Ding, W. J., Lim, J. Z. J., Do, H. T. B., Xiong, X., Mahfoud, Z., Png, C. E., … Wu, L. (2020). Particle simulation of plasmons. Nanophotonics, 9(10), 3303–3313. doi:10.1515/nanoph-2020-0067
Abstract:
Abstract
Particle simulation has been widely used in studying plasmas. The technique follows the motion of a large assembly of charged particles in their self-consistent electric and magnetic fields. Plasmons, collective oscillations of the free electrons in conducting media such as metals, are connected to plasmas by very similar physics, in particular, the notion of collective charge oscillations. In many cases of interest, plasmons are theoretically characterized by solving the classical Maxwell’s equations, where the electromagnetic responses can be described by bulk permittivity. That approach pays more attention to fields rather than motion of electrons. In this work, however, we apply the particle simulation method to model the kinetics of plasmons, by updating both particle position and momentum (Newton–Lorentz equation) and electromagnetic fields (Ampere and Faraday laws) that are connected by current. Particle simulation of plasmons can offer insights and information that supplement those gained by traditional experimental and theoretical approaches. Specifically, we present two case studies to show its capabilities of modeling single-electron excitation of plasmons, tracing instantaneous movements of electrons to elucidate the physical dynamics of plasmons, and revealing electron spill-out effects of ultrasmall nanoparticles approaching the quantum limit. These preliminary demonstrations open the door to realistic particle simulations of plasmons.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research / project is supported by the A*STAR SERC - Young Individual Research Grants
Grant Reference no. : A1784c0020
This research / project is supported by the National Research Foundation Singapore - NRF-NSFC 2nd Joint Grant Call (Quantum Technologies)
Grant Reference no. : NRF2017-NRF-NSFC002-015
This research / project is supported by the National Research Foundation Singapore - 2nd ANR-NRF Joint Grant Call
Grant Reference no. : NRF2016-NRF-ANR002