Led by scholars from The Hong Kong University of Science and Technology (HKUST), a research team has discovered that, since the early 2000s, both sea surface temperature changes near the equator and the associated atmospheric adjustments over the Pacific have accelerated markedly—becoming a key driver of the increasingly rapid loss of Arctic sea ice during autumn. The findings highlight that, under ongoing global warming, climate linkages between distant regions are far more dynamic and complex than previously understood.

Intramolecular charge transfer (ICT) is one of the most important photophysical mechanisms in organic fluorophores. Among ICT processes, TICT (Twisted Intramolecular Charge Transfer) and PICT (Planar Intramolecular Charge Transfer) represent two highly representative yet frequently confused mechanisms. Although their ground-state structures appear remarkably similar, their excited-state conformations and emission behaviors diverge dramatically. This “similar structures but opposite properties” paradox has long hindered the rational design of fluorescent molecules, making probe development costly, time-consuming, and difficult to scale to large molecular libraries. To address this challenge, the authors Prof. Jie Dong and Prof. Wenbin Zeng from the Xiangya School of Pharmaceutical Sciences, Central South University employed interpretable artificial intelligence to unveil the deep chemical structural essence distinguishing TICT and PICT fluorophores at a systematic level. They further proposed AI-guided design rules for intelligent fluorophore development, significantly improving design efficiency. The key highlights of the study include: (1) Constructing the first comprehensive TICT and PICT fluorophore dataset, covering molecules from nearly a decade of research. (2) Using interpretable algorithms to successfully identify the key factors that critically influence TICT and PICT mechanisms. (3) Releasing an easy-to-use decision tree only based on simple molecular descriptors and fingerprints, ensuring a fast decision and modification when designing TICT and PICT molecules. (4) Proposing the first AI-guided structural design rules for TICT and PICT fluorophores. (5) Conducting both experimental tests and quantitative calculations which confirmed the potential of the approach for the efficient and reliable discovery of TICT and PICT fluorophore candidates.

Direct electrochemical liquid ammonia splitting enables efficient onsite hydrogen generation at room temperature and low pressure (<1 MPa) using Ru nanoparticles on nitrogen-doped carbon. This breakthrough overcomes high-temperature barriers in traditional ammonia decomposition, offering a sustainable pathway for hydrogen production with superior activity and 100-hour stability, surpassing Pt/C catalysts.

Following the development of diffusion models that generate art and video from simple prompts, researchers at the Japan Advanced Institute of Science and Technology have created an artificial intelligence (AI) system that turns text descriptions into accurate architectural images. The model overcomes a major limitation in AI-design tools that only provide visual representations without structural accuracy. The system generates building images that follow structural rules, making AI tools more useful and reliable for architectural design.