Stochastic Inference of Surface-Induced Effects using Brownian Motion
Abstract
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.
Cite
@article{arxiv.2012.05512,
title = {Stochastic Inference of Surface-Induced Effects using Brownian Motion},
author = {Maxime Lavaud and Thomas Salez and Yann Louyer and Yacine Amarouchene},
journal= {arXiv preprint arXiv:2012.05512},
year = {2021}
}