Popular surface tension models were reviewed and tested on ten binary aqueous solutions. A parametrized sigmoid function was suggested as a new empirical model and shown to have excellent fit performance.

To understand the crystallization of aqueous solutions in the atmosphere, biological specimens, or pharmaceutical formulations, the rate at which ice nucleates from pure liquid water must be quantified. There is still an orders-of-magnitude spread in the homogeneous nucleation rate of water measured using different instruments, with the most important source of uncertainty being that of the measured temperature. Microfluidic platforms can generate hundreds to thousands of monodisperse water-in-oil droplets, unachievable by most other techniques. However, most microfluidic devices previously used to quantify homogeneous ice nucleation rates have reported high temperature uncertainties, between ± 0.3 and ± 0.7 K. We use the recently developed Microfluidic Ice Nuclei Counter Zurich (MINCZ) to observe the freezing of spherical water droplets with two diameters (75 and 100 μm) at two cooling rates (1 and 0.1 K min⁻¹). By varying both droplet volume and cooling rate, we were able to probe a temperature range of 236.5–239.3 K with an accuracy of ± 0.2 K, providing reliable data where previously determined nucleation rates suffered from large uncertainties and inconsistencies, especially at temperatures above 238 K. From these data and from Monte Carlo simulations, we demonstrate the importance of obtaining a sufficiently large dataset so that underlying nucleation rates are not overestimated at higher temperatures. Finally, we obtain new parameters for a previous parameterisation by fitting to our newly measured nucleation rates, enabling its use in applications where ice formation needs to be predicted.

A surface tension model is presented applicable to multi-component solutions containing water, salts, organic, and amphiphilic substances in a mixture.

In marine environments, sea spray aerosol (SSA) particles have been found to contain surface-active substances (surfactants) originating from the sea surface microlayer. These surfactants can lower the surface tension of the SSA particles, facilitating their activation to cloud droplets. This effect is not considered in classical Köhler theory, which assumes droplets to be homogeneous with a surface tension of pure water. In this study the cloud condensation nuclei (CCN) activity of SSA particles calculated with classical Köhler theory is compared to a more complex calculation that considers bulk–surface partitioning, surface tension lowering, and liquid–liquid phase separation. The model approach presented here combines the multi-component Eberhart model for surface tension with the monolayer model and an activity model (Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients, AIOMFAC). This combination allows for calculating Köhler curves of surfactant-containing particles with a large number of compounds for the first time. In a sensitivity study we show that organic compounds can be categorized into weak, intermediate, and strong surfactants for CCN activation based on their separation factor in water S_1i and their pure component surface tension σ_i. For a quaternary model system of SSA particles, it is shown that high content of hydrophobic organic material (i.e. strong surfactants) in Aitken mode particles does not necessarily prevent good CCN activation but rather facilitates effective activation via surface tension lowering. Since common climate models use parameterizations that are based on classical Köhler theory, these results suggest that the CCN activity of small SSA particles might be underestimated in climate models.

Ice nucleation in the atmosphere is the precursor to important processes that determine cloud properties and lifetime. Computational models that are used to predict weather and project future climate changes require parameterizations of both homogeneous nucleation (i.e. in pure water) and heterogeneous nucleation (i.e. catalysed by ice-nucleating particles, INPs). Microfluidic systems have gained momentum as a tool for obtaining such parameterizations and gaining insight into the stochastic and deterministic contributions to ice nucleation. To overcome the shortcomings of polydimethylsiloxane (PDMS) microfluidic devices with regard to temperature uncertainty and droplet instability due to continuous water adsorption by PDMS, we have developed a new instrument: the Microfluidic Ice Nuclei Counter Zürich (MINCZ). In MINCZ, droplets with a diameter of 75 µm are generated using a PDMS chip, and hundreds of these droplets are then stored in fluoropolymer tubing that is relatively impermeable to water and solvents. Droplets within the tubing are cooled in an ethanol bath. We validate MINCZ by measuring the homogeneous freezing temperatures of water droplets and the heterogeneous freezing temperatures of aqueous suspensions containing microcline, a common and effective INP in the atmosphere. We obtain results with a high accuracy of 0.2 K in measured droplet temperature. Pure water droplets with a diameter of 75 µm freeze at a median temperature of 237.3 K with a standard deviation of 0.1 K. Additionally, we perform several freeze–thaw cycles. In the future, MINCZ will be used to investigate the freezing behaviour of INPs, motivated by a need for better-constrained parameterizations of ice nucleation in weather and climate models, wherein the presence or absence of ice influences cloud optical properties and precipitation formation.

Freezing and freeze-drying processes are commonly used to extend the shelf life of drug products and to ensure their safety and efficacy upon use. When designing a freezing process, it is beneficial to characterize multiple physicochemical properties of the formulation, such as nucleation rate, crystal growth rate, temperature and concentration of the maximally freeze-concentrated solution, and melting point. Differential scanning calorimetry has predominantly been used in this context but does have practical limitations and is unable to quantify the kinetics of crystal growth and nucleation. In this work, we introduce a microfluidic technique capable of quantifying the properties of interest and use it to investigate aqueous sucrose solutions of varying concentration. Three freeze-thaw cycles were performed on droplets with 75-μm diameters at cooling and warming rates of 1 °C/min. During each cycle, the visual appearance of the droplets was optically monitored as they experienced nucleation, crystal growth, formation of the maximally freeze-concentrated solution, and melting. Nucleation and crystal growth manifested as increases in droplet brightness during the cooling phase. Heating was associated with a further increase as the temperature associated with the maximally freeze-concentrated solution was approached. Heating beyond the melting point corresponded to a decrease in brightness. Comparison with the literature confirmed the accuracy of the new technique while offering new visual data on the maximally freeze-concentrated solution. Thus, the microfluidic technique presented here may serve as a complement to differential scanning calorimetry in the context of freezing and freeze-drying. In the future, it could be applied to a plethora of mixtures that undergo such processing, whether in pharmaceutics, food production, or beyond.