In hydrogen production catalysts, water droplets must detach easily from the surface to prevent blockage by bubbles, allowing for faster hydrogen generation. In semiconductor manufacturing, the quality of the process is determined by how evenly water or liquid spreads on the surface, or how quickly it dries. However, directly observing how such water or liquid spreads and moves on a surface ('wettability') at the nanoscale has been technically almost impossible until now, forcing researchers to rely mostly on conjecture. KAIST announced on December 2nd that a research team led by Professor Seungbum Hong of the Department of Materials Science and Engineering, in collaboration with Professor Jongwoo Lim's team at Seoul National University, has developed a technology to directly observe nano-sized water droplets in real-time using an Atomic Force Microscope (AFM) and to calculate the contact angle based on the droplet's shape. This research, by enabling the visual confirmation of the actual shape of nano-droplets, allows for the precise analysis of how well water droplets adhere to and detach from a surface. This is expected to be immediately applicable to various advanced technologies where liquid movement determines performance, such as hydrogen production catalysts, fuel cells, batteries, and semiconductor processes.

New research  finds that a combination of extreme climate events, sea-level rise and land subsidence could create larger and deeper floods in coastal cities in future. 

The study focused on Shanghai in China, which is threatened with flooding by large and strong typhoons, or tropical storms, producing storm surges and waves. To avoid disaster a major adaptation effort is required - which will almost certainly include raising defences and constructing mobile flood barriers, like those seen at the Thames Barrier in London. However, the team warn there is also the risk of “catastrophic failure” of defences due to rising water levels, especially due to the combination of subsidence, sea-level rise and higher surges during typhoons, as occurred in New Orleans during Hurricane Katrina in 2005.  

Overreliance on generative AI risks eroding new and future doctors’ critical thinking skills, while potentially reinforcing existing data bias and inequity, warns an editorial published in the online journal BMJ Evidence Based Medicine.