Atomistic Simulation of Ice Nucleation on Silver Iodide (0001) Surfaces with Defects

Abstract

Small particles of silver iodide (AgI) are known to have excellent ice nucleating capabilities and have been used in rain seeding applications. It is widely believed that the silver terminated (0001) surface of β-AgI acts as a template for the basal plane of hexagonal ice. However, the (0001) surface of ionic crystals with the wurtzite structure is polar and will therefore exhibit reconstructions and defects. Here, we use atomistic molecular dynamics simulations to study how the presence of defects on AgI (0001) affects the rates and mechanism of heterogeneous ice nucleation at moderate supercooling at −10 • C. We consider AgI (0001) surfaces exhibiting vacancies, step edges, terraces, and pits, and compare them to simulations of the corresponding ideal surface. We find that while point defects have no significant effect on ice nucleation rates, step edges, terraces and pits reduce both the nucleation and growth rates by up to an order of magnitude. The reduction of the ice nucleation rate correlates well with the fraction of the surface area around the defects where perturbations of the hydration layer hinder the formation of a critical ice nucleus.

Effect of Graphene on Ice Polymorph

“…The study of Bi et al also suggests that the similarity between the graphene and the basal face of I h results in the selective promotion of the formation of I h over I c . Moreover, in the study of ice formation on AgI [43,44], it is also found that the substrate lattice structure can alter the polymorph of ice: I h mainly observed on the hexagonal β-AgI, while the Ic mainly found on cubic γ-AgI. These reports are in good agreement to our MD simulation results, confirming that the formation of I h can be selectively promoted by graphene surface.…”

Liquid Water and Interfacial, Cubic, and Hexagonal Ice Classification through Eclipsed and Staggered Conformation Template Matching

“…Further simulation details can be found in Ref. 9 We investigate the performance of the proposed method using different values of S min . In addition, we compare our method to a commonly used ice structure recognition algorithm based on spherical harmonics analysis, the CHILL+ algorithm, 15 in terms of ice structure recognition accuracy and computational efficiency.…”

“…However, the simulation-based studies require accurate and efficient algorithms for distinguishing the liquid and crystalline phases, and identifying different structures of ice crystals. [5][6][7][8][9] Depending on the temperature and pressure, more than 18 distinct ice polymorphs can exist. 10 However, under atmospheric conditions, only cubic ice (ice I c ) and hexagonal ice (ice I h ) are viable.…”

Effect of Hydrophobic Silicon Substrate on the Ice Formation at Different Temperatures

“…However, the surface area around the defects reduced the nucleation rate. This reduction is due to the perturbation of the hydration layer of the surface which will lead to retarding the critical nucleus formation [26].…”