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A Rice University-led study is forcing physicists to rethink superconductivity in uranium ditelluride, an A-list material in the worldwide race to create fault-tolerant quantum computers.

Uranium ditelluride crystals are believed to host a rare “spin-triplet” form of superconductivity, but puzzling experimental results published this week in Nature have upended the leading explanation of how the could arise in the material. Neutron-scattering experiments by physicists from Rice, Oak Ridge National Laboratory, the University of California, San Diego and the National High Magnetic Field Laboratory at Florida State University revealed telltale signs of antiferromagnetic spin fluctuations that were coupled to superconductivity in uranium ditelluride.

Spin-triplet superconductivity has not been observed in a solid-state material, but physicists have long suspected it arises from an ordered state that is ferromagnetic. The race to find spin-triplet materials has heated up in recent years due to their potential for hosting elusive quasiparticles called Majorana fermions that could be used to make error-free quantum computers.

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Tsinghua Unigroup Co, one of China’s biggest semiconductor giants and a key server supplier to the Chinese government entities is burdened with debt default.

The Chinese Communist Party (CCP) yet again finds itself in the middle of a battle with the private sector and tech entrepreneurs. This time over the all-important semiconductors. Tsinghua Unigroup Co., one of China’s biggest semiconductor giants and a key server supplier to the Chinese government entities, is burdened with debt defaults and undergoing rescue process.

Without naming the CCP, Zhao is promising to stand up to Communist Party leadership. In Xi’s enterprise-hating China, a private entity doesn’t simply rise out of nowhere and take over a leading semiconductor giant. And if any entity can dare to do that, it must be having the informal backing of the Communist Party.

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Solar and wind resources are the lowest marginal cost sources of electricity in most of the world. Solar, wind, and other forms of green energy produce power as and when it’s available. And as the world starts to transition away from cheap, responsive, and heavily polluting energy sources like coal, the electric grid now faces a challenge: how to manage the multi-day variability of renewable energy, even in periods of multi-day weather events, without sacrificing energy reliability or affordability.

In 2017, Tesla built and installed the world’s largest lithium-ion battery at Hornsdale in South Australia, which was a huge success. But there are inherent issues with lithium batteries; they are expensive, better suited to quick turnaround than long-term storage.

However, Form Energy is focused on developing low-cost energy storage technology to enable a reliable, secure, and fully renewable electric grid year-round. The Massachusetts-based startup recently unveiled a new rechargeable iron-air battery capable of delivering electricity for 100 hours at system costs competitive with conventional power plants and at less than 1/10th the cost of lithium-ion.

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Revolutionary new electronic components can be adapted to perform very different tasks – a technology perfectly suited for artificial intelligence.

Normally, computer chips consist of electronic components that always do the same thing. In the future, however, more flexibility will be possible: New types of adaptive transistors can be dynamically switched during run-time to perform different logical tasks. This fundamentally changes the possibilities of chip design and opens up completely new opportunities in the field of artificial intelligence, neural networks or even logic that works with more values than just 0 and 1.

In order to achieve this, scientists at TU Wien (Vienna) did not rely on the usual silicon technology, but on germanium. This was a success: The most flexible transistor in the world has now been produced using germanium. It has been presented in the journal ACS Nano. The special properties of germanium and the use of dedicated program gate electrodes made it possible to create a prototype for a new component that may usher in a new era of chip technology.

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Would you trust AI that has been trained on synthetic data, as opposed to real-world data? You may not know it, but you probably already do — and that’s fine, according to the findings of a newly released survey.

The scarcity of high-quality, domain-specific datasets for testing and training AI applications has left teams scrambling for alternatives. Most in-house approaches require teams to collect, compile, and annotate their own DIY data — further compounding the potential for biases, inadequate edge-case performance (i.e. poor generalization), and privacy violations.

However, a saving grace appears to already be at hand: advances in synthetic data. This computer-generated, realistic data intrinsically offers solutions to practically every item on the list of mission-critical problems teams currently face.

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Danish energy firm Orsted has announced that its Hornsea 2 offshore wind farm generated its first power, representing a significant milestone in the facility’s development.

When fully operational, Hornsea 2’s wind turbines will be capable of generating 1.32 GW of clean electricity – taking the title of ‘world’s largest operating offshore wind farm‘from its sibling project, Hornsea 1. Together, the two projects will be capable of providing enough power for well over 2.3 million homes.

Located 89 km off the UK’s east coast, the Hornsea 2 achieved its first power after its offshore substation (OSS), the world’s largest offshore AC substation, and reactive compensation station (RCS), were installed in late October 2021. Since that time, Ørsted and its partner companies have been working hard to commission and energize the wind farm in preparation for its anticipated operational date next year.

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Traditional robots can have difficulty grasping and manipulating soft objects if their manipulators are not flexible in the way elephant trunks, octopus tentacles, or human fingers can be.

In Applied Physics Reviews, investigators from Shanghai Jiao Tong University in China developed a type of multiple-segment soft manipulator inspired by these . The soft manipulators are based on pneu-nets, which are pneumatically actuated elastomeric structures.

These structures have a tentaclelike shape and consist of a series of connected internal chambers which can be inflated pneumatically, blowing them up like a balloon. One side of the tentacle is highly flexible while the other is stiffer. Increasing air pressure to the chambers causes the to bend toward the stiff side.

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as well as the defense industrial base, called the Joint University Microelectronics Program 2.0 or JUMP 2.0. The program will support high-risk, high-payoff research that addresses existing and emerging challenges in information and communication technologies (ICT). JUMP 2.0 builds on the agency’s history of supporting long-term, pathfinding university research through public-private partnerships that drive disruption in #microelectronics. https://www.darpa.mil/news-events/2021-12-22

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