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Nature’s strongest material now has some stiff competition. For the first time, researchers have hard evidence that human-made hexagonal diamonds are stiffer than the common cubic diamonds found in nature and often used in jewelry.

Named for their six-sided crystal structure, hexagonal diamonds have been found at some meteorite impact sites, and others have been made briefly in labs, but these were either too small or had too short of an existence to be measured.

Now scientists at Washington State University’s Institute for Shock Physics created hexagonal diamonds large enough to measure their stiffness using sound waves. Their findings are detailed in a recent paper in Physical Review B.

The center of the Milky Way is mysteriously glowing.

Sure, there’s a whole bunch of stars there, along with a black hole 4 million times the mass of the Sun — but subtract the light from all that, and we’re still left with this mysterious excess gamma radiation that suffuses the region.

It’s called the Galactic Center GeV Excess (GCE), and it’s puzzled scientists since its discovery by physicists Lisa Goodenough and Dan Hooper in 2009. In data from NASA’s Fermi telescope, they found excess gamma radiation — some of the most energetic light in the Universe — and we haven’t been able to directly detect whatever is causing it.

Researchers at the International Centre for Theoretical Physics (ICTP) in Italy and the PICO group at Aalto University in Finland have introduced the idea of an information demon that follows a customary gambling strategy to stop non-equilibrium processes at stochastic times. The new demons they realized, which differ from the renowned Maxwell’s demon, were presented in a paper published in Physical Review Letters.

“Our research was driven by curiosity,” Gonzalo Manzano, one of the researchers who carried out the study, told Phys.org. “We asked ourselves about the implications of processes whose fluctuations fulfill (or break) some strong properties of stochastic processes on the link between thermodynamics and information.”

The recent study by Gonzalo Manzano, Edgar Roldan and their colleagues is based on previous works investigating the link between information and thermodynamics at the stochastic level. It also draws inspiration from recent research that explored the properties of a unique family of stochastic processes known as martingales in the context of thermodynamics.

In physics, entropy is the process of a system losing energy and dissolving into chaos. This applies to social systems in everyday life, too. Limiting energy loss can make social systems run better.

World’s First Telescope Lens Capable Of zooming Your vision Three Time.

Science, science nature articles, physics topics, space information, technolog services, view search history, astronomy articles.

What is the origin of black holes and how is that question connected with another mystery, the nature of dark matter? Dark matter comprises the majority of matter in the Universe, but its nature remains unknown.

Multiple gravitational wave detections of merging black holes have been identified within the last few years by the Laser Interferometer Gravitational-Wave Observatory (LIGO), commemorated with the 2017 physics Nobel Prize to Kip Thorne, Barry Barish, and Rainer Weiss. A definitive confirmation of the existence of black holes was celebrated with the 2020 physics Nobel Prize awarded to Andrea Ghez, Reinhard Genzel and Roger Penrose. Understanding the origin of black holes has thus emerged as a central issue in physics.

Surprisingly, LIGO has recently observed a 2.6 solar-mass black hole candidate (event GW190814, reported in Astrophysical Journal Letters 896 (2020) 2, L44). Assuming this is a black hole, and not an unusually massive neutron star, where does it come from?

https://youtube.com/watch?v=NOujMHH3LAU

Holograms deliver an exceptional representation of 3D world around us. Plus, they’re beautiful. (Go ahead — check out the holographic dove on your Visa card.) Holograms offer a shifting perspective based on the viewer’s position, and they allow the eye to adjust focal depth to alternately focus on foreground and background.

Researchers have long sought to make computer-generated holograms, but the process has traditionally required a supercomputer to churn through physics simulations, which is time-consuming and can yield less-than-photorealistic results. Now, MIT researchers have developed a new way to produce holograms almost instantly — and the deep learning-based method is so efficient that it can run on a laptop in the blink of an eye, the researchers say.

The smallest-scale measurements of gravity ever made show that a tiny gold ball weighing 90 milligrams can move another gold ball just a few nanometres through gravitational pull.

Scientists have taken a major step forward in harnessing machine learning to accelerate the design for better batteries: Instead of using it just to speed up scientific analysis by looking for patterns in data, as researchers generally do, they combined it with knowledge gained from experiments and equations guided by physics to discover and explain a process that shortens the lifetimes of fast-charging lithium-ion batteries.

It was the first time this approach, known as “scientific machine learning,” has been applied to battery cycling, said Will Chueh, an associate professor at Stanford University and investigator with the Department of Energy’s SLAC National Accelerator Laboratory who led the study. He said the results overturn long-held assumptions about how lithium-ion batteries charge and discharge and give researchers a new set of rules for engineering longer-lasting batteries.

The research, reported today in Nature Materials, is the latest result from a collaboration between Stanford, SLAC, the Massachusetts Institute of Technology and Toyota Research Institute (TRI). The goal is to bring together foundational research and industry know-how to develop a long-lived electric vehicle battery that can be charged in 10 minutes.