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This video’s topic is close to my own research, cosmology. The current standard model of cosmology rests on the “cosmological principle” — the idea that the universe looks, on the average, the same everywhere. Alas, it doesn’t look good for the cosmological principle. Just what does the evidence say and, if it holds up, what does this mean? At the end of this video, you’ll know.

0:00 Intro.
0:43 Sponsor Message.
1:41 The Cosmological Principle.
5:58 Trouble for the Cosmological Principle.
10:20 What does it mean?

#physics #cosmology #astrophysics

Batteries are widely used in everyday applications like powering electric vehicles, electronic gadgets and are promising candidates for sustainable energy storage. However, as you’ve likely noticed with daily charging of batteries, their functionality drops off over time. Eventually, we need to replace these batteries, which is not only expensive but also depletes the rare earth elements used in making them.

A key factor in life reduction is the degradation of a battery’s structural integrity. To discourage structural degradation, a team of researchers from USC Viterbi School of Engineering are hoping to introduce “stretch” into battery materials so they can be cycled repeatedly without structural fatigue. This research was led by Ananya Renuka-Balakrishna, WiSE Gabilan Assistant Professor of Aerospace and Mechanical Engineering, and USC Viterbi Ph.D candidate, Delin Zhang, as well as Brown University researchers from Professor Brian Sheldon’s group. Their work was published in the Journal of Mechanics and Physics of Solids.

A typical battery works through a repetitive cycle of inserting and extracting Li-ions from electrodes, Zhang said. This insertion and extraction expands and compresses the lattices. These volume shifts create microcracks, fractures and defects over time.

Housed at Lawrence Livermore National Laboratory, the US$3.5-billion facility wasn’t designed to serve as a power-plant prototype, however, but rather to probe fusion reactions at the heart of thermonuclear weapons. After the United States banned underground nuclear testing at the end of the cold war in 1,992 the energy department proposed the NIF as part of a larger science-based Stockpile Stewardship Program, designed to verify the reliability of the country’s nuclear weapons without detonating any of them.

With this month’s laser-fusion breakthrough, scientists are cautiously optimistic that the NIF might live up to its promise, helping physicists to better understand the initiation of nuclear fusion — and thus the detonation of nuclear weapons. “That’s really the scientific question for us at the moment,” says Mark Herrmann, Livermore’s deputy director for fundamental weapons physics. “Where can we go? How much further can we go?”

Here Nature looks at the NIF’s long journey, what the advance means for the energy department’s stewardship programme and what lies ahead.

Proteins are essential to life, and understanding their 3D structure is key to unpicking their function. To date, only 17% of the human proteome is covered by an experimentally determined structure. Two papers in this week’s issue dramatically expand our structural understanding of proteins. Researchers at DeepMind, Google’s London-based sister company, present the latest version of their AlphaFold neural network. Using an entirely new architecture informed by intuitions about protein physics and geometry, it makes highly accurate structure predictions, and was recognized at the 14th Critical Assessment of Techniques for Protein Structure Prediction last December as a solution to the long-standing problem of protein-structure prediction. The team applied AlphaFold to 20,296 proteins, representing 98.5% of the human proteome.