DGIST develops key transistor for next-generation 3D stacked semiconductors based on successful development of a novel sandwich-structured transistor
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Updates every hour. Last Updated: 1-Apr-2026 01:15 ET (1-Apr-2026 05:15 GMT/UTC)
Midwives across the world are under growing pressure, with many reporting exhaustion, stress and a desire to leave the profession.
Australia is no exception. A 2024 national review commissioned by the Nursing and Midwifery Board of Australia found the country’s midwifery workforce is in “crisis,” and revealed that one in three midwives are considering leaving due to burnout, stress and low job satisfaction.
A Korean research team has developed a closed-loop 4D printing technology that enables self-actuating and recyclable structures using sulfur waste generated from petroleum refining processes. A joint research team led by Dr. Dong-Gyun Kim of the Korea Research Institute of Chemical Technology (KRICT), Professor Jeong Jae Wie of Hanyang University, and Professor Yong Seok Kim of Sejong University reported the world’s first 4D printing technology based on sulfur-rich polymers that respond to heat, light, and magnetic fields.
3D printing could change how we build parts for jet engines and power plants, but the process leaves microscopic holes that cause the materials to shatter. Publishing in International Journal of Extreme Manufacturing, Prof. Fangyong Niu's team in Dalian University of Technology have fixed the problem by doing something unconventional: they added a microwave.
Publishing in International Journal of Extreme Manufacturing, Prof. Yanquan Geng's team in Harbin Institute of Technology have devised a way to carve variable-depth, three-dimensional trenches into gallium antimonide, a notably brittle semiconductor, using a microscopic tip vibrating thousands of times per second.
Researchers have developed an ultrasoft, breathable, and multichannel “ear-computer interface” patch. This discreet wearable, made with high-tech MXene materials, can monitor mental fatigue with 90.5% accuracy and even allow users to steer unmanned vehicles using only their thoughts, offering a “burden-free” alternative to traditional brain-mapping caps.
Inspired by Pavlov’s classical conditioning, researchers propose a bio-inspired optical neural network trained via associative learning. Using a dual-color photoresist, sequential UV and visible light exposure encodes memory directly into the material’s fluorescence response, enabling in-situ, computation-free training for pattern recognition—bypassing conventional backpropagation and offering a scalable route to low-cost, edge-compatible photonic AI hardware.