Inverse Design of Multicomponent Assemblies

Abstract

Inverse design can be a useful strategy for discovering interactions that drive particles to spontaneously self-assemble into a desired structure. Here, we extend an inverse design methodology--relative entropy optimization--to determine isotropic interactions that promote assembly of targeted multicomponent phases, and we apply this extension to design interactions for a variety of binary crystals ranging from compact triangular and square architectures to highly open structures with dodecagonal and octadecagonal motifs. We compare the resulting optimized (self and cross) interactions for the binary assemblies to those obtained from optimization of analogous single-component systems. This comparison reveals that self interactions act as a `primer' to position particles at approximately correct coordination shell distances, while cross interactions act as the `binder' that refines and locks the system into the desired configuration. For simpler binary targets, it is possible to successfully design self-assembling systems while restricting one of these interaction types to be a hard-core-like. However, optimization of both self and cross interaction types appears necessary to design for assembly of more complex or open structures.

arXiv comment13 pages, 7 figures; Supplementary material available as an ancillary file

References in corpus (22)

• Past Achievements and Future Challenges in 3D Photonic Metamaterials
• Optimized Interactions for Targeted Self-Assembly: Application to Honeycomb Lattice
• Self-assembly of Microcapsules via Colloidal Bond Hybridization and Anisotropy
• Perspective: Inverse methods for material design
• Turning Statistical Physics Models Into Materials Design Engines
• Inverse design of simple pairwise interactions with low-coordinated 3D lattice ground states
• Inverse Design for Self Assembly via On-the-Fly Optimization
• Probabilistic inverse design for self assembling materials
• Designed Diamond Ground State via Optimized Isotropic Monotonic Pair Potentials
• Inverse Statistical Mechanics: Probing the Limitations of Isotropic Pair Potentials to Produce Ground-State Structural Extremes
• Designing isotropic interactions for self-assembly of complex lattices
• Monte-Carlo simulation of string-like colloidal assembly
• Designing convex repulsive pair potentials that favor assembly of kagome and snub square lattices
• Equilibrium cluster fluids: Pair interactions via inverse design
• Interactions and design rules for assembly of porous colloidal mesophases
• Self-assembly of three-dimensional open structures using patchy colloidal particles
• Dimensionality and design of isotropic interactions that stabilize honeycomb, square, simple cubic, and diamond lattices
• Designing Pairwise Interactions that Stabilize Open Crystals: Truncated Square and Truncated Hexagonal Lattices
• Using the uncertainty principle to design simple interactions for targeted self-assembly
• Breadth versus depth: Interactions that stabilize particle assemblies to changes in density or temperature
• Free-Energy Functional Method for Inverse Problem of Self Assembly
• Exploiting classical nucleation theory for reverse self-assembly

Cited by in corpus (12)

• Equilibrium mechanisms of self-limiting assembly
• Inverse methods for design of soft materials
• Assembly of particle strings via isotropic potentials
• Programmable patchy particles for materials design
• Neuroevolutionary learning of particles and protocols for self-assembly
• The Role of Pressure in Inverse Design for Assembly
• Bayesian Modelling of Pattern Formation from One Snapshot of Pattern
• Understanding Protein-Complex Assembly through Grand Canonical Maximum Entropy Modeling
• relentless: Transparent, reproducible molecular dynamics simulations for optimization
• Designing binary mixtures of colloidal particles with simple interactions that assemble complex crystals
• Free-Energy Functional Approach to Inverse Problems for Self-Assembly of Three-Dimensional Crystals
• Tuning Stoichiometry to Promote Formation of Binary Colloidal Superlattices