Computational study of the Rayleigh light scattering properties of atmospheric pre-nucleation clusters

Literature Information

Publication Date 2014-04-15
DOI 10.1039/C4CP01206B
Impact Factor 3.676
Authors

Jonas Elm, Patrick Norman, Merete Bilde, Kurt V. Mikkelsen


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Abstract

The Rayleigh and hyper Rayleigh scattering properties of the binary (H2SO4)(H2O)n and ternary (H2SO4)(NH3)(H2O)n clusters are investigated using a quantum mechanical response theory approach. The molecular Rayleigh scattering intensities are expressed using the dipole polarizability α and hyperpolarizability β tensors. Using density functional theory, we elucidate the effect of cluster morphology on the scattering properties using a combinatorial sampling approach. We find that the Rayleigh scattering intensity depends quadratically on the number of water molecules in the cluster and that a single ammonia molecule is able to induce a high anisotropy, which further increases the scattering intensity. The hyper Rayleigh scattering activities are found to be extremely low. This study presents the first attempt to map the scattering of atmospheric molecular clusters using a bottom-up approach.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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