Highly sensitive colorimetric detection of ascorbic acid using molecularly imprinted photonic crystal hydrogel sensor

Abstract

Molecular imprinted photonic crystal hydrogel (MICPH) sensors have gained recognition as an efficient platform for selectively detecting analyte molecules. In the present work, we report the development and implementation of a colorimetric sensor based on MIPCH for the selective detection of Ascorbic acid (AA). The fabrication process of the MIPCH sensor involves the photo-polymerization of a hydrogel precursor solution containing AA molecules, which is encapsulated in the interstitial spaces of photonic crystal (PC) opal film. Following the encapsulation, these molecules are selectively removed from the hydrogel network, forming an AA-MIPCH sensor. The sensor exhibits a vivid structural color that redshifts upon rebinding with different concentrations of AA molecules. This alteration in structural coloration serves as a straightforward and visually discernible indicator of the sensor response and enables the quantitative measurement of the target molecule. The sensor exhibits remarkable sensitivity, featuring a low limit of detection (LoD) of 0.011 µM with high selectivity, minimal response time, and promising long-term stability. In addition, the sensor demonstrates its capability to detect the AA even from the complex matrix. A CNN-based deep learning algorithm in MATLAB® was employed to quantitatively predict the concentration of the target molecule. The integration with the machine learning algorithm yields a highly efficient and accurate smart sensor system that is well-suited for real-time sensing of ascorbic acid.