Big grains eat small ones — LSW t^(1/3) coarsening
time t = 0
particles N = 0
mean radius <r> = 0
slope d(log r)/d(log t) = —
⚪ Ostwald Ripening — 2D Coarsening Field
About this simulation
A two-phase mixture is never truly at equilibrium while many small particles remain: their curved interfaces store surface energy. Over time the dispersed phase coarsens — large droplets grow while small ones dissolve and vanish — so the system reduces its total interfacial area. This 2D Canvas rendering shows that process directly on a plane, tracking the size distribution and the mean radius's t^(1/3) growth.
How it works
Each particle has a radius; the Gibbs-Thomson effect gives smaller particles a higher local solubility.
Solute diffuses from small (high-solubility) particles toward large ones, judged against the current critical radius r* (the mean radius).
Particles above r* grow; particles below it shrink and are removed when they vanish, handing their area to their neighbours.
Total area (the amount of the second phase) is conserved, so the size histogram shifts toward larger radii over time.
A faint background field shows local supersaturation: warm near shrinking (source) particles, cool near growing (sink) particles.
Initial particles — how many droplets seed the field.
Diffusion / temperature — scales the rate constant K (coarsening speed).
Gibbs-Thomson strength — how strongly curvature drives solubility.
Initial size spread — width of the starting radius distribution.
Click or tap the field — nucleate a fresh droplet at that point.
Pause / Play, Reset, ? — control the loop and reseed the field.
Did you know?
The same physics that makes large salt crystals grow at the expense of fine ones also ruins old ice cream: water recrystallises into ever-larger ice grains, giving that gritty texture. Ostwald ripening is why so many microstructures slowly coarsen — and why fast quenching is used to lock in fine, strong ones.