Self-assembly of emulsion droplets through programmable folding

Binding Site Programmable Self-Assembly of 3D Hierarchical DNA Origami Nanostructures

DNA nanotechnology has broad applications in biomedical drug delivery and programmable materials. Characterization of the self-assembly of DNA origami and quantum dots (QDs) is necessary for the development of new DNA-based nanostructures. We use computation and experiment to show that the self-assembly of 3D hierarchical nanostructures can be controlled by programming the binding site number and their positions on DNA origami. Using biotinylated pentagonal pyramid wireframe DNA origamis and streptavidin capped QDs, we demonstrate that DNA origami with 1 binding site at the outer vertex can assemble multimeric origamis with up to 6 DNA origamis on 1 QD, and DNA origami with 1 binding site at the inner center can only assemble monomeric and dimeric origamis. Meanwhile, the yield percentages of different multimeric origamis are controlled by the QD:DNA-origami stoichiometric mixing ratio. DNA origamis with 2 binding sites at the αγ positions (of the pentagon) make larger nanostructures than those with binding sites at the αβ positions. In general, increasing the number of binding sites leads to increases in the nanostructure size. At high DNA origami concentration, the QD number in each cluster becomes the limiting factor for the growth of nanostructures. We find that reducing the QD size can also affect the self-assembly because of the reduced access to the binding sites from more densely packed origamis.

Nanocrystal Assemblies: Current Advances and Open Problems

We explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

Emergent dynamics due to chemo-hydrodynamic self-interactions in active polymers

The field of synthetic active matter has, thus far, been led by efforts to create point-like, isolated (yet interacting) self-propelled objects (e.g. colloids, droplets, microrobots) and understanding their collective dynamics. The design of flexible, freely jointed active assemblies from autonomously powered sub-components remains a challenge. Here, we report freely-jointed active polymers created using self-propelled droplets as monomeric units. Our experiments reveal that the self-shaping chemo-hydrodynamic interactions between the monomeric droplets give rise to an emergent rigidity (the acquisition of a stereotypical asymmetric C-shape) and associated ballistic propulsion of the active polymers. The rigidity and propulsion of the chains vary systematically with their lengths. Using simulations of a minimal model, we establish that the emergent polymer dynamics are a generic consequence of quasi two-dimensional confinement and auto-repulsive trail-mediated chemical interactions between the freely jointed active droplets. Finally, we tune the interplay between the chemical and hydrodynamic fields to experimentally demonstrate oscillatory dynamics of the rigid polymer propulsion. Altogether, our work highlights the possible first steps towards synthetic self-morphic active matter.

Refractive-index and density-matched emulsions with programmable DNA interactions

Emulsion droplets on the colloidal length scale are a model system of frictionless compliant spheres. Direct imaging studies of the microscopic structure and dynamics of emulsions offer valuable insights into fundamental processes, such as gelation, jamming, and self-assembly. A microscope, however, can only resolve the individual droplets in a densely packed emulsion if the droplets are closely index-matched to their fluid medium. Mitigating perturbations due to gravity additionally requires the droplets to be density-matched to the medium. Creating droplets that are simultaneously index-matched and density-matched has been a long-standing challenge for the soft-matter community. The present study introduces a method for synthesizing monodisperse micrometer-sized siloxane droplets whose density and refractive index can be precisely and independently tuned by adjusting the volume fraction of three silane precursors. A systematic optimization protocol yields fluorescently labeled ternary droplets whose densities and refractive indexes match, to the fourth decimal place, those of aqueous solutions of glycerol or dimethylsiloxane. Because all of the materials in this system are biocompatible, we functionalize the droplets with DNA strands to endow them with programmed inter-droplet interactions. Confocal microscopy then reveals both the three-dimensional structure and the network of droplet-droplet contacts in a class of self-assembled droplet gels, free from gravitational effects. This experimental toolbox creates opportunities for studying the microscopic mechanisms that govern viscoelastic properties and self-assembly in soft materials.

Crystallization-Inspired Design and Modeling of Self-Assembly Lattice-Formation Swarm Robotics

Self-assembly formation is a key research topic for realizing practical applications in swarm robotics. Due to its inherent complexity, designing high-performance self-assembly formation strategies and proposing corresponding macroscopic models remain formidable challenges and present an open research frontier. Taking inspiration from crystallization, this paper introduces a distributed self-assembly formation strategy by defining free, moving, growing, and solid states for robots. Robots in these states can spontaneously organize into user-specified two-dimensional shape formations with lattice structures through local interactions and communications. To address the challenges posed by complex spatial structures in modeling a macroscopic model, this work introduces the structural features estimation method. Subsequently, a corresponding non-spatial macroscopic model is developed to predict and analyze the self-assembly behavior, employing the proposed estimation method and a stock and flow diagram. Real-robot experiments and simulations validate the flexibility, scalability, and high efficiency of the proposed self-assembly formation strategy. Moreover, extensive experimental and simulation results demonstrate the model's accuracy in predicting the self-assembly process under different conditions. Model-based analysis indicates that the proposed self-assembly formation strategy can fully utilize the performance of individual robots and exhibits strong self-stability.

Swarm Autonomy: From Agent Functionalization to Machine Intelligence

Swarm behaviors are common in nature, where individual organisms collaborate via perception, communication, and adaptation. Emulating these dynamics, large groups of active agents can self-organize through localized interactions, giving rise to complex swarm behaviors, which exhibit potential for applications across various domains. This review presents a comprehensive summary and perspective of synthetic swarms, to bridge the gap between the microscale individual agents and potential applications of synthetic swarms. It is begun by examining active agents, the fundamental units of synthetic swarms, to understand the origins of their motility and functionality in the presence of external stimuli. Then inter-agent communications and agent-environment communications that contribute to the swarm generation are summarized. Furthermore, the swarm behaviors reported to date and the emergence of machine intelligence within these behaviors are reviewed. Eventually, the applications enabled by distinct synthetic swarms are summarized. By discussing the emergent machine intelligence in swarm behaviors, insights are offered into the design and deployment of autonomous synthetic swarms for real-world applications.

Metabolically intact nuclei are fluidized by the activity of the chromatin remodeling motor BRG1

The structure and dynamics of the cell nucleus regulate nearly every facet of the cell. Changes in nuclear shape limit cell motility and gene expression. Although the nucleus is generally seen as the stiffest organelle in the cell, cells can nevertheless deform the nucleus to large strains by small mechanical stresses. Here, we show that the mechanical response of the cell nucleus exhibits active fluidization that is driven by the BRG 1 motor of the SWI/SNF/BAF chromatin-remodeling complex. Atomic force microscopy measurements show that the nucleus alters stiffness in response to the cell substrate stiffness, which is retained after the nucleus is isolated and that the work of nuclear compression is mostly dissipated rather than elastically stored. Inhibiting BRG 1 stiffens the nucleus and eliminates dissipation and nuclear remodeling both in isolated nuclei and in intact cells. These findings demonstrate a novel link between nuclear motor activity and global nuclear mechanics.

Superstructural ordering in self-sorting coacervate-based protocell networks

Bottom-up assembly of higher-order cytomimetic systems capable of coordinated physical behaviours, collective chemical signalling and spatially integrated processing is a key challenge in the study of artificial multicellularity. Here we develop an interactive binary population of coacervate microdroplets that spontaneously self-sort into chain-like protocell networks with an alternating sequence of structurally and compositionally dissimilar microdomains with hemispherical contact points. The protocell superstructures exhibit macromolecular self-sorting, spatially localized enzyme/ribozyme biocatalysis and interdroplet molecular translocation. They are capable of topographical reconfiguration using chemical or light-mediated stimuli and can be used as a micro-extraction system for macroscale biomolecular sorting. Our methodology opens a pathway towards the self-assembly of multicomponent protocell networks based on selective processes of coacervate droplet-droplet adhesion and fusion, and provides a step towards the spontaneous orchestration of protocell models into artificial tissues and colonies with ordered architectures and collective functions.

Organization of an Artificial Multicellular System with a Tunable DNA Patch on a Membrane Surface

Coordinating multiple artificial cellular compartments into a well-organized artificial multicellular system (AMS) is of great interest in bottom-up synthetic biology. However, developing a facile strategy for fabricating an AMS with a controlled arrangement remains a challenge. Herein, utilizing in situ DNA hybridization chain reaction on the membrane surface, we developed a DNA patch-based strategy to direct the interconnection of vesicles. By tuning the DNA patch that generates heterotrophic adhesion for the attachment of vesicles, we could produce an AMS with higher-order structures straightforwardly and effectively. Furthermore, a hybrid AMS comprising live cells and vesicles was fabricated, and we found the hybrid AMS with higher-order structures arouses efficient molecular transportation from vesicles to living cells. In brief, our work provides a versatile strategy for modulating the self-assembly of AMSs, which could expand our capability to engineer synthetic biological systems and benefit synthetic cell research in programmable manipulation of intercellular communications.

Synthetic-Cell-Based Multi-Compartmentalized Hierarchical Systems

In the extant lifeforms, the self-sustaining behaviors refer to various well-organized biochemical reactions in spatial confinement, which rely on compartmentalization to integrate and coordinate the molecularly crowded intracellular environment and complicated reaction networks in living/synthetic cells. Therefore, the biological phenomenon of compartmentalization has become an essential theme in the field of synthetic cell engineering. Recent progress in the state-of-the-art of synthetic cells has indicated that multi-compartmentalized synthetic cells should be developed to obtain more advanced structures and functions. Herein, two ways of developing multi-compartmentalized hierarchical systems, namely interior compartmentalization of synthetic cells (organelles) and integration of synthetic cell communities (synthetic tissues), are summarized. Examples are provided for different construction strategies employed in the above-mentioned engineering ways, including spontaneous compartmentalization in vesicles, host-guest nesting, phase separation mediated multiphase, adhesion-mediated assembly, programmed arrays, and 3D printing. Apart from exhibiting advanced structures and functions, synthetic cells are also applied as biomimetic materials. Finally, key challenges and future directions regarding the development of multi-compartmentalized hierarchical systems are summarized; these are expected to lay the foundation for the creation of a "living" synthetic cell as well as provide a larger platform for developing new biomimetic materials in the future.

The First Nucleic Acid Strands May Have Grown on Peptides via Primeval Reverse Translation

The central dogma of molecular biology dictates that, with only a few exceptions, information proceeds from DNA to protein through an RNA intermediate. Examining the enigmatic steps from prebiotic to biological chemistry, we take another road suggesting that primordial peptides acted as template for the self-assembly of the first nucleic acids polymers. Arguing in favour of a sort of archaic "reverse translation" from proteins to RNA, our basic premise is a Hadean Earth where key biomolecules such as amino acids, polypeptides, purines, pyrimidines, nucleosides and nucleotides were available under different prebiotically plausible conditions, including meteorites delivery, shallow ponds and hydrothermal vents scenarios. Supporting a protein-first scenario alternative to the RNA world hypothesis, we propose the primeval occurrence of short two-dimensional peptides termed "selective amino acid- and nucleotide-matching oligopeptides" (henceforward SANMAOs) that noncovalently bind at the same time the polymerized amino acids and the single nucleotides dispersed in the prebiotic milieu. In this theoretical paper, we describe the chemical features of this hypothetical oligopeptide, its biological plausibility and its virtues from an evolutionary perspective. We provide a theoretical example of SANMAO's selective pairing between amino acids and nucleosides, simulating a poly-Glycine peptide that acts as a template to build a purinic chain corresponding to the glycine's extant triplet codon GGG. Further, we discuss how SANMAO might have endorsed the formation of low-fidelity RNA's polymerized strains, well before the appearance of the accurate genetic material's transmission ensured by the current translation apparatus.

Dynamic interfaces for contact-time control of colloidal interactions

Understanding pairwise interactions between colloidal particles out of equilibrium has a profound impact on dynamical processes such as colloidal self assembly. However, traditional colloidal interactions are effectively quasi-static on colloidal timescales and cannot be modulated out of equilibrium. A mechanism to dynamically tune the interactions during colloidal contacts can provide new avenues for self assembly and material design. In this work, we develop a framework based on polymer-coated colloids and demonstrate that in-plane surface mobility and mechanical relaxation of polymers at colloidal contact interfaces enable an effective, dynamic interaction. Combining analytical theory, simulations, and optical tweezer experiments, we demonstrate precise control of dynamic pair interactions over a range of pico-Newton forces and seconds timescales. Our model helps further the general understanding of out-of-equilibrium colloidal assemblies while providing extensive design freedom via interface modulation and nonequilibrium processing.

Humidity-Controlled Molecular Assembly and Photoisomerization Behavior with a Bubble-Assisted Patterning Approach

Precise control of molecular assembly is of great significance in the application of functional molecules. This work has systematically investigated the humidity effect in bubble-assisted molecular assembly. This work finds humidity is critical in the evolution of the soft confined space, leading to the formation of microscale liquid confined space under high humidity, and nanoscale liquid confined space under low humidity. It is also revealed that the differences in surface wettability and adhesion play the key role. Consequently, a flat pattern with thermodynamically favorable ordered structure and a sharp pattern with dynamically favorable disordered structure are achieved, which show different solid-state photoisomerization behaviors and photoresponsiveness. Interestingly, conductivity of sharp pattern with disordered structure is higher than that of flat pattern with layered ordered structure due to electronic transport mechanism of different spatial dimensions. This work opens a new way for manipulating the molecular self-assembly to control the morphology and function of molecular patterns.

Self-organization of primitive metabolic cycles due to non-reciprocal interactions

One of the greatest mysteries concerning the origin of life is how it has emerged so quickly after the formation of the earth. In particular, it is not understood how metabolic cycles, which power the non-equilibrium activity of cells, have come into existence in the first instances. While it is generally expected that non-equilibrium conditions would have been necessary for the formation of primitive metabolic structures, the focus has so far been on externally imposed non-equilibrium conditions, such as temperature or proton gradients. Here, we propose an alternative paradigm in which naturally occurring non-reciprocal interactions between catalysts that can partner together in a cyclic reaction lead to their recruitment into self-organized functional structures. We uncover different classes of self-organized cycles that form through exponentially rapid coarsening processes, depending on the parity of the cycle and the nature of the interaction motifs, which are all generic but have readily tuneable features.

Flexible Colloidal Molecules with Directional Bonds and Controlled Flexibility

Colloidal molecules are ideal model systems for mimicking real molecules and can serve as versatile building blocks for the bottom-up self-assembly of flexible and smart materials. While most colloidal molecules are rigid objects, the development of colloidal joints has made it possible to endow them with conformational flexibility. However, their unrestricted range of motion does not capture the limited movement and bond directionality that is instead typical of real molecules. In this work, we create flexible colloidal molecules with an in situ controllable motion range and bond directionality by assembling spherical particles onto cubes functionalized with complementary surface-mobile DNA. By varying the sphere-to-cube size ratio, we obtain colloidal molecules with different coordination numbers and find that they feature a constrained range of motion above a critical size ratio. Using theory and simulations, we show that the particle shape together with the multivalent bonds creates an effective free-energy landscape for the motion of the sphere on the surface of the cube. We quantify the confinement of the spheres on the surface of the cube and the probability to change facet. We find that temperature can be used as an extra control parameter to switch in situ between full and constrained flexibility. These flexible colloidal molecules with a temperature switching motion range can be used to investigate the effect of directional yet flexible bonds in determining their self-assembly and phase behavior, and may be employed as constructional units in microrobotics and smart materials.

Design strategies for the self-assembly of polyhedral shells

The control over the self-assembly of complex structures is a long-standing challenge of material science, especially at the colloidal scale, as the desired assembly pathway is often kinetically derailed by the formation of amorphous aggregates. Here, we investigate in detail the problem of the self-assembly of the three Archimedean shells with five contact points per vertex, i.e., the icosahedron, the snub cube, and the snub dodecahedron. We use patchy particles with five interaction sites (or patches) as model for the building blocks and recast the assembly problem as a Boolean satisfiability problem (SAT) for the patch-patch interactions. This allows us to find effective designs for all targets and to selectively suppress unwanted structures. By tuning the geometrical arrangement and the specific interactions of the patches, we demonstrate that lowering the symmetry of the building blocks reduces the number of competing structures, which in turn can considerably increase the yield of the target structure. These results cement SAT-assembly as an invaluable tool to solve inverse design problems.

Essay: Collections of Deformable Particles Present Exciting Challenges for Soft Matter and Biological Physics

The field of soft matter physics has expanded rapidly over the past several decades, as physicists realize that a broad set of materials and systems are amenable to a physical understanding based on the interplay of entropy, elasticity, and geometry. The fields of biological physics and the physics of living systems have similarly emerged as bona fide independent areas of physics in part because tools from molecular and cell biology and optical physics allow scientists to make new quantitative measurements to test physical principles in living systems. This Essay will highlight two exciting future challenges I see at the intersection of these two fields: characterizing emergent behavior and harnessing actuation in highly deformable active objects. I will attempt to show how this topic is a natural extension of older and more recent discoveries and why I think it is likely to unfurl into a wide range of projects that can transform both fields. Progress in this area will enable new platforms for creating adaptive smart materials that can execute large-scale changes in shape in response to stimuli and improve our understanding of biological function, potentially allowing us to identify new targets for fighting disease. Part of a series of Essays which concisely present author visions for the future of their field.

Positional ordering induced by dynamic steric interactions in superparamagnetic rods

The dynamic motion produced by precessing magnetic fields can drive matter into far-from-equilibrium states. We predict 1D periodic ordering in systems of precessing rods when magnetic interactions between rods remain insignificant. The precession angle of the rods is completely determined by the field's precession angle and the ratio of the field's precession frequency and the characteristic response frequency of the rods. We develop a molecular dynamics model that explicitly calculates magnetic interactions between particles, and we also simulate rods in the limit of a strong and fast precessing magnetic field where inter-rod magnetic interactions are negligible, using a purely steric model. Our simulations show how steric interactions drive the rods from a positionally disordered phase (nematic) to a layered (smectic) phase. As the rod precession angle increases, the nematic-smectic transition density significantly decreases. The minimization of unfavorable steric interactions also induces phase separation in binary mixtures of rods of different lengths. This effect is general to any force that produces precession in elongated particles. This work will advance the understanding and control of out-of-equilibrium soft matter systems.

Optimization of non-equilibrium self-assembly protocols using Markov state models

The promise of self-assembly to enable the bottom-up formation of materials with prescribed architectures and functions has driven intensive efforts to uncover rational design principles for maximizing the yield of a target structure. Yet, despite many successful examples of self-assembly, ensuring kinetic accessibility of the target structure remains an unsolved problem in many systems. In particular, long-lived kinetic traps can result in assembly times that vastly exceed experimentally accessible timescales. One proposed solution is to design non-equilibrium assembly protocols in which system parameters change over time to avoid such kinetic traps. Here, we develop a framework to combine Markov state model (MSM) analysis with optimal control theory to compute a time-dependent protocol that maximizes the yield of the target structure at a finite time. We present an adjoint-based gradient descent method that, in conjunction with MSMs for a system as a function of its control parameters, enables efficiently optimizing the assembly protocol. We also describe an interpolation approach to significantly reduce the number of simulations required to construct the MSMs. We demonstrate our approach with two examples; a simple semi-analytic model for the folding of a polymer of colloidal particles, and a more complex model for capsid assembly. Our results show that optimizing time-dependent protocols can achieve significant improvements in the yields of selected structures, including equilibrium free energy minima, long-lived metastable structures, and transient states.