Sequential model-based design of experiments for development of mathematical models for thin film deposition using chemical vapor deposition process

Bayesian based reaction optimization for complex continuous gas–liquid–solid reactions

“…In general, reaction optimization algorithms can be divided into two categories at present: local optimization algorithms and global optimization algorithms. 14 Initially, local optimization algorithms were developed from the improvement of several direct search methods and surface response models, such as the Nelder–Mead simplex algorithm 15–20 and design of experiments (DoE), 18,21–28 and great performance has been achieved in practice. For instance, Fath et al (2020) developed a self-optimizing framework based on the Nelder–Mead and DoE methods for the optimization of a homogeneous condensation reaction.…”

“…19 The autonomous self-optimization system allowed fast and efficient optimization of the chemical steps leading to carpanone. Although the general applicability of these methods has been proved via different reactions, 17–28 researchers still focus on homogeneous reactions or simple gas–liquid reactions, and studies on the optimization of complex gas–liquid–solid reactions are rare. Indeed, for complex gas–liquid–solid reactions, there appear multiple local optima due to their complex response surface.…”

An innovative kinetic model allowing insight in the moderate temperature chemical vapor deposition of silicon oxynitride films from tris(dimethylsilyl)amine

“…Valuable information can indeed be obtained through this approach: local gas flow, temperature, species distribution profiles, local deposition rates and film composition profiles on the substrates at the reactor scale, inter alia. Moreover, once developed and validated, the simulation outcome can serve as an efficient tool for optimizing the deposition process on complex-in-shape, large, and/or multi-part substrates [17].…”