Caption: MIT researchers have demonstrated a 3D-printed plasma sensor for orbiting spacecraft that works just as well as much more expensive, semiconductor sensors. These durable, precise sensors could be used effectively on inexpensive, lightweight satellites known as CubeSats, which are commonly utilized for environmental monitoring or weather prediction. Credits:Figure courtesy of the researchers and edited by MIT News
Cheap and quick to produce, these digitally manufactured plasma sensors could help scientists predict the weather or study climate change.
MIT scientists have created the first completely digitally manufactured plasma sensors for orbiting spacecraft...
Researchers at Oxford University’s Department of Materials, working in collaboration with colleagues from Exeter and Munster, have developed an on-chip optical processor capable of detecting similarities in datasets up to 1,000 times faster than conventional machine learning algorithms running on electronic processors.
The new research published in Optica took its inspiration from Nobel Prize laureate Ivan Pavlov’s discovery of classical conditioning. In his experiments, Pavlov found that by providing another stimulus during feeding, such as the sound of a bell or metronome, his dogs began to link the two experiences and would salivate at the sound alone...
A new study shows that nickel oxide superconductors, which conduct electricity with no loss at higher temperatures than conventional superconductors do, contain a type of quantum matter called charge density waves, or CDWs, that can accompany superconductivity.
The presence of CDWs shows that these recently discovered materials, also known as nickelates, are capable of forming correlated states — “electron soups” that can host a variety of quantum phases, including superconductivity, researchers from the Department of Energy’s SLAC National Accelerator Laboratory and Stanford University reported in Nature Physics today.
“Unlike in any other superconductor we know about, CDWs appear even before we dope the material by replacing some atoms with others to change the number of elect...
Patients are 20% less likely to die of sepsis because a new AI system developed at Johns Hopkins University catches symptoms hours earlier than traditional methods, an extensive hospital study demonstrates.
The system, created by a Johns Hopkins researcher whose young nephew died from sepsis, scours medical records and clinical notes to identify patients at risk of life-threatening complications. The work, which could significantly cut patient mortality from one of the top causes of hospital deaths worldwide, is published today in Nature Medicine and npj Digital Medicine.
“It is the first instance where AI is implemented at the bedside, used by thousands of providers, and where we’re seeing lives saved,” said Suchi Saria, founding research director of the Malone Center for Engin...
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