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Micromachines
Special Issues
Microfluidic Platforms for Ice Nucleation Studies
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Microfluidic Platforms for Ice Nucleation Studies

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "C：Chemistry".

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 8084

Special Issue Editors

Dr. Mark D. Tarn

E-Mail Website
Guest Editor
School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
Interests: microfluidics; lab-on-a-chip; microfabrication; magnetic particles; analytical chemistry; immunoassays; radiopharmaceuticals for positron emission tomography (PET); ice nucleation
Dr. Naama Reicher

E-Mail Website
Guest Editor
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
Interests: microfluidics; lab-on-a-chip; microfabrication; analytical chemistry; immunoassays; ice nucleation

Special Issue Information

Dear Colleagues,

The freezing of water, involving the nucleation and crystallisation of ice, is an important factor for processes that include cloud glaciation, cryobiology, food preparation and storage, and various aspects of materials science. However, our understanding of its mechanisms in many of these operations is remarkably lacking, often resulting in bottlenecks in analyses or process control. The fluidic and spatial control offered by microfluidic technology offers the potential for greatly improving analytical throughput and control over critical freezing parameters. This includes, for example, high throughput analysis via the freezing of monodispersed droplets for atmospheric analysis or cryopreservation studies, the ability to study the effects of freezing on various species (and vice versa) in a well-defined environment, and the use of freeze-thaw ice valves for sequential processing, among others.

The Special Issue aims to showcase recent developments that demonstrate how ice nucleation in novel microfluidic systems can address challenges in analysis and process control for a range of environmental, chemical, and biological applications.

Dr. Mark D. Tarn
Dr. Naama Reicher
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ice Nucleation
  • Ice-Nucleating Particles (INPs)
  • Supercooled Water
  • Immersion Mode Freezing
  • Droplet Microfluidics
  • Atmospheric Science/Atmospheric Aerosol Analysis
  • Cryobiology/Cryopreservation
  • Freeze-Thaw Valves
  • Cryogel Particles

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Published Papers (2 papers)

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Research

18 pages, 3884 KiB  
Article
A Microfluidic Device for Automated High Throughput Detection of Ice Nucleation of Snomax®
by Priyatanu Roy, Margaret L. House and Cari S. Dutcher
Micromachines 2021, 12(3), 296; https://doi.org/10.3390/mi12030296 - 11 Mar 2021
Cited by 12 | Viewed by 4321
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Microfluidic Platforms for Ice Nucleation Studies)
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Graphical abstract

23 pages, 1895 KiB  
Article
Homogeneous Freezing of Water Using Microfluidics
by Mark D. Tarn, Sebastien N. F. Sikora, Grace C. E. Porter, Jung-uk Shim and Benjamin J. Murray
Micromachines 2021, 12(2), 223; https://doi.org/10.3390/mi12020223 - 23 Feb 2021
Cited by 12 | Viewed by 3189
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Microfluidic Platforms for Ice Nucleation Studies)
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