Memory effects in nanoparticle dynamics and transport

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 07, 2016
Source ID
10.1063/1.4964287

Entities

People

  • N. R. Aluru
  • Ravi Bhadauria
  • Tarun Sanghi

Organizations

  • Air Force Office of Scientific Research
  • National Science Foundation
  • University of Illinois Urbana–Champaign

Tags

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Mathematical Modeling and Probability Theory.
  • Nanocomposite Materials Science

Technology Areas

  • Biotechnology