Transport and bistable kinetics of a Brownian particle in a nonequilibrium environment

Chaudhuri, Jyotipratim Ray; Banik, Suman Kumar; Chattopadhyay, Sudip; Chaudhury, Pinaki

doi:10.1063/1.3013122

Cited by 1 publication

(1 citation statement)

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“…This phenomenon of increased probability of barrier crossing with the inclusion of memory is also reported in transport of ions through biological pores. 34 Alternative approaches to decrease the barrier crossing time have also been discussed in the context of modulating the host fluid to a non-equilibrium state, 42 or subjecting the nanoparticle to an external noise source of additive or multiplicative nature. 43,44 Thus, memory effects are important and should be included in the stochastic-simulation based multi-scale approaches used to study the dynamics and transport of fullerene-like nanoparticles in aqueous solution/biological environment.…”

Section: Gle Simulationmentioning

confidence: 99%

Memory effects in nanoparticle dynamics and transport

Sanghi

Bhadauria

Aluru

2016

The Journal of Chemical Physics

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In this work, we use the generalized Langevin equation (GLE) to characterize and understand memory effects in nanoparticle dynamics and transport. Using the GLE formulation, we compute the memory function and investigate its scaling with the mass, shape, and size of the nanoparticle. It is observed that changing the mass of the nanoparticle leads to a rescaling of the memory function with the reduced mass of the system. Further, we show that for different mass nanoparticles it is the initial value of the memory function and not its relaxation time that determines the "memory" or "memoryless" dynamics. The size and the shape of the nanoparticle are found to influence both the functional-form and the initial value of the memory function. For a fixed mass nanoparticle, increasing its size enhances the memory effects. Using GLE simulations we also investigate and highlight the role of memory in nanoparticle dynamics and transport.

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