Assembly of Nanoparticles at Liquid Interfaces: Crowding and Ordering

Experiments with the self-assembly of nanoparticles at liquid interfaces suggest that cooperative and slow dynamical processes due to particle crowding at the interface govern the adsorption and properties of the final assembly. Here we report a numerical approach to studying nonequilibrium adsorption, which elucidates these experimental observations. The analysis of particle rearrangements shows that local ordering processes are directly related to adsorption events at high interface coverage. Interestingly, this feature and the mechanism coupling local ordering to adsorption do not seem to change qualitatively upon increasing particle size polydispersity, although the latter changes the interface microstructure and its final properties. Our results indicate how adsorption kinetics can be used for the fabrication of 2D nanocomposites with controlled microstructure

Conformations and Effective Interactions of Polymer-Coated Nanoparticles at Liquid Interfaces

We investigate conformations and effective interactions of polymer-coated nanoparticles adsorbed at a model liquid–liquid interface via molecular dynamics simulations. The polymer shells strongly deform at the interface, with the shape governed by a balance between maximizing the decrease in interfacial area between the two solvent components, minimizing unfavorable contact between polymer and solvent, and maximizing the conformational entropy of the polymers. Using potential of mean force calculations, we compute the effective interaction between the nanoparticles at the liquid–liquid interface. We find that it differs quantitatively from the bulk and is significantly affected by the length of the polymer chains and by the solvent quality. Under good solvent conditions, the effective interactions are always repulsive and soft for long chains. The repulsion range decreases as the solvent quality decreases. In particular, under poor solvent conditions, short chains may fail to induce steric repulsion, leading to a net attraction between the nanoparticles, whereas with long-enough chains the effective interaction potential may feature an additional repulsive shoulder at intermediate distances

Dynamical Heterogeneity in the Supercooled Liquid State of the Phase Change Material GeTe

A contending technology for nonvolatile memories of the next generation is based on a remarkable property of chalcogenide alloys known as phase change materials, namely their ability to undergo a fast and reversible transition between the amorphous and crystalline phases upon heating. The fast crystallization has been ascribed to the persistence of a high atomic mobility in the supercooled liquid phase, down to temperatures close to the glass transition. In this work we unravel the atomistic, structural origin of this feature in the supercooled liquid state of GeTe, a prototypical phase change compound, by means of molecular dynamic simulations. To this end, we employed an interatomic potential based on a neural network framework, which allows simulating thousands of atoms for tens of ns by keeping an accuracy close to that of the underlying first-principles framework. Our findings demonstrate that the high atomic mobility is related to the presence of clusters of slow and fast moving atoms. The latter contain a large fraction of chains of homopolar Ge–Ge bonds, which at low temperatures have a tendency to move by discontinuous cage-jump rearrangements. This structural fingerprint of dynamical heterogeneity provides an explanation of the breakdown of the Stokes–Einstein relation in GeTe, which is the ultimate origin of the fast crystallization of phase change materials exploited in the devices