Ammonia gas, a popular industrial chemical, is dangerous to human health. A new study by Hanbat National University researchers presents a wearable ammonia gas sensor that detects harmful ammonia levels visually and electronically. The sensor is flexible, stretchable, and works reliably when attached to human skin and exposed to high humidity. By combining two sensing methods in one device, the platform remains accurate even if one sensing mode fails, making it suitable for real-world use.

Finely dispersed particulate matter with a diameter of ≤2.5 μm (PM_2.5) poses a significant health- and climate-risk, yet tracking its chemical composition remains a challenge. Now, researchers have developed a deep-learning model that accurately estimates hourly concentrations of five key PM_2.5 chemical components, without chemical analysis. Using air-quality and meteorological data, the model achieved high accuracy outperforming existing methods, and may strengthen air-pollution monitoring, fill data gaps, and support targeted emission control strategies worldwide.

POSTECH researchers demonstrate a foundation model for automating analog circuit layout design.

Comprehensive review reveals how nanostructure engineering can slash costs and boost durability for clean energy applications

For years, scientists have worked to uncover how the brain responds to mechanical forces and electromagnetic waves. Computer models offer useful simulations, but they don’t fully capture what goes on inside a living brain. Now, the team from Mizzou’s College of Engineering is working to close that gap by developing 3D-printed models of an artificial human brain.

A research team led by Dr. Byungju, Lee at the Computational Science Research Center of the Korea Institute of Science and Technology (KIST, President Sang-Rok Oh) has identified key factors governing lithium ion movement in amorphous solid electrolytes through AI-based atomic simulations. The team analyzed lithium-ion movement by distinguishing it into 'ease of movement between sites' and 'connectivity of movement paths'. They confirmed that overall performance is more significantly influenced by the difficulty of ions moving from one site to the next than by path connectivity.

Osaka Metropolitan University researchers conducted a preliminary study of the relevant challenges, divergence, and instabilities of an e-beam in an ionospheric atmosphere and identified them quantitatively through numerical simulations.