Abstract

Meniscus-guided coating provides great potential for fabricating the nanomaterial-based thin film into high-performance biomedical devices due to the strong relationship between its experimental parameters and the resulting structural properties. However, the complex leverages of various fluid dynamics phenomena hamper optimization of structural properties and device performances. This is due to the absence of in-depth analytical techniques to observe, interpret, and control the solidification process. In this work, we propose an analytical strategy based on the rheological properties of a rGO-based solution using computational fluid dynamics modeling and in situ high-speed microscopy. Through this, we reveal the principles of the solidification mechanism that creates a rGO-based nanocomposite in the form of highly- and evenly-wrinkled thin film and the experimental condition at which this mechanism occurs. The optimized thin film presents high electroconductivity, low chip-to-chip signal variation, and multiplexed electrochemical biosensing performance for three classes of antibodies related to the excessive enrichment of endoplasmic reticulum stress, with detection limits of picomolar levels. This optimizing technique can be universally applied to understanding various solution-based coating systems, and can streamline the production of large-area and high-quality nanocomposite biosensors.