A new type of fuel cell developed by MIT researchers could represent a pivotal breakthrough in the race to decarbonize heavy transportation. Designed around liquid sodium metal, the innovation offers more than triple the energy density of today’s lithium-ion batteries — potentially clearing a major hurdle for electric-powered aviation, rail, and maritime travel.

Unlike traditional batteries that require time-consuming recharging, this system operates like a fuel cell that can be refueled quickly using liquid sodium — a cheap, abundant substance derived from salt. The technology, which uses air as a reactant and a solid ceramic electrolyte to facilitate the reaction, was tested in lab prototypes and demonstrated energy densities exceeding 1,500 watt-hours per kilogram — a level that could enable regional electric flight and clean shipping.

“We expect people to think that this is a totally crazy idea,” said Professor Yet-Ming Chiang, lead author and Kyocera Professor of Ceramics, in a media statement. “If they didn’t, I’d be a bit disappointed because if people don’t think something is totally crazy at first, it probably isn’t going to be that revolutionary.”

Chiang explained that current lithium-ion batteries top out at around 300 watt-hours per kilogram — far short of the 1,000 watt-hours needed for electric aircraft to become viable at scale. The new sodium-based cell meets that benchmark, which could enable 80% of domestic flights and drastically reduce aviation’s carbon footprint.

Moreover, the sodium-fueled system offers environmental benefits beyond zero emissions. Its chemical byproduct, sodium oxide, reacts spontaneously in the atmosphere to capture carbon dioxide and convert it into sodium bicarbonate — better known as baking soda — which may help counteract ocean acidification if it ends up in marine environments.

“There’s this natural cascade of reactions that happens when you start with sodium metal,” Chiang said. “It’s all spontaneous. We don’t have to do anything to make it happen, we just have to fly the airplane.”

The team has already created two functioning lab-scale prototypes: one vertical and one horizontal model. In both, sodium gradually reacts with oxygen from air to generate electricity, and a moist air stream improves the process by allowing liquid byproducts to be expelled more easily.

Karen Sugano, one of the MIT doctoral students on the project, noted, “The key was that we can form this liquid discharge product and remove it easily, as opposed to the solid discharge that would form in dry conditions,” she said in a media statement.

The researchers have founded a startup, Propel Aero, housed in MIT’s startup incubator The Engine, to scale the technology. Their first commercial goal: a brick-sized fuel cell capable of powering a large agricultural drone — expected to be ready within a year.

Chiang emphasized the economic and safety benefits of using sodium, which melts just below 100°C and was once mass-produced in the U.S. for leaded gasoline production. “It reminds us that sodium metal was once produced at large scale and safely handled and distributed around the U.S.,” he said.

Critically, the fuel cell design also avoids many safety concerns of high-energy batteries by physically separating the fuel and oxidizer. “If you’re pushing for really, really high energy density, you’d rather have a fuel cell than a battery for safety reasons,” Chiang said.

By reviving and reimagining sodium-metal chemistry in a practical, scalable form, the MIT team may have lit the path toward clean, electrified transportation systems — from the skies above to the oceans below.

Researchers from MIT, Harvard University, and the Broad Institute have unveiled a groundbreaking artificial intelligence tool that can accurately predict where proteins are located within any human cell, even if both the protein and cell line have never been studied before. The method – Prediction of Unseen Proteins’ Subcellular Localization (or PUPS) – marks a major advancement in biological research and could significantly streamline disease diagnosis and drug discovery.

Protein localization—the precise location of a protein within a cell—is key to understanding its function. Misplaced proteins are known to contribute to diseases like Alzheimer’s, cystic fibrosis, and cancer. However, identifying protein locations manually is expensive and slow, particularly given the vast number of proteins in a single cell.

The new technique leverages a protein language model and a sophisticated computer vision system. It produces a detailed image that highlights where the protein is likely to be located at the single-cell level, offering far more precise insights than many existing models, which average results across all cells of a given type.

“You could do these protein-localization experiments on a computer without having to touch any lab bench, hopefully saving yourself months of effort. While you would still need to verify the prediction, this technique could act like an initial screening of what to test for experimentally,” said Yitong Tseo, a graduate student in MIT’s Computational and Systems Biology program and co-lead author of the study, in a media statement.

Tseo’s co-lead author, Xinyi Zhang, emphasized the model’s ability to generalize: “Most other methods usually require you to have a stain of the protein first, so you’ve already seen it in your training data. Our approach is unique in that it can generalize across proteins and cell lines at the same time,” she said in a media statement.

PUPS was validated through laboratory experiments and shown to outperform baseline AI methods in predicting protein locations with greater accuracy. The tool is also capable of accounting for the effects of protein mutations and cellular stress—key factors in disease progression.

Published in Nature Methods, the research was led by senior authors Fei Chen of Harvard and the Broad Institute, and Caroline Uhler, the Andrew and Erna Viterbi Professor at MIT. Future goals include enabling PUPS to analyze protein interactions and make predictions in live human tissue rather than cultured cells.

MIT researchers have unveiled an insect-scale robot capable of hopping across treacherous terrain—offering a new mobility solution for disaster response scenarios like collapsed buildings after earthquakes.

Unlike traditional crawling robots that struggle with tall obstacles or aerial robots that quickly drain power, this thumb-sized machine combines both approaches. By using a spring-loaded leg and four flapping-wing modules, the robot can leap over debris and uneven ground while using 60 percent less energy than a flying robot.

“Being able to put batteries, circuits, and sensors on board has become much more feasible with a hopping robot than a flying one. Our hope is that one day this robot could go out of the lab and be useful in real-world scenarios,” says Yi-Hsuan (Nemo) Hsiao, an MIT graduate student and co-lead author of a new paper published today in Science Advances.

The hopping mechanism allows the robot to jump nearly 20 centimeters—four times its height—at speeds up to 30 centimeters per second. It easily navigates ice, wet surfaces, and even dynamic environments, including hopping onto a hovering drone without damage.

Co-led by researchers from MIT and the City University of Hong Kong, the team engineered the robot with an elastic compression-spring leg and soft actuator-powered wings. These wings not only stabilize the robot mid-air but also compensate for any energy lost during impact with the ground.

“If you have an ideal spring, your robot can just hop along without losing any energy. But since our spring is not quite ideal, we use the flapping modules to compensate for the small amount of energy it loses when it makes contact with the ground,” Hsiao explains.

Its robust control system determines orientation and takeoff velocity based on real-time sensing data. The robot’s agility and light weight allow it to survive harsh impacts and perform acrobatic flips.

“We have been using the same robot for this entire series of experiments, and we never needed to stop and fix it,” Hsiao adds.

The robot has already shown promise on various surfaces—grass, ice, soil, wet glass—and can adapt its jump depending on the terrain. According to Hsiao, “The robot doesn’t really care about the angle of the surface it is landing on. As long as it doesn’t slip when it strikes the ground, it will be fine.”

Future developments aim to enhance autonomy by equipping the robot with onboard batteries and sensors, potentially enabling it to assist in search-and-rescue missions beyond the lab.