Lifeboat Foundation

Chances are you make it through most days without sparing a thought for Antarctica. At just over 5.4 million square miles, it’s a massive chunk of land that is nearly twice the size of Australia and dwarfs the continental United States. It’s also covered in ice, which makes it a lot less appealing as a potential vacation destination.

Still, it’s of great interest to scientists and researchers, and a new mapping effort has yielded the most stunning, high-resolution glimpse of the continent ever.

Scientists have developed a photoelectrode that can harvest 85 percent of visible light in a 30 nanometers-thin semiconductor layer between gold layers, converting light energy 11 times more efficiently than previous methods.

In the pursuit of realizing a sustainable society, there is an ever-increasing demand to develop revolutionary solar cells or artificial photosynthesis systems that utilize visible light energy from the sun while using as few materials as possible.

The research team, led by Professor Hiroaki Misawa of the Research Institute for Electronic Science at Hokkaido University, has been aiming to develop a photoelectrode that can harvest visible light across a wide spectral range by using gold nanoparticles loaded on a semiconductor. But merely applying a layer of gold nanoparticles did not lead to a sufficient amount of light absorption, because they took in light with only a narrow spectral range.

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A 2011 invention made by Aalto University’s researchers has proceeded from concept to reality. Just a few years ago the researchers obtained the record efficiency of 22% in the lab for nanostructured solar cells using atomic layer deposition, and now with the help of industrial partners and joint European collaboration, the first prototype modules have been manufactured on an industrial production line.

“Our timing could not have been better” prof. Hele Savin, who led the research, was pleased to tell. Indeed, 2018 is commonly called the “Year of Black Silicon” due to its rapid expansion in the photovoltaic (PV) industry. It has enabled the use of diamond-wire sawing in multicrystalline silicon, which reduces costs and environmental impact. However, there is still plenty of room for improvement as the current black silicon used in industry consists of shallow nanostructures that leads to sub-optimal optical properties and requires a separate antireflection coating.

Aalto’s approach consists of using deep needle-like nanostructures to make an optically perfect surface that eliminates the need for the antireflection coatings. Their industrial production, however, was not an easy task. “We were worried that such a fragile structure would not survive the multi-step mass production, because of rough handling by robots or module lamination.”

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Our mission is to make air travel personal, on demand and carbon free.

New observations from NASA’s Chandra X-ray Observatory reveal a very bright source of X-rays that is likely powered by either a ring of stellar-mass black holes or neutron stars located 300 million light-years from Earth.

In some domains the two knowledge systems are complementary, but in others they might be headed for conflict.

• By Abraham Loeb on September 10, 2018

Interfacing quantum information between discrete and continuous would allow exploiting the best of both worlds, but it has been shown only for single-rail encoding. Here, the authors extend this to the more practical dual-rail encoding, realizing teleportation between a polarization qubit and a CV qubit.

Realistic climate simulations require huge reserves of computational power. An LMU study now shows that new algorithms allow interactions in the atmosphere to be modeled more rapidly without loss of reliability.

Forecasting global and local climates requires the construction and testing of mathematical climate models. Since such models must incorporate a plethora of physical processes and interactions, climate simulations require enormous amounts of computational power. And even the best models inevitably have limitations, since the phenomena involved can never be modeled in sufficient detail. In a project carried out in the context of the DFG-funded Collaborative Research Center “Waves to Weather”, Stephan Rasp of the Institute of Theoretical Meteorology at LMU (Director: Professor George Craig) has now looked at the question of whether the application of artificial intelligence can improve the efficacy of climate modelling. The study, which was performed in collaboration with Professor Mike Pritchard of the University of California at Irvine und Pierre Gentine of Columbia University in New York, appears in the journal PNAS.

General circulation models typically simulate the global behavior of the atmosphere on grids whose cells have dimensions of around 50 km. Even using state-of-the-art supercomputers the relevant physical processes that take place in the atmosphere are simply too complex to be modelled at the necessary level of detail. One prominent example concerns the modelling of clouds which have a crucial influence on climate. They transport heat and moisture, produce precipitation, as well as absorb and reflect solar radiation, for instance. Many clouds extend over distances of only a few hundred meters, much smaller than the grid cells typically used in simulations – and they are highly dynamic. Both features make them extremely difficult to model realistically. Hence today’s climate models lack at least one vital ingredient, and in this respect, only provide an approximate description of the Earth system.

A team of experts has conducted tests in mice for a potent new vaccine against melanoma. So far, the researchers have observed a 100 percent success rate.