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Blog – Page 4718

Australian researchers have developed and tested a way to electrolyze hydrogen straight out of the air, anywhere on Earth, without requiring any other fresh water source. The Direct Air Electrolyzer (DAE) absorbs and converts atmospheric moisture – even down to a “bone-dry” 4% humidity.

Such a machine could be particularly relevant to a country like Australia, which has ambitions as a clean energy exporter, along with enormous solar energy potential – but also widespread drought conditions and limited access to clean water. Decoupling hydrogen production from the need for a water supply could allow green hydrogen to be produced more or less anywhere you can ship it out from – and since water scarcity and solar potential often go hand in hand, this could prove a boon for much of Africa, Asia, India and the Middle East, too.

Chemical engineers at Melbourne University came up with what they describe as a simple design: an electrolyzer with two flat plates acting as anode and cathode. Sandwiched between the two plates is a porous material – melamine sponge, for example, or sintered glass foam. This medium is soaked in a hygroscopic ionic solution – a chemical that can absorb moisture from the air spontaneously.

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The equations of quantum mechanics provide a roadmap to predicting the properties of chemicals starting from basic scientific theories. However, these equations quickly become too expensive in terms of computer time and power when used to predict behavior in large systems. Machine learning offers a promising approach to accelerating such large-scale simulations.

Researchers have shown that machine learning models can mimic the basic structure of the fundamental laws of nature. These laws can be very difficult to simulate directly. The machine learning approach enables predictions that are easy to compute and are accurate in a wide range of chemical systems.

The improved machine learning model can quickly and accurately predict a wide range of properties of molecules (Proceedings of the National Academy of Sciences, “Deep Learning of Dynamically Responsive Chemical Hamiltonians with Semi-Empirical Quantum Mechanics”). These approaches score very well on important benchmarks in computational chemistry and show how deep learning methods can continue to improve by incorporating more data from experiments. The model can also succeed at challenging tasks such as predicting excited state dynamics—how systems behave with elevated energy levels.

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Sometimes it’s easy to miss the forest for the trees. We spend so much time on what’s in front of us, we can miss the bigger picture. Alarm bells are going off across the world. We need to hear them.

An extreme heatwave and drought has been roasting China for 70 days straight, something that “has no parallel in modern record-keeping in China, or elsewhere around the world for that matter.”

Next door, in Pakistan, a “torrential downpour of biblical proportions” has so far killed 900 people and destroyed nearly 100,000 homes. Its neighbour India has suffered 200 heatwave days this year so far, compared to just 32 last year. South Korea received it’s the heaviest hourly downpour in Seoul for 80 years, flooding the capital and leaving 50 cities and towns with landslide warnings.

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Underwater robots that peered under Antarctica’s Thwaites Glacier, nicknamed the “Doomsday Glacier,” saw that its doom may come sooner than expected with an extreme spike in ice loss. A detailed map of the seafloor surrounding the icy behemoth has revealed that the glacier underwent periods of rapid retreat within the last few centuries, which could be triggered again through melt driven by climate change.

Thwaites Glacier is a massive chunk of ice — around the same size as the state of Florida in the U.S. or the entirety of the United Kingdom — that is slowly melting into the ocean off West Antarctica (opens in new tab). The glacier gets its ominous nickname because of the “spine-chilling” implications of its total liquidation, which could raise global sea levels between 3 and 10 feet (0.9 and 3 meters), researchers said in a statement (opens in new tab). Due to climate change, the enormous frozen mass is retreating twice as fast as it was 30 years ago and is losing around 50 billion tons (45 billion metric tons) of ice annually, according to the International Thwaites Glacier Collaboration (opens in new tab).

The Thwaites Glacier extends well below the ocean’s surface and is held in place by jagged points on the seafloor that slow the glacier’s slide into the water. Sections of seafloor that grab hold of a glacier’s underbelly are known as “grounding points,” and play a key role in how quickly a glacier can retreat.

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Daniel Dennett explores the first steps towards a unified theory of information, through common threads in the convergence of evolution, learning, and engineering.
Subscribe for regular science talks: http://bit.ly/RiSubscRibe.
Watch the Q&A now: https://www.youtube.com/watch?v=beKC_7rlTuw.

Buy Daniel Dennett’s book “Intuition Pumps and Other Tools for Thinking” — https://geni.us/pAyVW

The concept of information is fundamental to all areas of science, and ubiquitous in daily life in the Internet Age. However, it is still not well understood despite being recognised for more than 40 years. In this talk, Daniel Dennett explores steps towards a unified theory of information, through common threads in evolution, learning, and engineering.

This event was the first in a series on the theme of ‘Convergence’, exploring the links between neuroscience, philosophy and artificial intelligence. If you’re in London, look out for more events later in the year: http://rigb.org/whats-on.

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