On the Interpretation of Quantitative Experimental Data on Nucleation Rates Using Classical Nucleation Theory

2006 ◽  
Vol 110 (43) ◽  
pp. 21944-21949 ◽  
Author(s):  
Richard P. Sear
Author(s):  
Yogini Patel ◽  
Giteshkumar Patel ◽  
Teemu Turunen-Saaresti

The aim of the paper is to analyse the effect of turbulence and real gas models on the process of spontaneous condensation in converging diverging (CD) nozzle by using commercial Computational Fluid Dynamics (CFD) code. The calculations were based on the 2-D compressible Navier-Stokes (NS) equations coupled with two-equation turbulence model, and the non-equilibrium spontaneous condensing steam flow was solved on the basis of the classical nucleation theory. The results were validated to the available experimental data.


2014 ◽  
Vol 78 (6) ◽  
pp. 1437-1447 ◽  
Author(s):  
M. Prieto

Supersaturation-Nucleation-Time (S-N-T) diagrams are shown to be a useful tool to predict nucleation during reactive-transport processes in porous media. Such diagrams can be determined experimentally or estimated from theoretical calculations based on classical nucleation theory. With this aim, a ‘pragmatic’ understanding of the nucleation rate equation is adopted here and the meaning and magnitude of the interfacial tension and induction time discussed. Theoretical diagrams and experimental data are shown to match fairly well as long as there is an appropriate choice of the ‘relevant’ volume for induction-time calculations.


2017 ◽  
Vol 17 (3) ◽  
pp. 1713-1739 ◽  
Author(s):  
Luisa Ickes ◽  
André Welti ◽  
Ulrike Lohmann

Abstract. Heterogeneous ice formation by immersion freezing in mixed-phase clouds can be parameterized in general circulation models (GCMs) by classical nucleation theory (CNT). CNT parameterization schemes describe immersion freezing as a stochastic process, including the properties of insoluble aerosol particles in the droplets. There are different ways to parameterize the properties of aerosol particles (i.e., contact angle schemes), which are compiled and tested in this paper. The goal of this study is to find a parameterization scheme for GCMs to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. We showed in a previous publication that the resulting freezing curves from CNT are very sensitive to unconstrained kinetic and thermodynamic parameters in the case of homogeneous freezing. Here we investigate how sensitive the outcome of a parameter estimation for contact angle schemes from experimental data is to unconstrained kinetic and thermodynamic parameters. We demonstrate that the parameters describing the contact angle schemes can mask the uncertainty in thermodynamic and kinetic parameters. Different CNT formulations are fitted to an extensive immersion freezing dataset consisting of size-selected measurements as a function of temperature and time for different mineral dust types, namely kaolinite, illite, montmorillonite, microcline (K-feldspar), and Arizona test dust. We investigated how accurate different CNT formulations (with estimated fit parameters for different contact angle schemes) reproduce the measured freezing data, especially the time and particle size dependence of the freezing process. The results are compared to a simplified deterministic freezing scheme. In this context, we evaluated which CNT-based parameterization scheme able to represent particle properties is the best choice to describe immersion freezing in a GCM.


2016 ◽  
Author(s):  
L. Ickes ◽  
A. Welti ◽  
U. Lohmann

Abstract. Heterogeneous ice formation by immersion freezing in mixed-phase clouds can be parameterized in general circulation models (GCMs) by Classical Nucleation Theory (CNT). CNT parameterization schemes describe freezing as a stochastic process including the properties of insoluble aerosol particles, so called ice nuclei, in the droplets. There are different ways how to describe the properties of aerosol particles (i.e. contact angle schemes), which are compiled and tested in this paper. The goal of this study is to find a parameterization scheme for GCMs to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. The results of using CNT are very sensitive to unconstrained kinetic and thermodynamic parameters in the case of homogeneous freezing leading to uncertainties in calculated nucleation rates Jhom of several orders of magnitude. Here we investigate how sensitive the outcome of a parameter estimation for contact angle schemes from experimental data is to kinetic and thermodynamic parameters. We show that additional free parameter can mask the uncertainty of Jimm due to thermodynamic and kinetic parameters. Different CNT formulations are fitted to an extensive immersion freezing dataset as a function of particle diameter (d), temperature T and time t for different mineral dust types, namely kaolinite, illite, montmorillonite, microcline (K-feldspar) and Arizona test dust. It is investigated how accurate different CNT formulations (with the estimated fit parameters) reproduce the measured freezing curves, especially the time and particle size dependence of the freezing process. The results are compared to a simplified deterministic freezing scheme. It is evaluated in this context which CNT based parameterization scheme to represent particle properties is a good choice to describe immersion freezing in a GCM.


2016 ◽  
Vol 16 (4) ◽  
pp. 2083-2107 ◽  
Author(s):  
Peter A. Alpert ◽  
Daniel A. Knopf

Abstract. Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T, and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, Ntot, and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of Jhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Min Yang ◽  
Lu Wang ◽  
Wentao Yan

AbstractA three-dimensional phase-field model is developed to simulate grain evolutions during powder-bed-fusion (PBF) additive manufacturing, while the physically-informed temperature profile is implemented from a thermal-fluid flow model. The phase-field model incorporates a nucleation model based on classical nucleation theory, as well as the initial grain structures of powder particles and substrate. The grain evolutions during the three-layer three-track PBF process are comprehensively reproduced, including grain nucleation and growth in molten pools, epitaxial growth from powder particles, substrate and previous tracks, grain re-melting and re-growth in overlapping zones, and grain coarsening in heat-affected zones. A validation experiment has been carried out, showing that the simulation results are consistent with the experimental results in the molten pool and grain morphologies. Furthermore, the grain refinement by adding nanoparticles is preliminarily reproduced and compared against the experimental result in literature.


Minerals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 715
Author(s):  
Miodrag J. Lukić ◽  
Felix Lücke ◽  
Teodora Ilić ◽  
Katharina Petrović ◽  
Denis Gebauer

Nucleation of minerals in the presence of additives is critical for achieving control over the formation of solids in biomineralization processes or during syntheses of advanced hybrid materials. Herein, we investigated the early stages of Fe(III) (oxy)(hydr)oxide formation with/without polyglutamic acid (pGlu) at low driving force for phase separation (pH 2.0 to 3.0). We employed an advanced pH-constant titration assay, X-ray diffraction, thermal analysis with mass spectrometry, Fourier Transform infrared spectroscopy, and scanning electron microscopy. Three stages were observed: initial binding, stabilization of Fe(III) pre-nucleation clusters (PNCs), and phase separation, yielding Fe(III) (oxy)(hydr)oxide. The data suggest that organic–inorganic interactions occurred via binding of olation Fe(III) PNC species. Fourier Transform Infrared Spectroscopy (FTIR) analyses revealed a plausible interaction motif and a conformational adaptation of the polypeptide. The stabilization of the aqueous Fe(III) system against nucleation by pGlu contrasts with the previously reported influence of poly-aspartic acid (pAsp). While this is difficult to explain based on classical nucleation theory, alternative notions such as the so-called PNC pathway provide a possible rationale. Developing a nucleation theory that successfully explains and predicts distinct influences for chemically similar additives like pAsp and pGlu is the Holy Grail toward advancing the knowledge of nucleation, early growth, and structure formation.


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