Abstract
The assembly of colloidal nanocrystals (NCs) into superstructures with long-range translational and orientational order is sensitive to the molecular interactions between ligands bound to the NC surface. We illustrate how ligand coverage on colloidal PbS NCs can be exploited as a tunable parameter to direct the self-assembly of superlattices with predefined symmetry. We show that PbS NCs with dense ligand coverage assemble into face-centered cubic (fcc) superlattices whereas NCs with sparse ligand coverage assemble into body-centered cubic (bcc) superlattices which also exhibit orientational ordering of NCs in their lattice sites. Surface chemistry characterization combined with density functional theory calculations suggest that the loss of ligands occurs preferentially on {100} than on reconstructed {111} NC facets. The resulting anisotropic ligand distribution amplifies the role of NC shape in the assembly and leads to the formation of superlattices with translational and orientational order. © 2011 American Chemical Society.
Original language | English (US) |
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Pages (from-to) | 3131-3138 |
Number of pages | 8 |
Journal | Journal of the American Chemical Society |
Volume | 133 |
Issue number | 9 |
DOIs | |
State | Published - Mar 9 2011 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUS-C1-018-02
Acknowledgements: This work was supported in part by Award No. KUS-C1-018-02, made by King Abdullah University of Science and Technology (KAUST) and by the National Science Foundation, Award NSF-CBET 0828703. J.J.C. was supported by the NSF IGERT Fellowship Program on "Nanoscale Control of Surfaces and Interfaces," administered by Cornell's MRSEC. K.B. was supported by NSF-CBET 0828703. GISAXS measurements were conducted at the Cornell High Energy Synchrotron Source (CHESS), which is supported by the National Science Foundation and the National Institutes of Health/National Institute of General Medical Sciences under NSF Award DMR-0936384. This research used computational resources of the Computation Center for Nanotechnology Innovation at Rensselaer Polytechnic Institute and was supported in part by the National Science Foundation through TeraGrid computational resources provided by the National Center for Supercomputing Applications, the Texas Advanced Computing Center and under the Louisiana Optical Network Initiative under Grant No. DMR050036
This publication acknowledges KAUST support, but has no KAUST affiliated authors.