Understanding How Charged Nanoparticles Electrostatically Assemble and Distribute in 1‑D

The effects of increasing the driving forces for a 1-D assembly of nanoparticles onto a surface are investigated with experimental results and models. Modifications, which take into account not only the particle–particle interactions but also particle–surface interactions, to previously established extended random sequential adsorption simulations are tested and verified. Both data and model are compared against the heterogeneous random sequential adsorption simulations, and finally, a connection between the two models is suggested. The experiments and models show that increasing the particle–surface interaction leads to narrower particle distribution; this narrowing is attributed to the surface interactions compensating against the particle–particle interactions. The long-term advantage of this work is that the assembly of nanoparticles in solution is now understood as controlled not only by particle–particle interactions but also by particle–surface interactions. Both particle–particle and particle–surface interactions can be used to tune how nanoparticles distribute themselves on a surface

Nonperturbative Chemical Modification of Graphene for Protein Micropatterning

Graphene’s extraordinary physical properties and its planar geometry make it an ideal candidate for a wide array of applications, many of which require controlled chemical modification and the spatial organization of molecules on its surface. In particular, the ability to functionalize and micropattern graphene with proteins is relevant to bioscience applications such as biomolecular sensors, single-cell sensors, and tissue engineering. We report a general strategy for the noncovalent chemical modification of epitaxial graphene for protein immobilization and micropatterning. We show that bifunctional molecule pyrenebutanoic acid-succinimidyl ester (PYR-NHS), composed of the hydrophobic pyrene and the reactive succinimide ester group, binds to graphene noncovalently but irreversibly. We investigate whether the chemical treatment perturbs the electronic band structure of graphene using X-ray photoemission (XPS) and Raman spectroscopy. Our results show that the sp2 hybridization remains intact and that the π band maintains its characteristic Lorentzian shape in the Raman spectra. The modified graphene surfaces, which bind specifically to amines in proteins, are micropatterned with arrays of fluorescently labeled proteins that are relevant to glucose sensors (glucose oxidase) and cell sensor and tissue engineering applications (laminin)

Fabricating Nanoscale Chemical Gradients with ThermoChemical NanoLithography

Production of chemical concentration gradients on the submicrometer scale remains a formidable challenge, despite the broad range of potential applications and their ubiquity throughout nature. We present a strategy to quantitatively prescribe spatial variations in functional group concentration using ThermoChemical NanoLithography (TCNL). The approach uses a heated cantilever to drive a localized nanoscale chemical reaction at an interface, where a reactant is transformed into a product. We show using friction force microscopy that localized gradients in the product concentration have a spatial resolution of ∼20 nm where the entire concentration profile is confined to sub-180 nm. To gain quantitative control over the concentration, we introduce a chemical kinetics model of the thermally driven nanoreaction that shows excellent agreement with experiments. The comparison provides a calibration of the nonlinear dependence of product concentration versus temperature, which we use to design two-dimensional temperature maps encoding the prescription for linear and nonlinear gradients. The resultant chemical nanopatterns show high fidelity to the user-defined patterns, including the ability to realize complex chemical patterns with arbitrary variations in peak concentration with a spatial resolution of 180 nm or better. While this work focuses on producing chemical gradients of amine groups, other functionalities are a straightforward modification. We envision that using the basic scheme introduced here, quantitative TCNL will be capable of patterning gradients of other exploitable physical or chemical properties such as fluorescence in conjugated polymers and conductivity in graphene. The access to submicrometer chemical concentration and gradient patterning provides a new dimension of control for nanolithography