Physics-constrained machine learning for the inverse design of multifunctional composites
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 3-Nov-2026 06:16 ET (3-Nov-2026 11:16 GMT/UTC)
The novel physics-constrained AI framework PHICS realizes a full closed loop spanning multiscale inverse design and experimental validation. Leveraging interface, phase, and carrier engineering, PHICS breaks long-standing material trade-offs to yield composite phase-change materials that achieve simultaneous enhancements in thermal conductivity and electrical insulation while maintaining high thermal storage density, paving new pathways for designing advanced electronic thermal management materials.
Embodied AI can act in the physical world, but the purpose guiding its actions often remains buried in prompts, rewards or predefined goals. In a Review published in National Science Review, Nanning Zheng proposes Intent-Driven Embodied Artificial Intelligence (IDEAI), a four-layer framework built around explicit, revisable and verifiable intent. Seven technical pillars map how that intent could shape knowledge, planning, safety and value alignment in real-world systems.
No-code biological modeling: BSC researchers developed open-access tools (MCP servers) that connect AI agents with specialized computational biology software, allowing complex multicellular models to be built through simple conversation.
From months to 10 minutes: The framework enables experimental biologists to generate initial 3D tumor digital twin prototypes in under 10 minutes without writing a single line of code or mastering complex software.
Accelerating cancer research: Published in npj Systems Biology and Applications, the study demonstrates how targeted, iterative AI interactions ensure reproducibility, paving the way for AI-assisted modeling of complex diseases.
A study in Geodesy and Geodynamics used satellite radar to examine the November 2025 Hayli Gubbi eruption in Ethiopia’s Afar Depression. Researchers combined NISAR’s left-looking radar with Sentinel-1’s right-looking observations to reconstruct three-dimensional ground movement. Although the eruption occurred at Hayli Gubbi, the strongest deformation was detected at Erta Ale, where the summit crater partially collapsed and the ground sank inward. Modeling linked this to two shallow dikes beneath Erta Ale, both about 1 km deep. The event also reactivated nine nearby faults. Compared with a larger eruption earlier in 2025, the November event was more localized and relied mainly on shallow magma storage.
The Korea Research Institute of Chemical Technology (KRICT; President SeokminShin) is joining forces with the SK Innovation Institute of Environmental Science & Technology (SKI; President Pilseok Kim) to develop next-generation cooling materials and technologies aimed at reducing the rapidly growing power consumption of artificial intelligence (AI) data centers.
Now, a team of researchers from the University of Macau's Department of Electromechanical Engineering and Centre for Artificial Intelligence and Robotics has published (DOI: 10.1016/j.esci.2026.100549) a comprehensive perspective on this very question. In the journal eScience (Volume 6, Issue 4, July 2026), the team lays out a roadmap for achieving embodied intelligence in insect‑scale robots—charting a course from laboratory prototypes to practical, intelligent systems.