A core-shell Pd@CeO₂/γ-Al₂O₃ catalyst improves exhaust treatment for stoichiometric natural gas vehicles by promoting lower-temperature CH₄ and NO conversion and strong hydrothermal stability. The design lowers reaction barriers at Pd-CeO₂ interfaces and retains high activity after severe aging. After aging at 800 °C for 16 hours, the catalyst showed only minor losses in CH₄ and NO conversion over a 100-hour test, offering a promising route to cleaner and more durable NGV aftertreatment.

As competition among the world’s leading ports intensifies, ports must become not only bigger and faster, but also smarter, more resilient and more sustainable. Singapore’s ability to stay ahead depends on how well it plans, models and optimises increasingly complex port systems. At the Centre of Excellence in Modelling and Simulation for Next Generation Ports (C4NGP) at the College of Design and Engineering at NUS research in digital twins, simulation and decision-support tools is helping shape the future of Singapore’s port ecosystem. Working closely with government agencies and industry partners, C4NGP supports evidence-based planning across port design, operations, resilience and sustainability, contributing to initiatives such as Singapore’s Maritime Digital Twin and long-term low-carbon port development. Learn how research and innovation are helping prepare Singapore’s ports for the future.

A team of researchers from the North China Electric Power University and the National Institute of Metrology in China has published a perspective on a promising class of materials for extracting uranium from aqueous environments. Their work details the design and application of heterocyclic-linked covalent organic frameworks (COFs), which use light to perform this critical task. This approach holds significant potential for both cleaning up contaminated water sources and securing a sustainable supply of uranium, the primary fuel for nuclear energy, by extracting it from seawater.

The dual need for environmental remediation and resource security has spurred the development of new technologies for uranium capture. Traditional methods face challenges with selectivity and capacity. The authors explain that photocatalysis offers a distinct advantage by using light to trigger specific redox reactions, reducing soluble and mobile uranium (U(VI)) into insoluble and immobile forms (U(IV)). The success of this technique depends on creating highly efficient photocatalysts. The focus of this perspective is on COFs, which are crystalline, porous materials built from organic molecules linked by strong covalent bonds.

Researchers at KAIST have demonstrated a chip-scale photonic approach for generating ultralow-noise and highly stable microwave and millimeter-wave signals based on optical frequency combs (microcombs), offering a potential pathway toward compact, high-performance frequency sources for next-generation technologies.

High-frequency signals in the tens to hundreds of gigahertz range are essential for emerging applications such as 6G communications, radar, and precision sensing. However, achieving both low noise and high stability at these frequencies remains a fundamental challenge for conventional electronic signal sources.

CAMBRIDGE, Mass. - April 29, 2026. Researchers at the Massachusetts Institute of Technology have introduced Bioinspired123D, a generative AI system that translates plain-English design descriptions into executable 3D geometries inspired by biological materials, from crab exoskeletons to horse hoof walls. The work, published in AI for Science, shows that controllable, high-fidelity 3D generation for scientific design does not require massive 3D foundation models.

Developed by graduate student Rachel K. Luu and Professor Markus J. Buehler in MIT's Laboratory for Atomistic and Molecular Mechanics (LAMM), the system departs from mainstream text-to-3D methods that rely on meshes, voxels, or point clouds. Instead, Bioinspired123D generates compact Blender Python scripts — programs that, when executed, produce parametric, smooth, and fabricable structures. This "code-as-geometry" representation makes the resulting designs interpretable, editable, and ready for downstream simulation or 3D printing.

"Biological materials encode an extraordinary amount of design intelligence in their geometry - helicoidal plies in stomatopod clubs, gradient porosity in horse hooves, cellular cores in bird beaks," said Buehler, the McAfee Professor of Engineering at MIT and senior author of the paper. "We wanted to build a system that can take that intuition, expressed in natural language, and turn it directly into structures you can fabricate, without needing a supercomputer to do it."