Simulating Surface-Enhanced Hyper-Raman Scattering Using Atomistic Electrodynamics-Quantum Mechanical Models

Zhongwei Hu, Dhabih V. Chulhai, Lasse Jensen

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Surface-enhanced hyper-Raman scattering (SEHRS) is the two-photon analogue of surface-enhanced Raman scattering (SERS), which has proven to be a powerful tool to study molecular structures and surface enhancements. However, few theoretical approaches to SEHRS exist and most neglect the atomistic descriptions of the metal surface and molecular resonance effects. In this work, we present two atomistic electrodynamics-quantum mechanical models to simulate SEHRS. The first is the discrete interaction model/quantum mechanical (DIM/QM) model, which combines an atomistic electrodynamics model of the nanoparticle with a time-dependent density functional theory description of the molecule. The second model is a dressed-tensors method that describes the molecule as a point-dipole and point-quadrupole object interacting with the enhanced local field and field-gradients (FG) from the nanoparticle. In both of these models, the resonance effects are treated efficiently by means of damped quadratic response theory. Using these methods, we simulate SEHRS spectra for benzene and pyridine. Our results show that the FG effects in SEHRS play an important role in determining both the surface selection rules and the enhancements. We find that FG effects are more important in SEHRS than in SERS. We also show that the spectral features of small molecules can be accurately described by accounting for the interactions between the molecule and the local field and FG of the nanoparticle. However, at short distances between the metal and molecule, we find significant differences in the SEHRS enhancements predicted using the DIM/QM and the dressed-tensors methods.

Original languageEnglish (US)
Pages (from-to)5968-5978
Number of pages11
JournalJournal of Chemical Theory and Computation
Volume12
Issue number12
DOIs
StatePublished - Dec 13 2016

Bibliographical note

Funding Information:
L.J. acknowledges support from the NSF award CHE-1362825 and support received from Research Computing and Cyberinfrastructure, a unit of Information Technology Services at Penn State.

Publisher Copyright:
© 2016 American Chemical Society.

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