Analytical van der Waals interaction potential for faceted nanoparticles

Molecular dynamics simulations of anisotropic particles accelerated by neural-net predicted interactions

Rigid bodies, made of smaller composite beads, are commonly used to simulate anisotropic particles with molecular dynamics or Monte Carlo methods. To accurately represent the particle shape and to obtain smooth and realistic effective pair interactions between two rigid bodies, each body may need to contain hundreds of spherical beads. Given an interacting pair of particles, traditional molecular dynamics methods calculate all the inter-body distances between the beads of the rigid bodies within a certain distance. For a system containing many anisotropic particles, these distance calculations are computationally costly and limit the attainable system size and simulation time. However, the effective interaction between two rigid particles should only depend on the distance between their center of masses and their relative orientation. Therefore, a function capable of directly mapping the center of mass distance and orientation to the interaction energy between the two rigid bodies would completely bypass inter-bead distance calculations. It is challenging to derive such a general function analytically for almost any non-spherical rigid body. In this study, we have trained neural nets, powerful tools to fit nonlinear functions to complex datasets, to achieve this task. The pair configuration (center of mass distance and relative orientation) is taken as an input, and the energy, forces, and torques between two rigid particles are predicted directly. We show that molecular dynamics simulations of cubes and cylinders performed with forces and torques obtained from the gradients of the energy neural-nets quantitatively match traditional simulations that use composite rigid bodies. Both structural quantities and dynamic measures are in agreement, while achieving up to 23 times speedup over traditional molecular dynamics, depending on hardware and system size. The method presented here can, in principle, be applied to any irregular concave or convex shape with any pair interaction, provided that sufficient training data can be obtained.

Theory and simulation of ligand functionalized nanoparticles - a pedagogical overview

Synthesizing reconfigurable nanoscale synthons with predictive control over shape, size, and interparticle interactions is a holy grail of bottom-up self-assembly. Grand challenges in their rational design, however, lie in both the large space of experimental synthetic parameters and proper understanding of the molecular mechanisms governing their formation. As such, computational and theoretical tools for predicting and modeling building block interactions have grown to become integral in modern day self-assembly research. In this review, we provide an in-depth discussion of the current state-of-the-art strategies available for modeling ligand functionalized nanoparticles. We focus on the critical role of how ligand interactions and surface distributions impact the emergent, pre-programmed behaviors between neighboring particles. To help build insights into the underlying physics, we first define an "ideal" limit - the short ligand, "hard" sphere approximation - and discuss all experimental handles through the lens of perturbations about this reference point. Finally, we identify theories that are capable of bridging interparticle interactions to nanoscale self-assembly and conclude by discussing exciting new directions for this field.

Effects of particle shape and surface roughness on van der Waals interactions and coupling to dynamics in nanocrystals

The van der Waals interaction between colloids and nanoparticles is one of the key components to understanding particle aggregation, attachment, and assembly. While the ubiquity of anisotropic particle shapes and surface roughness is well-recognized in nanocrystalline materials, the effects of both on van der Waals forces and torques have not been adequately investigated. In this study, we develop a numerical scheme to determine the van der Waals forces and torques between cubic particles with multiple configurations and relative orientations. Our results show that the van der Waals torque due to anisotropic particle shapes is appreciable at nearly all configurations and mutual angles, outcompeting Brownian torque for various materials systems and conditions. Surface roughness enhances this particle shape effect, resulting in stronger van der Waals interactions ascribed to protrusions on the surfaces. Moreover, a scaling analysis indicates that the surface roughness alters the separation dependence of the van der Waals force and, more importantly, significantly influences the dynamics of two approaching particles. Our results clearly demonstrate that surface roughness and anisotropic shape play a crucial role in the energetics and kinetics of various particle-scale and emergent phenomena, such as crystal growth by oriented attachment, nanomaterials synthesis and assembly, mud flow rheology, as well as the deposition of natural nanocrystals within the subsurface.

Discovery of two-dimensional binary nanoparticle superlattices using global Monte Carlo optimization

Binary nanoparticle (NP) superlattices exhibit distinct collective plasmonic, magnetic, optical, and electronic properties. Here, we computationally demonstrate how fluid-fluid interfaces could be used to self-assemble binary systems of NPs into 2D superlattices when the NP species exhibit different miscibility with the fluids forming the interface. We develop a basin-hopping Monte Carlo (BHMC) algorithm tailored for interface-trapped structures to rapidly determine the ground-state configuration of NPs, allowing us to explore the repertoire of binary NP architectures formed at the interface. By varying the NP size ratio, interparticle interaction strength, and difference in NP miscibility with the two fluids, we demonstrate the assembly of an array of exquisite 2D periodic architectures, including AB-, AB₂-, and AB₃-type monolayer superlattices as well as AB-, AB₂-, A₃B₅-, and A₄B₆-type bilayer superlattices. Our results suggest that the interfacial assembly approach could be a versatile platform for fabricating 2D colloidal superlattices with tunable structure and properties.

Assembly mechanism of surface-functionalized nanocubes

Faceted nanoparticles can be used as building blocks to assemble nanomaterials with exceptional optical and catalytic properties. Recent studies have shown that surface functionalization of such nanoparticles with organic molecules, polymer chains, or DNA can be used to control the separation distance and orientation of particles within their assemblies. In this study, we computationally investigate the mechanism of assembly of nanocubes grafted with short-chain molecules. Our approach involves computing the interaction free energy landscape of a pair of such nanocubes via Monte Carlo simulations and using the Dijkstra algorithm to determine the minimum free energy pathway connecting key states in the landscape. We find that the assembly pathway of nanocubes is very rugged involving multiple energy barriers and metastable states. Analysis of nanocube configurations along the pathway reveals that the assembly mechanism is dominated by sliding motion of nanocubes relative to each other punctuated by their local dissociation at grafting points involving lineal separation and rolling motions. The height of energy barriers between metastable states depends on factors such as the interaction strength and surface roughness of the nanocubes and the steric repulsion from the grafts. These results imply that the observed assembly configuration of nanocubes depends not only on their globally stable minimum free energy state but also on the assembly pathway leading to this state. The free energy landscapes and assembly pathways presented in this study along with the proposed guidelines for engineering such pathways should be useful to researchers aiming to achieve uniform nanostructures from self-assembly of faceted nanoparticles.

Reconfigurable Chirality of DNA-Bridged Nanorod Dimers

Gold nanorods assembled in a side-by-side chiral configuration have potential applications in sensing due to their strong chiroptical surface plasmon resonances. Recent experiments have shown that dimers of gold nanorods bridged by double-stranded DNA exhibit variable chiral configurations depending on the chemical and ionic properties of the solvent medium. Here, we uncover the underlying physics governing this intriguing chiral behavior of such DNA-bridged nanorods by theoretically evaluating their configurational free energy landscape. Our results reveal how chiral configurations emerge from an interplay between the twist-stretch coupling of the intervening DNA and the intermolecular interactions between the nanorods, with dimers exhibiting left-handed chirality when the interparticle interactions are dominated by attractive depletion or van der Waals forces and right-handed chirality when dominated by repulsive electrostatic or steric forces. We demonstrate how changes in the depletant or ion concentration of the solvent medium lead to different classes of configurational responses by the dimers, including chirality-switching behavior, in good agreement with experimental observations. Based on extensive analyses of how material properties like nanorod aspect ratio, DNA length, and graft height modulate the free energy landscape, we propose strategies for tuning the environmentally responsive reconfigurability of the nanorod dimers. Overall, this work should help control the chirality and related optical activity of nanoparticle dimers and higher-order assemblies for various applications.