Calibrate Ligand-ligand Interaction on Nanocrystals via the Dynamic Volume of Chain Segments

27 April 2022, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The intermolecular ligand-ligand interaction is crucial for the surface chemistry, solution properties, and self-assembly processes of colloidal nanocrystals (NCs). The studies on the ligand-ligand interaction are hampered by the disordered and dynamic nature of the surface, the low electron contrast of organic moieties, and the non-characteristic weak intermolecular forces. Solid-state nuclear magnetic resonance (NMR) can provide site-specific information on organic ligands and especially the motional behavior of chain segments. In this work, we develop an advanced solid-state NMR measurement and modelling strategy to quantify the “dynamic volume” of chain segments. The dynamic volume depicts the accessible space of a chain segment under the confinement of neighboring molecules, and is inversely proportional to the intermolecular interaction energy. The ligand-ligand interaction energies have been obtained for NCs with alkanoate ligands of different lengths. We show that the calculated ligand-ligand interaction energy determines solution dispersity and the melting transitions of NCs. This dynamic volume concept can be extended beyond experimental NMR measurements and offer semi-empirical predictions of the interaction energies for arbitrary selections of alkanoate ligands. Our study not only advances the quantitative understanding of ligand-ligand interaction on NCs but also establishes novel tactics to calibrate weak intermolecular interactions.

Keywords

dynamic volume
colloidal nanocrystals
ligand-ligand interaction
solid-state NMR
segmental dynamics

Supplementary materials

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Supplementary Information for Calibrate Ligand-ligand Interaction on Nanocrystals via the Dynamic Volume of Chain Segments
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Supplementary Information for Calibrate Ligand-ligand Interaction on Nanocrystals via the Dynamic Volume of Chain Segments
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