NCs to date have focused primarily on choosing ligands with specific anchoring groups rather than on tuning the length and type of alkyl chains, as this is time-consuming and requires a large number of syntheses. Our recent developments in the computational chemistry of colloidal NCs are expected to provide a pivotal role in this direction since they can be integrated with machine learning models to investigate with greater details the ligand-NC, ligand-ligand, and ligand-solvent interactions and ultimately find optimal candidates through the prediction of surfactant properties using high-throughput data sets.
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Trizio et al. (2023) studied this question.
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