Tarn Mark D, Sikora Sebastien N F, Porter Grace C E, Shim Jung-Uk, Murray Benjamin J
School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK.
School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT, UK.
Micromachines (Basel). 2021 Feb 23;12(2):223. doi: 10.3390/mi12020223.
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 (()) was determined in the temperature region of -35.1 to -36.9 °C, covering a greater () 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 () 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, 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.
水的均匀冻结在云层中冰的形成过程中很重要,但文献中对水的均匀冻结的描述仍存在很大差异。新型仪器的开发,如液滴微流控平台,可能有助于通过在时间和空间可控环境中对单分散、尺寸选定的水滴进行分析,来限制我们对均匀冻结动力学的理解。在此,我们评估了使用芯片上实验室浸没粒子成核仪器(LOC-NIPI)获得的液滴冻结数据,该仪器在连续流中生成并冻结液滴。这种高通量方法用于在三次实验运行中分析超过16000个水滴(直径86μm),生成了高精度和可重复性的数据,而这些数据在微流控文献中大多未被呈现。利用这些数据,在-35.1至-36.9°C的温度范围内确定了体积成核速率系数(())的新LOC-NIPI参数化,由于分析的水滴数量较多,与大多数其他微流控技术相比,覆盖了更大的()。与近期理论的比较表明理论表述存在不一致,进一步意味着微流控可用于为参数化的变化提供信息。通过将经典成核理论(CNT)应用于我们的()数据,我们比其他微流控均匀冻结示例更进一步,计算出堆积无序的冰-过冷水界面能,估计为22.5±0.7 mJ m,与理论预测相比再次发现不一致。此外,我们简要回顾并汇编了文献中所有可用的微流控均匀冻结数据,发现LOC-NIPI和其他微流控生成的数据与常用的非微流控数据集相比表现良好,但通常更容易获得,且单分散液滴数量更多。