Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Muckley, Eric S.; Vasudevan, Rama K.; Sumpter, Bobby G.; Advincula, Rigoberto C.; Ivanov, Ilia N.

doi:10.1021/acsami.2c16088

Title: Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Journal Article · Wed Dec 28 00:00:00 EST 2022 · ACS Applied Materials and Interfaces

DOI:https://doi.org/10.1021/acsami.2c16088· OSTI ID:1959579

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^[1]; Advincula, Rigoberto C. ^[1];

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Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1959579

Journal Information:: ACS Applied Materials and Interfaces, Vol. 15, Issue 1; ISSN 1944-8244

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Title: Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

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