Direct measurement of thermophoretic forces

We study the thermophoretic motion of a micron sized single colloidal particle in front of a flat wall by evanescent light scattering. To quantify thermophoretic effects we analyse the nonequilibrium steady state (NESS) of the particle in a constant temperature gradient perpendicular to the confining walls. We propose to determine thermophoretic forces from a 'generalized potential' associated with the probability distribution of the particle position in the NESS. Experimentally we demonstrate, how this spatial probability distribution is measured and how thermophoretic forces can be extracted with 10 fN resolution. By varying temperature gradient and ambient temperature, the temperature dependence of Soret coefficient $S_T(T)$ is determined for $r = 2.5 \mu m$ polystyrene and $r = 1.35 \mu m$ melamine particles. The functional form of $S_T(T)$ is in good agreement with findings for smaller colloids. In addition, we measure and discuss hydrodynamic effects in the confined geometry. The theoretical and experimental technique proposed here extends thermophoresis measurements to so far inaccessible particle sizes and particle solvent combinations

Anisotropic diffusion in square lattice potentials: giant enhancement and control

The unbiased thermal diffusion of an overdamped Brownian particle in a square lattice potential is considered in the presence of an externally applied ac driving. The resulting diffusion matrix exhibits two orthogonal eigenvectors with eigenvalues $D_1>D_2>0$, indicating anisotropic diffusion along a "fast" and a "slow principal axis". For sufficiently small temperatures, $D_1$ may become arbitrarily large and at the same time $D_2$ arbitrarily small. The principal diffusion axis can be made to point into (almost) any direction by varying either the driving amplitude or the coupling of the particle to the potential, without changing any other property of the system or the driving.Comment: 7 pages, 7 figure

Measurement of Anomalous Diffusion Using Recurrent Neural Networks

Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNN) can efficiently characterize anomalous diffusion by determining the exponent from a single short trajectory, outperforming the standard estimation based on the MSD when the available data points are limited, as is often the case in experiments. Furthermore, the RNN can handle more complex tasks where there are no standard approaches, such as determining the anomalous diffusion exponent from a trajectory sampled at irregular times, and estimating the switching time and anomalous diffusion exponents of an intermittent system that switches between different kinds of anomalous diffusion. We validate our method on experimental data obtained from sub-diffusive colloids trapped in speckle light fields and super-diffusive microswimmers.Comment: 6 pages, 4 figures. Supplemental material available as separate file in the Ancillary Files sectio

Exploiting lattice potentials for sorting chiral particles

Several ways are demonstrated of how periodic potentials can be exploited for sorting molecules or other small objects which only differ by their chirality. With the help of a static bias force, the two chiral partners can be made to move along orthogonal directions. Time-periodic external forces even lead to motion into exactly opposite directions.Comment: 4 pages, 4 figure

Energetics of a Microscopic Feynman Ratchet

A general formalism is derived describing both dynamical and energetic properties of a microscopic Feynman ratchet. Work and heat flows are given as a series expansion in the thermodynamic forces, obtaining analytical expressions for the (non)linear response coefficients. Our results extend previously obtained expressions in the context of a chiral heat pump.Comment: 12 pages, 1 figur

Particle sorting by a structured microfluidic ratchet device with tunable selectivity: Theory and Experiment

We theoretically predict and experimentally demonstrate that several different particle species can be separated from each other by means of a ratchet device, consisting of periodically arranged triangular (ratchet) shaped obstacles. We propose an explicit algorithm for suitably tailoring the externally applied, time-dependent voltage protocol so that one or several, arbitrarily selected particle species are forced to migrate oppositely to all the remaining species. As an example we present numerical simulations for a mixture of five species, labelled according to their increasing size, so that species 2 and 4 simultaneously move in one direction and species 1, 3, and 5 in the other. The selection of species to be separated from the others can be changed at any time by simply adapting the voltage protocol. This general theoretical concept to utilize one device for many different sorting tasks is experimentally confirmed for a mixture of three colloidal particle species