Caltech physicists have created the largest qubit array ever assembled: 6,100 neutral-atom qubits trapped in a grid by lasers. Previous arrays of this kind contained only hundreds of qubits.   

Led by Professor Bartosz A. GRZYBOWSKI, researchers at the Center for Robotized and Algorithmic Synthesis (CARS) within the Institute for Basic Science (IBS) in Ulsan, South Korea, put their robots to the challenge and extend the traditional view of chemical reactions. Historically, such reactions have been represented as one-line formulas describing the conversion of substrates into a desired and rigidly defined major product, with byproducts acknowledged but undesirable and generally considered unproductive. The CARS work, to be published in Nature on Sept 24, tells us that reactions should be thought of as complex networks programmable to yield different products under different conditions.

Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the local rules that govern interactions among individuals. The approach specifies when an ordered state should appear from random initial conditions and tunes geometric features (average radius, cluster size, flock size). Furthermore, trained on published GPS trajectories of real pigeons (Nagy et al., 2010), the model uncovers interaction mechanisms observed in real flocks.

Sea foam is a common sight along the coastline as breaking waves churn up air and algae. Now, a study in ACS’ Environmental Science & Technology reports that sea foam from several beaches along North Carolina’s coast contain higher levels of per- and polyfluoroalkyl substances (PFAS) compared to the water below. Some foam samples had more PFAS than what is allowed in drinking water, highlighting the need to clean up and reduce environmental PFAS pollution.

A team of researchers from the University of Science and Technology of China and the Zhongguancun Institute of Artificial Intelligence has developed SciGuard, an agent-based safeguard designed to control the misuse risks of AI in chemical science. By combining large language models with principles and guidelines, external knowledge databases, relevant laws and regulations, and scientific tools and models, SciGuard ensures that AI systems remain both powerful and safe, achieving state-of-the-art defense against malicious use without compromising scientific utility. This study not only highlights the dual-use potential of AI in high-stakes science, but also provides a scalable framework for keeping advanced technologies aligned with human values.