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IN A NUTSHELL 🌍 NASA collaborates with private and academic sectors to develop the Quantum Gravity Gradiometer Pathfinder, a revolutionary space-based quantum sensor. ❄️ The gradiometer uses ultra-cold rubidium atoms to measure Earth’s gravitational variations with high precision, free from environmental disturbances. 🔬 Quantum sensors in the QGGPf offer 10 times greater sensitivity and are

Japan has taken a significant step forward in renewable energy with the successful deployment of its first megawatt-scale tidal turbine, the AR1100. Installed in the Naru Strait, this 1.1 MW tidal turbine represents a major breakthrough in marine energy technology. As Japan moves towards a sustainable, fossil-fuel-free future, tidal energy is poised to play a crucial role in the country’s energy transition.

This latest achievement builds upon the success of the AR500 pilot project, which demonstrated the viability of tidal energy with a 97% availability rate. With the AR1100 now operational, Japan has entered the global race to harness ocean power on a large scale.

This article will explore how tidal energy works, the advantages of this technology, Japan’s commitment to renewable energy, and the impact of the AR1100 project on the future of clean power generation.

It’s obvious when a dog has been poorly trained. It doesn’t respond properly to commands. It pushes boundaries and behaves unpredictably. The same is true with a poorly trained artificial intelligence (AI) model. Only with AI, it’s not always easy to identify what went wrong with the training.

Research scientists globally are working with a variety of AI models that have been trained on experimental and theoretical data. The goal: to predict a material’s properties before taking the time and expense to create and test it. They are using AI to design better medicines and industrial chemicals in a fraction of the time it takes for experimental trial and error.

But how can they trust the answers that AI models provide? It’s not just an academic question. Millions of investment dollars can ride on whether AI model predictions are reliable.

The resuspension of seafloor sediments—triggered by human activities such as bottom trawling as well as natural processes like storms and tides—can significantly increase the release of carbon dioxide (CO2) into the atmosphere. When these sediments are exposed to oxygen-rich seawater, large-scale oxidation of pyrite occurs.

This reaction plays a much greater role in CO2 emissions than previously assumed, exceeding the contribution from the of . A new study, published in Communications Earth & Environment, provides the first quantitative evidence of this effect in the western Baltic Sea.

“Fine-grained, muddy sediments are important reservoirs of organic carbon and pyrite,” says lead author Habeeb Thanveer Kalapurakkal, a Ph.D. student in the Benthic Biogeochemistry working group at GEOMAR.

A study conducted by CNRS researchers describes a new method of recycling silicone waste (caulk, sealants, gels, adhesives, cosmetics, etc.). It has the potential to significantly reduce the sector’s environmental impacts.

This is the first universal recycling process that brings any type of used silicone material back to an earlier state in its where each molecule has only one silicon atom. And there is no need for the currently used to design new silicones. Moreover, since it is chemical and not mechanical recycling, the reuse of the material can be carried out infinitely.

The associated study is published in Science.

To learn more about the nature of matter, energy, space, and time, physicists smash high-energy particles together in large accelerator machines, creating sprays of millions of particles per second of a variety of masses and speeds. The collisions may also produce entirely new particles not predicted by the standard model, the prevailing theory of fundamental particles and forces in our universe. Plans are underway to create more powerful particle accelerators, whose collisions will unleash even larger subatomic storms. How will researchers sift through the chaos?

The answer may lie in . Researchers from the U.S. Department of Energy’s Fermi National Accelerator Laboratory (Fermilab), Caltech, NASA’s Jet Propulsion Laboratory (which is managed by Caltech), and other collaborating institutions have developed a novel high-energy particle detection instrumentation approach that leverages the power of quantum sensors—devices capable of precisely detecting single particles.

“In the next 20 to 30 years, we will see a in particle colliders as they become more powerful in energy and intensity,” says Maria Spiropulu, the Shang-Yi Ch’en Professor of Physics at Caltech.

Could the seismic signal of an underground nuclear test explosion be “hidden” by the signal generated by a natural earthquake?

It’s possible, according to a new review article published in the Bulletin of the Seismological Society of America that contradicts the conventional wisdom about “masking.”

The new analysis by Joshua Carmichael and colleagues at Los Alamos National Laboratory found that advanced signal detector technology that can identify a 1.7-ton buried explosion with a 97% success rate only has a 37% when from that explosion are hidden within the seismic waveforms of an earthquake that happens within 100 seconds and about 250 kilometers away from the explosion.