The increasing accumulation of discarded plastics has already caused serious environmental pollution. Simple landfills and incineration will inevitably lead to the loss of the abundant carbon resources contained in plastic waste. In contrast, photoconversion technology provides a green and sustainable solution to the global plastic waste crisis by converting plastics into hydrogen fuel and valuable chemicals. This review briefly introduces the advantages of photoconversion technology and highlights recent research progress, with a focus on photocatalyst design as well as the thermodynamics and kinetics of the reaction process. It discusses in detail the degradation of typical common plastic types into hydrogen and fine chemicals via photoconversion. Additionally, it outlines future research directions, including the application of artificial intelligence in catalyst design. Although photocatalytic technology remains at the laboratory stage, with challenges in catalyst performance and industrial scalability, the potential for renewable energy generation and plastic valorization is promising.

The University of Maryland Institute for Health Computing (UM-IHC) held its first-ever Continuing Medical Education course on October 28 for healthcare practitioners in a daylong session held on their campus. The topic focused on the use of artificial intelligence (AI) in healthcare. 

As the C language, which forms the basis of critical global software like operating systems, faces security limitations, KAIST's research team is pioneering core original technology research for the accurate automatic conversion to Rust to replace it. By proving the mathematical correctness of the conversion, a limitation of existing Artificial Intelligence (LLM) methods, and solving C language security issues through automatic conversion to Rust, they presented a new direction and vision for future software security research. This work has been selected as the cover story for CACM, the world's highest-authority academic journal, thereby demonstrating KAIST's global research leadership in the field of computer science.

Did you know your brain might be more receptive to learning new things depending on the time of day? This study examined how a 24-hour cycle alters brain plasticity and neuronal excitability in rats.