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Heterogeneous ice nucleation in the atmosphere regulates cloud properties, such as phase (ice versus liquid) and lifetime. Aerosol particles of marine origin are relevant ice nucleating particle sources when marine aerosol layers are lifted over mountainous terrain and in higher latitude ocean boundary layers, distant from terrestrial aerosol sources. Among many particle compositions associated with ice nucleation by sea spray aerosols are highly saturated fatty acids. Previous studies have not demonstrated their ability to freeze dilute water droplets. This study investigates ice nucleation by monolayers at the surface of supercooled droplets and as crystalline particles at temperatures exceeding the threshold for homogeneous freezing. Results show the poor efficiency of long chain fatty acid (C16, C18) monolayers in templating freezing of pure water droplets and seawater subphase to temperatures of at least −30 °C, consistent with theory. This contrasts with freezing of fatty alcohols (C22 used here) at nearly 20 °C warmer. Evaporation of μL-sized droplets to promote structural compression of a C19 acid monolayer did not favor warmer ice formation of drops. Heterogeneous ice nucleation occurred for nL-sized droplets condensed on 5 to 100 μm crystalline particles of fatty acid (C12 to C20) at a range of temperatures below −28 °C. These experiments suggest that fatty acids nucleate ice at warmer than −36 °C only when the crystalline phase is present. Rough estimates of ice active site densities are consistent with those of marine aerosols, but require knowledge of the proportion of surface area comprised of fatty acids for application.
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A Microfluidic Device for Automated High Throughput Detection of Ice Nucleation of Snomax®
Measurement of ice nucleation (IN) temperature of liquid solutions at sub-ambient temperatures has applications in atmospheric, water quality, food storage, protein crystallography and pharmaceutical sciences. Here we present details on the construction of a temperature-controlled microfluidic platform with multiple individually addressable temperature zones and on-chip temperature sensors for high-throughput IN studies in droplets. We developed, for the first time, automated droplet freezing detection methods in a microfluidic device, using a deep neural network (DNN) and a polarized optical method based on intensity thresholding to classify droplets without manual counting. This platform has potential applications in continuous monitoring of liquid samples consisting of aerosols to quantify their IN behavior, or in checking for contaminants in pure water. A case study of the two detection methods was performed using Snomax® (Snomax International, Englewood, CO, USA), an ideal ice nucleating particle (INP). Effects of aging and heat treatment of Snomax® were studied with Fourier transform infrared (FTIR) spectroscopy and a microfluidic platform to correlate secondary structure change of the IN protein in Snomax® to IN temperature. It was found that aging at room temperature had a mild impact on the ice nucleation ability but heat treatment at 95 °C had a more pronounced effect by reducing the ice nucleation onset temperature by more than 7 °C and flattening the overall frozen fraction curve. Results also demonstrated that our setup can generate droplets at a rate of about 1500/min and requires minimal human intervention for DNN classification.
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- Award ID(s):
- 1801971
- PAR ID:
- 10232176
- Date Published:
- Journal Name:
- Micromachines
- Volume:
- 12
- Issue:
- 3
- ISSN:
- 2072-666X
- Page Range / eLocation ID:
- 296
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/mi12030296
