The deposit patterns derived from droplet evaporation allow current development of medical tests and new strategies for diagnostic in patients. For such purpose, the development and implementation of algorithms capable of characterizing and differentiating deposits are crucial elements. We report the study of deposit patterns formed by the droplet evaporation of binary mixtures of proteins containing NaCl. Optical microscopy reveals aggregates such as tip arrow-shaped, dendritic and semi-rosette patterns, needle-like and scalloped lines structures, as well as star-like and prism-shaped salt crystals. We use the first-order statistics (FOS) and gray level co-occurrence matrix (GLCM) to characterize the complex texture of deposit patterns. Three significant findings arise from this analysis: first, the FOS and GLCM parameters structurally characterize protein deposits. Secondly, they conform to simple exponential laws that change as a function of the NaCl concentration. Finally, the parameters are capable of revealing the different structural changes that occur during the droplet evaporation.

We experimentally and theoretically study the dynamics of a low-Reynolds number helical swimmer moving across viscosity gradients. Experimentally, a double-layer viscosity is generated by superposing two miscible fluids with similar densities but different dynamic viscosities. A synthetic helical magnetically driven swimmer is then made to move across the viscosity gradients along four different configurations: either head-first (pusher swimmer) or tail-first (puller), and through either positive (i.e., going from low to high viscosity) or negative viscosity gradients. We observe qualitative differences in the penetration dynamics for each case. We find that the swimming speed can either increase or decrease while swimming across the viscosity interface, which results from the fact that the head and the tail of the swimmer can be in environments in which the local viscosity leads to different relative amounts of drag and thrust. In order to rationalize the experimental measurements, we next develop a theoretical hydrodynamic model. We assume that the classical resistive-force theory of slender filaments is locally valid along the helical propeller and use it to calculate the swimming speed as a function of the position of the swimmer relative to the fluid-fluid interface. The predictions of the model agree well with experiments for the case of positive viscosity gradients. When crossing across a negative gradient, gravitational forces in the experiment become important, and we modify the model to include buoyancy, which agrees with experiments. In general our results show that it is harder for a pusher swimmer to cross from low to high viscosity, whereas for a puller swimmer it is the opposite. Our model is also extended to the case of a swimmer crossing a continuous viscosity gradient.

Chromatography is, at present, the most used technique to determine the purity of alcoholic drinks. This involves a careful separation of the components of the liquid elements. However, since this technique requires sophisticated instrumentation, there are alternative techniques such as conductivity measurements and UV-Vis and infrared spectrometries. We report here a method based on salt-induced crystallization patterns formed during the evaporation of alcoholic drops. We found that droplets of different samples form different structures upon drying, which we characterize by their radial density profiles. We prove that using the dried deposit of a spirit as a control sample, our method allows us to differentiate between pure and adulterated drinks. As a proof of concept, we study tequila.

The morphological analysis of patterns in dried droplets has allowed the generation of efficient techniques for the detection of molecules of medical interest. However, the effectiveness of this method to reveal the coexistence of macromolecules of the same species, but different conformational states, is still unknown. To address this problem, we present an experimental study on pattern formation in dried droplets of bovine serum albumin (BSA), in folded and unfolded conformational states, in saline solution (NaCl). Folded proteins produce a well-defined coffee ring and crystal patterns all over the dry droplet. Depending on the NaCl concentration, the crystals can be small, large, elongated, entangled, or dense. Optical microscopy reveals that the relative concentration of unfolded proteins determines the morphological characteristics of deposits. At a low relative concentration of unfolded proteins (above 2%), small amorphous aggregates emerge in the deposits, while at high concentrations (above 16%), the “eye-like pattern”, a large aggregate surrounded by a uniform coating, is produced. The radial intensity profile, the mean pixel intensity, and the entropy make it possible to characterize the patterns in dried droplets. We prove that it is possible to achieve 100% accuracy in identifying 4% of unfolded BSA contained in a protein solution.

The quality control of medicines guarantees the effectiveness of treatments for diseases. We explore the use of texture analysis of patterns in dried droplets as a tool to readily detect both impurities and changes in drug concentration. Four types of medicines associated with different routes of administration were analyzed: Methotrexate, Ciprofloxacin, Clonazepam, and Budesonide. We use NaCl and a hot substrate at 63 ${}^{\circ }$C to promote aggregate formation and to reduce droplet drying time. Depending on the medicine, optical microscopy reveals different complex aggregates such as circular to oval splatters, fern-like islands, crown shapes, crown needle-like and bump-like patterns as well as dendritic branched and star-like crystals. We use some physical features of the stains (as the stain diameter and superficial area) and gray level co-occurrence matrix (GLCM) to characterize patterns of dried droplets. Finally, we show that structural analysis of stains can achieve 95% accuracy in identifying medicines with 30% water dilution, while it achieves 99% accuracy in detecting drugs with 10% other substances.