Ultra–high-power particle pulses could boost x-ray science and laboratory astrophysics.
Category: particle physics – Page 4
Superconductivity is an intriguing property observed in some materials, which entails the ability to conduct electric current combined with an electrical resistance of zero at low temperatures. Physicists have observed this property in various solid materials with different characteristics and atomic thicknesses.
A team of researchers at Nanjing University in China recently carried out a study aimed at further exploring the behavior of niobium diselenide (NbSe₂), a layered material that has been found to be a superconductor when it is atomically thin. Their paper, published in Physical Review Letters, unveils resilient superconducting fluctuations in atomically thin NbSe₂, which could play a part in the anomalous metallic state previously observed in this material.
“Our study was inspired by a long-standing puzzle in condensed matter physics, which can be summarized by the question: can metals truly exist in two dimensions as the ground state?” Xiaoxiang Xi, senior author of the paper, told Phys.org. “While we understand the behavior of everyday metals and insulators, ultrathin materials—like sheets just one atom thick—challenge these conventional rules.”
Graphyne is a crystalline form of carbon that is distinct from both diamond and graphite. Unlike diamond, where each atom possesses four immediate neighbors, or graphite, where each atom has three, graphyne’s structure combines two-coordinate and three-coordinate carbons.
Computational models suggest that graphyne has highly compelling electronic, mechanical and optical properties. It is predicted to be a semiconductor with a band gap appropriate for electronic devices, ultra-high charge carrier mobility far surpassing that of silicon, and ultimate strength comparable to that of graphene.
Applications of graphyne in carbon electronics, energy harvesting and storage, gas separations and catalysis have been proposed. While graphyne was first theoretically predicted more than three decades ago, its synthesis remained elusive.
A research team, led by Professor Jimin Lee and Professor Eisung Yoon in the Department of Nuclear Engineering at UNIST, has unveiled a deep learning–based approach that significantly accelerates the computation of a nonlinear Fokker–Planck–Landau (FPL) collision operator for fusion plasma.
The findings are published in the Journal of Computational Physics.
Nuclear fusion reactors, often referred to as artificial sun, rely on maintaining a high-temperature plasma environment similar to that of the sun. In this state, matter is composed of negatively charged electrons and positively charged ions. Accurately predicting the collisions between these particles is crucial for sustaining a stable fusion reaction.
High-temperature superconducting magnets made from REBCO, an acronym for rare-earth barium copper oxide, make it possible to create an intense magnetic field that can confine the extremely hot plasma needed for fusion reactions, which combine two hydrogen atoms to form an atom of helium, releasing a neutron in the process.
But some early tests suggested that neutron irradiation inside a fusion power plant might instantaneously suppress the superconducting magnets’ ability to carry current without resistance (called critical current), potentially causing a reduction in the fusion power output.
Now, a series of experiments has clearly demonstrated that this instantaneous effect of neutron bombardment, known as the “beam on effect,” should not be an issue during reactor operation, thus clearing the path for projects such as the ARC fusion system being developed by MIT spinoff company Commonwealth Fusion Systems.
The company uses so-called “photonic” quantum computing, which has long been dismissed as impractical.
The approach, which encodes data in individual particles of light, offers some compelling advantages — low noise, high-speed operation, and natural compatibility with existing fibre-optic networks. However, it was held back by extreme hardware demands to manage the fact photons fly with blinding speed, get lost, and are hard to create and detect.
PsiQuantum now claims to have addressed many of these difficulties. Yesterday, in a new peer-reviewed paper published in Nature, the company unveiled hardware for photonic quantum computing they say can be manufactured in large quantities and solves the problem of scaling up the system.
A new imaging technique can show the wave-like behavior of unconfined quantum particles.
A research team has shown that a method for imaging atoms held in a 2D array of optical traps can be used to reveal the wave-like behavior of the atoms when they are released into free space [1]. The team placed atoms in the traps, turned the traps off for a short time, and then turned them back on again. By making many measurements of the atoms’ locations after the traps were reactivated, the researchers could deduce the atoms’ wave-like behavior. The team plans to use this technique to simulate interacting systems of particles in quantum states that are not well understood.
Systems composed of many quantum particles, such as certain types of electronic or magnetic states of matter, can be investigated by simulating them using atoms distributed within arrays of optical traps, like eggs in a vast egg carton. One method for studying such atom arrays, called quantum gas microscopy, involves probing the positions and the quantum states of the atoms by using laser beams to make them fluoresce [2]. Joris Verstraten at the École Normale Supérieure in France and his colleagues have adapted the technique to observe collections of atoms allowed to move in free space, unconstrained by traps.
A fractal butterfly pattern produced by an unusual configuration of magnetic fields, first predicted almost 50 years ago, has been seen in detail for the first time in a twisted piece of graphene.
While a physics student in 1976, the computer scientist Douglas Hofstadter predicted that when certain two-dimensional crystals were placed in magnetic fields, their electrons’ energy levels should produce a strange pattern that looks the same no matter how far you zoom in, known as a fractal. At the time, however, Hofstadter calculated that the atoms of the crystal would have to be impossibly close together to produce such a pattern.
Image: Yazdani Lab, Princeton University
The electrons in a twisted piece of graphene show a strange repeating pattern first predicted in 1976, but never directly measured until now.
Long Ju, the lead researcher, describes the new material, rhombohedral pentalayer graphene, as a gold mine, with discoveries revealed at every step.
A novel class of quantum particles behaves in unexpected ways
Rhombohedral pentalayer graphene is a unique form of pencil lead. Pencil lead, or graphite, consists of graphene, a single layer of carbon atoms arranged in a hexagonal pattern. Rhombohedral pentalayer graphene has five layers of graphene stacked in a specific order.