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Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures

Nature Chemistry volume 13, pages 940–949 (2021)Cite this article

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Abstract

Coulombic interactions can be used to assemble charged nanoparticles into higher-order structures, but the process requires oppositely charged partners that are similarly sized. The ability to mediate the assembly of such charged nanoparticles using structurally simple small molecules would greatly facilitate the fabrication of nanostructured materials and harnessing their applications in catalysis, sensing and photonics. Here we show that small molecules with as few as three electric charges can effectively induce attractive interactions between oppositely charged nanoparticles in water. These interactions can guide the assembly of charged nanoparticles into colloidal crystals of a quality previously only thought to result from their co-crystallization with oppositely charged nanoparticles of a similar size. Transient nanoparticle assemblies can be generated using positively charged nanoparticles and multiply charged anions that are enzymatically hydrolysed into mono- and/or dianions. Our findings demonstrate an approach for the facile fabrication, manipulation and further investigation of static and dynamic nanostructured materials in aqueous environments.

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Fig. 1: Electrostatic co-assembly of positively charged NPs and negatively charged small molecules.
Fig. 2: MD simulations of electrostatic interactions between positively charged NPs and small anions.
Fig. 3: Dynamics of small anions and the annealing of TMA-functionalized Au NPs.
Fig. 4: Self-assembly of co-crystals of TMA-functionalized Au NPs and small anions.
Fig. 5: Electrostatic co-assembly of negatively charged NPs and positively charged small molecules.
Fig. 6: DSA of gold NPs driven by ATP.

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Data availability

All the data supporting the findings of this study are available within the main text of the paper, the Supplementary Information and also from the corresponding author on request. Source data are provided with this paper.

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Acknowledgements

This work was supported by the European Research Council (ERC) (grants 820008 to R.K. and 818776 to G.M.P.), the Minerva Foundation with funding from the Federal German Ministry for Education and Research and the Swiss National Science Foundation (grants 200021_175735 and IZLIZ2_183336 to G.M.P.). We acknowledge funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 812868. Z.C. acknowledges support from the Planning and Budgeting Committee of the Council for Higher Education, the Koshland Foundation and a McDonald–Leapman grant. The authors acknowledge the computational resources provided by the Swiss National Supercomputing Centre (CSCS). The support of the Irving and Cherna Moskowitz Center for Nano and Bio-Nano Imaging is gratefully acknowledged. This research used resources of the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility, operated for the DOE Office of Science by Argonne National Laboratory under Contract no. DE-AC02-06CH11357. Extraordinary facility operations were supported in part by the DOE Office of Science through the National Virtual Biotechnology Laboratory, a consortium of DOE national laboratories focused on the response to COVID-19, with funding provided by the Coronavirus CARES Act.

Author information

Authors and Affiliations

  1. Department of Organic Chemistry, Weizmann Institute of Science, Rehovot, Israel

    Tong Bian, Julius Gemen, Zonglin Chu & Rafal Klajn

  2. Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Lugano-Viganello, Switzerland

    Andrea Gardin, Claudio Perego & Giovanni M. Pavan

  3. Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy

    Andrea Gardin & Giovanni M. Pavan

  4. Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, Israel

    Lothar Houben & Nadav Elad

  5. X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, IL, USA

    Byeongdu Lee

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Contributions

T.B. synthesized positively charged NPs, studied their interactions with oligoanions and developed a method to prepare crystalline NP aggregates. A.G. and C.P. performed the computational studies. J.G. developed the reverse system of negatively charged NPs and oligocations. B.L. performed and analysed the SAXS measurements. N.E. and L.H. performed cryo-STEM imaging and analysis. Z.C. contributed to the characterization of the NPs. R.K. supervised the project, coordinating with G.M.P., who supervised the computational studies. R.K. prepared the manuscript, with contributions from all the authors.

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Correspondence to Rafal Klajn.

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Peer review information Nature Chemistry thanks Tobias Kraus, Asaph Widmer-Cooper and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Dependence of the titration behavior on nanoparticle size.

Differently sized TMA-functionalized Au NPs (4.8 nm, 8.8 nm, and 13.1 nm) at the same overall concentration of TMA in solution were titrated with the same solution of EDTA3– (the NPs were prepared analogously to those described in the Methods section). a, Left: Change in the position of Au·TMA’s SPR peak as a function of amount of EDTA3– added. In all cases, the amount of NP-adsorbed TMA was 20 nmol. The dashed red line denotes the point of electroneutrality (6.7 nmol of triply charged EDTA). Right: Relative dimensions of Au·TMA used in titration experiments. b, Normalized position of Au·TMA’s SPR peak as a function of amount of EDTA3– added (replotted from a). The normalized data show that the titration profiles are nearly the same irrespective of the NP size, indicating that the interparticle interactions are governed predominantly by electrostatics. The dashed red line denotes the point of electroneutrality (6.7 nmol of triply charged EDTA).

Extended Data Fig. 2 Representative SEM images of colloidal crystals co-assembled from TMA-functionalized Au NPs and various multiply charged anions.

The following anions were used: a–c, EDTA3–; d–j, citrate3–; k, l, pyrophosphate4–; m–s, triphosphate5–; t, u, trimetaphosphate3–; v, w, hexametaphosphate6–; x–z, ATP4–. The size of the NPs was 4.7 nm (panels n–r), 7.4 nm (panels a–f, j–m, and s–z), and 11.4 nm (panels g–i). In all cases, the counterion was Na+.

Extended Data Fig. 3 Nanoparticle packing on the faces of colloidal crystals.

SEM images of crystals co-assembled from TMA-functionalized 4.7 nm Au NPs and ATP. The magnified images in (b) and (e) show the hexagonal packing of NPs characteristic of the (111) facet of the face-centered cubic (fcc) structure. The magnified image in (g) shows the cubic packing of NPs characteristic of the (100) facet of the fcc structure.

Extended Data Fig. 4 SEM images of colloidal crystals co-assembled from negatively charged NPs and an organic trication.

The crystals were prepared using MUS-functionalized 4.7 nm Au NPs and triply charged cations, OMA3+, as described in the Methods section.

Extended Data Fig. 5 Cryo-STEM images of aggregates of TMA-functionalized Au NPs and P3O105− or ATP.

a, Contrast-inverted bright-field cryo-STEM images of Au·TMA/P3O105− aggregates. Reconstruction and analysis of the aggregates denoted by circles are shown in Extended Data Fig. 6. b, Contrast-inverted bright-field cryo-STEM image of Au·TMA/ATP aggregates. Reconstruction and analysis of the aggregates denoted by circles are shown in Extended Data Fig. 7. All panels show single images at zero tilt, part of a tilt series spanning the tilt range of 60°.

Extended Data Fig. 6 Reconstruction and analysis of Au·TMA/P3O105− aggregates.

Labels a–d correspond to the locations indicated with the same labels in Extended Data Fig. 5. Left panel: ‘Atomistic’ models of the aggregates obtained after 3D reconstruction and particle coordinate refinement. Middle panel: Numbers of nearest neighbors in the first coordination shell in a color-coded representation for each NP. Average number of nearest neighbors = 6.4 (±0.8) (measured on ten different aggregates). Right panel: Pair correlation functions; the nearest-neighbor distance, Δ = 8.27 (±0.03) nm.

Extended Data Fig. 7 Reconstruction and analysis of Au·TMA/ATP aggregates.

Labels a–d correspond to the locations indicated with the same labels in Extended Data Fig. 5. First panel: Contrast-inverted bright-field cryo-STEM images of individual Au·TMA/ATP aggregates. Second panel: ‘Atomistic’ models of the aggregates obtained after 3D reconstruction and particle coordinate refinement. Third panel: Numbers of nearest neighbors in the first coordination shell in a color-coded representation for each NP. Average number of nearest neighbors = 7.4 (±0.5) (measured on five different aggregates). Fourth panel: Pair correlation functions; the nearest-neighbor distance, Δ = 8.08 (±0.07) nm.

Supplementary information

Supplementary Information

Detailed description of experimental and computational procedures, Supplementary Figs. 1–40 and references.

Supplementary Video 1

CG-MD simulation of citrate-mediated self-assembly of two TMA-decorated Au NPs.

Supplementary Video 2

CG-MD simulation of citrate-mediated self-assembly of four TMA-decorated Au NPs.

Source data

Source Data Fig. 1

Statistical source data for Fig. 1d,e.

Source Data Fig. 2

Statistical source data for Fig. 2b,d.

Source Data Fig. 4

Statistical source data for Fig. 4j,l.

Source Data Fig. 5

Statistical source data for Fig. 5c,d.

Source Data Fig. 6

Statistical source data for Fig. 6c,d,f–h,k,l.

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Bian, T., Gardin, A., Gemen, J. et al. Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures. Nat. Chem. 13, 940–949 (2021). https://doi.org/10.1038/s41557-021-00752-9

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