Abstract

Monosaccharides, which include the simple sugars such as glucose and fructose, are among the most important carbohydrates in the human diet. Certain chronic diseases, e.g., diabetes mellitus, are associated with anomalous glucose blood levels. Detecting and measuring the levels of monosaccharides in vivo or in aqueous solutions is thus of the utmost importance in life science, health, and point-of-care applications. Noninvasive sensing would avoid problems such as pain and potential infection hazards. Here, with the help of surface enhanced infrared absorption (SEIRA) spectroscopy, we demonstrate the reliable optical detection in the mid-infrared spectral range of pure glucose and fructose solutions as well as mixtures of both in aqueous solution. We utilize a reflection flow cell geometry with physiologically relevant concentrations as small as 10 g/L. As significant improvement over the standard baseline correction employed in SEIRA applications, we utilize principal component analysis (PCA) as machine learning algorithm, which is ideally suited for the extraction of vibrational data. We anticipate our results as important step in biosensing applications that will stimulate efforts to further improve the employed SEIRA substrates, the noise level of the spectroscopic light source, as well as the flow cell environment en route to significantly higher sensitivities and quantitative analysis, even in tear drops.

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