would be to allow data centres that agree to flexible electricity use to connect to the grid sooner.

“One big concern about these data centers now is how long it takes for them to connect to the grid,” Knittel said. “One way to provide flexibility now is what’s called ‘connect and manage,’ which is, connecting you faster to the grid if you agree to provide flexibility. Tech firms would take that deal. They would rather connect a year earlier, and throttle down computation a few hours a day, than to have to wait. We do this with power plants too.”

He added that industry-wide rules would help address competitive concerns.

“Tech companies say they won’t provide flexibility alone. But if everyone in the industry has to, it’s okay.”

Balancing AI Growth With Sustainable Energy

As governments and technology companies race to build the computing infrastructure needed for the AI era, the study suggests that when data centres consume electricity may prove to be as important as how much they consume.

The researchers conclude that smarter scheduling of electricity demand, combined with supportive public policy, could lower power system costs while reducing pressure on electricity grids. At the same time, the study highlights that the environmental benefits of flexible energy use will depend on how individual regions generate electricity, reinforcing the need for location-specific energy planning.