In micro-channels, the flow of viscous liquids e.g. water, is laminar due to the low Reynolds number in miniaturized dimensions. An aqueous solution becomes viscoelastic with a minute amount of polymer additives; its flow behavior can become drastically different and turbulent. However, the molecules are typically invisible. Here we have developed a novel visualization technique to examine the extension and relaxation of polymer molecules at high flow velocities in a viscoelastic turbulent flow. Using high speed videography to observe the fluorescein labeled molecules, we show that viscoelastic turbulence is caused by the sporadic, non-uniform release of energy by the polymer molecules. This developed technique allows the examination of a viscoelastic liquid at the molecular level, and demonstrates the inhomogeneity of viscoelastic liquids as a result of molecular aggregation. It paves the way for a deeper understanding of viscoelastic turbulence, and could provide some insights on the high Weissenberg number problem. In addition, the technique may serve as a useful tool for the investigations of polymer drag reduction.

Life of bacteria is governed by the physical dimensions of life in microscales, which is dominated by fast diffusion and flow at low Reynolds numbers. Microbial biofilms are structurally and functionally heterogeneous and their development is suggested to be interactively related to their microenvironments. In this study, we were guided by the challenging requirements of precise tools and engineered procedures to achieve reproducible experiments at high spatial and temporal resolutions. Here, we developed a robust precise engineering approach allowing for the quantification of real-time, high-content imaging of biofilm behaviour under well-controlled flow conditions. Through the merging of engineering and microbial ecology, we present a rigorous methodology to quantify biofilm development at resolutions of single micrometre and single minute, using a newly developed flow cell. We designed and fabricated a high-precision flow cell to create defined and reproducible flow conditions. We applied high-content confocal laser scanning microscopy and developed image quantification using a model biofilm of a defined opportunistic strain, Pseudomonas putida OUS82. We observed complex patterns in the early events of biofilm formation, which were followed by total dispersal. These patterns were closely related to the flow conditions. These biofilm behavioural phenomena were found to be highly reproducible, despite the heterogeneous nature of biofilm.

Many fluids, including biological fluids such as mucus and blood, are viscoelastic. Through the introduction of chaotic flows in a micro-channel and the construction of maps of characteristic chaos parameters, differences in viscoelastic properties of these fluids can be measured. This is demonstrated by creating viscoelastic chaotic flows induced in an H-shaped micro-channel through the steady infusion of a polymeric fluid of polyethylene oxide (PEO) and another immiscible fluid (silicone oil). A protocol for chaos analysis was established and demonstrated for the analysis of the chaotic flows generated by two polymeric fluids of different molecular weight but with similar relaxation times. The flows were shown to be chaotic through the computation of their correlation dimension (D2) and the largest Lyapunov exponent (λ1), with D2 being fractional and λ1 being positive. Contour maps of D2 and λ1 of the respective fluids in the operating space, which is defined by the combination of polymeric fluids and silicone oil flow rates, were constructed to represent the characteristic of the chaotic flows generated. It was observed that, albeit being similar, the fluids have generally distinct characteristic maps with some similar trends. The differences in the D2 and λ1 maps are indicative of the difference in the molecular weight of the polymers in the fluids because the driving force of the viscoelastic chaotic flows is of molecular origin. This approach in constructing the characteristic maps of chaos parameters can be employed as a diagnostic tool for biological fluids and, more generally, chaotic signals.