Predicting the optical properties of organometallic nanoparticles with a scale-bridging method: The importance of the embedding

TL;DR

This paper presents a multi-scale modeling approach combining quantum chemistry and Maxwell simulations to accurately predict the optical properties of large organometallic nanoparticles, emphasizing the importance of environmental embedding effects.

Contribution

It introduces a scale-bridging method that incorporates environment effects into quantum chemical calculations for better optical property predictions of nanoparticles.

Findings

Embedding effects are crucial for accurate optical predictions.

The method aligns well with experimental data.

Environment considerations significantly alter optical response predictions.

Abstract

It remains a prime question of how to describe the optical properties of large molecular clusters accurately. Quantum chemical methods capture essential electronic details but are infeasible for entire clusters, while optical simulations handle cluster-scale effects but miss crucial quantum effects. To overcome such limitations, we apply here a multi-scale modeling approach, combining precise quantum chemistry calculations with Maxwell scattering simulations, to study the linear and nonlinear optical response of finite-size supramolecular gold-cysteine nanoparticles dispersed in water. In this approach, every molecular unit that forms the cluster is represented by a polarizability and a hyperpolarizability, and the overall response is obtained from solving an optical multiple scattering problem. We particularly demonstrate how important it is to accurately consider the environment of the individual molecular units when computing their polarizability and hyperpolarizability. In our quantum chemical simulations, we do so at the level of a static partial charge field that represents the presence of other molecular units. Without correctly considering these effects of the embedding, predictions would deviate from experimental observations even qualitatively. Our findings pave the way for more accurate predictions of the optical response of complex molecular systems, which is crucial for advancing applications in nanophotonics, biosensing, and molecular optoelectronics.