Maximizing the performance of information engines

Information engines are the modern realization of the Maxwell demon, a thought experiment that revealed the close connection between thermodynamics and information. We introduce a “textbook” model of an information engine and experimentally study it. The engine is based on an optically trapped heavy colloidal bead in water. The water functions as a thermal bath, whose fluctuation forces can, via a feedback algorithm, ratchet the bead “up”, storing the gravitational energy in a work reservoir (battery). We optimize both the rate of energy storage and the directed velocity and find that big beads store more energy, while small beads go faster. However, increasing trap stiffness improves both criteria, showing the fundamental role of the material parameters of the motor. Our observations agree well with a recently developed theory based on mean first-passage times. By optimizing the feedback algorithm and trap parameters, we have observed energy storage rates of 1000 k_BT/s and directed velocities of 190 µm/s, numbers that exceed previous efforts by an order of magnitude.