Water testing is becoming increasingly important due to dangerous phenomena such as Harmful Algal Blooms (HABs). Commonly, the content of a water sample is measured for the detection, monitoring and control of these events. Raman spectroscopy is a technique for the molecular characterization of materials in solid, liquid or gaseous form, which makes it an attractive method for analysing materials’ components. However, Raman scattering is a weak optical process and requires an accurate system for detection. In our work, we present, from design to fabrication, a microfluidic device on fused silica adapted to optimise the Raman spectrum of liquid samples when using a Raman probe. The device features a portable design for rapid on-site continuous flow measurements avoiding the use of large, costly and complex laboratory equipment. The main manufacturing technique used was ultrafast laser-assisted etching (ULAE). Finally, the effectiveness of the microfluidic device was demonstrated by comparing the Raman spectra of a known species of cyanobacteria with those obtained using other conventional substrates in laboratory analysis. The results demonstrate that the microfluidic device, under continuous flow conditions, exhibited a lower standard deviation of the Raman signal, reduced background noise and avoided signal variations caused by sample drying in static measurements.

Archaeological mollusk shells, such as those of Littorina obtusata/fabalis, hold valuable information about past human behavior and cultural practices. However, the original coloration of these shells, crucial for understanding their symbolic significance, is often lost due to taphonomic processes. Raman spectroscopy is a powerful technique for non-destructive analysis of archaeological samples, enabling the identification of pigments and mineralogical components. In this study, we present a methodology to predict, using Raman spectroscopy and k-means clustering, the original coloration of archaeological L. obtusata/fabalis shells which have lost their original coloration. Raman spectra were acquired from both modern shells, exhibiting a range of natural colors, and archaeological shell samples from La Chora cave (Cantabria, northern Spain). Spectral data were preprocessed to remove noise and baseline effects, and k-means clustering was applied to group the spectra based on their inherent spectral similarities. By comparing the spectral signatures of the archaeological samples with those of the modern shells within the generated clusters, we inferred the likely original coloration of the archaeological specimens. This approach provides a quantitative framework for predicting archaeological shell colors.