Autonomous sputter synthesis of thin film nitrides with composition
controlled by Bayesian optimization of optical plasma emission
- URL: http://arxiv.org/abs/2305.11122v3
- Date: Thu, 10 Aug 2023 16:30:52 GMT
- Title: Autonomous sputter synthesis of thin film nitrides with composition
controlled by Bayesian optimization of optical plasma emission
- Authors: Davi M. Febba, Kevin R. Talley, Kendal Johnson, Stephen Schaefer, Sage
R. Bauers, John S. Mangum, Rebecca W. Smaha, Andriy Zakutayev
- Abstract summary: We report the design and implementation of an autonomous workflow for sputter deposition of thin films with controlled composition.
We modeled film composition, measured by x-ray fluorescence, as a linear function of emission lines monitored during the co-sputtering.
A Bayesian control algorithm, informed by OES, navigates the space of sputtering power to fabricate films with user-defined composition.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Autonomous experimentation has emerged as an efficient approach to accelerate
the pace of materials discovery. Although instruments for autonomous synthesis
have become popular in molecular and polymer science, solution processing of
hybrid materials and nanoparticles, examples of autonomous tools for physical
vapor deposition are scarce yet important for the semiconductor industry. Here,
we report the design and implementation of an autonomous workflow for sputter
deposition of thin films with controlled composition, leveraging a highly
automated sputtering reactor custom-controlled by Python, optical emission
spectroscopy (OES), and a Bayesian optimization algorithm. We modeled film
composition, measured by x-ray fluorescence, as a linear function of emission
lines monitored during the co-sputtering from elemental Zn and Ti targets in
N$_2$ atmosphere. A Bayesian control algorithm, informed by OES, navigates the
space of sputtering power to fabricate films with user-defined composition, by
minimizing the absolute error between desired and measured emission signals. We
validated our approach by autonomously fabricating Zn$_x$Ti$_{1-x}$N$_y$ films
with deviations from the targeted cation composition within relative 3.5 %,
even for 15 nm thin films, demonstrating that the proposed approach can
reliably synthesize thin films with specific composition and minimal human
interference. Moreover, the proposed method can be extended to more difficult
synthesis experiments where plasma intensity depends non-linearly on pressure,
or the elemental sticking coefficients strongly depend on the substrate
temperature.
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