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Software allows scientists to simulate nanodevices on a supercomputer

From computers to smartphones, from smart appliances to the internet itself, the technology we use every day only exists thanks to decades of improvements in the semiconductor industry, that have allowed engineers to keep miniaturizing transistors and fitting more and more of them onto integrated circuits, or microchips. It’s the famous Moore’s scaling law, the observation—rather than an actual law—that the number of transistors on an integrated circuit tends to double roughly every two years.

The current growth of artificial intelligence, robotics and cloud computing calls for more powerful chips made with even smaller transistors, which at this point means creating components that are only a few nanometers (or millionths of millimeters) in size. At that scale, classical physics is no longer enough to predict how the device will function, because, among other effects, electrons get so close to each other that quantum interactions between them can hugely affect the performance of the device.

AI makes quantum field theories computable

An old puzzle in particle physics has been solved: How can quantum field theories be best formulated on a lattice to optimally simulate them on a computer? The answer comes from AI.

Quantum field theories are the foundation of modern physics. They tell us how particles behave and how their interactions can be described. However, many complicated questions in particle physics cannot be answered simply with pen and paper, but only through extremely complex quantum field theory computer simulations.

This presents exceptionally complex problems: Quantum field theories can be formulated in different ways on a computer. In principle, all of them yield the same physical predictions—but in radically different ways. Some variants are computationally completely unusable, inaccurate, or inefficient, while others are surprisingly practical. For decades, researchers have been searching for the optimal way to embed quantum theories in computer simulations. Now, a team from TU Wien, together with teams from the U.S. and Switzerland, has shown that artificial intelligence can bring about tremendous progress in this area. Their paper is published in Physical Review Letters.

AI sheds light on mysterious dinosaur footprints

A new app, powered by artificial intelligence (AI), could help scientists and the public identify dinosaur footprints made millions of years ago, a study reveals.

For decades, paleontologists have pondered over a number of ancient dinosaur tracks and asked themselves if they were left by fierce carnivores, gentle plant-eaters or even early species of birds?

Now, researchers and dinosaur enthusiasts alike can upload an image or sketch of a dinosaur footprint from their mobile phone to the DinoTracker app and receive an instant analysis.

From fleeting to stable: Scientists uncover recipe for new carbon dioxide-based energetic materials

When materials are compressed, their atoms are forced into unusual arrangements that do not normally exist under everyday conditions. These configurations are often fleeting: when the pressure is released, the atoms typically relax back to a stable low-pressure state. Only a few very specific materials, like diamond, retain their high-pressure structure after returning to room temperature and atmospheric pressure.

But locking those atomic arrangements in place under ambient conditions could create new classes of useful materials with a wide range of potential applications. One particularly compelling example is energetic materials, which are useful for propellants and explosives.

In a study published in Communications Chemistry, researchers at Lawrence Livermore National Laboratory (LLNL) identified a first-of-its-kind carbon dioxide-equivalent polymer that can be recovered from high-pressure conditions.

Sloshing liquefied natural gas in cargo tanks causes higher impact forces than expected

What happens if liquefied natural gas (LNG) hits the wall of the cargo tanks in a ship? New research from the team of physicist Devaraj van der Meer from the University of Twente, published in the Proceedings of the National Academy of Sciences, shows that much higher pressure peaks can occur during impact than previously assumed. This insight is important for the design and safety of LNG ships and future liquid hydrogen transport systems.

Normally, a thin layer of air prevents a liquid from hitting a surface directly. The gas acts as a cushion and dampens the blow. In LNG ships, that air has been replaced by vapor from the LNG itself. And that vapor can condense back into liquid during impact. As a result, the cushion disappears, and the load on the wall increases sharply.

Watching atoms roam before they decay

Together with an international team, researchers from the Molecular Physics Department at the Fritz Haber Institute have revealed how atoms rearrange themselves before releasing low-energy electrons in a decay process initiated by X-ray irradiation. For the first time, they have gained detailed insights into the timing of the process—shedding light on related radiation damage mechanisms. Their research is published in the Journal of the American Chemical Society.

High-energy radiation, for example in the X-ray range, can cause damage to our cells. This is because energetic radiation can excite atoms and molecules, which then often decay—meaning that biomolecules are destroyed and larger biological units can lose their function. There is a wide variety of such decay processes, and studying them is of great interest in order to better understand and avert radiation damage.

In the study, researchers from the Molecular Physics Department, together with international partners, investigated a radiation-induced decay process that plays a key role in radiation chemistry and biological damage processes: electron-transfer-mediated decay (ETMD). In this process, one atom is excited by irradiation. Afterward, this atom relaxes by stealing an electron from a neighbor, while the released energy ionizes yet another nearby atom.

Establishing a new QM/MM design principle based on electronic-state responses

A research team has proposed a new design principle for QM/MM (quantum mechanics/molecular mechanics) simulations. The approach enables objective and automatic determination of the quantum-mechanical region based on electronic-state changes, addressing a long-standing challenge in multiscale molecular simulations.

The researchers included Professor Hirotoshi Mori (Department of Applied Chemistry, Faculty of Science and Engineering, Chuo University), together with Nichika Ozawa (first-year Ph.D. student at Ochanomizu University) and Assistant Professor Nahoko Kuroki of Ochanomizu University.

The findings are published in the journal Advanced Science as a cover article.

Superconducting nanowire memory array achieves significantly lower error rate

Quantum computers, systems that process information leveraging quantum mechanical effects, will require faster and energy-efficient memory components, which will allow them to perform well on complex tasks. Superconducting memories are promising memory devices that are made from superconductors, materials that conduct electricity with a resistance of zero when cooled below a critical temperature.

These memory devices could be faster and consume significantly less energy than existing memories based on superconductors. Despite their potential, most existing superconducting memories are prone to errors and are difficult to scale up to create larger systems containing several memory cells.

Researchers at Massachusetts Institute of Technology (MIT) recently developed a new scalable superconducting memory that is based on nanowires, one-dimensional (1D) nanostructures with unique optoelectronic properties. This memory, introduced in a paper published in Nature Electronics, was found to be less prone to errors than many other superconducting nanowire-based memories introduced in the past.

Brain Scans Reveal Hidden Changes After Menopause

New research suggests menopause is associated with brain volume loss in key regions tied to memory and emotions, along with higher rates of anxiety, depression, and sleep issues.

Hormone therapy didn’t prevent these changes, though it may slow age-related declines in reaction speed.

Menopause linked to brain changes and mental health challenges.

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