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Over the past few years, thermoelectric generators have become the focus of a growing number of studies, due to their ability to convert waste heat into electrical energy. Quantum dots, semiconductor crystals with distinctive conductive properties, could be good candidates for thermoelectric generation, as their discrete resonant levels provide excellent energy filters.

In a recent study, researchers at the University of Cambridge, in collaboration with colleagues in Madrid, Rochester, Duisburg and Sheffield, have experimentally demonstrated the potential of an autonomous nanoscale energy harvester based on resonant tunneling quantum dots. This harvester is based on previous research carried out by part of their team, who had proposed a three-terminal energy harvester based on two resonant-tunneling quantum dots with different energy levels.

The energy harvester device was realized at Cavendish Laboratory in Cambridge by a researcher called Gulzat Jaliel. The original theoretical proposal for the device, however, was introduced by Andrew Jordan in 2013, and the theoretical work behind the harvester was carried out by him in collaboration with renowned semiconductor physicist Markus Büttiker and a team of post-doctoral students in Geneva.

We’ve all heard that the future menu may involve less meat and dairy. But don’t worry, we could have customised diets, outlandish vegetables, robot chefs and guilt-free gorging to look forward to instead. And we reckon that makes up for missing out on the odd sausage.

SpaceX’s Starship prototype is coming together: Elon Musk recently teased some photos of the spacecraft and its construction site looks like something straight out of Star Wars.

The spacecraft, which serves as a prototype for SpaceX’s Mars-bound Starship, is currently under development, CNN reported. It follows the Starhopper, SpaceX’s first Starship prototype that aced a major hover test in August. Now, SpaceX is ready to build a prototype that may be able to fly into our planet’s orbit.

Droid Junkyard, Tatooine pic.twitter.com/yACFR9y04P

Researchers have made news in letting their AI ambitions play out a formidable game of hide and seek with formidable results. The agents’ environment had walls and movable boxes for a challenge where some were the hiders and others, seekers. Much happened along the way, with surprises.

Stating what was learned, the authors blogged: “We’ve observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek,” where the agents built “a series of six distinct strategies and counterstrategies, some of which we did not know our environment supported.”

Continue reading “AI: Agents show surprising behavior in hide and seek game” »

A team of scientists has developed a computational model that uses artificial intelligence to find sites for hydropower dams in order to help reduce greenhouse gas emissions.

Hydropower dams can provide large quantities of energy with carbon footprints as low as sources like solar and wind. But because of how they’re formed, some dams emit dangerously high levels of greenhouse gases, threatening sustainability goals.

With hundreds of hydropower dams currently proposed for the Amazon basin—an ecologically sensitive area covering more than a third of South America—predicting their greenhouse emissions in advance could be critical for the region, and the planet.

A new class of chemical instrumentation seeks to alleviate the tedium and complexity of organic syntheses.

Billionaire company founder Elon Musk tweeted a pair of photos this week apparently showing progress on one of the Starship prototypes SpaceX is currently developing.

SpaceX has said it plans to use the rockets to shuttle passengers and cargo across the planet or beyond it.

“Droid Junkyard, Tatooine,” Musk wrote in the first tweet, making a joking “Star Wars” reference.

NASA is on a mission to go back to the moon by 2024 and use it as a “backyard” of experimentation, according to Lucien Junkin, chief engineer of the space exploration vehicle at NASA.

ABC toured NASA’s Johnson Space Center’s robotics design area: https://abcn.ws/2AleGSQ

Wave function represents the quantum state of an atom, including the position and movement states of the nucleus and electrons. For decades researchers have struggled to determine the exact wave function when analyzing a normal chemical molecule system, which has its nuclear position fixed and electrons spinning. Fixing wave function has proven problematic even with help from the Schrödinger equation.

Previous research in this field used a Slater-Jastrow Ansatz application of quantum Monte Carlo (QMC) methods, which takes a linear combination of Slater determinants and adds the Jastrow multiplicative term to capture the close-range correlations.

Now, a group of DeepMind researchers have brought QMC to a higher level with the Fermionic Neural Network — or Fermi Net — a neural network with more flexibility and higher accuracy. Fermi Net takes the electron information of the molecules or chemical systems as inputs and outputs their estimated wave functions, which can then be used to determine the energy states of the input chemical systems.