Ateneo futurists envision AI-powered food stalls, sari-sari stores
Peer-Reviewed Publication
Updates every hour. Last Updated: 16-Nov-2025 23:11 ET (17-Nov-2025 04:11 GMT/UTC)
The Ateneo de Manila University’s Business Insights Laboratory for Development (BUILD) is looking at ways for artificial intelligence (AI) to augment human labor in small businesses, which make up the bulk of the Philippine economy.
The relentless pursuit of advanced X-ray detection technologies has been significantly bolstered by the emergence of metal halides perovskites (MHPs) and their derivatives, which possess remarkable light yield and X-ray sensitivity. This comprehensive review delves into cutting-edge approaches for optimizing MHP scintillators performances by enhancing intrinsic physical properties and employing engineering radioluminescent (RL) light strategies, underscoring their potential for developing materials with superior high-resolution X-ray detection and imaging capabilities. We initially explore into recent research focused on strategies to effectively engineer the intrinsic physical properties of MHP scintillators, including light yield and response times. Additionally, we explore innovative engineering strategies involving stacked structures, waveguide effects, chiral circularly polarized luminescence, increased transparency, and the fabrication of flexile MHP scintillators, all of which effectively manage the RL light to achieve high-resolution and high-contrast X-ray imaging. Finally, we provide a roadmap for advancing next-generation MHP scintillators, highlighting their transformative potential in high-performance X-ray detection systems.
A research team has revealed key trends, research hotspots, and emerging collaborations in herbal tea research over the past two decades.
Researchers from New Jersey Institute of Technology (NJIT) have used artificial intelligence to tackle a critical problem facing the future of energy storage: finding affordable, sustainable alternatives to lithium-ion batteries.
The NJIT team successfully applied generative AI techniques to rapidly discover new porous materials capable of revolutionizing multivalent-ion batteries. These batteries, using abundant elements like magnesium, calcium, aluminum and zinc, offer a promising, cost-effective alternative to lithium-ion batteries, which face global supply challenges and sustainability issues.