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Researchers at MIT and elsewhere have significantly boosted the output from a system that can extract drinkable water directly from the air even in dry regions, using heat from the sun or another source.

The system, which builds on a design initially developed three years ago at MIT by members of the same team, brings the process closer to something that could become a practical water source for remote regions with limited access to water and electricity. The findings are described today in the journal Joule, in a paper by Professor Evelyn Wang, who is head of MIT’s Department of Mechanical Engineering; graduate student Alina LaPotin; and six others at MIT and in Korea and Utah.

The earlier device demonstrated by Wang and her co-workers provided a proof of concept for the system, which harnesses a temperature difference within the device to allow an adsorbent material — which collects liquid on its surface — to draw in moisture from the air at night and release it the next day. When the material is heated by sunlight, the difference in temperature between the heated top and the shaded underside makes the water release back out of the adsorbent material. The water then gets condensed on a collection plate.

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Researchers have developed a method to ‘squeeze’ visible light in order to see inside tiny memory devices. The technique will allow researchers to probe how these devices break down and how their performance can be improved for a range of applications.

The team, led by the University of Cambridge, used the technique to investigate the materials used in random access memories, while in operation. The results, reported in the journal Nature Electronics, will allow detailed study of these materials, which are used in devices.

The ability to understand how structural changes characterize the function of these materials, which are used for , ultra-responsive devices called memristors, is important to improve their performance. However, looking inside the 3D nanoscale devices is difficult using traditional techniques.

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Chemical space contains every possible chemical compound. It includes every drug and material we know and every one we’ll find in the future. It’s practically infinite and can be frustratingly complex. That’s why some chemists are turning to artificial intelligence: AI can explore chemical space faster than humans, and it might be able to find molecules that would elude even expert scientists. But as researchers work to build and refine these AI tools, many questions still remain about how AI can best help search chemical space and when AI will be able to assist the wider chemistry community.

Outer space isn’t the only frontier curious humans are investigating. Chemical space is the conceptual territory inhabited by all possible compounds. It’s where scientists have found every known medicine and material, and it’s where we’ll find the next treatment for cancer and the next light-absorbing substance for solar cells.

But searching chemical space is far from trivial. For one thing, it might as well be infinite. An upper estimate says it contains 10180 compounds, more than twice the magnitude of the number of atoms in the universe. To put that figure in context, the CAS database—one of the world’s largest—currently contains about 108 known organic and inorganic substances, and scientists have synthesized only a fraction of those in the lab. (CAS is a division of the American Chemical Society, which publishes C&EN.) So we’ve barely seen past our own front doorstep into chemical space.

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