Ryan B. Jadrich

Linking Semiconductor Nanocrystals into Gel Networks through All‐Inorganic Bridges

For colloidal semiconductor nanocrystals (NCs), replacement of insulating organic capping ligands with chemically diverse inorganic clusters enables the development of functional solids in which adjacent NCs are strongly coupled. Yet controlled assembly methods are lacking to direct the arrangement of charged, inorganic cluster-capped NCs into open networks. Herein, we introduce coordination bonds between the clusters capping the NCs thus linking the NCs into highly open gel networks. As linking cations (Pt(2+)) are added to dilute (under 1u2005volu2009%) chalcogenidometallate-capped CdSe NC dispersions, the NCs first form clusters, then gels with viscoelastic properties. The phase behavior of the gels for variable [Pt(2+)] suggests they may represent nanoscale analogues of bridged particle gels, which have been observed to form in certain polymer colloidal suspensions.

Communication: Inverse design for self-assembly via on-the-fly optimization

Inverse methods of statistical mechanics have facilitated the discovery of pair potentials that stabilize a wide variety of targeted lattices at zero temperature. However, such methods are complicated by the need to compare, within the optimization framework, the energy of the desired lattice to all possibly relevant competing structures, which are not generally known in advance. Furthermore, ground-state stability does not guarantee that the target will readily assemble from the fluid upon cooling from higher temperature. Here, we introduce a molecular dynamics simulation-based, optimization design strategy that iteratively and systematically refines the pair interaction according to the fluid and crystalline structural ensembles encountered during the assembly process. We successfully apply this probabilistic, machine-learning approach to the design of repulsive, isotropic pair potentials that assemble into honeycomb, kagome, square, rectangular, truncated square, and truncated hexagonal lattices.

Origin and Detection of Microstructural Clustering in Fluids with Spatial-Range Competitive Interactions

Fluids with competing short-range attractions and long-range repulsions mimic dispersions of charge-stabilized colloids that can display equilibrium structures with intermediate-range order (IRO), including particle clusters. Using simulations and analytical theory, we demonstrate how to detect cluster formation in such systems from the static structure factor and elucidate links to macrophase separation in purely attractive reference fluids. We find that clusters emerge when the thermal correlation length encoded in the IRO peak of the structure factor exceeds the characteristic length scale of interparticle repulsions. We also identify qualitative differences between the dynamics of systems that form amorphous versus microcrystalline clusters.

Equilibrium cluster fluids: pair interactions via inverse design

Inverse methods of statistical mechanics are becoming productive tools in the design of materials with specific microstructures or properties. While initial studies have focused on solid-state design targets (e.g., assembly of colloidal superlattices), one can alternatively design fluid states with desired morphologies. This work addresses the latter and demonstrates how a simple iterative Boltzmann inversion strategy can be used to determine the isotropic pair potential that reproduces the radial distribution function of a fluid of amorphous clusters with prescribed size. The inverse designed pair potential of this ideal cluster fluid, with its broad attractive well and narrow repulsive barrier at larger separations, is qualitatively different from the so-called SALR form most commonly associated with equilibrium cluster formation in colloids, which features short-range attractive (SA) and long-range repulsive (LR) contributions. These differences reflect alternative mechanisms for promoting cluster formation with an isotropic pair potential, and they in turn produce structured fluids with qualitatively different static and dynamic properties. Specifically, equilibrium simulations show that the amorphous clusters resulting from the inverse designed potentials display more uniformity in size and shape, and they also show greater spatial and temporal resolution than those resulting from SALR interactions.

Probabilistic inverse design for self-assembling materials

One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven particularly effective for the discovery of interparticle interactions suitable for this aim. Here we evaluate the generality and robustness of a recently introduced inverse design strategy [B. A. Lindquist et al., J. Chem. Phys. 145, 111101 (2016)] by applying this simulation-based machine learning method to optimize for interparticle interactions that self-assemble particles into a variety of complex microstructures as follows: cluster fluids, porous mesophases, and crystalline lattices. Using the method, we discover isotropic pair interactions that lead to the self-assembly of each of the desired morphologies, including several types of potentials that were not previously understood to be capable of stabilizing such systems. One such pair potential led to the assembly of the hi...

Interactions and design rules for assembly of porous colloidal mesophases

Porous mesophases, where well-defined particle-depleted void spaces are present within a particle-rich background fluid, can be self-assembled from colloidal particles interacting via isotropic pair interactions with competing attractions and repulsions. While such structures could be of wide interest for technological applications (e.g., filtration, catalysis, absorption, etc.), relatively few studies have investigated the interactions that lead to these morphologies and how they compare to those that produce other micro-phase-separated structures, such as clusters. In this work, we use inverse methods of statistical mechanics to design model isotropic pair potentials that form porous mesophases. We characterize the resulting porous structures, correlating features of the pair potential with the targeted pore size and the particle packing fraction. The former is primarily encoded by the amplitude and range of the repulsive barrier of the designed pair potential and the latter by the attractive well depth. We observe a trade-off with respect to the packing fraction of the targeted morphology: greater values support more spherical and monodisperse pores that themselves organize into periodic structures, while lower values yield more mobile pores that do not assemble into ordered structures but remain stable over a larger range of packing fraction. We conclude by commenting on the limitations of targeting a specific pore diameter within the present inverse design approach as well as by describing future directions to overcome these limitations.

On the formation of equilibrium gels via a macroscopic bond limitation

Restricting the number of attractive physical bonds that can form between particles in a fluid suppresses the usual demixing phase transition to very low particle concentrations, allowing for the formation of open, percolated, and homogeneous states, aptly called equilibrium or empty gels. Most demonstrations of this concept have directly limited the microscopic particle valence via anisotropic (patchy) attractions; however, an alternative macroscopic valence limitation would be desirable for greater experimental tunability and responsiveness. One possibility, explored in this paper, is to employ primary particles with attractions mediated via a secondary species of linking particles. In such a system, the linker-to-primary particle ratio serves as a macroscopic control parameter for the average microscopic valence. We show that the phase behavior of such a system predicted by Wertheims first order perturbation theory is consistent with equilibrium gel formation: the primary particle concentrations corresponding to the two-phase demixing transition are significantly suppressed at both low and high linker-to-primary particle ratios. Extensive molecular dynamics simulations validate these theoretical predictions but also reveal the presence of loops of bonded particles, which are neglected in the theory. Such loops cause densification and inhibit percolation, and hence the range of viable empty gel state conditions is somewhat reduced relative to the Wertheim theory predictions.

Inverse design of multicomponent assemblies

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 potential. However, optimization of both self- and cross interaction types appears necessary to design for assembly of more complex or open structures.

Design of two-dimensional particle assemblies using isotropic pair interactions with an attractive well

Using ground-state and relative-entropy based inverse design strategies, isotropic interactions with an attractive well are determined to stabilize and promote assembly of particles into two-dimensional square, honeycomb, and kagome lattices. The design rules inferred from these results are discussed and validated in the discovery of interactions that favor assembly of the highly open truncated-square and truncated-hexagonal lattices.

Gelation of plasmonic metal oxide nanocrystals by polymer-induced depletion attractions

Significance Self-supported gelation of optically active nanocrystals offers a modular pathway to harness optoelectronic functionality in multiscale materials by directly controlling volume fraction, bonding, and structure during assembly. We combine depletion attractions that emerge from the incorporation of small polymer chains and electrostatic repulsions to induce the gelation of isotropic metal oxide nanocrystals. We develop a theoretical model to assess our experimental fluid-to-gel-phase progression observations. By preventing nanocrystal fusion during network assembly, we achieve gels with a strong near-infrared absorption, reminiscent of the inherent near-infrared localized surface plasmon resonance of the nanocrystal building blocks. Gelation of colloidal nanocrystals emerged as a strategy to preserve inherent nanoscale properties in multiscale architectures. However, available gelation methods to directly form self-supported nanocrystal networks struggle to reliably control nanoscale optical phenomena such as photoluminescence and localized surface plasmon resonance (LSPR) across nanocrystal systems due to processing variabilities. Here, we report on an alternative gelation method based on physical internanocrystal interactions: short-range depletion attractions balanced by long-range electrostatic repulsions. The latter are established by removing the native organic ligands that passivate tin-doped indium oxide (ITO) nanocrystals while the former are introduced by mixing with small PEG chains. As we incorporate increasing concentrations of PEG, we observe a reentrant phase behavior featuring two favorable gelation windows; the first arises from bridging effects while the second is attributed to depletion attractions according to phase behavior predicted by our unified theoretical model. Our assembled nanocrystals remain discrete within the gel network, based on X-ray scattering and high-resolution transmission electron microscopy. The infrared optical response of the gels is reflective of both the nanocrystal building blocks and the network architecture, being characteristic of ITO nanocrystals’ LSPR with coupling interactions between neighboring nanocrystals.