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Category: particle physics – Page 158

A team of Rice University researchers mapped out how flecks of 2D materials move in liquid ⎯ knowledge that could help scientists assemble macroscopic-scale materials with the same useful properties as their 2D counterparts.

“Two-dimensional nanomaterials are extremely thin—only several atoms thick—sheet-shaped materials,” said Utana Umezaki, a Rice graduate student who is a lead author on a study published in ACS Nano. “They behave very differently from materials we’re used to in daily life and can have really useful properties: They can withstand a lot of force, resist high temperatures and so on. To take advantage of these unique properties, we have to find ways to turn them into larger-scale materials like films and fibers.”

In order to maintain their special properties in bulk form, sheets of 2D materials have to be properly aligned ⎯ a process that often occurs in solution phase. Rice researchers focused on graphene, which is made up of , and hexagonal boron nitride, a material with a similar structure to graphene but composed of boron and nitrogen atoms.

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A consensus has arisen in the astronomical community that familiar matter made of atoms is not the dominant form of matter in the Universe. Instead, an invisible form of matter, called dark matter, is thought to be far more prevalent. However, a small group of researchers deny the existence of dark matter, instead saying our understanding of how objects move is incomplete. A recent paper in the Monthly Notices of the Royal Astronomical Society seems to have ruled this out definitively.

Stars, planets, and galaxies move under the direction of the force of gravity, and Isaac Newton worked out the laws that govern that motion, which we now call Newtonian dynamics. However, despite the enormous success of Newtonian dynamics, this success is not universal. Indeed, when Newton’s equations are applied to certain astronomical phenomena, they do not make the correct predictions. One such example is the speed at which galaxies rotate. When astronomers measure the speed of stars in the periphery of a galaxy, they move faster than can be explained by accepted theory. Instead, the galaxies should fly apart.

The solution to this mystery favored by most scientists is that beyond the familiar stars and clouds of gas, our galaxy also hosts a large amount of invisible matter, called dark matter. This dark matter adds to the gravitational force holding the galaxy together. Thus, the evidence for dark matter is indirect. It has never been observed in the laboratory; yet its ability to explain the motion of galaxies is strong circumstantial evidence that it exists.

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Artificial intelligence using neural networks performs calculations digitally with the help of microelectronic chips. Physicists at Leipzig University have now created a type of neural network that works not with electricity but with so-called active colloidal particles. In their publication in Nature Communications, the researchers describe how these microparticles can be used as a physical system for artificial intelligence and the prediction of time series.

“Our neural network belongs to the field of physical computing, which uses the dynamics of physical processes, such as water surfaces, bacteria or octopus tentacle models, to make calculations,” says Professor Frank Cichos, whose research group developed the network with the support of ScaDS.AI.

“In our realization, we use synthetic self-propelled particles that are only a few micrometers in size,” explains Cichos. “We show that these can be used for calculations and at the same time present a method that suppresses the influence of disruptive effects, such as noise, in the movement of the .” Colloidal particles are particles that are finely dispersed in their dispersion medium (solid, gas or liquid).

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As artificial intelligence technologies such as Chat-GPT are utilized in various industries, the role of high-performance semiconductor devices for processing large amounts of information is becoming increasingly important. Among them, spin memory is attracting attention as a next-generation electronics technology because it is suitable for processing large amounts of information with lower power than silicon semiconductors that are currently mass-produced.

Utilizing recently discovered in spin memory is expected to dramatically improve performance by improving signal ratio and reducing power, but to achieve this, it is necessary to develop technologies to control the properties of quantum materials through electrical methods such as current and voltage.

Dr. Jun Woo Choi of the Center for Spintroncs Research at the Korea Institute of Science and Technology (KIST) and Professor Se-Young Park of the Department of Physics at Soongsil University have announced the results of a collaborative study showing that ultra-low-power memory can be fabricated from quantum materials. The findings are published in the journal Nature Communications.

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For the first time, a team of scientists has imaged a single atom by using X-rays. And according to the resulting study published in the journal Nature, it offers transformative advantages over other techniques.

“Atoms can be routinely imaged with scanning probe microscopes, but without X-rays one cannot tell what they are made of,” study co-author Sai Wai Hla, a physicist at Ohio University and the Argonne National Laboratory, said in a press release.

“We can now detect exactly the type of a particular atom, one atom-at-a-time, and can simultaneously measure its chemical state,” Hla added. “Once we are able to do that, we can trace the materials down to the ultimate limit of just one atom.”

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Collisions of high energy particles produce “jets” of quarks, anti-quarks, or gluons. Due to the phenomenon called confinement, scientists cannot directly detect quarks. Instead, the quarks from these collisions fragment into many secondary particles that can be detected.

Scientists recently addressed jet production using quantum simulations. They found that the propagating jets strongly modify the quantum vacuum—the with the lowest possible energy. In addition, the produced quarks retain quantum entanglement, the linkage between particles across distances. This finding, published in Physical Review Letters, means that scientists can now study this entanglement in experiments.

This research performed that have detected the modification of the vacuum by the propagating jets. The simulations have also revealed quantum entanglement among the jets. This entanglement can be detected in nuclear experiments. The work is also a step forward in quantum-inspired classical computing. It may result in the creation of new application-specific integrated circuits.

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“The memory requirements for PRIYA simulations are so big you cannot put them on anything other than a supercomputer,” Bird said.

TACC awarded Bird a Leadership Resource Allocation on the Frontera supercomputer. Additionally, analysis computations were performed using the resources of the UC Riverside High-Performance Computer Cluster.

The PRIYA simulations on Frontera are some of the largest cosmological simulations yet made, needing over 100,000 core-hours to simulate a system of 30723 (about 29 billion) particles in a ‘box’ 120 megaparsecs on edge, or about 3.91 million light-years across. PRIYA simulations consumed over 600,000 node hours on Frontera.

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