Lifeboat Foundation

MIT researchers have developed a computational approach that makes it easier to predict mutations that will lead to optimized proteins, based on a relatively small amount of data. Credit: MIT News; iStock.

MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.

To engineer proteins with useful functions, researchers usually begin with a natural protein that has a desirable function, such as emitting fluorescent light, and put it through many rounds of random mutation that eventually generate an optimized version of the protein.

The advance offers a way to characterize a fundamental resource needed for quantum computing.

Entanglement is a form of correlation between quantum objects, such as particles at the atomic scale. This uniquely quantum phenomenon cannot be explained by the laws of classical physics, yet it is one of the properties that explains the macroscopic behavior of quantum systems.

Because entanglement is central to the way quantum systems work, understanding it better could give scientists a deeper sense of how information is stored and processed efficiently in such systems.

A novel mathematical technique from the University of Surrey now simplifies space mission planning by mapping efficient routes, akin to a subway map, potentially revolutionizing travel to the Moon and beyond.

Just as sat-nav did away with the need to argue over the best route home, scientists from the University of Surrey have developed a new method to find the optimal routes for future space missions without the need to waste fuel.

The new method uses mathematics to reveal all possible routes from one orbit to another without guesswork or using enormous computer power.

The organic electrochemical transistor stands out as a tool for constructing powerful biosensors owing to its high signal transduction ability and adaptability to various geometrical forms. However, the performance of organic electrochemical transistors relies on stable and seamless interfaces with biological systems. This Review examines strategies to improve and optimize interfaces between organic electrochemical transistors and various biological components.

Massive wafer scale ‘chips’ to become even more formidable.

The company is already the industry leader when it comes to gate-all-around transistors, but so far it’s yet to really make a dent in TSMC’s market share.

Hubble Network has become the first company in history to establish a Bluetooth connection directly to a satellite — a critical technology validation for the company, potentially opening the door to connecting millions more devices anywhere in the world.

The Seattle-based startup launched its first two satellites to orbit on SpaceX’s Transporter-10 rideshare mission in March; since that time, the company confirmed that it has received signals from the onboard 3.5mm Bluetooth chips from over 600 kilometers away.

The sky is truly the limit for space-enabled Bluetooth devices: The startup says its technology can be used in markets including logistics, cattle tracking, smart collars for pets, GPS watches for kids, car inventory, construction sites and soil temperature monitoring. Haro said the low-hanging fruit is those industries that are desperate for network coverage even once per day, like remote asset monitoring for the oil and gas industry. As the constellation scales, Hubble will turn its attention to sectors that may need more frequent updates, like soil monitoring, to continuous coverage use cases like fall monitoring for the elderly.

TSMC has announced a new process for 2026 that seems to be a direct attack on Intel. As we all know, Intel’s first Angstrom node is Intel 20A, to be followed by Intel 18A. In a move reminiscent of a disposable razor commercial, TSMC has announced a new process called “A16” for 2026—which, as you can see, has a lower number than Intel’s competing nodes. It will also be the first TSMC process to offer backside power delivery, which Intel will also deliver with its Angstrom nodes.

TSMC unveiled the A16 process at its North America Technology Symposium in Santa Clara this week. Notably, Intel has its headquarters in Santa Clara, so this is like TSMC standing on the company’s front lawn and yelling, “You want some of this?!” The A16 process will follow the company’s 2nm node and feature nanosheet gate-all-around (GAA) transistors along with backside power delivery, which it calls Super Power Rail architecture. TSMC says A16 will offer 8–10% more performance than N2P at the same power or enable a 15–20% reduction in power requirements with the same performance. It will also feature a 1.1x increase in density.

QUIONE, a unique quantum-gas microscope developed by ICFO researchers in Spain, utilizes strontium to simulate complex quantum systems and explore materials at the atomic level. It aims to solve problems beyond current computational capabilities and has already demonstrated phenomena like superfluidity.

Quantum physics needs high-precision sensing techniques to delve deeper into the microscopic properties of materials. From the analog quantum processors that have emerged recently, the so-called quantum-gas microscopes have proven to be powerful tools for understanding quantum systems at the atomic level. These devices produce images of quantum gases with very high resolution: they allow individual atoms to be detected.

Development of QUIONE.