Modeling magnetic nanoparticle biosensors

ORAL

Abstract

Magnetic nanoparticles have attracted attention as sensors for specific molecules. By choosing an appropriate coating for the particles, they specifically interact with another substance. If the substance of choice is found, the particles can bind to it and form clusters. In clumping, the ensemble rotational Brownian dynamics of the particles are changed drastically, and through magnetic spectroscopy, the change can be quantified. In this work, we show the high sensitivity that is possible using this scheme. Additionally, with stochastic Langevin equation simulations of the nanoparticle dynamics, we show how the increases in the characteristic timescales of the particles due to binding can be modeled using log-normal distributions for particle sizes.

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Authors

  • Daniel Reeves

    Dartmouth College Physics

  • Christopher Lane

    College of the Holy Cross, Bridgewater State University, Brown University, Harvard University, University of Tennessee at Chattanooga, Boston College, Istanbul Technical University, Dartmouth College Physics and Radiology, Northeastern University, University of Colorado, Northeastern University, National University of Singapore