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Studies that explore how the denser sections of atoms, known as atomic nuclei, interact with neutrons (i.e., particles with no electric charge) can have valuable implications both for the understanding of these atoms’ underlying physics and for the development of nuclear energy solutions. A process that is central to these interactions is neutron capture, which entails the absorption of a neutron by a nucleus, followed by the emission of gamma-rays.

Researchers at Los Alamos National Laboratory recently carried out a study aimed at better understanding the origin of the exceptional neutron capture capabilities of the zirconium-88 (88 Zr), using a new experimental methodology. Their findings, published in Physical Review Letters, offer valuable insight that could help to improve existing nuclear and astrophysical models.

“The probability (per unit area) of a nucleus capturing a neutron at a given kinetic energy is called neutron-capture cross section,” Thanos Stamatopoulos, first author of the paper, told Phys.org. “The probability across several kinetic energies from 0.5 eV up to infinity is called resonance integral. Typically, in nature, when the cross section for neutrons with a kinetic energy of 25 meV (thermal cross section) is very large, the resonance integral is small.”

Superconductivity is a quantum physical state in which a metal is able to conduct electricity perfectly without any resistance. In its most familiar application, it enables powerful magnets in MRI machines to create the magnetic fields that allow doctors to see inside our bodies. Thus far, materials can only achieve superconductivity at extremely low temperatures, near absolute zero (a few tens of Kelvin or colder).

But physicists dream of superconductive materials that might one day operate at room temperature. Such materials could open entirely new possibilities in areas such as , the energy sector, and medical technologies.

“Understanding the mechanisms leading to the formation of superconductivity and discovering exotic new superconducting phases is not only one of the most stimulating pursuits in the fundamental study of quantum materials but is also driven by this ultimate dream of achieving room-temperature superconductivity,” says Stevan Nadj-Perge, professor of applied physics and materials science at Caltech.

Over the past decades, roboticists have introduced a wide range of systems that can move in various complex environments, including different terrains, on the ground, in the air, and even in water. To safely navigate real-world dynamic environments without colliding with humans or nearby objects, most robots rely on sensors and cameras.

Researchers at Tsinghua University have recently developed WHERE-Bot, a new wheel-less, everting (i.e., a flexible robot that moves by turning its body structure inside out) that safely moves in unstructured environments without using sensors to detect obstacles. This robot, introduced in a paper published on the arXiv preprint server and set to be presented at the 8th IEEE International Conference on Soft Robotics (RoboSoft) in April, leverages its unique helical ring-based structure to move in all directions.

“One day, while playing with a Slinky toy during a lab meeting,” Shuguang Li, senior author of the paper, told Tech Xplore. “Suddenly, a new idea struck us: what if we connected the head and tail of the spring toy? By joining its two ends, the spring could be endlessly turned inside-out—a motion we now call ‘everting’—presenting a fascinating color flow. This sparked our curiosity about how such a helical ring—perhaps with some structure modifications—would behave in various environments: on the ground, along a pipe, underwater, on sand, and even in the air.”

How gravity causes a perfectly spherical ball to roll down an inclined plane is part of the elementary school physics canon. But the world is messier than a textbook.

Scientists in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have sought to quantitatively describe the much more complex rolling physics of real-world objects. Led by L. Mahadevan, the Lola England de Valpine Professor of Applied Mathematics, Physics, and Organismic and Evolutionary Biology in SEAS and FAS, they combined theory, simulations, and experiments to understand what happens when an imperfect, spherical object is placed on an inclined plane.

Published in Proceedings of the National Academy of Sciences, the research, which was inspired by nothing more than curiosity about the everyday world, could provide fundamental insights into anything that involves irregular objects that roll, from nanoscale cellular transport to robotics.

Photonic circuits, which manipulate light to perform various computational tasks, have become essential tools for a range of advanced technologies—from quantum simulations to artificial intelligence. These circuits offer a promising way to process information with minimal energy loss, especially in fields like quantum computing where complex systems are simulated to test theories of quantum mechanics.

However, the growth in circuit size and complexity has historically led to a rise in optical losses, making it challenging to scale these systems for large-scale applications, such as multiphoton quantum experiments or all-optical AI systems.

As reported in Advanced Photonics, researchers at the University of Naples Federico II have now developed a new approach to address this problem. Using a liquid-crystal (LC)-based platform, the team designed an optical processor capable of handling hundreds of optical modes in a compact, two-dimensional setup. This breakthrough offers a solution to a key limitation in traditional , where losses increase as the number of modes grows.

The oceans hold an enormous amount of very diluted uranium that could potentially serve as a sustainable fuel source for nuclear power. But how can uranium be extracted quickly and efficiently from seawater?

Balancing high selectivity for ions with rapid transport of those ions has long been a major challenge in obtaining uranium from the sea. Now a groundbreaking study suggests a solution.

A research team led by Prof. Wen Liping from the Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has developed a biomimetic adsorbent that can attract and hold uranium ions. The inspiration for this adsorbent is the natural porous structure of the spiky, globular fruit of the Chinese sweetgum tree, Liquidambar formosana. The team’s findings were recently published in Matter.

Photovoltaic (PV) solutions, which are designed to convert sunlight into electrical energy, are becoming increasingly widespread worldwide. Over the past decades, engineers specialized in energy solutions have been trying to identify new solar cell designs and PV materials that could achieve even better power conversion efficiencies, while also retaining their stability and reliably operating for long periods of time.

The many emerging PV solutions that have proven to be particularly promising include tandem based on both perovskites (a class of materials with a characteristic crystal structure) and organic materials. Perovskite/organic tandem solar cells could be more affordable than existing silicon-based solar cells, while also yielding higher power conversion efficiencies.

These solar cells are manufactured using wide-bandgap perovskites, which have an electronic bandgap greater than 1.6 electronvolts (eV) and can thus absorb higher-energy photons. Despite their enhanced ability to absorb high-energy light particles, these materials have significant limitations, which typically adversely impact the stability of solar cells.

Accurate and robust 3D imaging of specular, or mirror-like, surfaces is crucial in fields such as industrial inspection, medical imaging, virtual reality, and cultural heritage preservation. Yet anyone who has visited a house of mirrors at an amusement park knows how difficult it is to judge the shape and distance of reflective objects.

This challenge also persists in science and engineering, where the accurate 3D imaging of specular surfaces has long been a focus in both optical metrology and computer vision research. While specialized techniques exist, their inherent limitations often confine them to narrow, domain-specific applications, preventing broader interdisciplinary use.

In a study published in the journal Optica, University of Arizona researchers from the Computational 3D Imaging and Measurement (3DIM) Lab at the Wyant College of Optica l Sciences present a novel approach that significantly advances the 3D imaging of specular surfaces.

Together with an international team of researchers from the Universities of Southern California, Central Florida, Pennsylvania State and Saint Louis, physicists from the University of Rostock have developed a novel mechanism to safeguard a key resource in quantum photonics: optical entanglement. Their discovery is published in Science.

Declared as the International Year of Quantum Science and Technology by the United Nations, 2025 marks 100 years since the initial development of quantum mechanics. As this strange and beautiful description of nature on the smallest scales continues to fascinate and puzzle physicists, its quite tangible implications form the basis of modern technology as well as , and are currently in the process of revolutionizing information science and communications.

A key resource to quantum computation is so-called entanglement, which underpins the protocols and algorithms that make quantum computers exponentially more powerful than their classical predecessors. Moreover, entanglement allows for the secure distribution of encryption keys, and entangled photons provide increased sensitivity and noise resilience that dramatically exceed the classical limit.

Researchers have discovered a way to protect quantum information from environmental disruptions, offering hope for more reliable future technologies.

In their study published in Nature Communications, the scientists have shown how certain quantum states can maintain their critical information even when disturbed by . The team includes researchers from the University of the Witwatersrand in Johannesburg, South Africa (Wits University) in collaboration with Huzhou University in China.

“What we’ve found is that topology is a powerful resource for information encoding in the presence of noise,” says Professor Andrew Forbes from the Wits School of Physics.