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Multicomponent self-assembly mixtures offer the possibility of encoding multiple target structures with the same set of interacting components. Selective retrieval of one of the stored structures has been attempted by preparing an initial state that favors the assembly of the required target, through seeding, concentration patterning, or specific choices of interaction strengths. This may not be possible in an experiment where on-the-fly reconfiguration of the building blocks to switch functionality may be required. In this paper, we explore principles of inverse design of a multicomponent, self-assembly mixture capable of encoding two competing structures that can be selected through simple temperature protocols. We design the target structures to realize the generic situation in which one of the targets has the lower nucleation barrier, while the other is globally more stable. We observe that, to avoid the formation of spurious or chimeric aggregates, the number of neighboring component pairs that occur in both structures should be minimal. Our design also requires the inclusion of components that are part of only one of the target structures. We observe, however, that to maximize the selectivity of retrieval, the component library itself should be maximally shared by the two targets, within such a constraint. We demonstrate that temperature protocols can be designed that lead to the formation of either one of the target structures with high selectivity. We discuss the important role played by secondary aggregation products in improving selectivity, which we term “vestigial aggregates.”

A key challenge in nano-science is to design ligand-coated nano-particles that can bind selectively to surfaces that display the cognate receptors above a threshold (surface) concentration. Nano-particles that bind monovalently to a target surface do not discriminate sharply between surfaces with high and low receptor coverage. In contrast, \"multivalent\" nano-particles that can bind to a larger number of ligands simultaneously, display regimes of \"super selectivity\" where the fraction of bound particles varies sharply with the receptor concentration. We present numerical simulations that show that multivalent nano-particles can be designed such that they approach the \"on-off\" binding behavior ideal for receptor-concentration selective targeting. We propose a simple analytical model that accounts for the super selective behavior of multivalent nano-particles. The model shows that the super selectivity is due to the fact that the number of distinct ligand-receptor binding arrangements increases in a highly nonlinear way with receptor coverage. Somewhat counterintuitively, our study shows that selectivity can be improved by making the individual ligand-receptor bonds weaker. We propose a simple rule of thumb to predict the conditions under which super selectivity can be achieved. We validate our model predictions against the Monte Carlo simulations.

The field of complex self-assembly is moving toward the design of multiparticle structures consisting of thousands of distinct building blocks. To exploit the potential benefits of structures with such “addressable complexity,” we need to understand the factors that optimize the yield and the kinetics of self-assembly. Here we use a simple theoretical method to explain the key features responsible for the unexpected success of DNA-brick experiments, which are currently the only demonstration of reliable self-assembly with such a large number of components. Simulations confirm that our theory accurately predicts the narrow temperature window in which error-free assembly can occur. Even more strikingly, our theory predicts that correct assembly of the complete structure may require a time-dependent experimental protocol. Furthermore, we predict that low coordination numbers result in nonclassical nucleation behavior, which we find to be essential for achieving optimal nucleation kinetics under mild growth conditions. We also show that, rather surprisingly, the use of heterogeneous bond energies improves the nucleation kinetics and in fact appears to be necessary for assembling certain intricate 3D structures. This observation makes it possible to sculpt nucleation pathways by tuning the distribution of interaction strengths. These insights not only suggest how to improve the design of structures based on DNA bricks, but also point the way toward the creation of a much wider class of chemical or colloidal structures with addressable complexity.

Gelation and densification of calcium–silicate–hydrate take place during cement hydration. Both processes are crucial for the development of cement strength, and for the long-term evolution of concrete structures. However, the physicochemical environment evolves during cement formation, making it difficult to disentangle what factors are crucial for the mechanical properties. Here we use Monte Carlo and Molecular Dynamics simulations to study a coarse-grained model of cement formation, and investigate the equilibrium and arrested states. We can correlate the various structures with the time evolution of the interactions between the nano-hydrates during the preparation of cement. The novel emerging picture is that the changes of the physicochemical environment, which dictate the evolution of the effective interactions, specifically favour the early gel formation and its continuous densification. Our observations help us understand how cement attains its unique strength and may help in the rational design of the properties of cement and related materials. The origins of the unique properties of cement are poorly understood. Using simulations the authors show that the early formation of a soft nano-particle gel, followed by slow densification, plays a crucial role in giving cement its unique mechanical properties.

Understanding entropic contributions to common ordering transitions is essential for the design of self-assembling systems with addressable complexity. Irreversible changes in physical systems only occur because of an increase in entropy. The earliest example of a system that has an ordered phase with higher entropy than that of the disordered phase at the same density is LarsOnsagers model for a fluid of thin, hard rods.

The methodology to simulate transport phenomena in bulk systems is well-established. In contrast, there is no clear consensus about the choice of techniques to model cross-transport phenomena and phoretic transport, mainly because some of the hydrodynamic descriptions are incomplete from a thermodynamic point of view. In the present paper, we use a unified framework to describe diffusio-osmosis(phoresis), and we report non-equilibrium molecular dynamics (NEMD) on such systems. We explore different simulation methods to highlight some of the technical problems that arise in the calculations. For diffusiophoresis, we use two NEMD methods: boundary-driven and field-driven. Although the two methods should be equivalent in the limit of very weak gradients, we find that finite Peclet-number effects are much stronger in boundary-driven flows than in the case where we apply fictitious color forces. Graphic abstract

Nanoactuators and nanomachines have long been sought after, but key bottlenecks remain. Forces at submicrometer scales are weak and slow, control is hard to achieve, and power cannot be reliably supplied. Despite the increasing complexity of nanodevices such as DNA origami and molecular machines, rapid mechanical operations are not yet possible. Here, we bind temperature-responsive polymers to charged Au nanoparticles, storing elastic energy that can be rapidly released under light control for repeatable isotropic nanoactuation. Optically heating above a critical temperature Tc = 32 °C using plasmonic absorption of an incident laser causes the coatings to expel water and collapse within a microsecond to the nanoscale, millions of times faster than the base polymer. This triggers a controllable number of nanoparticles to tightly bind in clusters. Surprisingly, by cooling below Tc their strong van der Waals attraction is overcome as the polymer expands, exerting nanoscale forces of several nN. This large force depends on van der Waals attractions between Au cores being very large in the collapsed polymer state, setting up a tightly compressed polymer spring which can be triggered into the inflated state. Our insights lead toward rational design of diverse colloidal nanomachines.

Specific targeting is common in biology and is a key challenge in nanomedicine. It was recently demonstrated that multivalent probes can selectively target surfaces with a defined density of surface binding sites. Here we show, using a combination of experiments and simulations on multivalent polymers, that such “superselective” binding can be tuned through the design of the multivalent probe, to target a desired density of binding sites. We develop an analytical model that provides simple yet quantitative predictions to tune the polymer’s superselective binding properties by its molecular characteristics such as size, valency, and affinity. This work opens up a route toward the rational design of multivalent probes with defined superselective targeting properties for practical applications, and provides mechanistic insight into the regulation of multivalent interactions in biology. To illustrate this, we show how the superselective targeting of the extracellular matrix polysaccharide hyaluronan to its main cell surface receptor CD44 is controlled by the affinity of individual CD44–hyaluronan interactions. Significance A basic requirement in biomedical research is the ability to specifically target cells and tissues. Targeting typically relies on the specific binding of a “ligand” on a tailor-made probe to a “receptor” on the desired cell/tissue. Conventional probes efficiently distinguish a biological entity displaying the receptor from others that do not, but exhibit limited selectivity when the entities to be distinguished display a given receptor at different densities. Multivalent probes that bind several receptors simultaneously potentially can sharply discriminate between different receptor densities. We demonstrate how such “superselective” binding can be tuned through probe design to target a desired receptor density, and thus lay the foundation for the rational design of a new generation of analytical, diagnostic, and therapeutic probes.

Significance The assembly of normally soluble proteins into large fibrils, known as amyloid aggregation, is associated with a range of pathologies. Prefibrillar protein oligomers but not the grown fibers are believed to be the main toxic agents. It is unresolved if these oligomers are necessary for fibril assembly or just a dangerous byproduct. We show using computer simulations that, at physiological concentrations, amyloid formation must proceed through a two-step process including prefibrillar oligomers. We find that there is an optimal oligomeric size for amyloid nucleation and that classical nucleation theory cannot be applied to this process. Formation of oligomers and hence, fibrils, is controlled by the strength of nonspecific attractions, whose weakening may be crucial in preventing amyloid aggregation. Protein oligomers have been implicated as toxic agents in a wide range of amyloid-related diseases. However, it has remained unsolved whether the oligomers are a necessary step in the formation of amyloid fibrils or just a dangerous byproduct. Analogously, it has not been resolved if the amyloid nucleation process is a classical one-step nucleation process or a two-step process involving prenucleation clusters. We use coarse-grained computer simulations to study the effect of nonspecific attractions between peptides on the primary nucleation process underlying amyloid fibrillization. We find that, for peptides that do not attract, the classical one-step nucleation mechanism is possible but only at nonphysiologically high peptide concentrations. At low peptide concentrations, which mimic the physiologically relevant regime, attractive interpeptide interactions are essential for fibril formation. Nucleation then inevitably takes place through a two-step mechanism involving prefibrillar oligomers. We show that oligomers not only help peptides meet each other but also, create an environment that facilitates the conversion of monomers into the β -sheet–rich form characteristic of fibrils. Nucleation typically does not proceed through the most prevalent oligomers but through an oligomer size that is only observed in rare fluctuations, which is why such aggregates might be hard to capture experimentally. Finally, we find that the nucleation of amyloid fibrils cannot be described by classical nucleation theory: in the two-step mechanism, the critical nucleus size increases with increases in both concentration and interpeptide interactions, which is in direct contrast with predictions from classical nucleation theory.