Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation

Sumner B. Harris; Arpan Biswas; Seok Joon Yun; Kevin M. Roccapriore; Christopher M. Rouleau; Alexander A. Puretzky; Rama K. Vasudevan; David B. Geohegan; Kai Xiao

doi:10.1002/smtd.202301763

Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation

Sumner B. Harris, Arpan Biswas, Seok Joon Yun, Kevin M. Roccapriore, Christopher M. Rouleau, Alexander A. Puretzky, Rama K. Vasudevan, David B. Geohegan, Kai Xiao

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Autonomous systems that combine synthesis, characterization, and artificial intelligence can greatly accelerate the discovery and optimization of materials, however platforms for growth of macroscale thin films by physical vapor deposition techniques have lagged far behind others. Here this study demonstrates autonomous synthesis by pulsed laser deposition (PLD), a highly versatile synthesis technique, in the growth of ultrathin WSe₂ films. By combing the automation of PLD synthesis and in situ diagnostic feedback with a high-throughput methodology, this study demonstrates a workflow and platform which uses Gaussian process regression and Bayesian optimization to autonomously identify growth regimes for WSe₂ films based on Raman spectral criteria by efficiently sampling 0.25% of the chosen 4D parameter space. With throughputs at least 10x faster than traditional PLD workflows, this platform and workflow enables the accelerated discovery and autonomous optimization of the vast number of materials that can be synthesized by PLD.

Original language	English
Article number	2301763
Journal	Small Methods
Volume	8
Issue number	9
DOIs	https://doi.org/10.1002/smtd.202301763
State	Published - Sep 20 2024

Funding

This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. The development and deployment of software for the autonomous synthesis routine and the ex situ characterization was supported by the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory.

Funders	Funder number
Basic Energy Sciences
Division of Materials Sciences and Engineering
Oak Ridge National Laboratory
Center for Nanophase Materials Sciences
U.S. Department of Energy
Office of Science

Keywords

automation
autonomous synthesis
in situ diagnostics
machine learning
pulsed laser deposition

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10.1002/smtd.202301763

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title = "Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation",

abstract = "Autonomous systems that combine synthesis, characterization, and artificial intelligence can greatly accelerate the discovery and optimization of materials, however platforms for growth of macroscale thin films by physical vapor deposition techniques have lagged far behind others. Here this study demonstrates autonomous synthesis by pulsed laser deposition (PLD), a highly versatile synthesis technique, in the growth of ultrathin WSe2 films. By combing the automation of PLD synthesis and in situ diagnostic feedback with a high-throughput methodology, this study demonstrates a workflow and platform which uses Gaussian process regression and Bayesian optimization to autonomously identify growth regimes for WSe2 films based on Raman spectral criteria by efficiently sampling 0.25% of the chosen 4D parameter space. With throughputs at least 10x faster than traditional PLD workflows, this platform and workflow enables the accelerated discovery and autonomous optimization of the vast number of materials that can be synthesized by PLD.",

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AU - Roccapriore, Kevin M.

AU - Rouleau, Christopher M.

AU - Puretzky, Alexander A.

AU - Vasudevan, Rama K.

AU - Geohegan, David B.

AU - Xiao, Kai

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AB - Autonomous systems that combine synthesis, characterization, and artificial intelligence can greatly accelerate the discovery and optimization of materials, however platforms for growth of macroscale thin films by physical vapor deposition techniques have lagged far behind others. Here this study demonstrates autonomous synthesis by pulsed laser deposition (PLD), a highly versatile synthesis technique, in the growth of ultrathin WSe2 films. By combing the automation of PLD synthesis and in situ diagnostic feedback with a high-throughput methodology, this study demonstrates a workflow and platform which uses Gaussian process regression and Bayesian optimization to autonomously identify growth regimes for WSe2 films based on Raman spectral criteria by efficiently sampling 0.25% of the chosen 4D parameter space. With throughputs at least 10x faster than traditional PLD workflows, this platform and workflow enables the accelerated discovery and autonomous optimization of the vast number of materials that can be synthesized by PLD.

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Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation

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