A fundamental link between two counterintuitive phenomena in spin glasses— reentrance and temperature chaos—has been mathematically proven for the first time. By extending the Edwards–Anderson model to include correlated disorder, researchers at Science Tokyo and Tohoku University provided the first rigorous proof that reentrance implies temperature chaos. The breakthrough enhances understanding of disordered systems and could advance applications in machine learning and quantum technologies, where controlling disorder and errors is crucial.

An out-of-this-world idea: placing data centres in space could pave the way for sustainable computing with unlimited solar energy and free cooling, says scientists from Nanyang Technological University, Singapore (NTU Singapore). The researchers outline a practical path to building carbon-neutral data centres in Low Earth Orbit (LEO), a concept particularly relevant to land-scarce cities like Singapore, where limited land and high real estate costs make conventional data centres increasingly expensive. Published in the peer-reviewed journal Nature Electronics, the study presents a framework for how satellites equipped with advanced processors could serve as orbital edge and cloud data centres. The new paper asserts that space offers two unparalleled environmental advantages, virtually unlimited solar energy and natural radiative cooling enabled by the extreme cold temperatures. In addition, virtual models show that solar-powered orbital data centres could offset their launch emissions within a few years of operation.

Collaborating authors include Professor Joshua Agar (Drexel University), Professors Chris Wolverton and Peter Voorhees (Northwestern University), Professor Peter Littlewood (University of St Andrews), and Professor Sergei Kalinin (University of Tennessee).

Paper Title: Artificial Intelligence for Materials Discovery, Development, and Optimization

The era has arrived in which artificial intelligence (AI) autonomously imagines and predicts the structures and properties of new materials. Today, AI functions as a researcher’s “second brain,” actively participating in every stage of research, from idea generation to experimental validation.