Beyond ab initio reaction simulator: an application to GaN metalorganic vapor phase epitaxy

TL;DR

This paper develops a reaction simulation method for GaN vapor phase epitaxy by integrating high-resolution mass spectrometry data with ab initio knowledge, enabling accurate prediction of reaction pathways and precursor species.

Contribution

It introduces a data assimilation approach that combines experimental TOF-MS data with ab initio calculations for improved reaction modeling in epitaxy processes.

Findings

Successfully reproduces CH$_4$ concentration and reaction pathways

Predicts significant production of GaH$_3$, a key precursor

Demonstrates applicability to other physics fields

Abstract

To develop a quantitative reaction simulator, data assimilation was performed using high-resolution time-of-flight mass spectrometry (TOF-MS) data applied to GaN metalorganic vapor phase epitaxy system. Incorporating ab initio knowledge into the optimization successfully reproduces not only the concentration of CH$_4$ (an impurity precursor) as an objective variable but also known reaction pathways. The simulation results show significant production of GaH$_3$, a precursor of GaN, which has been difficult to detect in TOF-MS experiments. Our proposed approach is expected to be applicable to other applied physics fields that require quantitative prediction that goes beyond ab initio reaction rates.