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Description
Publication abstract: Measurement of ice nucleation (IN) temperature of liquid solutions at subambient temperatures has applications in atmospheric, protein crystallography, food storage and pharmaceutical sciences. We have developed a temperature-controlled microfluidic platform with on-chip temperature sensors and automated detection algorithms for high throughput IN studies in droplets. Our platform can generate a temperature gradient for achieving a specified cooling rate or a constant temperature using multiple temperature zones. Detection of freezing was automated using a pretrained deep neural network (DNN) to classify droplets into liquid or frozen classes. A polarized optical method based on intensity thresholding was also developed without the need for training. A case study of the two automated methods was performed using Snomax, an ideal ice nucleating particle (INP). Effects of aging and heat treatment of Snomax was studied with Fourier transform infrared spectroscopy and 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 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. The detection algorithms and experimental platform will be used in future studies of different INPs and homogeneous nucleation of pure water. This work was supported by NSF through the NSF Center for Aerosol Impacts on Chemistry of the Environment (CAICE), an NSF Funded Center for Chemical Innovation (CHE1801971). Portions of this work were conducted in the Minnesota Nano Center, which is supported by the National Science Foundation through the National Nano Coordinated Infrastructure Network (NNCI) under Award Number ECCS2025124. Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp) Roy, Priyatanu; House, Margaret; Dutcher, Cari (2021). Data from: A Microfluidic Device for Automated High Throughput Detection of Ice Nucleation of Snomax®. In Center for Aerosol Impacts on Chemistry of the Environment (CAICE). UC San Diego Library Digital Collections. https://doi.org/10.6075/J02N50T8 This package contains an explanatory readme file and the code and the data used to generate "A Microfluidic Device for Automated High Throughput Detection of Ice Nucleation of Snomax®".
Type
dataset
Identifier
ark:/20775/bb5023335q
Language
No linguistic content
Subject
High throughput Ice nucleating particles Snomax Automated detection Machine learning Microfluidic device Deep neural network Polarized light
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