Hybrid Neural Network Modeling of Anion Exchange at the Interfaces of Mixed Anion III–V Heterostructures Grown by Molecular Beam Epitaxy

Abstract

A hybrid neural network model is constructed by characterizing the growth of GaAs 1 P -GaAs superlattices (SLs) grown on (001) GaAs substrates by molecular beam epitaxy. These heterostructures are formed by the P 2 exposure of an As-stabilized GaAs surface, and ex situ high-resolution X-ray diffraction (HRXRD) is performed to determine the phosphorus composition at the interfaces. A first-order kinetic model is then developed to describe the mechanisms of anion exchange, surface desorption, and diffusion. A semi-empirical hybrid neural network is used to estimate the parameters of the kinetic model and analyze the microscopic processes occurring at the interfaces of the mixed anion III-V heterostructures. The phosphorus diffusion process in GaAs is estimated to have a diffusion coefficient of = 1 4 10 14 exp( 0 11 eV ) cm 2 s 1 for samples with As = 4 10 6 torr and exhibits enhanced phosphorus intermixing for samples with lower As-stabilizing fluxes.Index Terms-Anion exchange, hybrid neural networks, kinetic modeling, molecular beam epitaxy.

Fundamental reactions controlling anion exchange during mixed anion heterojunction formation: Chemistry and kinetics of P-for-As exchange reaction

“…Furthermore, for As-rich GaAs surfaces at T Ͻ 520°C, intermixing occurs over approximately 100 Å with a graded layer going from the ternary GaP 0.1 As 0.9 to GaAs, and a pure GaAs layer approximately 100 Å thick is still present. 17 The neural network component of the model has the MBE process conditions as its inputs. The strong dependence of the P incorporation and exchange on the GaAs surface reconstruction found in the present work is consistent with previous data from Tatsuoka et al, 16 who showed that the incorporation and migration of group-V molecules significantly depend on the GaAs surface orientation.…”

Investigation of Phosphorus In-Diffusion and Strain in GaAsP/GaAs Using High-Resolution Transmission Electron Microscopy

“…Molecular beam epitaxy (MBE) plays a vital role in the development of compositionally abrupt interfaces with atomic layer precision. When a GaAs surface is exposed to phosphorus, however, several reactions can occur such as anion exchange [5], island formation [6], and in-diffusion [7] at the interface, thus degrading carrier transport and optical properties. In addition, misfit dislocations [8] occur at the interface when the epitaxial layer exceeds the critical thickness.…”

Time delay neural network modeling for particle size in SAG mills

“…A neural network has been used to address complex and irregular features of nonlinear systems, and has been applied to expert systems in various fields with proven advantages and improved predictions in many applications [1][2][3][4][5][6][7]. Using time-series data and multivariate analysis, a neural network was used to predict the real time system and detect faulty operation [8].…”