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Category: particle physics – Page 30

Shape-shifting collisions offer new tool for studying early matter produced in Big Bang’s aftermath

This summer, the Large Hadron Collider (LHC) took a breath of fresh air. Normally filled with beams of protons, the 27-km ring was reconfigured to enable its first oxygen–oxygen and neon–neon collisions. First results from the new data, recorded over a period of six days by the ALICE, ATLAS, CMS and LHCb experiments, were presented during the Initial Stages conference held in Taipei, Taiwan, on 7–12 September.

Smashing into one another allows physicists to study the quark–gluon plasma (QGP), an extreme state of matter that mimics the conditions of the universe during its first microseconds, before atoms formed. Until now, exploration of this hot and dense state of free particles at the LHC relied on collisions between (like lead or xenon), which maximize the size of the plasma droplet created.

Collisions between lighter ions, such as oxygen, open a new window on the QGP to better understand its characteristics and evolution. Not only are they smaller than lead or xenon, allowing a better investigation of the minimum size of nuclei needed to create the QGP, but they are less regular in shape. A neon nucleus, for example, is predicted to be elongated like a bowling pin—a picture that has now been brought into sharper focus thanks to the new LHC results.

How you make it matters: Spintronics device performance tied to atomic interface changes

Spintronics devices will be key to realizing faster and more energy-efficient computers. To give us a better understanding of how to make them, a Kobe University team now showed how different manufacturing techniques influence the material properties of a key component.

Electronic devices could be made more efficient and faster if electrons could carry more information at once. This is the basic idea behind spintronics, where researchers try to use the electrons’ spin in addition to charge in , processing and sensor devices to significantly improve our computers.

One component for such devices is the “,” which may be used, for example, for neuron-like behavior in information processing or in a new type of fast and non-volatile memory. They consist of two ferromagnets, usually a nickel-iron alloy, sandwiching a thin insulating layer such as graphene.

Monitoring sediment buildup in underwater bridge tunnels with the help of high-energy muons

Over 200 underwater bridge tunnels exist for vehicular traffic around the world, providing connectivity between cities. Once constructed, however, these tunnels are difficult to monitor and maintain, often requiring shutdowns or invasive methods that pose structural risks.

Muography—an using , called , which can traverse hundreds of meters within the Earth—can provide a noninvasive approach to examining subterranean infrastructure.

In the Journal of Applied Physics, a group of researchers from public and private organizations in Shanghai applied this technique to the Shanghai Outer Ring Tunnel, which runs under the Huangpu River as part of the city’s ring expressway.

Ultrathin films of ferromagnetic oxide reveal a hidden Hall effect mechanism

Researchers from Japan have discovered a unique Hall effect resulting from deflection of electrons due to “in-plane magnetization” of ferromagnetic oxide films (SrRuO3). Arising from the spontaneous coupling of spin-orbit magnetization within SrRuO3 films, the effect overturns the century-old assumption that only out-of-plane magnetization can trigger the Hall effect.

The study, now published in Advanced Materials, offers a new way to manipulate with potential applications in advanced sensors, , and spintronic technologies.

When an electric current flows through a material in the presence of a magnetic field, its electrons experience a subtle sideways force which deflects their path. This effect of electron deflection is called the Hall effect—a phenomenon that lies at the heart of modern sensors and electronic devices. When this effect results from internal magnetization of the conducting material, it is called “anomalous Hall effect (AHE).”

An AI model can forecast harmful solar winds days in advance

Scientists at NYU Abu Dhabi (NYUAD) have developed an artificial intelligence (AI) model that can forecast solar wind speeds up to four days in advance, significantly more accurately than current methods. The study is published in The Astrophysical Journal Supplement Series.

Solar wind is a continuous stream of charged particles released by the sun. When these particles speed up, they can cause “space weather” events that disrupt Earth’s atmosphere and drag satellites out of orbit, damage their electrons, and interfere with power grids. In 2022, a strong event caused SpaceX to lose 40 Starlink satellites, showing the urgent need for better forecasting.

The NYUAD team, led by Postdoctoral Associate Dattaraj Dhuri and Co-Principal Investigator at the Center for Space Science (CASS) Shravan Hanasoge, trained their AI model using high-resolution ultraviolet (UV) images from NASA’s Solar Dynamics Observatory, combined with historical records of solar wind.

Machine learning unravels quantum atomic vibrations in materials

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group focuses on interactions among atomic vibrations, or phonons—interactions that govern a wide range of material properties, including heat transport, thermal expansion, and phase transitions. The new machine learning approach could be extended to compute all quantum interactions, potentially enabling encyclopedic knowledge about how particles and excitations behave in materials.

Scientists like Marco Bernardi, professor of applied physics, physics, and at Caltech, and his graduate student Yao Luo (MS ‘24) have been trying to find ways to speed up the gargantuan calculations required to understand such particle interactions from first principles in real materials—that is, beginning with only a material’s atomic structure and the laws of quantum mechanics.

Last year, Bernardi and Luo developed a data-driven method based on a technique called singular value decomposition (SVD) to simplify the enormous mathematical matrices scientists use to represent the interactions between electrons and phonons in a material.

New laser technique reveals nearly 20 previously hidden states of matter

In 2023, physicist Xiaodong Xu at the University of Washington —working with researchers from Cornell and Shanghai Jiao Tong University —found that twisting atom-thin layers of molybdenum ditelluride into a special pattern called a moiré lattice could produce the fractional quantum anomalous Hall effect without magnets. This was a huge leap, because magnets can disrupt superconducting materials used in quantum technology.

Xu’s team discovered two such magnet-free fractional states. That alone was remarkable. But Zhu and his colleagues suspected there were more waiting to be found. The secret lies in the moiré pattern. When the layers are slightly rotated relative to each other, they form a honeycomb-like grid at the atomic scale.

This structure changes the way electrons move, encouraging them to team up in unusual ways that create fractional charges. In other words, the twist turns the material into a playground for exotic quantum phases.

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