Spray drying and electrospraying are well-established drying processes that already have proven their value in the pharmaceutical field. However, there is currently still a lack of knowledge on the fundamentals of the particle formation process, thereby hampering fast and cost-effective particle engineering. To get a better understanding of how functional particles are formed with respect to process and formulation parameters, it is indispensable to offer a comprehensive overview of critical aspects of the droplet drying and particle formation process. This review therefore closely relates single droplet drying to pharmaceutical applications. Although excellent reviews exist of the different aspects, there is, to the best of our knowledge, no single review that describes all steps that one should consider when trying to engineer a certain type of particle morphology. The findings presented in this article have strengthened the predictive value of single droplet drying for pharmaceutical drying applications like spray drying and electrospraying. Continuous follow-up of the particle formation process in single droplet drying experiments hence allows optimization of manufacturing processes and particle engineering approaches and acceleration of process development.

Existing energy balance models, which estimate maximum droplet spreading, insufficiently capture the droplet spreading from low to high Weber and Reynolds numbers and contact angles. This is mainly due to the simplified definition of the viscous dissipation term and incomplete modeling of the maximum spreading time. In this particular research, droplet impact onto a smooth sapphire surface is studied for seven glycerol concentrations between 0% and 100%, and 294 data points are acquired using high-speed photography. Fluid properties, such as density, surface tension, and viscosity, are also measured. For the first time according to the authors' knowledge, we incorporate the fluid viscosity in the modeling of the maximum spreading time based on the recorded data. We also estimate the characteristic velocity of the viscous dissipation term in the energy balance equation. These viscosity-based characteristic scales help to formulate a more comprehensive maximum droplet spreading model. Thanks to this improvement, our model successfully fits the data available in the literature for various fluids and surfaces compared to the existing models.

The influence of metachronal patterns on ciliary fluid flow has been studied using a soft robotic cilia array and simulations.

Cooling by impinging droplets has been the subject of several studies for decades and still is, and, in the last few years, the potential heat transfer enhancement obtained thanks to nanofluids’ use has received increased interest. Indeed, the use of high thermal conductivity fluids, such as nanofluids’, is considered today as a possible way to strongly enhance this heat transfer process. This enhancement is related to several physical mechanisms. It is linked to the nanofluids’ rheology, their degree of stabilization, and how the presence of the nanoparticles impact the droplet/substrate dynamics. Although there are several articles on droplet impact dynamics and nanofluid heat transfer enhancement, there is a lack of review studies that couple these two topics. As such, this review aims to provide an analysis of the available literature dedicated to the dynamics between a single nanofluid droplet and a hot substrate, and the consequent enhancement or reduction of heat transfer. Finally, we also conduct a review of the available publications on nanofluids spray cooling. Although using nanofluids in spray cooling may seem a promising option, the few works present in the literature are not yet conclusive, and the mechanism of enhancement needs to be clarified.

Objectives: Gaseous microemboli (GME) are a cause of neurocognitive deficit postcardiac surgery with cardiopulmonary bypass. However, the measurement of microbubbles during cardiopulmonary bypass is not easy, because blood is an opaque fluid and contains microparticles. Recently, two new microbubble counters, the Gampt BC200 and the emboli detection and classification (EDAC) quantifier, were developed for use during cardiac surgery. The accuracy of both devices was validated against industrial standards. Methods: A clear blood analogue (30%/70% glycerol–water) was pumped, by means of a rollerpump out of a partially filled arterial line screen filter with a nominal pore size of 20 μm. Downstream the pump, all test sensors and an optical cuvette, were inserted in a vertically mounted 3/8 inch tubing. Measurements were taken at flows of 405, 1080, 3000 and 6000 ml/min. Backlight shadowgraphy and optical counting were used as industrial reference techniques for measuring size and counts. Results: On average the EDAC quantifier underestimates average bubble diameter by 35±1%, 13±8%, 71±7% and 33±4% at 405, 1080, 3000 and 6000 ml/min, respectively. The Gampt BC200 has good sizing agreement at 1080 ml/min (+5±17%) and 3000 ml/min (+33±6%) but overestimates average diameter by 220±40% and 295±49% at 405 and 6000 ml/min, respectively. Both devices only partially count the number of microbubbles at higher flows. At 3 l/min the EDAC counts 38%, the Gampt 18% of total counts and at 6 l/min both the EDAC and Gampt only count 3% of total counts. Conclusions: Both the EDAC and Gampt can be used in a clinical setting for monitoring basal GME production. However, both devices have some major limitations when used for studying ‘worst case’ scenarios. One should take great caution when correlating measured data with neurocognitive outcome. Finally, results obtained by one device in a first study cannot be compared nor exchanged with results from the other device in a second study.