Researchers pioneer next-generation AI semiconductors with ‘thermal constraining’ technique
A research team led by Professor Taesung Kim from the School of Mechanical Engineering at Sungkyunkwan University has developed a technology that precisely controls the internal structure of semiconductors using heat, much like stamping out “bungeoppang” (fish-shaped pastry) in a mold. The team report that this approach improves the performance of next-generation artificial intelligence (AI) hardware. With this technology, complex AI computations can be processed more quickly using significantly less electricity than before. The findings are published in the journal ACS Nano.
A new approach could help make future AI chips smaller and more energy-efficient. A KAIST-led research team has used a single material to address one of the major obstacles facing atomically thin semiconductors: the difficulty of efficiently injecting charge. The technology could contribute to next-generation AI and low-power semiconductor devices…
An international study team, led by Flinders University in collaboration with Khalifa University UAE, built the machine-learning platform to act like a "smart materials discovery engine," which is capable of dramatically reducing the time spent on complex computer or lab experiments to test and find new materials for future semiconductors.
Tandem solar cells based on perovskite semiconductors convert sunlight to electricity more efficiently than conventional silicon solar cells. In order to make this technology ready for the market, further improvements with regard to stability and manufacturing processes are required.