10.1021/acsphotonics.8b00122.s001
Chao Chen
Chao
Chen
Shuzhou Li
Shuzhou
Li
Valence Electron
Density-Dependent Pseudopermittivity
for Nonlocal Effects in Optical Properties of Metallic Nanoparticles
American Chemical Society
2018
LSPR
TDDFT
surface plasmonic resonance
nanoparticle
nonlocal effects
Valence Electron Density-Dependent Pseudopermittivity
pseudopermittivity
2018-05-12 00:00:00
Journal contribution
https://acs.figshare.com/articles/journal_contribution/Valence_Electron_Density-Dependent_Pseudopermittivity_for_Nonlocal_Effects_in_Optical_Properties_of_Metallic_Nanoparticles/6304130
The peak positions
of localized surface plasmonic resonance (LSPR)
are strongly dependent on the sizes of metallic nanoparticles. TDDFT
calculations have shown a remarkable size effect for metallic nanoparticles
smaller than 1 nm, because it could account for fully nonlocal effects.
Due to the high resource consumption of TDDFT, several semiquantum
approaches have been proposed to reduce the computation time while
addressing nonlocal effects, and it is still desirable to introduce
new ideas into this area since physical origins of related fields
are not completely known yet. In this work, we took account of both
spilling out of s-band electrons and the screening effect of d-band
electrons in the LSPR phenomena and developed a model using pseudopermittivity
to describe several quantum mechanical effects that contribute to
nonlocal effects in LSPR. With incorporation of machine learning,
this model is capable of calculating the optical response of large
nanostructures above the nanometer scale. Besides successful prediction
for different metallic nanoparticle monomers, the tunneling effect
occurring in dimers can also be well described by using the concept
of pseudopermittivity. The employing of pseudopermittivity and machine
learning is expected to achieve both high accuracy and high efficiency
in quantum plasmonics. It provides a new ideology in the simulation
of wave–matter interactions.