Carbon dioxide (CO2) hydrates are important in a diverse
range of applications and technologies in the environmental and energy
fields. The development of such technologies relies on fundamental
understanding, which necessitates not only experimental but also computational
studies of the growth behavior of CO2hydrates and the
factors affecting their crystal morphology. As experimental observations
show that the morphology of CO2hydrate particles differs
depending on growth conditions, a detailed understanding of the relation
between the hydrate structure and growth conditions would be helpful.
To this end, this work adopts a modeling approach based on hybrid
probabilistic cellular automata to investigate variations in CO2hydrate crystal morphology during hydrate growth from stagnant
liquid water presaturated with CO2. The model, which uses
free energy density profiles as inputs, correlates the variations
in growth morphology to the system subcoolingΔT, i.e., the temperature deficiency from the triple CO2–hydrate–water equilibrium temperature under a given
pressure, and properties of the growing hydrate-water interface, such
as surface tension and curvature. The model predicts that whenΔTis large, parabolic needle-like or dendrite crystals
emerge from planar fronts that deform and lose stability. In agreement
with chemical diffusion-limited growth, the position of such planar
fronts versus time follows a power law. In contrast, the tips of the
emerging parabolic crystals steadily grow in proportion to time. The
modeling framework is computationally fast and produces complex growth
morphology phenomena under diffusion-controlled growth from simple,
easy-to-implement rules, opening the way for employing it in multiscale
modeling of gas hydrates.