A machine condition transfer function approach to run-to-run and machine-to-machine reproducibility of III-V compound semiconductor molecular beam epitaxial growth

Abstract

A concept of machine condition transfer function (MCTF) based on the use of in-situ sensor response to intrinsic surface property of the material is proposed to meet the challenge of run-to-run and machine-to-machine reproducibility of optimized growth conditions for III-V compound semiconductor molecular beam epitaxical growth. The variation in the intensity of the specular beam in reflection high-energy electron diffraction from compound semiconductor surface, measured as a function of the temperature and anion pressure prior to growth, is used as the intrinsic surface property for the generation of MCTF's. The mathematical methodology for realizing MCTF's, including the sensor response surface reconstruction and optimal minimization in combination with a composite statistical design for initial estimation, is presented. Numerical evaluation of the developed methodology shows its promise in practice.