Lifeboat Foundation

Non-metal nitrides are compounds in which nitrogen and non-metallic elements are linked by covalent bonds. Because of their technologically interesting properties, they have increasingly become the focus of materials research. In Chemistry—A European Journal, an international team with researchers from the University of Bayreuth presents previously unknown phosphorus-nitrogen compounds synthesized under very high pressures.

They contain structural units whose existence could not be empirically proven before. The study exemplifies the great, as yet untapped potential of high-pressure research for nitrogen chemistry.

The researchers succeeded in synthesizing a previously unknown modification of the phosphorus nitride P₃N₅, the polymorph δ-P₃N₅, at a pressure of 72 gigapascals. At 134 gigapascals, the phosphorus nitride PN₂ formed in the diamond anvil cell. Both compounds are classified as ultra-incompressible materials with the bulk moduli above 320 GPa.

Finally, there’s a solution for the hard-to-reach small intestine.

Imagine if we could power devices inside the body. This would lead to major developments in biomedical research and much potential for new applications in chemical sensors, drug-delivery systems and electrical stimulation devices.

Now, Binghamton University researchers have invented a capsule-sized biobattery they believe may be a solution for the hard-to-reach small intestine, according to a press release by the institution published on Thursday.

One of the most enduring human mysteries is why we possess sentient awareness, a paradox known to science as the “hard problem of consciousness.”

At the physiological level, we have a good understanding that consciousness is driven by electrical impulses and chemical signals between neurons in the brain. Though precisely what regions of the brain are responsible for thoughtful experience is still a matter of debate.

However, scientists still do not understand why the same essential elements of the universe can come together to form an inanimate object like a rock or a highly complex organic structure like the human brain.

Researchers at Japan’s National Institute for Materials Science (NIMS) have developed a device capable of taking hundreds of times more electrochemical measurements than conventional devices. By analyzing the device’s large amounts of data, the team has identified molecular mechanisms that enable electrogenic bacteria to efficiently generate electricity even when subjected to a wide range of electrode potentials.

This technique can also be used to analyze materials interacting with microorganisms (e.g., biodegradable plastics), potentially facilitating efforts to discover innovative microbial degradable materials.

The work was published in the journal Patterns in October, 2022.

Covering interstellar distances in a human lifetime is far from easy. Going at 1 percent of the speed of light, it would take over 400 years to reach the closest star, and we have not been able to propel any spacecraft even close to that speed. But a new method aims to get to those speeds and maybe more – and it takes inspiration from the mighty albatross.

Chemical propulsion can be very useful in achieving high speeds pretty quickly, but there’s the drawback in that you need to carry the fuel with you, which means you need to be able to generate more thrust to shift the extra fuel and so on. It’s a huge issue when it comes to rocket science. A realistic alternative is ion propulsion, used to slowly and successfully maneuver the Dawn spacecraft, but it would take an equally long time to reach enough speed with such a steady but small acceleration.

Solar sails hold a more intriguing possible approach. Proposals such as the Breakthrough Starshot see lasers used to massively accelerate a spacecraft the size of a credit card to one-fifth the speed of light. But, you need to build a very powerful laser. A similar method using sunlight might also work, although not up to such a high speed.

Amino acids have been found in meteorites, and now an experiment shows how they might have been created by chemical reactions in these space rocks.

CRISPR, the Nobel Prize-winning gene editing technology, is poised to have a profound impact on the fields of microbiology and medicine yet again.

A team led by CRISPR pioneer Jennifer Doudna and her longtime collaborator Jill Banfield has developed a clever tool to edit the genomes of bacteria-infecting viruses called bacteriophages using a rare form of CRISPR. The ability to easily engineer custom-designed phages —which has long eluded the research community —could help researchers control microbiomes without antibiotics or harsh chemicals, and treat dangerous drug-resistant infections. A paper describing the work was recently published in Nature Microbiology.

“Bacteriophages are some of the most abundant and diverse biological entities on Earth. Unlike prior approaches, this editing strategy works against the tremendous genetic diversity of bacteriophages,” said first author Benjamin Adler, a postdoctoral fellow in Doudna’s lab. “There are so many exciting directions here—discovery is literally at our fingertips.”

Researchers at Tohoku University, the University of Messina, and the University of California, Santa Barbara (UCSB) have developed a scaled-up version of a probabilistic computer (p-computer) with stochastic spintronic devices that is suitable for hard computational problems like combinatorial optimization and machine learning.

Moore’s law predicts that computers get faster every two years because of the evolution of semiconductor chips. While this is what has historically happened, the continued evolution is starting to lag. The revolutions in machine learning and artificial intelligence means much higher computational ability is required. Quantum computing is one way of meeting these challenges, but significant hurdles to the practical realization of scalable quantum computers remain.

A p-computer harnesses naturally stochastic building blocks called probabilistic bits (p-bits). Unlike bits in traditional computers, p-bits oscillate between states. A p-computer can operate at room-temperature and acts as a domain-specific computer for a wide variety of applications in machine learning and artificial intelligence. Just like quantum computers try to solve inherently quantum problems in quantum chemistry, p-computers attempt to tackle probabilistic algorithms, widely used for complicated computational problems in combinatorial optimization and sampling.

How far away could an artificial brain be? Perhaps a very long way off still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

The artificial neural networks that power today’s machine-learning algorithms are software that models a large collection of electronics-based “neurons,” along with their many connections, or synapses. Instead of representing neural networks in software, researchers think that faster, more energy-efficient AI would result from representing the components, especially the synapses, with real devices. This concept, called analog AI, requires a memory cell that combines a whole slew of difficult-to-obtain properties: it needs to hold a large enough range of analog values, switch between different values reliably and quickly, hold its value for a long time, and be amenable to manufacturing at scale.