Microfluidic immersion freezing of binary mineral mixtures containing microcline, montmorillonite, or quartz
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Date
2025-12-09
Publication Type
Journal Article
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yes
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Abstract
Mineral dusts are among the most active ice-nucleating particles present in cloud droplets, with their properties influencing radiative properties and precipitation formation. To improve weather predictions and climate projections, it is important to understand under which conditions ice will form on mineral dusts. Laboratory experiments have primarily focused on single minerals, and field samples are complex mixtures that cannot be controlled in their composition or particle size. To fill this gap, a bottom-up investigation of suspensions containing pure or binary mixtures of microcline, montmorillonite, or quartz at concentrations between 0.0001 and 0.1 wt % is presented. Arrays of monodisperse aqueous droplets (diameters of 75 μm) are generated using a microfluidic device and subsequently cooled at a rate of 1 K min-1. The probability of freezing in the presence of binary mixtures generally follows that of the most ice-active mineral. Each pure mineral's nucleation site density is fit as a function of temperature and used to predict the frozen fraction curves for each binary mixture assuming additivity of mineral surface area. Predictions are also made for Arizona Test Dust from the obtained pure mineral fits, and general agreement with experiments is observed. This work presents a systematic study of ice formation in the presence of pure and binary mixtures of common mineral dusts, providing information for the future design of composition-aware parameterizations for ice nucleation in the atmosphere.
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published
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Journal / series
Volume
25 (23)
Pages / Article No.
17997 - 18014
Publisher
Copernicus
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Organisational unit
03914 - deMello, Andrew / deMello, Andrew
03690 - Lohmann, Ulrike / Lohmann, Ulrike
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Funding
20-1 FEL-46 - Ice nucleation in mineral dust mixtures: measurements, predictions, and implications for the climate (ETHZ)
Related publications and datasets
Is supplemented by: https://doi.org/10.3929/ethz-b-000736892