Spectroscopic properties of nanocrystalline oxide materials for optical sensor applications

Abstract

With advances in science and technology, humans have been able to manipulate and transform materials in the nano-world. Unlike bulk, nanomaterials have the advantage of high reactivity with a large surface-to-volume ratio. And nanomaterials are actively studied in various fields due to their physicochemical diversity through surface chemistry and shape deformation. There are many types of nanomaterials, depending on their dimension, shape, state, and chemical composition. Among them, nanocrystalline oxides have high oxygen mobility owing to oxygen vacancies occurring in the crystal structure. Therefore, the oxygen affinity of the material is increased, and thus various researches for its application are being actively conducted, including the optical sensing application. Optical sensing is very useful in a wide area of research fields of materials, physics, chemistry, and biomedical science, as it allows direct and intuitive observation of various effects according to state changes. Optical sensors implementing nanocrystalline oxide materials nowadays have a wide range of application areas including spectral absorbance, photoluminescence, chemiluminescence, and interferogram. In this study, spectroscopic studies were performed to understand of the optical properties of nanocrystalline oxide materials (rGO, rGOQD, CexOy), to look for their possible application into optical sensors. Here, three types of optical sensors are studied. First, Interference-based two-mode microfiber device with CYTOP-rGO is developed as temperature and humidity sensor. Second, rGOQDs were prepared by one-pot synthesis based on perfluorotributylamine. And then, rGOQDs were used as a glucose sensor through a colorimetric method using the spectral change in the photoluminescence according to oxidation. Third, CexOy nanoparticle based contact lens is developed for glucose sensing. For an easy-access and portable sensing platform, a customized color image processing algorithm is developed and applied to smartphones.