Motor Driven High Performance Stochastic Microscale Machines
Implementing Organization
University of Hyderabad
Principal Investigator
Dr. Sudipto Muhuri
University Of Hyderabad
sudiptomuhuri@uohyd.ac.in
CO-Principal Investigator
Dr. Arnab Saha
University Of Calcutta, 87 /1, College Street, Kolkata,West Bengal,Kolkata-700073
Project Overview
Research on designing efficient and powerful artificial machines at the microscales are currently one of the most challenging, frontier problems of physics and engineering. In recent landmark experiments using micron size colloidal bead within an optical trap, microscale Carnot and Stirling engines operating between thermal baths have been realized. For these microengines, thermal fluctuations play a dominant role. The typical work output per engine cycle was of the order of k_b T. The engine performance and its characteristics could be well described within the framework of stochastic thermodynamics. It has been observed that when the nature of the bath is changed by bacterial activity, the performance of the engine can be enhanced. It may be noted that both for the case of passive and active colloidal microengines, the underlying working principle, much like macroscopic heat engines, relied upon conversion of thermal or athermal fluctuations of the bath into work output of the system. However, a fundamental drawback for this class of microengines is that the work output per cycle is of the order of few k_b T only. Therefore utilizing the work output effectively is a challenging proposition. In this backdrop, under this proposed project, we would provide a theoretical design and template for realization of a microscale engine, which would be powered by molecular motors. The proposed engine would be able to generate useful thermodynamic work in cyclic fashion and as such its performance is expected to supercede that of other microengines experimentally realized so far. In particular, the work output is expected to exceed the thermal fluctuations at least by an order of magnitude. We have recently investigated the transport properties of cargo (e.g. a single colloidal bead) transported by molecular motors - both singly and in teams - in a harmonic optical trap. In this proposal, we will extend this formalism towards developing microengines by making the trap strength time-periodic with suitable motor-state dependent feedback control. Importantly, we would investigate the conditions under which the engine substantially outperforms microengines realized hitherto. In particular, if the work output per cycle is at least one order of magnitude higher than thermal fluctuations then such an engine can be a promising prototype for fabricating a useful microdevice for future. Our preliminary investigations ( reported in arXiv:2503.07112) indicates that for such an engine which is powered by a single motor protein, the engine performance is improved drastically in comparison to other microengines realized so far . The important characteristic of the proposed microengine will be the role of motor activity as stochastic mechanical driver of the system. This is in contrast to other active microengines devised so far, for which the activity influences only the noise statistics of the engine. While for other microengines, the work output is strongly influenced by the noise fluctuations of the bath, for this microengine, fluctuations of the work output is primarily determined by the stochasticity of the motor (un)binding processes and not thermal fluctuations. The novelty of the working principle of this microengine - which hinges upon the mechanics and binding-unbinding kinetics of the motor proteins, will not only delineate itself from other microengines, but it will result in a drastic improvement of engine performance in comparison to microengines realized hitherto. Furthermore, our theoretical investigation using the framework of stochastic thermodynamics and theoretical modeling of bead-motor-microtubule complex will provide the testbed for studying the interplay of nanoscale mechanics ( of motor protein ) with information and thermodynamics at microscopic scales.
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