Lifeboat Foundation

A groundbreaking study reveals that Rhizobia bacteria can fix nitrogen in partnership with marine diatoms, a discovery that could have significant implications for agriculture and marine ecosystems.

Nitrogen is an essential component of all living organisms. It is also the key element controlling the growth of crops on land, as well as the microscopic oceanic plants that produce half the oxygen on our planet.

Atmospheric nitrogen gas is by far the largest pool of nitrogen, but plants cannot transform it into a usable form. Instead, crop plants like soybeans, peas and alfalfa (collectively known as legumes) have acquired Rhizobial bacterial partners that “fix” atmospheric nitrogen into ammonium. This partnership makes legumes one of the most important sources of proteins in food production.

New 3D printing method produces commercial grade microlenses with smooth surfaces, which could advance optical device design.

Researchers in Canada have developed a new 3D printing method called blurred tomography that can rapidly produce microlenses with commercial-level optical quality. The new method may make it easier and faster to design and fabricate a variety of optical devices.

“We purposely added optical blurring to the beams of light used for this 3D printing method to manufacture precision optical components,” said Daniel Webber from the National Research Council of Canada. “This enables production of optically smooth surfaces.”

Superfast levitating trains, long-range lossless power transmission, faster MRI machines—all these fantastical technological advances could be in our grasp if we could just make a material that transmits electricity without resistance—or “superconducts”—at around room temperature.

Like many good ideas in science, it started with a walk in the woods. During a stroll through the Berlin Botanic Garden in 2019, HHMI Janelia Research Campus Group Leader Jan Funke and some of his scientific colleagues started chatting about a familiar topic: How to get more information out of insect connectomes.

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.

Recent experiments might have finally confirmed the existence of glueballs, particles made entirely of gluons.

“We employed this configuration for the first time to characterize the signal field emerging from a resonantly excited plasmonic sample,” says Francesca Calegari, lead scientist at DESY, physics Professor at Universität Hamburg and a spokesperson of the Cluster of Excellence “CUI: Advanced Imaging of Matter.”

The difference of the reconstructed pulse with plasmon interaction to the reference pulse allowed the scientists to trace the emergence of the plasmon and its fast decay which they confirmed by electrodynamic model calculations.

“Our approach can be used to characterize arbitrary plasmonic samples in ambient conditions and in the far-field,” adds CUI scientist Prof. Holger Lange. Additionally, the precise characterization of the laser field emerging from nanoplasmonic materials could constitute a new tool to optimize the design of phase-shaping devices for ultrashort laser pulses.

Artificial intelligence (AI) has progressed at an astounding pace over the last few years. Some scientists are now looking towards the development of artificial superintelligence (ASI) – a form of AI that would not only surpass human intelligence but would not be bound by the learning speeds of humans.

But what if this milestone isn’t just a remarkable achievement? What if it also represents a formidable bottleneck in the development of all civilizations, one so challenging that it thwarts their long-term survival?

This idea is at the heart of a research paper I recently published in Acta Astronautica. Could AI be the universe’s “great filter” – a threshold so hard to overcome that it prevents most life from evolving into space-faring civilizations?

By analyzing images made of colored dots created by quantum simulators, ETH researchers have studied a special kind of magnetism. In the future this method could also be used to solve other physics puzzles, for instance in superconductivity.