Kyle J. M. Bishop

Programmable self-assembly.

Two conceptual strategies for encoding information into self-assembling building blocks highlight opportunities and challenges in the realization of programmable colloidal nanostructures.

Templated Synthesis of Amphiphilic Nanoparticles at the Liquid–Liquid Interface

A simple and reliable method is described to produce inorganic nanoparticles functionalized asymmetrically with domains of hydrophobic and hydrophilic ligands on their respective hemispheres. These amphiphilic, Janus-type particles form spontaneously by a thermodynamically controlled process, in which the particle cores and two competing ligands assemble at the interface between two immiscible liquids to reduce the interfacial energy. The asymmetric surface chemistry resulting from this process was confirmed using contact angle measurements of water droplets on nanoparticle monolayers deposited onto hydrophobic and hydrophilic substrates-particles presenting their hydrophobic face give contact angles of ∼96°, those presenting their hydrophilic face ∼19°. The spontaneous assembly process is rationalized by a thermodynamic model, which accounts both for the energetic contributions driving the assembly and for the entropic penalties that must be overcome. Consistent with the model, amphiphilic NPs form only when there is sufficient interfacial area to accommodate them; however, this potential limitation is easily overcome by mechanical agitation of the two-phase mixture. While it is straightforward to vary the ratio of hydrophobic and hydrophilic ligands, the accumulation of amphiphilic particles at the interface is maximal for ligand ratios near 1:1. In addition to gold nanoparticles and thiolate ligands, we demonstrate the generality of this approach by extending it to the preparation of amphiphilic iron oxide nanoparticles using two types of diol-terminated ligands. Depending on the material properties of the inorganic cores, the resulting amphiphilic particles should find applications as responsive particle surfactants that respond dynamically to optical (plasmonic particles) and/or magnetic (magnetic particles) fields.

Using shape for self-assembly

A 1980 poem by Alan Mackay outlines his aspiration ‘to see what all have seen but think what none have thought’: a daunting task, which he accomplished not once, but several times. A ‘truly myriadminded, manysided man—a veritable triacontahedron’ in the words of his colleagues and friends, Alan Mackay pursued a lifelong interest in the problems of morphogenesis and form, a comprehension of which necessitated him crisscrossing the borders of the inanimate and animate world of soft and hard materials, through the integration of concepts and methods of chemistry, physics, mathematics and biology. In other words, he realized in his time a genuinely interdisciplinary approach to complex problems that still to this day remains beyond much of the academic community. Being invited to contribute a paper on the theme ‘beyond crystals’, we naturally wondered how Alan Mackay would think about the world of nanoscale self-assembly where so much depends on shape and form.

Integration of Gold Nanoparticles into Bilayer Structures via Adaptive Surface Chemistry

We describe the spontaneous incorporation of amphiphilic gold nanoparticles (Au NPs) into the walls of surfactant vesicles. Au NPs were functionalized with mixed monolayers of hydrophilic (deprotonated mercaptoundecanoic acid, MUA) and hydrophobic (octadecanethiol, ODT) ligands, which are known to redistribute dynamically on the NP surface in response to changes in the local environment. When Au NPs are mixed with preformed surfactant vesicles, the hydrophobic ODT ligands on the NP surface interact favorably with the hydrophobic core of the bilayer structure and guide the incorporation of NPs into the vesicle walls. Unlike previous strategies based on small hydrophobic NPs, the present approach allows for the incorporation of water-soluble particles even when the size of the particles greatly exceeds the bilayer thickness. The strategy described here based on inorganic NPs functionalized with two labile ligands should in principle be applicable to other nanoparticle materials and bilayer structures.

Antibacterial Nanoparticle Monolayers Prepared on Chemically Inert Surfaces by Cooperative Electrostatic Adsorption (CELA)

Cooperative electrostatic adsorption (CELA) is used to deposit monolayer coatings of silver nanoparticles on relatively chemically inert polymers, polypropylene, and Tygon. Medically relevant components (tubing, vials, syringes) coated by this method exhibit antibacterial properties over weeks to months with the coatings being stable under constant-flow conditions. Antibacterial properties of the coatings are due to a slow release of Ag(+) from the particles. The rate of this release is quantified by the dithiol-precipitation method coupled with inductively coupled plasma optical emission spectrometer (ICP-OES) analysis.

Charged nanoparticles as supramolecular surfactants for controlling the growth and stability of microcrystals

Microcrystals of desired sizes are important in a range of processes and materials, including controlled drug release, production of pharmaceutics and food, bio- and photocatalysis, thin-film solar cells and antibacterial fabrics. The growth of microcrystals can be controlled by a variety of agents, such as multivalent ions, charged small molecules, mixed cationic-anionic surfactants, polyelectrolytes and other polymers, micropatterned self-assembled monolayers, proteins and also biological organisms during biomineralization. However, the chief limitation of current approaches is that the growth-modifying agents are typically specific to the crystalizing material. Here, we show that oppositely charged nanoparticles can function as universal surfactants that control the growth and stability of microcrystals of monovalent or multivalent inorganic salts, and of charged organic molecules. We also show that the solubility of the microcrystals can be further tuned by varying the thickness of the nanoparticle surfactant layers and by reinforcing these layers with dithiol crosslinks.

Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry

The entire chemical-synthetic knowledge created since the days of Lavoisier to the present can be represented as a complex network (Figure 1a) comprising millions of compounds and reactions. While it is simply beyond cognition of any individual human to understand and analyze all this collective chemical knowledge, modern computers have become powerful enough to perform suitable network analyses within reasonable timescales. In this context, a problem that is both fundamentally interesting and practically important is the identification of optimal synthetic pathways leading to desired, known molecules from commercially available substrates. In either manual searches or semiautomated search tools, such as Reaxys, this procedure is done by back-tracking the possible syntheses step-by-step. Such “manual” methods, however, give virtually no chance of finding an optimal pathway, as the number of possible syntheses to consider is very large (for example, ca. 10 within five steps). Moreover, the problem becomes dramatically more complex when one aims to optimize the syntheses of multiple substances simultaneously when, for example, a company producing N products would strive to design synthetic pathways sharing many common substrates/intermediates and minimizing the overall synthetic cost (Figure 1a). As we show herein, however, judicious combination of combinatorial optimization with network search algorithms allows the parallel optimization of tens to thousands of syntheses. The algorithms we describe traverse the network of organic chemistry (henceforth, NOC or simply the network) probing different synthetic paths according to the cost criterion as defined by a combination of labor cost and the cost of staring materials. In a specific case study, we show that our optimization can reduce the cost of an existing synthetic company (here, ProChimia Surfaces) by almost 50%. Overall, this communication is the first instance in which synthetic optimizations are based on the entire body of synthetic knowledge as stored in the NOC and combined with economical descriptors (that is, prices). While each of the individual reactions in the NOC is known, the network search algorithms create new chemical knowledge in the form of near optimal reaction sequences; notably, the syntheses that are optimal for making any molecule individually can be different from those optimizing the synthesis of this and other molecules simultaneously. Our analyses are based on a network of about 7 million reactions and about 7 million substances derived as described in the first communication in this series (also see Refs. [1, 2]). While in our earlier analyses of NOC, the simple dot–arrow representation was typically sufficient, the analysis of specific syntheses involving multiple substrates and/or products requires the so-called bipartite-graph representation with two types of nodes: those corresponding to specific substances (blue dots in Figure 1b), and those representing the reactions (black dots in Figure 1b). This representation of the NOC captures the causal synthetic dependencies and accounts for the fact that a viable synthesis (see the Supporting Information, Section 2) cannot proceed without all of the necessary reactants, which must either be synthesized by another suitable reaction or purchased. Also, as our network searches are intended to compare the actual costs of syntheses, we have linked the NOC to a test Figure 1. The network of organic chemistry and its bipartite wiring plan. a) Small fraction of the network (ca. 0.025%) centered on six target compounds (red). Computational methods described herein allow for the identification of near optimal synthesis plans (inset) despite the size and complexity of the network. b) Illustration of the mapping from a list of chemical reactions to a directed, bipartite network.

Precision assembly of oppositely and like-charged nanoobjects mediated by charge-induced dipole interactions.

The range of electrostatic interactions controls precisely the mutual orientations of assembling charged nanoobjects. For nonspherically symmetric particles, polarization effects and induced dipoles can dominate charge-charge interactions. These charge-induced dipole interactions mediate orientation-specific aggregation of both oppositely and like-charged particles.

Dynamic self-assembly in ensembles of camphor boats.

Millimeter-sized gel particles loaded with camphor and floating at the interface between water and air generate convective flows around them. These flows give rise to repulsive interparticle interactions, and mediate dynamic self-assembly of nonequilibrium particle formations. When the numbers of particles, N, are small, particle motions are uncorrelated. When, however, N exceeds a threshold value, particles organize into ordered lattices. The nature of hydrodynamic forces underlying these effects and the dynamics of the self-assembling system are modeled numerically using Navier-Stokes equations as well as analytically using scaling arguments.

Dynamic internal gradients control and direct electric currents within nanostructured materials

Switchable nanomaterials--materials that can change their properties and/or function in response to external stimuli-have potential applications in electronics, sensing and catalysis. Previous efforts to develop such materials have predominately used molecular switches that can modulate their properties by means of conformational changes. Here, we show that electrical conductance through films of gold nanoparticles coated with a monolayer of charged ligands can be controlled by dynamic, long-range gradients of both mobile counterions surrounding the nanoparticles and conduction electrons on the nanoparticle cores. The internal gradients and the electric fields they create are easily reconfigurable, and can be set up in such a way that electric currents through the nanoparticles can be modulated, blocked or even deflected so that they only pass through select regions of the material. The nanoion/counterion hybrids combine the properties of electronic conductors with those of ionic gels/polymers, are easy to process by solution-casting and, by controlling the internal gradients, can be reconfigured into different electronic elements (current rectifiers, switches and diodes).