Sub-5 nm Anisotropic Pattern Transfer via Colloidal Lithography of a Self-Assembled GdF3 Nanocrystal Monolayer.

Patterning materials with nanoscale features opens many research opportunities ranging from fundamental science to technological applications. However, current nanofabrication methods are ill-suited for sub-5 nm patterning and pattern transfer. We demonstrate the use of colloidal lithography to transfer an anisotropic pattern of discrete features into substrates with a critical dimension below 5 nm. The assembly of monodisperse, anisotropic nanocrystals (NCs) with a rhombic-plate morphology spaced by dendrimer ligands results in a well-ordered monolayer that serves as a 2D anisotropic hard mask pattern. This pattern is transferred into the underlying substrate using dry etching followed by removal of the NC mask. We exemplify this approach by fabricating an array of pillars with a rhombic cross-section and edge-to-edge spacing of 4.4 ± 1.1 nm. The fabrication approach enables broader access to patterning materials at the deep nanoscale by implementing innovative processes into well-established fabrication methods while minimizing process complexity.

Machine-learning-assisted materials discovery using failed experiments.

Inorganic-organic hybrid materials such as organically templated metal oxides, metal-organic frameworks (MOFs) and organohalide perovskites have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility, photovoltaic properties, gas adsorption capacity or lithium-ion intercalation) to identify promising target candidates for synthetic efforts; determination of the structure-property relationship from large bodies of experimental data, enabled by integration with high-throughput synthesis and measurement tools; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification or gas adsorption properties). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on 'dark' reactions--failed or unsuccessful hydrothermal syntheses--collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted conditions for new organically templated inorganic product formation with a success rate of 89 per cent. Inverting the machine-learning model reveals new hypotheses regarding the conditions for successful product formation.

A metallo-biopolymer conjugate of elastin-like polypeptide: photoluminescence enhancement in the coacervate microenvironment.

An optically active metallo-polymer assembly is demonstrated via conjugation of a genetically engineered elastin-like polypeptide (ELP) and a ruthenium(II) polypyridyl complex. By taking advantage of the phase transition of ELPs in water, photophysical properties of the resultant conjugate are investigated for both phases, below and above the critical transition temperature. Upon coacervation, the luminescence of the metallo-ELP is greatly enhanced as a consequence of local effects on the metal-ligand luminophore. These findings open a possibility to harness the temperature control of stimuli-responsive properties of biopolymers.

Improved Chemical and Colloidal Stability of Gold Nanoparticles through Dendron Capping.

Nanoparticle (NP) stability is imperative for commercialization of nanotechnology. In this study, we compare the stability of Au NPs with surfaces functionalized with oleylamine, dodecanethiol, and two dendritic ligands of different generations. Dendrimer ligands provide a significant increase in the chemical stability of Au NPs when analyzed by cyanide-induced NP decomposition as well as an investigation into their colloidal stability at ambient conditions. These results were supported by absorption measurements, transmission electron microscopy, thermogravimetric analysis, nuclear magnetic resonance, and small-angle transmission X-ray scattering and show that dendrimers play a key role in improving the chemical and colloidal stability of NPs.

Evaporation-Driven Coassembly of Hierarchical, Multicomponent Networks.

Self-assembly is an increasingly popular approach to systematically control the formation of complex, multicomponent materials with structural features orders of magnitude larger than the constituent colloidal nanocrystals. Common approaches often involve templating via prefabricated patterns to control particle organization- or programming-specific interactions between individual building blocks. While effective, such fabrication methods suffer from major bottlenecks due to the complexity required in mask creation for patterning or surface modification techniques needed to program directed interactions between particles. Here, we propose an alternative strategy that aims to bypass such limitations. First, we design a ligand structure that can bridge two distinct nanocrystal types. Then, by leveraging the solvent's evaporative dynamics to drive particle organization, we direct a cross-linked, multicomponent system of nanocrystals to organize hierarchically into ordered, open-network structures with domain sizes orders of magnitude larger than the constituent building blocks. We employ simulation and theory to rationalize the driving forces governing this evaporation-driven process, showing excellent agreement across theory, simulations, and experiments. These results suggest that evaporation-driven organization can be a powerful approach to designing and fabricating hierarchical, multifunctional materials.

Anisotropic nanocrystal shape and ligand design for co-assembly.

The use of nanocrystal (NC) building blocks to create metamaterials is a powerful approach to access emergent materials. Given the immense library of materials choices, progress in this area for anisotropic NCs is limited by the lack of co-assembly design principles. Here, we use a rational design approach to guide the co-assembly of two such anisotropic systems. We modulate the removal of geometrical incompatibilities between NCs by tuning the ligand shell, taking advantage of the lock-and-key motifs between emergent shapes of the ligand coating to subvert phase separation. Using a combination of theory, simulation, and experiments, we use our strategy to achieve co-assembly of a binary system of cubes and triangular plates and a secondary system involving two two-dimensional (2D) nanoplates. This theory-guided approach to NC assembly has the potential to direct materials choices for targeted binary co-assembly.

Electron accepting naphthalene bisimide ligand architectures for modulation of π-π stacking in nanocrystal hybrid materials.

Investigation of charge transfer in quantum dot (QD) systems is an area of great interest. Specifically, the relationship between capping ligand and rate of charge transfer has been studied as a means to optimize these materials. To investigate the role of ligand interaction on the QD surface for electron transfer, we designed and synthesized a series of ligands containing an electron accepting moiety, naphthalene bisimide (NBI). These ligands differ in their steric bulk: as one allows for π-π stacking between the NBI moieties at high surface coverages, while the other does not, allowing for a direct comparison of these effects. Once grafted onto QDs, these hybrid materials were studied using UV-Vis, fluorescence, and transient absorption spectroscopy. Interestingly, the sample with the fastest electron transfer was not the sample with the most NBI π-π stacking, it was instead where these ligands were mixed amongst oleic acid, breaking up H-aggregates between the NBI groups.

Nanocrystal Core Size and Shape Substitutional Doping and Underlying Crystalline Order in Nanocrystal Superlattices.

Substitutional doping is a potentially powerful technique to control the properties of nanocrystal (NC) superlattices (SLs). However, not every NC can be substituted into any lattice, as the NCs have to be close in size and shape, limiting the application of substitutional doping. Here we show that this limitation can be overcome by employing ligands of various size. We show that small NCs with long ligands can be substituted into SLs of big NCs with short ligands. Furthermore, we show that shape differences can also be overcome and that cubes can substitute spheres when both are coated with long ligands. Finally, we use the NC effective ligand size, softness, and effective overall size ratio to explain observed doping behaviors.

Dendrimer Ligand Directed Nanoplate Assembly.

Many studies on nanocrystal (NC) self-assembly into ordered superlattices have focused mainly on attractive forces between the NCs, whereas the role of organic ligands on anisotropic NCs is only in its infancy. Herein, we report the use of a series of dendrimer ligands to direct the assembly of nanoplates into 2D and 3D geometries. It was found that the dendrimer-nanoplates consistently form a directionally offset architecture in 3D films. We present a theory to predict ligand surface distribution and Monte Carlo simulation results that characterize the ligand shell around the nanoplates. Bulky dendrimer ligands create a nontrivial corona around the plates that changes with ligand architecture. When this organic-inorganic effective shape is used in conjunction with thermodynamic perturbation theory to predict both lattice morphology and equilibrium relative orientations between NCs, a lock-and-key type of mechanism is found for the 3D assembly. We observe excellent agreement between our experimental results and theoretical model for 2D and 3D geometries, including the percent of offset between the layers of NCs. Such level of theoretical understanding and modeling will help guide future design frameworks to achieve targeted assemblies of NCs.

A semi-combinatorial approach for investigating polycatenar ligand-controlled synthesis of rare-earth fluoride nanocrystals.

Rare-earth nanocrystals (RE NCs) are a valuable class of nanomaterials due to their ability to bring the attractive properties of rare earth bulk crystals to biomedical applications and solution-processable engineering. Of the bottom-up synthesis approaches, solvothermal methods yield highly crystalline and monodisperse RE NCs. Herein, we report a polycatenar ligand controlled synthesis of RE NCs using a semi-combinatorial approach with a microreactor setup that enables the investigation of the influences of several reaction parameters on the growth of the RE NCs. This approach enabled the discovery of conditions that yield highly monodisperse elongated plates with neutral, positive, and negative curvatures, as well as provide evidence of the formation of chiral morphologies.