Simulations show which 2D transistor designs best control leakage as devices shrink, helping guide future chip scaling below ...

Design engineering is running headfirst into a materials bottleneck. Industries such as automotive, aerospace, electronics, and semiconductors now depend on increasingly complex materials. Yet ...

David J. Silvester, a mathematics professor at the University of Manchester, has developed a novel machine-learning method to detect sudden changes in fluid behavior, improving speed and the cost of ...

Despite the huge technological interest in boron nitride (BN), understanding the relative stability of its different structural phases remains a challenge owing to conflicting results from experiments ...

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the development of an innovative high-precision, high-throughput reconfigurable simulation technology, aimed at providing ...

A new technical paper titled “Multiscale Simulation and Machine Learning Facilitated Design of Two-Dimensional Nanomaterials-Based Tunnel Field-Effect Transistors: A Review” was published by ...

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Nissan Motor Co., Ltd. announced that it has conducted research on vehicle aerodynamic analysis using quantum computing in ...

With the growing demand for resilient, efficient, and low carbon infrastructure, increasing attention has been directed toward novel materials and ...

Ishikawa, Japan-- Boron nitride (BN) is a versatile material with applications in a variety of engineering and scientific fields. This is largely due to an interesting property of BN called ...