Highly Active Ice-Nucleating Particles at the Summer North Pole.

The amount of ice versus supercooled water in clouds is important for their radiative properties and role in climate feedbacks. Hence, knowledge of the concentration of ice-nucleating particles (INPs) is needed. Generally, the concentrations of INPs are found to be very low in remote marine locations allowing cloud water to persist in a supercooled state. We had expected the concentrations of INPs at the North Pole to be very low given the distance from open ocean and terrestrial sources coupled with effective wet scavenging processes. Here we show that during summer 2018 (August and September) high concentrations of biological INPs (active at >-20°C) were sporadically present at the North Pole. In fact, INP concentrations were sometimes as high as those recorded at mid-latitude locations strongly impacted by highly active biological INPs, in strong contrast to the Southern Ocean. Furthermore, using a balloon borne sampler we demonstrated that INP concentrations were often different at the surface versus higher in the boundary layer where clouds form. Back trajectory analysis suggests strong sources of INPs near the Russian coast, possibly associated with wind-driven sea spray production, whereas the pack ice, open leads, and the marginal ice zone were not sources of highly active INPs. These findings suggest that primary ice production, and therefore Arctic climate, is sensitive to transport from locations such as the Russian coast that are already experiencing marked climate change.

Homogeneous Freezing of Water Using Microfluidics.

The homogeneous freezing of water is important in the formation of ice in clouds, but there remains a great deal of variability in the representation of the homogeneous freezing of water in the literature. The development of new instrumentation, such as droplet microfluidic platforms, may help to constrain our understanding of the kinetics of homogeneous freezing via the analysis of monodisperse, size-selected water droplets in temporally and spatially controlled environments. Here, we evaluate droplet freezing data obtained using the Lab-on-a-Chip Nucleation by Immersed Particle Instrument (LOC-NIPI), in which droplets are generated and frozen in continuous flow. This high-throughput method was used to analyse over 16,000 water droplets (86 µm diameter) across three experimental runs, generating data with high precision and reproducibility that has largely been unrepresented in the microfluidic literature. Using this data, a new LOC-NIPI parameterisation of the volume nucleation rate coefficient (JV(T)) was determined in the temperature region of -35.1 to -36.9 °C, covering a greater JV(T) compared to most other microfluidic techniques thanks to the number of droplets analysed. Comparison to recent theory suggests inconsistencies in the theoretical representation, further implying that microfluidics could be used to inform on changes to parameterisations. By applying classical nucleation theory (CNT) to our JV(T) data, we have gone a step further than other microfluidic homogeneous freezing examples by calculating the stacking-disordered ice-supercooled water interfacial energy, estimated to be 22.5 ± 0.7 mJ m-2, again finding inconsistencies when compared to theoretical predictions. Further, we briefly review and compile all available microfluidic homogeneous freezing data in the literature, finding that the LOC-NIPI and other microfluidically generated data compare well with commonly used non-microfluidic datasets, but have generally been obtained with greater ease and with higher numbers of monodisperse droplets.

On-chip density-based sorting of supercooled droplets and frozen droplets in continuous flow.

The freezing of supercooled water to ice and the materials which catalyse this process are of fundamental interest to a wide range of fields. At present, our ability to control, predict or monitor ice formation processes is poor. The isolation and characterisation of frozen droplets from supercooled liquid droplets would provide a means of improving our understanding and control of these processes. Here, we have developed a microfluidic platform for the continuous flow separation of frozen from unfrozen picolitre droplets based on differences in their density, thus allowing the sorting of ice crystals and supercooled water droplets into different outlet channels with 94 ± 2% efficiency. This will, in future, facilitate downstream or off-chip processing of the frozen and unfrozen populations, which could include the analysis and characterisation of ice-active materials or the selection of droplets with a particular ice-nucleating activity.

On-chip analysis of atmospheric ice-nucleating particles in continuous flow.

Ice-nucleating particles (INPs) are of atmospheric importance because they catalyse the freezing of supercooled cloud droplets, strongly affecting the lifetime and radiative properties of clouds. There is a need to improve our knowledge of the global distribution of INPs, their seasonal cycles and long-term trends, but our capability to make these measurements is limited. Atmospheric INP concentrations are often determined using assays involving arrays of droplets on a cold stage, but such assays are frequently limited by the number of droplets that can be analysed per experiment, often involve manual processing (e.g. pipetting of droplets), and can be susceptible to contamination. Here, we present a microfluidic platform, the LOC-NIPI (Lab-on-a-Chip Nucleation by Immersed Particle Instrument), for the generation of water-in-oil droplets and their freezing in continuous flow as they pass over a cold plate for atmospheric INP analysis. LOC-NIPI allows the user to define the number of droplets analysed by simply running the platform for as long as required. The use of small (∼100 µm diameter) droplets minimises the probability of contamination in any one droplet and therefore allows supercooling all the way down to homogeneous freezing (around -36 °C), while a temperature probe in a proxy channel provides an accurate measure of temperature without the need for temperature modelling. The platform was validated using samples of pollen extract and Snomax®, with hundreds of droplets analysed per temperature step and thousands of droplets being measured per experiment. Homogeneous freezing of purified water was studied using >10 000 droplets with temperature increments of 0.1 °C. The results were reproducible, independent of flow rate in the ranges tested, and the data compared well to conventional instrumentation and literature data. The LOC-NIPI was further benchmarked in a field campaign in the Eastern Mediterranean against other well-characterised instrumentation. The continuous flow nature of the system provides a route, with future development, to the automated monitoring of atmospheric INP at field sites around the globe.

The study of atmospheric ice-nucleating particles via microfluidically generated droplets.

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 103-106 ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK's annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies.

Annulus fibrosus functional extrafibrillar and fibrous mechanical behaviour: experimental and computational characterisation.

The development of current surgical treatments for intervertebral disc damage could benefit from virtual environment accounting for population variations. For such models to be reliable, a relevant description of the mechanical properties of the different tissues and their role in the functional mechanics of the disc is of major importance. The aims of this work were first to assess the physiological hoop strain in the annulus fibrosus in fresh conditions (n = 5) in order to extract a functional behaviour of the extrafibrillar matrix; then to reverse-engineer the annulus fibrosus fibrillar behaviour (n = 6). This was achieved by performing both direct and global controlled calibration of material parameters, accounting for the whole process of experimental design and in silico model methodology. Direct-controlled models are specimen-specific models representing controlled experimental conditions that can be replicated and directly comparing measurements. Validation was performed on another six specimens and a sensitivity study was performed. Hoop strains were measured as 17 ± 3% after 10 min relaxation and 21 ± 4% after 20-25 min relaxation, with no significant difference between the two measurements. The extrafibrillar matrix functional moduli were measured as 1.5 ± 0.7 MPa. Fibre-related material parameters showed large variability, with a variance above 0.28. Direct-controlled calibration and validation provides confidence that the model development methodology can capture the measurable variation within the population of tested specimens.

Methodology to Produce Specimen-Specific Models of Vertebrae: Application to Different Species.

Image-based continuum-level finite element models have been used for bones to evaluate fracture risk and the biomechanical effects of diseases and therapies, capturing both the geometry and tissue mechanical properties. Although models of vertebrae of various species have been developed, an inter-species comparison has not yet been investigated. The purpose of this study was to derive species-specific modelling methods and compare the accuracy of image-based finite element models of vertebrae across species. Vertebral specimens were harvested from porcine (N = 12), ovine (N = 13) and bovine (N = 14) spines. The specimens were experimentally loaded to failure and apparent stiffness values were derived. Image-based finite element models were generated reproducing the experimental protocol. A linear relationship between the element grayscale and elastic modulus was calibrated for each species matching in vitro and in silico stiffness values, and validated on independent sets of models. The accuracy of these relationships were compared across species. Experimental stiffness values were significantly different across species and specimen-specific models required species-specific linear relationship between image grayscale and elastic modulus. A good agreement between in vitro and in silico values was achieved for all species, reinforcing the generality of the developed methodology.