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Machine Learning‐Enabled Correlation and Modeling of Multimodal Response of Thin Film to Environment on Macro and Nanoscale Using “Lab‐on‐a‐Crystal”

by Eric S Muckley, Liam F Collins, Bernadeta R Srijanto, Ilia N Ivanov
Publication Type
Journal
Journal Name
Advanced Functional Materials
Publication Date
Page Number
1908010
Volume
30
Issue
10

To close the feedback loop between materials design and functionality, materials must undergo vigorous testing of their response to environmen. We developed a platform for rapid multi-functional materials characterization using a quartz crystal microbalance (QCM) with auxiliary in-plane electrodes and a custom gas/vapor flow cell, enabling simultaneous scanning probe microscopy (SPM), electrical, optical, gravimetric, and viscoelastic characterization on the same film under controlled environment. We demonstrate viability of the platform by carrying out multi-functional characterization of hydroscopic PEDOT:PSS polymer film under changing relative humidity (RH). The results provide a foundation for development of lab-on-a-crystal based techniques in which multiple functional film modalities are probed simultaneously under operandi conditions.