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      Passive and active colloidal chemotaxis in a microfluidic channel: mesoscopic and stochastic models

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          Abstract

          Chemotaxis is the response of a particle to a gradient in the chemical composition of the environment. While it was originally observed for biological organisms, it is of great interest in the context of synthetic active particles such as nanomotors. Experimental demonstration of chemotaxis for chemically-powered colloidal nanomotor was reported in the literature in the context of chemo-attraction in a still fluid or in a microfluidic channel where the gradient is sustained by a specific inlet geometry. In this work, we use mesoscopic particle-based simulations of the colloid and solvent to demonstrate chemotaxis in a microfluidic channel. On the basis of this particle-based model, we evaluate the chemical concentration profiles in the presence of passive or chemically active colloids, compute the chemotactic force acting upon them and propose a stochastic model that rationalises our findings on colloidal chemotaxis. Our model is also able to explain the results of an earlier simulation work that uses a simpler geometry and to extend its interpretation.

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          Most cited references 31

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          The NumPy array: a structure for efficient numerical computation

          In the Python world, NumPy arrays are the standard representation for numerical data. Here, we show how these arrays enable efficient implementation of numerical computations in a high-level language. Overall, three techniques are applied to improve performance: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. We first present the NumPy array structure, then show how to use it for efficient computation, and finally how to share array data with other libraries.
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            Rattle: A “velocity” version of the shake algorithm for molecular dynamics calculations

             Hans Andersen (1983)
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              Mesoscopic model for solvent dynamics

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                Author and article information

                Journal
                2017-01-18
                Article
                10.5281/zenodo
                1701.05020

                http://creativecommons.org/licenses/by/4.0/

                Custom metadata
                11 pages, 11 figures
                cond-mat.soft cond-mat.stat-mech
                Pierre de Buyl

                Condensed matter

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