Colorimetric detection of bisphenol A in water: a smartphone-based sensor using inverse opal molecularly imprinted photonic crystal hydrogel

Abstract

Molecularly imprinted photonic crystal hydrogel (MIPCH) serves as a highly effective platform for the sensitive and selective detection of various analyte molecules. In this study, we present a smartphone-based inverse opal MIPCH (IOMIPCH) sensor designed for the sensitive and selective detection of bisphenol A (BPA) in water samples. The sensor is prepared by photopolymerizing the hydrogel precursor solution within the voids of a polystyrene (PS) photonic crystal (PC) opal film. This is followed by the etching of BPA molecules and the removal of PS spheres, forming an inverse opal structure with binding sites for the analyte BPA. The sensor displays a vibrant structural colour that experiences a redshift upon rebinding of the BPA molecules. The structural colour change provides a visually observable indication of the sensor response. The IOMIPCH-BPA sensor demonstrates a low limit of detection (LoD) of 0.69 fM and a rapid response time of 4 minutes with the ability to selectively detect BPA even in complex sample matrices. Additionally, it is reusable and maintains its performance for up to one month. We used the sensor response images to train a deep learning-based regression model on the smartphone, enabling quantitative predictions of BPA concentration. This integration creates an accurate, portable smart sensor platform capable of real-time BPA sensing.

Graphical abstract: Colorimetric detection of bisphenol A in water: a smartphone-based sensor using inverse opal molecularly imprinted photonic crystal hydrogel

Supplementary files

Article information

Article type
Paper
Submitted
11 Nov 2024
Accepted
14 Jul 2025
First published
14 Jul 2025

Analyst, 2025, Advance Article

Colorimetric detection of bisphenol A in water: a smartphone-based sensor using inverse opal molecularly imprinted photonic crystal hydrogel

S. S. S. S., S. Thomas, D. P. Jacob, V. S. Suniya, S. Nalini and K. N. Madhusoodanan, Analyst, 2025, Advance Article , DOI: 10.1039/D4AN01426J

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