The growth of fingering patterns in dewetting nanofluids (colloidal solutions of thiol-passivated gold nanoparticles) has been followed in real time using contrast-enhanced video microscopy. The fingering instability on which we focus here arises from evaporatively driven nucleation and growth in a nanoscopically thin precursor solvent film behind the macroscopic contact line. We find that well-developed isotropic fingering structures only form for a narrow range of experimental parameters. Numerical simulations, based on a modification of the Monte Carlo approach introduced by Rabani et al. [Nature (London) 426, 271 (2003)10.1038/nature02087], reproduce the patterns we observe experimentally.

Various experimental settings that involve drying solutions or suspensions of nanoparticles-often called nanofluids-have recently been used to produce structured nanoparticle layers. In addition to the formation of polygonal networks and spinodal-like patterns, the occurrence of branched structures has been reported. After reviewing the experimental results we use a modified version of the Monte Carlo model first introduced by Rabani [Nature 426, 271 (2003)] to study structure formation in evaporating films of nanoparticle solutions for the case that all structuring is driven by the interplay of evaporating solvent and diffusing nanoparticles. After introducing the model and its general behavior we focus on receding dewetting fronts which are initially straight but develop a transverse fingering instability. We analyze the dependence of the characteristics of the resulting branching patterns on the driving effective chemical potential, the mobility and concentration of the nanoparticles, and the interaction strength between liquid and nanoparticles. This allows us to understand the underlying instability mechanism.

We have achieved highly localized control of pattern formation in two-dimensional nanoparticle assemblies by direct modification of solvent dewetting dynamics. A striking dependence of nanoparticle organization on the size of atomic force microscope-generated surface heterogeneities is observed and reproduced in numerical simulations. Nanoscale features induce a rupture of the solvent-nanoparticle film, causing the local flow of solvent to carry nanoparticles into confinement. Microscale heterogeneities instead slow the evaporation of the solvent, producing a remarkably abrupt interface between different nanoparticle patterns.

A structural motif that appears very frequently not only in a wide range of nanostructured systems but also on mesoscopic to macroscopic length scales is the “cellular network”. We present a quantitative analysis of the morphology of cellular networks formed by thiol-passivated Au nanoparticles, and, for comparison, organometallic molecules, spin cast onto native oxide-terminated silicon substrates. The structural parameters determined from Voronoi tessellation and Minkowski functional analyses of the experimental data are compared to those extracted from Monte Carlo simulations of nanoparticle network formation. The key result of this comparative study is that although the cell positions are spatially correlated, i.e., they deviate strongly from those expected for a Poisson point set, this correlation arises simply from a coalescence of neighboring cells during network formation. Complex nonlinear processes such as spinodal decomposition or Marangoni convection are therefore not always a prerequisite for the formation of spatially correlated networks.

The transport of electrons through topologically complex two-dimensional Au nanoparticle networks has been investigated using a combination of low temperature (4.5 K) direct current I(V) measurements and numerical simulations. Intricate, spatially correlated nanostructured networks were formed via spin-casting. The topological complexity of the nanoparticle assemblies produces I(V) curves associated with nonlinearity exponents, zeta approximately 4.0. Simulations based on tunneling transport in sparse and inhomogeneous planar networks are used to elucidate the influence of topology on the value of zeta.