| Literature DB >> 29629080 |
William Edwards1, Nicolas Marro1, Grace Turner1, Euan R Kay1.
Abstract
Surface chemical composition is fundamental to determining properties on the nanoscale, making precise control over surface chemistry critical to being able to optimise nanomaterials for virtually any application. Surface-engineering independent of the preparation of the underlying nanomaterial is particularly attractive for efficient, divergent synthetic strategies, and for the potential to create reactive, responsive and smart nanodevices. For monolayer-stabilised nanoparticles, established methods include ligand exchange to replace the ligand shell in its entirety, encapsulation with amphiphilic (macro)molecules, noncovalent interactions with surface-bound biomolecules, or a relatively limited number of covalent bond forming reactions. Yet, each of these approaches has considerable drawbacks. Here we show that dynamic covalent exchange at the periphery of the nanoparticle-stabilizing monolayer allows surface-bound ligand molecular structure to be substantially modified in mild and reversible processes that are independent of the nanoparticle-molecule interface. Simple stoichiometric variation allows the extent of exchange to be controlled, generating a range of kinetically stable mixed-monolayer compositions across an otherwise identical, self-consistent series of nanoparticles. This approach can be used to modulate nanoparticle properties that are defined by the monolayer composition. We demonstrate switching of nanoparticle solvent compatibility between widely differing solvents - spanning hexane to water - and the ability to tune solubility across the entire continuum between these extremes, all from a single nanoparticle starting point. We also demonstrate that fine control over mixed-monolayer composition influences the assembly of discrete, colloidally stable nanoparticle clusters. By carefully assessing monolayer composition in each state, using both in situ and ex situ methods, we are able to correlate the molecular-level details of the nanoparticle-bound monolayer with system-level properties and behaviour. These empirically determined relationships contribute fundamental insights on nanoscale structure-function relationships, which are currently beyond the capabilities of ab initio prediction.Entities:
Year: 2017 PMID: 29629080 PMCID: PMC5869618 DOI: 10.1039/c7sc03666c
Source DB: PubMed Journal: Chem Sci ISSN: 2041-6520 Impact factor: 9.825
Fig. 1The dynamic covalent approach to reversible nanoparticle property tuning. From a single, synthetically optimised starting point, dynamic covalent modification gives access to multiple single-component or mixed-component nanoparticle-bound monolayer compositions, and hence, nanoparticle property states; for example, tuning nanoparticle solubility, illustrated schematically here as depth of magenta colour for nanoparticle solutions in a range of solvents.
Fig. 2Reversible switching of nanoparticle solvophilicity between three states by dynamic covalent hydrazone exchange from a single nanoparticle starting point AuNP-1. Dynamic covalent exchange conditions: aldehyde 2, 3, or 4 (5 equivalents with respect to nanoparticle-bound ligand), THF/CH2Cl2/D2O (interconversions between AuNP-1 and AuNP-5) or THF/D2O (interconversions between AuNP-1 and AuNP-6), CF3CO2H (20 mM), 50 °C. Digital photographs of nanoparticles at 0.5 mg mL–1 in solvents: (A) n-hexane; (B) CCl4; (C) Et2O; (D) tetrahydrofuran (THF); (E) CH2Cl2; (F) N,N-dimethylformamide (DMF); (G) (CH3)2SO; (H) EtOH; (I) H2O.
Continuum tuning of binary mixed-monolayer compositions of components 1 and 5 (for full experimental details and sample characterization, see ESI Sections 4, 5, and Table S1)
| Sample | Equivalents | % |
|
| AuNP- | 0.26 | 29% | 0.29 |
| AuNP- | 0.52 | 37% | 0.41 |
| AuNP- | 0.54 | 46% | 0.50 |
| AuNP- | 0.80 | 56% | 0.61 |
| AuNP- | 1.1 | 68% | 0.71 |
| AuNP- | 2.1 | 79% | 0.78 |
| AuNP- | 3.1 | 89% | 0.88 |
| AuNP- | 4.1 | 85% | 0.89 |
| AuNP- | 5.2 | 89% | 0.89 |
| AuNP- | 5.1 | 100% | >0.97 |
Molar equivalents with respect to initial concentration of nanoparticle-bound ligand 1.
Determined by in situ19F NMR.
Determined by oxidative ligand stripping using I2 (see ESI, Section 5).
Nanoparticle precipitation observed.
Dynamic covalent hydrazone exchange driven to completion by increasing the proportion of CH2Cl2 to maintain nanoparticle solubility.
Continuum tuning of binary mixed-monolayer compositions of components 1 and 6 (for full experimental details and sample characterization, see ESI Sections 4, 5, and Table S2)
| Sample | Equivalents | % |
|
| AuNP- | 0.12 | n.d. | 0.10 |
| AuNP- | 0.50 | n.d. | 0.20 |
| AuNP- | 0.29 | 26% | 0.28 |
| AuNP- | 0.47 | 45% | 0.43 |
| AuNP- | 1.0 | n.d. | 0.46 |
| AuNP- | 0.67 | 52% | 0.51 |
| AuNP- | 1.1 | 59% | 0.59 |
| AuNP- | 3.0 | n.d. | 0.69 |
| AuNP- | 5.0 | n.d. | 0.85 |
| AuNP- | 8.0 | 88% | 0.88 |
| AuNP- | 5.0 | 100% | >0.97 |
Molar equivalents with respect to initial concentration of nanoparticle-bound ligand 1.
Determined by in situ19F NMR (n.d. = not determined).
Determined by exhaustive hydrazone exchange in the presence of excess 4-nitrobenzaldehyde (see ESI, Section 5).
Experiments performed at higher initial concentrations of AuNP-1 (see Table S2) tended to give lower than expected conversions, likely resulting from aggregation of aldehyde 3 and/or nanoparticle products.‖
Nanoparticle precipitation observed.
Dynamic covalent hydrazone exchange driven to completion by increasing the proportion of D2O to maintain nanoparticle solubility.
Fig. 3Continuum solubility tuning by dynamic covalent modification of monolayer composition. Absorbance values for saturated solutions of nanoparticle samples bearing a range of monolayer compositions from highly hydrophobic to highly hydrophilic. In both series, the second monolayer component is 4-fluorobenzylidine hydrazone 1. Absorbance at 517 nm has been normalized to the value for a saturated solution of the most soluble sample for that solvent (i.e., n-hexane: AuNP-5, 35 mg mL–1; DMF: AuNP-1, 41 mg mL–1; THF: AuNP-1, 34 mg mL–1; water: AuNP-6, 22 mg mL–1).
Fig. 4Monolayer composition-dependent solvophobic nanoparticle clustering. (a) Variation in solvodynamic size with solvent polarity as measured by DLS for AuNP-5 (red circles), AuNP-10.150.9 (blue squares), AuNP-10.350.7 (green triangles). Monomodal size distributions were observed throughout; sizes are the mean of three measurements for distributions expressed in terms of % number of particles; error bars indicate ±1 standard deviation. See ESI, Section 7.1† for DLS measurements at higher proportions of water, and size distributions for selected sample points, expressed as both % number of particles and % volume. (b–f) Micrographs of dried samples corresponding to: (b) AuNP-5, 100% THF; (c) AuNP-5, 7% H2O/THF; (d) AuNP-5, 10% H2O/THF; (e) AuNP-10.150.9, 10% H2O/THF; (f) AuNP-10.350.7, 13% THF. Scale bar: 200 nm. See ESI, Section 7.2† for additional TEM images.