Diffusion Process Modeling for High-speed Avalanche Photodiodes using Neural Networks

고속 애벌린치 포토타이모드 제작을 위한 확산 공정의 신경망 모델링

This paper presents the modeling methodology of Zinc diffusion process applied for high-speed avalanche photodiode fabrication using neural networks. Three process factors (sealing pressure, amount of Zn$_3$P$_2$ source per volume, and doping concentration of diffused layer) are examined by means of D-optimal design experiment. Then, diffusion rate and doping concentration of Zinc in diffused layer are characterized by a static response model generated by training fred-forward error back-propagation neural networks. It is observed that the process models developed here exhibit good agreement with experimental results.