The optical response of metallic nanoparticles (MNPs) exhibit localized surface plasmonic resonance (LSPR) with peak energy dependent on particle size. This size effect has been predicted by ab initio calculations, but cannot be resolved by classical electromagnetic models (CEM). In this work, we systematically studied three quantum effects (surface atom relaxation, s-band electron spilling out and d-band electron screening) that may lead to failure of CEM in contrast simulations and proposed a machine learning enhanced semi-classical semi-quantum model, valence electron density dependent core-shell model. This new model describes ground state valence electron densities by incorporating s-band electron spilling out effect and d-band screening effect into shell region and core region of a nano-spherical model and successfully predicted red and blueshifts in LSPR energy of sodium and silver particles, respectively, with decreasing of size. The optical spectra by core-shell model show excellent agreements with ab initio calculations, and the extrapolation of LSPR energies to mesoscopic scale also agrees with quasistatic limits. Our core-shell model manages to calculate optical properties of intermediated sized MNPs efficiently, fulfilling the simulation gap left by CEM and ab initio.

Electron density dependent core-shell model in simulation optical properties of metallic nanoparticles

254th National Meeting (2017)

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