Quantitative 3D determination of self-assembled structures on nanoparticles using small angle neutron scattering

Zhi Luo, Domenico Marson, Quy K. Ong, Anna Loiudice, Joachim Kohlbrecher, Aurel Radulescu, Anwen Krause-Heuer, Tamim Darwish, Sandor Balog, Raffaella Buonsanti, Dmitri I. Svergun, Paola Posocco and Francesco Stellacci ()
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Zhi Luo: École Polytechnique Fédérale de Lausanne
Domenico Marson: University of Trieste
Quy K. Ong: École Polytechnique Fédérale de Lausanne
Anna Loiudice: École Polytechnique Fédérale de Lausanne
Joachim Kohlbrecher: Paul-Scherrer Institute
Aurel Radulescu: Forschungszentrum Jülich GmbH
Anwen Krause-Heuer: Australian Nuclear Science and Technology Organisation
Tamim Darwish: Australian Nuclear Science and Technology Organisation
Sandor Balog: University of Fribourg
Raffaella Buonsanti: École Polytechnique Fédérale de Lausanne
Dmitri I. Svergun: EMBL c/o DESY
Paola Posocco: University of Trieste
Francesco Stellacci: École Polytechnique Fédérale de Lausanne

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract The ligand shell (LS) determines a number of nanoparticles’ properties. Nanoparticles’ cores can be accurately characterized; yet the structure of the LS, when composed of mixture of molecules, can be described only qualitatively (e.g., patchy, Janus, and random). Here we show that quantitative description of the LS’ morphology of monodisperse nanoparticles can be obtained using small-angle neutron scattering (SANS), measured at multiple contrasts, achieved by either ligand or solvent deuteration. Three-dimensional models of the nanoparticles’ core and LS are generated using an ab initio reconstruction method. Characteristic length scales extracted from the models are compared with simulations. We also characterize the evolution of the LS upon thermal annealing, and investigate the LS morphology of mixed-ligand copper and silver nanoparticles as well as gold nanoparticles coated with ternary mixtures. Our results suggest that SANS combined with multiphase modeling is a versatile approach for the characterization of nanoparticles’ LS.

Date: 2018
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DOI: 10.1038/s41467-018-03699-7

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