Facile Optimization of Combinatorial Sputtering Processes with Arbitrary Numbers of Components for Targeted Compositions
Shelby Sutton Fields, Christopher David White, Keith Knipling, and Steven Bennett

TL;DR
This paper presents a new, efficient method for optimizing the composition of combinatorial sputtering processes involving multiple components, enabling targeted thin film synthesis without iterative guesswork.
Contribution
It introduces a composition optimization procedure that uses rapid composition mapping to facilitate targeted synthesis in multi-component sputtering.
Findings
Successfully optimized a multi-component alloy film with targeted composition.
Reduced the complexity of tuning sputtering parameters for multiple components.
Demonstrated applicability to a five-element alloy system.
Abstract
Combinatorial sputtering is a physical vapor deposition method that enables the high-throughput synthesis of compositionally varied thin films. Using this technique, the effects of stoichiometry on specific properties of alloy thin films with analog composition gradients can be mapped using high-throughput characterization. To obtain specific stoichiometries, such as those desired for an equiatomic, intermetallic, or doped compounds, the sputter power of each target must be simultaneously tuned to optimize the deposition rate of each component. This optimization problem increases in complexity with the number of components, which commonly leads to iterative guess-and-check processing and can limit the intrinsic high-throughput advantages of this synthesis method. To circumvent this challenge, this work introduces a composition optimization procedure that enables the facile synthesis of…
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Taxonomy
TopicsInorganic Chemistry and Materials · Magnetic properties of thin films · Machine Learning in Materials Science
