Smallest Stable Si/SiO2 Interface that Suppresses Quantum Tunneling from Machine-Learning-Based Global Search

While the downscaling of size for field effect transistors is highly desirable for computation efficiency, quantum tunneling at the Si/SiO2 interface becomes the leading concern when approaching the nanometer scale. By developing a machine-learning-based global search method, we now reveal all the likely Si/SiO2 interface structures from thousands of candidates. Two high Miller index Si(210) and (211) interfaces, being only -1 nm in periodicity, are found to possess good carrier mobility, low carrier trapping, and low interfacial energy. The results provide the basis for fabricating stepped Si surfaces for next-generation transistors.

Automated summary

By using a machine-learning-based global search method, researchers have identified two promising Si/SiO2 interface structures for next-generation transistors.