We present a study of the adsorption of chitosan on silica. The adsorption behavior and the resulting layer properties are investigated by combining optical reflectometry and the quartz crystal microbalance. Exactly the same surfaces are used to measure the amount of adsorbed chitosan with both techniques, allowing the systematic combination of the respective experimental results. This experimental protocol makes it possible to accurately determine the thickness of the layers and their water content for chitosan adsorbed on silica from aqueous solutions of varying composition. In particular, we study the effect of pH in 10 mM NaCl, and we focus on the influence of electrolyte type and concentration for two representative pH conditions. Adsorbed layers are stable, and their properties are directly dependent on the behavior of chitosan in solution. In mildly acidic solutions, chitosan behaves like a weakly charged polyelectrolyte, whereby electrostatic attraction is the main driving force for adsorption. Under these conditions, chitosan forms rigid and thin adsorption monolayers with an average thickness of approximately 0.5 nm and a water content of roughly 60%. In neutral solutions, on the other hand, chitosan forms large aggregates, and thus adsorption layers are significantly thicker (∼10 nm) as well as dissipative, resulting in a large maximum of adsorbed mass around the pK of chitosan. These films are also characterized by a substantial amount of water, up to 95% of their total mass. Our results imply the possibility to produce adsorption layers with tailored properties simply by adjusting the solution chemistry during adsorption.

The sensorial properties of Colombian coffee are renowned worldwide, which is reflected in its market value. This raises the threat of fraud by adulteration using coffee grains from other countries, thus creating a demand for robust and cost-effective methods for the determination of geographical origin of coffee samples. Spectroscopic techniques such as Nuclear Magnetic Resonance (NMR), near infrared (NIR), and mid-infrared (mIR) have arisen as strong candidates for the task. Although a body of work exists that reports on their individual performances, a faithful comparison has not been established yet. We evaluated the performance of 1H-NMR, Attenuated Total Reflectance mIR (ATR-mIR), and NIR applied to fraud detection in Colombian coffee. For each technique, we built classification models for discrimination by species (C. arabica versus C. canephora (or robusta)) and by origin (Colombia versus other C. arabica) using a common set of coffee samples. All techniques successfully discriminated samples by species, as expected. Regarding origin determination, ATR-mIR and 1H-NMR showed comparable capacity to discriminate Colombian coffee samples, while NIR fell short by comparison. In conclusion, ATR-mIR, a less common technique in the field of coffee adulteration and fraud detection, emerges as a strong candidate, faster and with lower cost compared to 1H-NMR and more discriminating compared to NIR.