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Diatoms are microalgae with unique photonic crystal structures, which can be found in every habitat where water is present. Their abundance and wide distribution make them ideal materials for a wide range of applications as living organisms. We have developed diatom photonic crystals with plasmonic nanoparticles (NPs) as ultra-sensitive, low-cost substrates for surface-enhanced Raman scattering (SERS) sensing and imaging. We also reported the unique micro-fluidic flow, analyte concentration effect, and thin layer chromatography (TLC) on diatom biosilica, which enables selection, separation, detection, and analysis of complex chemical and biological samples. Especially, we developed a lab-on-a-chip technology based on TLC-SERS sensing and successfully applied it to various applications including food safety, illicit drug residue sensing, and biomarker detection. As a relatively new analytical tool, SERS techniques face tremendous challenges in quantitative sensing due to the intrinsic variation of the enhancement factors. In the last topic, we will discuss our efforts of applying data science including support vector regression and convolutional neural network to analyze the data and imaging collected by diatom photonic crystal biosensors, which showed superior performance in quantitative sensing.
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