scholarly journals The enhancement and suppression of immersion mode heterogeneous ice-nucleation by solutes

2018 ◽  
Vol 9 (17) ◽  
pp. 4142-4151 ◽  
Author(s):  
Thomas F. Whale ◽  
Mark A. Holden ◽  
Theodore W. Wilson ◽  
Daniel O'Sullivan ◽  
Benjamin J. Murray
Keyword(s):  
Liquid Water ◽  
Heterogeneous Nucleation ◽  
Alkali Halides ◽  
Supercooled Liquid ◽  
Ice Nucleation ◽  
Ammonium Salts ◽  
Atmospherically Relevant ◽  
Heterogeneous Ice Nucleation

Heterogeneous nucleation of ice from supercooled liquid water by some atmospherically relevant nucleators is enhanced by ammonium salts and suppressed by alkali halides.

scholarly journals Mechanism of ice nucleation in liquid water on alkali feldspars

2022 ◽  
Author(s):  
Alice Keinert ◽  
Kathrin Deck ◽  
Tilia Gädeke ◽  
Thomas Leisner ◽  
Alexei A. Kiselev
Keyword(s):  
Liquid Water ◽  
Heterogeneous Nucleation ◽  
Supercooled Liquid ◽  
Nucleation Site ◽  
Ice Nucleation ◽  
Natural Environments ◽  
Mineral Surfaces ◽  
Aqueous Interfaces ◽  
Alkali Feldspars

Crystallization of supercooled liquid water in most natural environments starts with heterogeneous nucleation of ice induced by a nucleation site. Mineral surfaces, which form the majority of aqueous interfaces in...

scholarly journals Predicting heterogeneous ice nucleation with a data-driven approach

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Martin Fitzner ◽  
Philipp Pedevilla ◽  
Angelos Michaelides
Keyword(s):  
Liquid Water ◽  
Ice Nucleation ◽  
Lattice Match ◽  
Density Reduction ◽  
Local Ordering ◽  
Data Driven Approach ◽  
Quantitative Understanding ◽  
Foreign Materials ◽  
Learning Analysis ◽  
Heterogeneous Ice Nucleation

Abstract Water in nature predominantly freezes with the help of foreign materials through a process known as heterogeneous ice nucleation. Although this effect was exploited more than seven decades ago in Vonnegut’s pioneering cloud seeding experiments, it remains unclear what makes a material a good ice former. Here, we show through a machine learning analysis of nucleation simulations on a database of diverse model substrates that a set of physical descriptors for heterogeneous ice nucleation can be identified. Our results reveal that, beyond Vonnegut’s connection with the lattice match to ice, three new microscopic factors help to predict the ice nucleating ability. These are: local ordering induced in liquid water, density reduction of liquid water near the surface and corrugation of the adsorption energy landscape felt by water. With this we take a step towards quantitative understanding of heterogeneous ice nucleation and the in silico design of materials to control ice formation.

scholarly journals Photomineralization mechanism changes the ability of dissolved organic matter to activate cloud droplets and to nucleate ice crystals

2019 ◽  
Vol 19 (19) ◽  
pp. 12397-12412 ◽  
Author(s):  
Nadine Borduas-Dedekind ◽  
Rachele Ossola ◽  
Robert O. David ◽  
Lin S. Boynton ◽  
Vera Weichlinger ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Dissolved Organic Matter ◽  
Organic Acids ◽  
Liquid Water ◽  
Supercooled Liquid ◽  
Ice Nucleation ◽  
Ice Crystals ◽  
Cloud Droplets ◽  
Photochemical Processing

Abstract. An organic aerosol particle has a lifetime of approximately 1 week in the atmosphere during which it will be exposed to sunlight. However, the effect of photochemistry on the propensity of organic matter to participate in the initial cloud-forming steps is difficult to predict. In this study, we quantify on a molecular scale the effect of photochemical exposure of naturally occurring dissolved organic matter (DOM) and of a fulvic acid standard on its cloud condensation nuclei (CCN) and ice nucleation (IN) activity. We find that photochemical processing, equivalent to 4.6 d in the atmosphere, of DOM increases its ability to form cloud droplets by up to a factor of 2.5 but decreases its ability to form ice crystals at a loss rate of −0.04 ∘CT50 h−1 of sunlight at ground level. In other words, the ice nucleation activity of photooxidized DOM can require up to 4 ∘C colder temperatures for 50 % of the droplets to activate as ice crystals under immersion freezing conditions. This temperature change could impact the ratio of ice to water droplets within a mixed-phase cloud by delaying the onset of glaciation and by increasing the supercooled liquid fraction of the cloud, thereby modifying the radiative properties and the lifetime of the cloud. Concurrently, a photomineralization mechanism was quantified by monitoring the loss of organic carbon and the simultaneous production of organic acids, such as formic, acetic, oxalic and pyruvic acids, CO and CO2. This mechanism explains and predicts the observed increase in CCN and decrease in IN efficiencies. Indeed, we show that photochemical processing can be a dominant atmospheric ageing process, impacting CCN and IN efficiencies and concentrations. Photomineralization can thus alter the aerosol–cloud radiative effects of organic matter by modifying the supercooled-liquid-water-to-ice-crystal ratio in mixed-phase clouds with implications for cloud lifetime, precipitation patterns and the hydrological cycle.Highlights. During atmospheric transport, dissolved organic matter (DOM) within aqueous aerosols undergoes photochemistry. We find that photochemical processing of DOM increases its ability to form cloud droplets but decreases its ability to form ice crystals over a simulated 4.6 d in the atmosphere. A photomineralization mechanism involving the loss of organic carbon and the production of organic acids, CO and CO2 explains the observed changes and affects the liquid-water-to-ice ratio in clouds.

scholarly journals Ice is born in low-mobility regions of supercooled liquid water

2019 ◽  
Vol 116 (6) ◽  
pp. 2009-2014 ◽  
Author(s):  
Martin Fitzner ◽  
Gabriele C. Sosso ◽  
Stephen J. Cox ◽  
Angelos Michaelides
Keyword(s):  
Liquid Water ◽  
Dynamical Behavior ◽  
Supercooled Liquid ◽  
Ice Nucleation ◽  
Water Molecules ◽  
Ice Crystal ◽  
Surrounding Water ◽  
Dynamical Heterogeneity ◽  
Complex Dynamical Behavior

When an ice crystal is born from liquid water, two key changes occur: (i) The molecules order and (ii) the mobility of the molecules drops as they adopt their lattice positions. Most research on ice nucleation (and crystallization in general) has focused on understanding the former with less attention paid to the latter. However, supercooled water exhibits fascinating and complex dynamical behavior, most notably dynamical heterogeneity (DH), a phenomenon where spatially separated domains of relatively mobile and immobile particles coexist. Strikingly, the microscopic connection between the DH of water and the nucleation of ice has yet to be unraveled directly at the molecular level. Here we tackle this issue via computer simulations which reveal that (i) ice nucleation occurs in low-mobility regions of the liquid, (ii) there is a dynamical incubation period in which the mobility of the molecules drops before any ice-like ordering, and (iii) ice-like clusters cause arrested dynamics in surrounding water molecules. With this we establish a clear connection between dynamics and nucleation. We anticipate that our findings will pave the way for the examination of the role of dynamical heterogeneities in heterogeneous and solution-based nucleation.

scholarly journals Magnetic control of heterogeneous ice nucleation with nanophase magnetite: Biophysical and agricultural implications

2018 ◽  
Vol 115 (21) ◽  
pp. 5383-5388 ◽  
Author(s):  
Atsuko Kobayashi ◽  
Masamoto Horikawa ◽  
Joseph L. Kirschvink ◽  
Harry N. Golash
Keyword(s):  
Magnetic Fields ◽  
Heterogeneous Nucleation ◽  
Ferromagnetic Material ◽  
Ice Nucleation ◽  
Rotating Magnetic Fields ◽  
Water Ice ◽  
Nucleation Sites ◽  
Material Tailoring ◽  
Mechanical Rotation ◽  
Heterogeneous Ice Nucleation

In supercooled water, ice nucleation is a stochastic process that requires ∼250–300 molecules to transiently achieve structural ordering before an embryonic seed crystal can nucleate. This happens most easily on crystalline surfaces, in a process termed heterogeneous nucleation; without such surfaces, water droplets will supercool to below −30 °C before eventually freezing homogeneously. A variety of fundamental processes depends on heterogeneous ice nucleation, ranging from desert-blown dust inducing precipitation in clouds to frost resistance in plants. Recent experiments have shown that crystals of nanophase magnetite (Fe3O4) are powerful nucleation sites for this heterogeneous crystallization of ice, comparable to other materials like silver iodide and some cryobacterial peptides. In natural materials containing magnetite, its ferromagnetism offers the possibility that magneto-mechanical motion induced by external oscillating magnetic fields could act to disrupt the water–crystal interface, inhibiting the heterogeneous nucleation process in subfreezing water and promoting supercooling. For this to act, the magneto-mechanical rotation of the particles should be higher than the magnitude of Brownian motions. We report here that 10-Hz precessing magnetic fields, at strengths of 1 mT and above, on ∼50-nm magnetite crystals dispersed in ultrapure water, meet these criteria and do indeed produce highly significant supercooling. Using these rotating magnetic fields, we were able to elicit supercooling in two representative plant and animal tissues (celery and bovine muscle), both of which have detectable, natural levels of ferromagnetic material. Tailoring magnetic oscillations for the magnetite particle size distribution in different tissues could maximize this supercooling effect.

scholarly journals A new parameterization of ice heterogeneous nucleation coupled to aerosol chemistry in WRF-Chem model version 3.5.1: evaluation through the ISDAC measurements

2020 ◽  
Author(s):  
Setigui Aboubacar Keita ◽  
Eric Girard ◽  
Jean-Christophe Raut ◽  
Maud Leriche ◽  
Jean-Pierre Blanchet ◽  
...  
Keyword(s):  
Heterogeneous Nucleation ◽  
Climate Model ◽  
Poor Performance ◽  
Cloud Microphysics ◽  
Ice Nucleation ◽  
Ice Crystals ◽  
The Arctic ◽  
Microphysics Scheme ◽  
Ice Clouds ◽  
Heterogeneous Ice Nucleation

Abstract. In the Arctic, during polar night and early spring, ice clouds are separated into two leading types: (1) TIC1 clouds characterized by large concentration of very small crystals, and TIC2 clouds characterized by low concentration of large ice crystals. Using suitable parameterization of heterogeneous ice nucleation is essential for properly representing ice cloud in meteorological and climate model and subsequently understanding their interactions with aerosols and radiation. Here, we describe a new parameterization for ice crystals formation by heterogeneous nucleation coupled to aerosols chemistry in WRF-Chem. The parameterization is implemented in the Milbrandt and Yau’s two-moment cloud microphysics scheme and we assess how the WRF-Chem model responds to the real time interaction between chemistry and the new parameterization. Well-documented reference cases provided us in situ data from the spring 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) campaign over Alaska. Our analysis reveals that the new parameterization clearly improves the representation of the IWC in polluted or unpolluted air masses and shows the poor performance of the reference parameterization in representing ice clouds with low IWC. The new parameterization is, thus able to represent TIC1 and TIC2 microphysical characteristics at the top of the clouds were heterogeneous ice nucleation is most likely occurring even knowing the bias of simulated aerosols by WRF-Chem over Arctic.

scholarly journals Predicting Heterogeneous Ice Nucleation With a Data-Driven Approach

2020 ◽  
Author(s):  
Martin Fitzner ◽  
Philipp Pedevilla ◽  
Angelos Michaelides
Keyword(s):  
Liquid Water ◽  
Ice Nucleation ◽  
Lattice Match ◽  
Density Reduction ◽  
Local Ordering ◽  
Data Driven Approach ◽  
Quantitative Understanding ◽  
Foreign Materials ◽  
Learning Analysis ◽  
Heterogeneous Ice Nucleation

Abstract Water in nature predominantly freezes with the help of foreign materials through a process known as heterogeneous ice nucleation. Although this effect was exploited more than seven decades ago in Vonnegut's pioneering cloud seeding experiments, it remains unclear what makes a material a good ice former. Here, we show through a machine learning analysis of ice nucleation simulations on a database of diverse model substrates that a set of physical descriptors for heterogeneous ice nucleation can be identified. Our results reveal that, beyond Vonnegut's original connection with the lattice match to ice, three new microscopic and experimentally accessible factors help to predict the ice nucleating ability. These are: i) the local ordering induced in liquid water; ii) the density reduction of the liquid water near the surface; and iii) the corrugation of the adsorption energy landscape felt by water. With this we take a step towards a quantitative understanding of heterogeneous ice nucleation and the in silico design of materials to control ice formation.

scholarly journals Using critical area analysis to deconvolute internal and external particle variability in heterogeneous ice nucleation

2016 ◽  
Author(s):  
Hassan Beydoun ◽  
Ryan C. Sullivan
Keyword(s):  
Surface Area ◽  
Active Site ◽  
Internal Variability ◽  
Ice Nucleation ◽  
Critical Surface ◽  
Critical Area ◽  
Concentration Data ◽  
Immersion Freezing ◽  
Atmospherically Relevant ◽  
Heterogeneous Ice Nucleation

Abstract. Heterogeneous ice nucleation remains one of the outstanding problems in cloud physics and atmospheric science. Experimental challenges in properly simulating particle induced freezing processes under atmospherically relevant conditions have largely contributed to the absence of a consistent and comprehensive parameterization of immersion freezing properties. Here we formulate an ice active surface site based stochastic model of heterogeneous freezing with the unique feature of invoking a continuum assumption on the ice nucleating activity (contact angle) of an aerosol particle's surface, that requires no assumptions about the size or number of active sites. The result is a particle specific property g that defines a distribution of local ice nucleation rates. Upon integration this yields a full freezing probability function for an ice-nucleating particle. Current cold plate droplet freezing measurements provide a great resource for studying the freezing properties of many atmospheric aerosol systems. A method based on statistical significance to determine an ice nucleating species' specific critical surface area is presented that can resolve the two-dimensional nature of the ice nucleation ability of aerosol particles: internal variability in active site strengths and freezing rates along an individual particle's surface, as well as external variability between two particles of the same type in an aerosol population. By applying this method to experimental data we demonstrate its ability to comprehensively interpret immersion freezing temperature spectra of droplets containing variable particle concentrations. It is shown that general active site density functions such as the popular ns parameterization cannot be reliably extrapolated below this critical area threshold to describe freezing curves for lower particle surface area concentrations. Freezing curves obtained below this threshold translate to higher ns values, while the ns values are essentially the same from curves obtained above the critical area threshold. However, we can successfully predict the lower concentration freezing curves, which are more atmospherically relevant, through a process of random sampling from the statistically significant global distribution obtained from high particle concentration data. Our analysis further revealed that one individual atmospheric illite mineral particle will not contain the entire range of ice active site activity for that system (its internal variability). Comprehensive parameterizations that can predict the temporal evolution of the frozen fraction of cloud droplets in larger atmospheric models are also derived from this new framework.

scholarly journals A Three-Year Climatology of Cloud-Top Phase over the Southern Ocean and North Pacific

2011 ◽  
Vol 24 (9) ◽  
pp. 2405-2418 ◽  
Author(s):  
Anthony E. Morrison ◽  
Steven T. Siems ◽  
Michael J. Manton
Keyword(s):  
Southern Ocean ◽  
Liquid Water ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Supercooled Liquid ◽  
Global Climate Models ◽  
Shortwave Radiation ◽  
Orthogonal Polarization ◽  
Temperature Range ◽  
Cloud Tops

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 observations from the Terra satellite are used to create a 3-yr climatology of cloud-top phase over a section of the Southern Ocean (south of Australia) and the North Pacific Ocean. The intent is to highlight the extensive presence of supercooled liquid water over the Southern Ocean region, particularly during summer. The phase of such clouds directly affects the absorbed shortwave radiation, which has recently been found to be “poorly simulated in both state-of-the-art reanalysis and coupled global climate models” (Trenberth and Fasullo). The climatology finds that supercooled liquid water is present year-round in the low-altitude clouds across this section of the Southern Ocean. Further, the MODIS cloud phase algorithm identifies very few glaciated cloud tops at temperatures above −20°C, rather inferring a large portion of “uncertain” cloud tops. Between 50° and 60°S during the summer, the albedo effect is compounded by a seasonal reduction in high-level cirrus. This is in direct contrast to the Bering Sea and Gulf of Alaska. Here MODIS finds a higher likelihood of observing warm liquid water clouds during summer and a reduction in the relative frequency of cloud tops within the 0° to −20°C temperature range. As the MODIS cloud phase product has limited ability to confidently identify cloud-top phase between −5° and −25°C, future research should include observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and other space-based sensors to help with the classification within this temperature range. Further, multiregion in situ verification of any remotely sensed observations is vital to further understanding the cloud phase processes.

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