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Superconductors can carry electricity without losing energy, a superpower that makes them invaluable for a range of sought-after applications, from maglev trains to quantum computers. Generally, this comes at the price of having to keep them extremely cold, an opportunity cost that has frequently hindered widespread use.

Understanding of how work has also progressed, but there still remains a great deal about them that is unknown. For example, among many materials known to have , some do not behave according to conventional theory.

One such puzzling material is strontium ruthenate or Sr2RuO4, which has challenged scientists since it was discovered to be a superconductor in 1994. Initially, researchers thought this material had a special type of called a “spin-triplet” state, which is notable for its spin supercurrent. But even after considerable investigation, a full understanding of its behavior has remained a mystery.

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In order to find rare processes from collider data, scientists use computer algorithms to determine the type and properties of particles based on the faint signals that they leave in the detector. One such particle is the tau lepton, which is produced, for example, in the decay of the Higgs boson.

The leaves a spray or jet of low-energy , the subtle pattern of which in the jet allows one to distinguish them from jets produced by other particles. The jet also contains about the energy of the tau lepton, which is distributed among the daughter particles, and on the way is decayed. Currently, the best algorithms use multiple steps of combinatorics and computer vision.

ChatGPT has shown much stronger performance in rejecting backgrounds than computer-vision based methods. In this paper, researchers showed that such language-based models can find the tau leptons from the jet patterns, and also determine the energy and decay properties more accurately than before.

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For the first time, a team of researchers at Lawrence Livermore National Laboratory (LLNL) quantified and rigorously studied the effect of metal strength on accurately modeling coupled metal/high explosive (HE) experiments, shedding light on an elusive variable in an important model for national security and defense applications.

The team used a Bayesian approach to quantify with tantalum and two common explosive materials and integrated it into a coupled metal/HE . Their findings could lead to more accurate models for equation-of-state-studies, which assess the state of matter a material exists in under different conditions. Their paper —featured as an editor’s pick in the Journal of Applied Physics —also suggested that metal strength uncertainty may have an insignificant effect on result.

“There has been a long-standing field lore that HE model calibrations are sensitive to the metal strength,” said Matt Nelms, the paper’s first author and a group leader in LLNL’s Computational Engineering Division (CED). “By using a rigorous Bayesian approach, we found that this is not the case, at least when using tantalum.”

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Challenging centuries-old assumptions about thermodynamics, a new study published in Physical Review Letters has shown that it is theoretically possible to design a heat engine that achieves maximum power output while approaching Carnot efficiency.

The Carnot heat engine is a thermodynamic device that converts heat into by operating between two temperature reservoirs, a hot and cold one.

The engine works by taking heat from the hot reservoir, converting some of it into useful work, and rejecting the remaining heat to the cold reservoir. The thermodynamic cycle followed by the engine is known as the Carnot cycle.

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In a new study published in Nature Physics, researchers have developed the first controlled method for exciting and observing Kelvin waves in superfluid helium-4.

First described by Lord Kelvin in 1880, Kelvin waves are helical (spiral-shaped) waves that travel along the lines, playing a vital role in how energy dissipates in . However, they are difficult to study experimentally.

Creating a controlled setting to observe them has been the biggest challenge that the researchers overcame. Phys.org spoke to the first author of the study, Associate Prof. Yosuke Minowa from Kyoto University.

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The mutual control of magnetization and polarization in multiferroics is key to spintronic devices, but ensuring its stability at room temperature is essential for practical applications. Here, magnetic control of ferroelectric polarization in Tb2(MoO4)3 is demonstrated up to 432 K, ensuring the stability of magnetoelectric effect well above room temperature.

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Antimony is widely used in the production of materials for electronics, as well as metal alloys resistant to corrosion and high temperatures.

“Antimony melt is interesting because near the melting point, the atoms in this melt can form bound structures in the form of compact clusters or extended chains and remain in a bound state for quite a long time. We found out that the basic unit of these structures are linked triplets of adjacent atoms, and the centers of mass of these linked atoms are located at the vertices of right triangles. It is from these triplets that larger structures are formed, the presence of which causes anomalous structural features detected in neutron and X-ray diffraction experiments,” explains Dr. Anatolii Mokshin, study supervisor and Chair of the Department of Computational Physics and Modeling of Physical Processes.

The computer modeling method based on quantum-chemical calculations made it possible to reproduce anomalies in the structure of molten with high accuracy.

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Microsoft fixes CVE-2025–21415 (CVSS 9.9) and CVE-2025–21396 flaws, addressing privilege escalation risks in Azure AI Face Service and Microsoft Account that could allow a malicious actor to escalate their privileges under certain conditions.

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