Liquid metal dealloying creates nanoporous silicon carbide at just 800°C
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Oct-2026 03:16 ET (22-Oct-2026 07:16 GMT/UTC)
In the International Journal of Extreme Manufacturing, Prof. Yang Li at Zhejiang University and his co-workers developed a dual-sided stencil printing technique that packs high-capacity energy storage into electrode tracks just 80 μm wide by giving a tungsten stencil two distinct physical personalities—a dual-sided "Janus mask" named after the two-faced Roman god.
Cardiovascular medicine is inherently multimodal, but the data available at the clinical decision point are rarely as complete or as synchronized as benchmark evaluations assume. Recent reviews identify incomplete datasets, heterogeneous data characteristics, and missing modalities as persistent barriers to multimodal clinical AI. A correspondence published in Medicine Discovery argues that the central problem is not how to fuse more data, but how to reason when clinically relevant data are incomplete, temporally misaligned, or no longer representative of the patient's current state. The authors distinguish five linked but non-equivalent problems — conventional multimodal fusion, robustness to missing modalities, temporally aware modeling, uncertainty-aware selective prediction, and clinically informed interpretation of why a modality is unavailable — and treat modality availability as an observation state rather than a data defect. They define deferral operationally, separate it from calibration, uncertainty estimation, and distribution-shift detection, propose hybrid deferral rules that combine non-compensatory clinical hard stops with graded model-derived signals, and set out five candidate conditions for an intended-use-specific minimum evaluation suite. The framework is offered as a complement to existing clinical AI guidance (TRIPOD+AI, PROBAST+AI, FUTURE-AI, DECIDE-AI, CONSORT-AI, SPIRIT-AI) rather than a replacement, and as a conceptual proposal requiring prospective evaluation and multi-stakeholder consensus.
KAIST, Caltech, and Nanyang Technological University (NTU) in Singapore develop “BeetleBot,” a soft robot based on artificial muscles. The robot combines walking and object gripping with visual and tactile sensing, so users can steer it while checking camera images and contact information. In demonstrations, the robot avoided obstacles and picked up and carried a target object, which lays the groundwork for soft robots used in remote tasks.
Researchers have developed a new electrochemical sensor for rapidly and accurately detecting a naturally occurring compound widely used in the food, beverage and fragrance industries.
The first Europe-wide expert working group on Artificial Intelligence in mental health launches today to the ECNP congress in Munich, where the group will host an open discussion, setting out the potential, the problems, and possible directions for AI in psychiatry and neuroscience. Going forward, the group will set out plans to guide the regulation and development of artificial intelligence (AI) in mental health in Europe.
For decades, physicists have sought a practical two-dimensional topological insulator: an ultrathin material whose interior blocks electricity but whose edges conduct it. In ordinary wires, electrons constantly bounce off imperfections, losing energy. But along the edges of a 2D topological insulator, electrons with opposite spins travel in opposite directions, like cars in one-way lanes, so they rarely scatter and lose energy. Now, researchers at the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) have shown that ultrathin films of bismuth telluride are such a material. The work, published in ACS Nano, used a new approach to produce a uniform-thickness bismuth telluride film and confirm theoretical predictions about the material’s properties.