Computational Modelling of Doubly‐Photopolymerized Holographic Biosensors

Abstract

AbstractHolographic sensors are optical devices capable of tuning reflection wavelength, dependent upon nanostructured variations in refractive index. Computational modelling is utilized to simulate the recording and swelling characteristics of developed doubly photopolymerized (DP) holographic sensors. The holographic devices simplify fabrication processes, reduce financial costs, and improve biocompatibility. A holographic grating is achieved through in situ photopolymerization of a highly crosslinked polymer to produce nanostructured refractive index modulation. The unique swelling characteristics DP holographic sensors possess necessitate the development of system‐specific computational modelling. Hydrogel parameters, including film thickness, refractive index change, layer number, and external medium refractive index are examined for their effect on reflection spectra. Optimized computational models are utilized to study the effect of differential swelling rates of individual layer spacings on sensor response, indicating an idealized reduction in a swelling of 50% for the highly crosslinked region. A 2D photonic crystal geometry with additional periodicity is developed, to inform further sensor design opportunities. Optimized parameters for both 1D and 2D photonic structures will assist the further development of DP holographic sensors.