While the downscaling of size for field effect transistors is highly desirable for computation efficiency, quantum tunneling at the $\mathrm{Si}/{\mathrm{SiO}}_2$ 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 $\mathrm{Si}/{\mathrm{SiO}}_2$ interface structures from thousands of candidates. Two high Miller index Si(210) and (211) interfaces, being only $\sim 1\mathrm{nm}$ 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.

Close

PrevNext

View figure in article

• Carrier dynamics
• Machine learning
• Structural properties
• Interfaces