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Jan 7, 2025

Quantum phase transition in indium oxide films defies superconductor norms

Posted by in categories: entertainment, quantum physics

A team of physicists at Université Grenoble Alpes, CNRS, in France, working with a colleague from Karlsruhe Institute of Technology, in Germany, has observed an odd quantum phase transition in indium oxide films. In their study published in the journal Nature Physics, the group used microwave spectroscopy to study the internal properties and behavior of indium oxide films as they transitioned between superconducting and insulating states.

Prior research has shown that when a superconductor undergoes a phase transition between superconductivity and insulation, its stiffness generally occurs in a smooth, continuous fashion. Superfluid stiffness is a measurement that has been developed to gauge how resistant a material is to changing from one phase to another. In this new study, the research team found an exception to that rule in indium oxide films.

In their work, the researchers were investigating the properties of indium oxide, a material that, when chilled to a certain temperature, changes to a superconductor—it is also known to have multiple disorders at multiple levels. Such disorders give the material unusual properties.

Jan 7, 2025

New simulation method models antineutrinos emitted from nuclear reactors during fission

Posted by in categories: nuclear energy, particle physics

Nuclear fission is the most reliable source of antineutrinos, but they are difficult to characterize. A recent study suggests how their emission can be simulated most effectively.

Antineutrinos are mysterious fundamental anti-particles with no charge and an exceptionally small but non-zero mass. The JUNO project (Jiangmen Underground Neutrino Observatory) in China is a large scintillation detector designed to detect them and to characterize their properties, particularly in precise measurements of that tiny mass. Anti-particles are hard to measure and even harder to control, even when they come from a strong and reliable source.

A group of Italian physicists, led by Monica Sisti of the Istituto Nazionale di Fisica Nucleare (INFN) in Milan and Antonio Cammi of the Politecnico di Milano and part of the JUNO collaboration of over 700 scientists from 17 countries, has now modeled parameters that determine the ‘antineutrino spectrum’ emitted by a source.

Jan 7, 2025

Exploring the impacts of particle parameters on self-propelled motions

Posted by in category: particle physics

Phase transitions in the collective motions of self-propelled particles are directly impacted both by the initial velocity of each particle, and the repulsive radius surrounding them.

Collective motions of self-propelled particles can be found across many systems in nature. One of the most striking features of this phenomenon is the way in which systems transition between different states of motion: a behavior which can be compared directly with in physics. So far, however, it is still not fully understood how these transitions are impacted by the initial parameters of these deeply .

Through analysis published in The European Physical Journal E, Salma Moushi and colleagues at the University of Hassam II, Morocco, show how the conditions required for transitions to occur are heavily dependent on the initial velocities of each particle, and the repulsion radius surrounding them.

Jan 7, 2025

Thin, Fast, and Powerful: MIT’s “Stacked” 3D Chips Shatter Industry Constraints

Posted by in category: robotics/AI

An electronic stacking technique has the potential to exponentially boost the number of transistors on chips, paving the way for more efficient AI hardware.

The electronics industry is approaching a limit to the number of transistors that can be packed onto the surface of a computer chip. So, chip manufacturers are looking to build up rather than out.

Instead of squeezing ever-smaller transistors onto a single surface, the industry is aiming to stack multiple surfaces of transistors and semiconducting elements — akin to turning a ranch house into a high-rise. Such multilayered chips could handle exponentially more data and carry out many more complex functions than today’s electronics.

Jan 7, 2025

Unlocking the Potential of Platinum: New Catalyst Enhances CO2 Reduction Efficiency

Posted by in categories: chemistry, sustainability

A new study uncovers a molecular modification method for converting CO2 into valuable chemical resources using a platinum surface.

Copper-based (Cu) materials are widely recognized for their efficiency in converting CO2 into valuable hydrocarbons via the CO2 reduction reaction (CO2RR). However, their stability, particularly in acidic environments, needs significant improvement. In contrast, metallic platinum (Pt) demonstrates excellent stability under both acidic and alkaline conditions. However, its high activity in the hydrogen evolution reaction (HER) hinders its effectiveness in CO2RR applications.

To address these challenges, composite materials incorporating metal-doped molecules offer a promising solution. These modified molecules can be securely retained at the interface, forming a unique structure that enhances the metal interface properties. This configuration not only increases the contact between reactants and active sites but also optimizes the adsorption strength of critical intermediates, ultimately improving catalytic performance.

Jan 7, 2025

Storm Surfers of the Sky: How Bats Harness Winds to Power Migration

Posted by in categories: energy, innovation

Migrating bats cleverly harness the warm winds of storm fronts to reduce energy use during their long seasonal journeys, as revealed by innovative tracking technology.

Scientists found these tiny nocturnal travelers exhibit unexpected flexibility and adaptability in their migration patterns. Yet, they face mounting challenges from anthropogenic threats and environmental changes, underscoring the urgency for conservation efforts.

Continue reading “Storm Surfers of the Sky: How Bats Harness Winds to Power Migration” »

Jan 7, 2025

Open-World Games’ Affordance of Cognitive Escapism, Relaxation, and Mental Well-Being Among Postgraduate Students: Mixed Methods Study

Posted by in categories: entertainment, neuroscience

Background: Open-world games, characterized by their expansive and interactive environments, may offer unique cognitive escapism opportunities, potentially leading to relaxation and enhanced well-being. These games, such as “The Legend of Zelda: Breath of the Wild” and “The Legend of Zelda: Tears of the Kingdom,” allow players to experience a sense of freedom and autonomy, which can reduce stress and improve mental health. While previous research has examined the general impact of video games on mental well-being, specific studies on the effects of open-world games among postgraduate students are limited.

Objective: This study aims to investigate the relationships between cognitive escapism provided by open-world games and their effects on relaxation and well-being. The goal was to understand how the immersive nature of these games contributes to stress reduction and overall mental health improvement among postgraduate students.

Methods: A mixed methods approach was used, which involved in-depth exploratory qualitative interviews and a survey of 609 players of popular open-world games. Quantitative data were collected using standardized questionnaires to measure open-world games’ affordance of cognitive escapism, relaxation, and well-being. Qualitative data were obtained through 32 in-depth interviews that explored players’ experiences and perceptions of cognitive escapism, relaxation, and mental well-being.

Jan 7, 2025

Researchers Push Boundaries of Quantum Simulation With Novel Photonic Chip

Posted by in categories: computing, particle physics, quantum physics

USTC researchers created a groundbreaking on-chip photonic simulator, leveraging thin-film lithium niobate chips to simplify quantum simulations of complex structures, achieving high-dimensional synthetic dimensions with reduced frequency demands.

A research team led by Prof. Chuanfeng Li from the University of Science and Technology of China (USTC) has made a significant breakthrough in quantum photonics. The team successfully developed an on-chip photonic simulator capable of modeling arbitrary-range coupled frequency lattices with gauge potential. This achievement was detailed in a recent publication in Physical Review Letters.

<em>Physical Review Letters (PRL)</em> is a prestigious peer-reviewed scientific journal published by the American Physical Society. Launched in 1958, it is renowned for its swift publication of short reports on significant fundamental research in all fields of physics. PRL serves as a venue for researchers to quickly share groundbreaking and innovative findings that can potentially shift or enhance understanding in areas such as particle physics, quantum mechanics, relativity, and condensed matter physics. The journal is highly regarded in the scientific community for its rigorous peer review process and its focus on high-impact papers that often provide foundational insights within the field of physics.

Jan 7, 2025

Controlling Human Body Temperature to Mimic Hibernation

Posted by in categories: biotech/medical, neuroscience

Summary: Researchers have discovered a way to control human body temperature, mimicking the hibernation process of animals like bears. By manipulating the brain’s temperature regulation system, they can induce a state of “thermoregulatory inversion” (TI) in rats, reducing heat production even in cold environments.

This breakthrough could lead to controlled hypothermia in humans, improving survival rates in life-threatening situations like heart attacks and strokes. The discovery opens the door to therapeutic hypothermia, which can protect tissues from damage by lowering metabolism and oxygen demand.

Jan 7, 2025

Meta unveils HOT3D dataset for advanced computer vision training

Posted by in category: robotics/AI

While most humans can innately use their hands to communicate with others or grab and manipulate objects, many existing robotic systems only excel at simple manual tasks. In recent years, computer scientists worldwide have been developing machine learning-based models that can process images of humans completing manual tasks, using acquired information to improve robot manipulation, which could in turn enhance a robot’s interactions with both humans and objects in its surroundings.

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