Recent Developments in Smartphone Spectrometer Sample Analysis

Abstract

This paper presents an overview of recent developments in smartphone spectrometers focusing on light collection, dispersion, detection and spectral calibration. These spectrometers potentially offer unprecedented field diagnostics that can exploit real-time IoT edge data transfer into the cloud and back. However, there are technical challenges if these are to perform as well, if not better, than laboratory-based instruments. Limitations of traditional spectral calibration are addressed by considering an accurate non-linear wavelength increment over the spatial region of the detector pixels and dispersion associated with the effective refractive index (n) variation of a sample and its holder. To evaluate the performance of novel wavelength calibration, the algorithm was applied to the measurement of absorption spectra of vegetable oils (olive and soybean) using a double beam smartphone spectrometer. In the presence of a significant variation of sample n, the spectrometer measures spectra that overlap well with the spectra obtained using a standard spectrometer. The results also show a significant variation in absorbance spectrum between oil types with distinct absorption bands. This allows one to use the instrument as a straightforward tool for determining the adulteration level of olive oils in the fields and a means of addressing global food fraud more generally.