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Article Dans Une Revue Physical Review Research Année : 2021

Stochastic Inference of Surface-Induced Effects using Brownian Motion

Résumé

Brownian motion in confinement and at interfaces is a canonical situation, encountered from fundamental biophysics to nanoscale engineering. Using the Lorenz-Mie framework, we optically record the thermally-induced tridimensional trajectories of individual microparticles, within salty aqueous solutions, in the vicinity of a rigid wall, and in the presence of surface charges. We construct the time-dependent position and displacement probability density functions, and study the non-Gaussian character of the latter which is a direct signature of the hindered mobility near the wall. Based on these distributions, we implement a novel, robust and self-calibrated multifitting method, allowing for the thermal-noise-limited inference of diffusion coefficients spatially-resolved at the nanoscale, equilibrium potentials, and forces at the femtoNewton resolution.
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Dates et versions

hal-03047058 , version 1 (08-12-2020)
hal-03047058 , version 2 (28-04-2021)

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Maxime Lavaud, Thomas Salez, Yann Louyer, Yacine Amarouchene. Stochastic Inference of Surface-Induced Effects using Brownian Motion. Physical Review Research, 2021, 3, pp.L032011. ⟨hal-03047058v2⟩

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