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Smallest Stable Si/SiO_{2} Interface that Suppresses Quantum Tunneling from Machine-Learning-Based Global Search.

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While the downscaling of size for field effect transistors is highly desirable for computation efficiency, quantum tunneling at the Si/SiO_{2} interface becomes the leading concern when approaching the nanometer scale.… Click to show full abstract

While the downscaling of size for field effect transistors is highly desirable for computation efficiency, quantum tunneling at the Si/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 Si/SiO_{2} 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.

Keywords: quantum tunneling; machine learning; interface; based global; learning based; sio interface

Journal Title: Physical review letters
Year Published: 2022

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