  Colloidal particles can create reconfigurable nanomaterials, with
applications such as color-changing, self-repairing, and self-regulating
materials and reconfigurable drug delivery systems. However, top-down methods
for manipulating colloids are limited in the scale they can control. We
consider here a new method for using chemical reactions to multiply the effects
of existing top-down colloidal manipulation methods to arrange large numbers of
colloids with single-particle precision, which we refer to as chemical herding.
Using simulation-based methods, we show that if a set of chemically active
colloids (herders) can be steered using external forces (i.e. electrophoretic,
dielectrophoretic, magnetic, or optical forces), then a larger set of colloids
(followers) that move in response to the chemical gradients produced by the
herders can be steered using the control algorithms given in this paper. We
also derive bounds that predict the maximum number of particles that can be
steered in this way, and we illustrate the effectiveness of this approach using
Brownian dynamics simulations. Based on the theoretical results and
simulations, we conclude that chemical herding is a viable method for
multiplying the effects of existing colloidal manipulation methods to create
useful structures and materials.
