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 co...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/12/2/223 |
| _version_ | 1797395614609178624 |
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| author | Mark D. Tarn Sebastien N. F. Sikora Grace C. E. Porter Jung-uk Shim Benjamin J. Murray |
| author_facet | Mark D. Tarn Sebastien N. F. Sikora Grace C. E. Porter Jung-uk Shim Benjamin J. Murray |
| author_sort | Mark D. Tarn |
| collection | DOAJ |
| description | 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 (<i>J</i><sub>V</sub>(<i>T</i>)) was determined in the temperature region of −35.1 to −36.9 °C, covering a greater <i>J</i><sub>V</sub>(<i>T</i>) 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 <i>J</i><sub>V</sub>(<i>T</i>) 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<sup>−2</sup>, 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. |
| first_indexed | 2024-03-09T00:38:02Z |
| format | Article |
| id | doaj.art-ffd7425074304f62b232db1af375313a |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-09T00:38:02Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-ffd7425074304f62b232db1af375313a2023-12-11T18:05:12ZengMDPI AGMicromachines2072-666X2021-02-0112222310.3390/mi12020223Homogeneous Freezing of Water Using MicrofluidicsMark D. Tarn0Sebastien N. F. Sikora1Grace C. E. Porter2Jung-uk Shim3Benjamin J. Murray4School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UKSchool of Earth and Environment, University of Leeds, Leeds LS2 9JT, UKSchool of Earth and Environment, University of Leeds, Leeds LS2 9JT, UKSchool of Physics and Astronomy, University of Leeds, Leeds LS2 9JT, UKSchool of Earth and Environment, University of Leeds, Leeds LS2 9JT, UKThe 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 (<i>J</i><sub>V</sub>(<i>T</i>)) was determined in the temperature region of −35.1 to −36.9 °C, covering a greater <i>J</i><sub>V</sub>(<i>T</i>) 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 <i>J</i><sub>V</sub>(<i>T</i>) 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<sup>−2</sup>, 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.https://www.mdpi.com/2072-666X/12/2/223ice nucleationhomogeneous freezinginterfacial energywaterdroplet microfluidics |
| spellingShingle | Mark D. Tarn Sebastien N. F. Sikora Grace C. E. Porter Jung-uk Shim Benjamin J. Murray Homogeneous Freezing of Water Using Microfluidics Micromachines ice nucleation homogeneous freezing interfacial energy water droplet microfluidics |
| title | Homogeneous Freezing of Water Using Microfluidics |
| title_full | Homogeneous Freezing of Water Using Microfluidics |
| title_fullStr | Homogeneous Freezing of Water Using Microfluidics |
| title_full_unstemmed | Homogeneous Freezing of Water Using Microfluidics |
| title_short | Homogeneous Freezing of Water Using Microfluidics |
| title_sort | homogeneous freezing of water using microfluidics |
| topic | ice nucleation homogeneous freezing interfacial energy water droplet microfluidics |
| url | https://www.mdpi.com/2072-666X/12/2/223 |
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