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AI designs working molecular scissors that recognize and cut selected protein targets

Proteases are naturally occurring enzymes that break down proteins into peptides and even single amino acids. They are useful in medicine and industrial processes, where they clean tissue, digest waste and help in the manufacture of everyday products. Now scientists have used artificial intelligence to design new versions from scratch.

AI tools have already successfully generated new protein shapes and structures, but using AI to create functional proteases is a significant leap forward. That’s because the resulting enzyme has to both recognize a chosen protein sequence and cut it efficiently.

To see if it could be done, David Baker at the University of Washington and his colleagues combined several advanced artificial intelligence tools to create both cysteine and zinc proteases.

New 3D model reveals how shadows reshape chemistry in stellar nurseries

How do young stars reshape the clouds from which they are born? A new high-resolution 3D model developed by an international team led by Dr Brandt Gaches from the University of Duisburg-Essen shows how the uneven structure of stellar nurseries creates shadows that alter their chemistry and influence the infrared emission observed by the James Webb Space Telescope. The model has now been published in Astronomy & Astrophysics.

Stars are born inside vast clouds of cold gas and dust. As massive young stars begin to shine, their intense ultraviolet light heats the gas, breaks apart molecules and triggers a cascade of chemical reactions in the clouds’ outer layers. These boundary zones are known as photodissociation, or photon-dominated, regions. Their light provides astronomers with important clues about how stars form and how gas is recycled to create future generations of stars and planets both within our own galaxy and in investigations of star formation across cosmological history.

“The Orion Bar is an ideal natural laboratory for studying these processes,” says Dr. Brandt Gaches. Located about 1,350 light-years from Earth, it can be observed in exceptional detail. “We see it nearly edge-on, so its different chemical layers are particularly easy to distinguish. That makes it a benchmark for testing models of photon-dominated regions,” adds Gaches, who leads an Emmy Noether Research Group on molecular astrophysics at the University of Duisburg-Essen (UDE).

Infrared light overcomes mirror coating obstacle in gravitational wave detector upgrades

Researchers have developed and tested a new locking method for gravitational wave detectors that will advance the discovery of distant black holes and neutron stars colliding.

Researchers from ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) nodes at The University of Western Australia, the Australian National University and the University of Adelaide co-authored the study published in Physical Review D.

Lead author Dr. Jian Liu, from UWA’s School of Physics, Mathematics and Computing, said gravitational wave detectors, such as LIGO, detected ripples in space-time created by colliding black holes by measuring changes in distance 1,000 times smaller than the width of a proton.

Sunlight gives biodiesel byproduct a second life as hydrogen and valuable chemicals

Australian researchers and international collaborators have demonstrated a solar-driven approach to convert glycerol, a low-value byproduct of biodiesel production, into hydrogen and higher-value chemicals. Using advanced techniques at the Australian Synchrotron, they revealed how the catalyst changed while it was working.

The study, led by researchers at the University of New South Wales, investigated a process known as photoreforming, in which light energy is used to drive chemical reactions to simultaneously produce hydrogen and transform organic feedstocks into useful products. The research was published in Applied Catalysis B: Environment and Energy.

Glycerol is produced in large quantities by the growing biodiesel industry, with approximately 100 kilograms (220 pounds) generated for every ton of biodiesel. Crude glycerol can be worth as little as US$0.11 per kilogram. Chemicals can be produced from it, such as glyceraldehyde and dihydroxyacetone, which have applications in the chemical and pharmaceutical industries and are valued at approximately US$75 and US$150 per kilogram, respectively.

New high-frequency method boosts 2D material readout for next-gen quantum computers

Quantum computers represent a next step in the fast-paced evolution of technology. Using quantum bits (qubits), they have the potential to run certain calculations exponentially faster than conventional computers. However, developing and fine-tuning quantum computers requires an enormous number of repetitive tests. To accelerate quantum technology development, we need a method that can read quantum states at ultrafast speeds.

A research team from Tohoku University and the National Institute for Materials Science (NIMS) has developed a method that enables ultrasensitive, high-speed charge detection in 2D-material-based quantum devices necessary to accelerate this development. It brings us one step closer to the realization of next-generation quantum computers, which could eventually revolutionize industries like medicine, logistics and cybersecurity.

A highway instead of a racetrack: Strong coupling of light and sound in an optical fiber

For the first time, scientists have achieved strong coupling between light and long-lived acoustic vibrations in an optical fiber. Optical fibers are used in both classical telecommunications and quantum communication and could serve not only as connections between computing nodes but also as quantum processors themselves in the future. The results, published in Nature Physics, pave the way for new technologies in quantum signal processing.

Mechanical and acoustic vibrations can be used to convert signals across various frequency ranges, from optical frequencies (terahertz) to microwaves (gigahertz) and even lower frequencies (megahertz or kilohertz). For instance, this capability is essential to connect multiple quantum computers operating at gigahertz frequencies via optical links. Furthermore, acoustic waves propagate at speeds significantly lower than the speed of light. So, they provide a medium capable of transporting slowly moving information—which is of great interest for data storage and the temporary buffering of information.

However, to utilize one of these processing capabilities for quantum information via mechanical vibrations, one prerequisite is needed: the strong coupling regime. This regime ensures that quantum information is exchanged before it is lost due to losses and decoherence. Decoherence describes the state in which the waves no longer oscillate in unison. In the strong coupling regime, quantum information can be processed more quickly—faster than the rate at which noise enters the system—without losing quantum properties.

World-record intensity in attosecond hard-X-ray pulses could unlock closer study of electrons in atoms and molecules

Researchers used the European XFEL to create X-ray flashes that were not only extremely short but also reached record intensity for this type of pulse. The researchers focused the X-rays to an area roughly 100,000 times smaller than the cross section of a typical human hair. This concentrated the X-ray light into a tiny but extremely powerful spot. The method could enable detailed studies of how electrons behave in atoms and molecules and, in the long term, could even allow researchers to control electrons during chemical reactions. The team has now published the results of the experiment, carried out in April 2026, in the journal Optica.

“This is a world record in intensity and fluence for a hard-X-ray attosecond pulse,” says Ichiro Inoue from the University of Tokyo, first author of the publication. Hard X-rays are light waves with a particularly short wavelength. Fluence measures how much energy this light delivers to a certain area. Intensity also takes into account how quickly that energy arrives.

New drug-delivery method offers promise in fight against neurodegenerative diseases

For patients battling neurodegenerative diseases like ALS, Parkinson’s, Alzheimer’s and other dementias, delivering disease-fighting antibody drugs directly to the brain has proven to be a difficult task. Our bodies set up tight walls to prevent infections from spreading to the brain, where they often become fatal.

Unfortunately, this protective feature also prevents us from getting drugs into the brain. Approximately 1 in 10,000 antibodies injected into patients actually makes it to the brain, with these cellular fighters trapped in the blood rather than escaping through cracks in the blood vessels into the brain.

Now, researchers have mapped out a new transit process to enable drugs to reach the brain using extracellular vesicles—tiny bubbles naturally produced by cells in our bodies.

Maxwell’s demon learns to turn concealed information into usable energy for microscopic systems

Since its introduction more than 150 years ago, the thought-provoking idea of Maxwell’s demon has profoundly shaped our understanding of the relationship between information and energy. Maxwell’s demon is an imagined microscopic gatekeeper that exploits information at the microscopic scale to produce macroscopic work.

Initially controversial, the demon appeared to challenge a fundamental law of thermodynamics by suggesting that work could be extracted from a system in thermal equilibrium.

Today, this apparent paradox is resolved by recognizing the thermodynamic value of information: Information itself is a physical resource that can be converted into work. This insight has inspired growing interest in information engines—microscopic machines that, unlike conventional heat engines, are powered by information rather than by temperature differences.

Physics-guided AI reconstructs hidden patterns inside ultrathin magnets from external fields

To build faster and more energy-efficient computers, researchers need to understand nanoscale magnetic materials. But looking inside these tiny magnets is surprisingly difficult: Modern microscopes only measure the magnetic field outside the material, not the magnetic pattern inside. Because many different internal patterns can produce the exact same field, working backwards has long been a challenge.

Physicists at the University of Vienna, together with colleagues in Dresden, Singapore, and Ulsan, have now solved this problem by building the laws of physics directly into modern machine learning methods. Their method reveals the realistic magnetic structure and even determines the precise distance between the sensor and the sample. The study is published in Physical Review Letters, and the software is freely available as open source.