Mean-squared displacement from 2D random walks — measuring D from trajectories
10
2.0
1.00
200
D (fitted)
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α (slope log-log)
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Δt elapsed
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⟨R²⟩ current
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Mean-squared displacement (MSD): the canonical observable for diffusion. For normal (Brownian) diffusion in 2D, MSD(τ) = 4Dτ — a linear rise. The diffusion coefficient D = kBT/(6πηr) (Stokes-Einstein) connects molecular size r, viscosity η, and temperature. Anomalous diffusion occurs in crowded media: sub-diffusion (MSD ~ τ^α, α < 1) arises from obstacles, caging, or viscoelastic cytoplasm; super-diffusion (α > 1) from active transport or Lévy flights. In practice, D is extracted by fitting the linear (or power-law) regime of the ensemble-averaged MSD. The MSD log-log plot (right) shows the fitted slope α and intercepts. This technique is standard in single-particle tracking, NMR relaxation, and neutron scattering.