The structural complexity of composite biomaterials and biomineralized particles arises from the hierarchical ordering of inorganic building blocks over multiple scales. Although empirical observations of complex nanoassemblies are abundant, the physicochemical mechanisms leading to their geometrical complexity are still puzzling, especially for nonuniformly sized components. We report the self-assembly of hierarchically organized particles (HOPs) from polydisperse gold thiolate nanoplatelets with cysteine surface ligands. Graph theory methods indicate that these HOPs, which feature twisted spikes and other morphologies, display higher complexity than their biological counterparts. Their intricate organization emerges from competing chirality-dependent assembly restrictions that render assembly pathways primarily dependent on nanoparticle symmetry rather than size. These findings and HOP phase diagrams open a pathway to a large family of colloids with complex architectures and unusual chiroptical and chemical properties.

Adsorbing small charged nanoparticles onto the outer surfaces of liposomes has become an effective strategy to stabilize liposomes against fusion prior to “seeing” target bacteria, yet allow them to fuse with the bacteria upon arrival at the infection sites. As a result, nanoparticle-stabilized liposomes have become an emerging drug delivery platform for treatment of various bacterial infections. To facilitate the translation of this platform for clinical tests and uses, herein we integrate nanoparticle-stabilized liposomes with hydrogel technology for more effective and sustained topical drug delivery. The hydrogel formulation not only preserves the structural integrity of the nanoparticle-stabilized liposomes, but also allows for controllable viscoeleasticity and tunable liposome release rate. Using Staphylococcus aureus bacteria as a model pathogen, we demonstrate that the hydrogel formulation can effectively release nanoparticle-stabilized liposomes to the bacterial culture, which subsequently fuse with bacterial membrane in a pH-dependent manner. When topically applied onto mouse skin, the hydrogel formulation does not generate any observable skin toxicity within a 7-day treatment. Collectively, the hydrogel containing nanoparticle-stabilized liposomes hold great promise for topical applications against various microbial infections.

Batteries with conformal shape and multiple functionalities could provide new degrees of freedom in the design of robotic devices. For example, the ability to provide both load bearing and energy storage can increase the payload and extend the operational range for robots. However, realizing these kinds of structural power devices requires the development of materials with suitable mechanical and ion transport properties. Here, we report biomimetic aramid nanofibers–based composites with cartilage-like nanoscale morphology that display an unusual combination of mechanical and ion transport properties. Ion-conducting membranes from these aramid nanofiber composites enable pliable zinc-air batteries with cyclic performance exceeding 100 hours that can also serve as protective covers in various robots including soft and flexible miniaturized robots. The unique properties of the aramid ion conductors are attributed to the percolating network architecture of nanofibers with high connectivity and strong nanoscale filaments designed using a graph theory of composite architecture when the continuous aramid filaments are denoted as edges and intersections are denoted as nodes. The total capacity of these body-integrated structural batteries is 72 times greater compared with a stand-alone Li-ion battery with the same volume. These materials and their graph theory description enable a new generation of robotic devices, body prosthetics, and flexible and soft robotics with nature-inspired distributed energy storage.

Many materials with remarkable properties are structured as percolating nanoscale networks (PNNs). The design of this rapidly expanding family of composites and nanoporous materials requires a unifying approach for their structural description. However, their complex aperiodic architectures are difficult to describe using traditional methods that are tailored for crystals. Another problem is the lack of computational tools that enable one to capture and enumerate the patterns of stochastically branching fibrils that are typical for these composites. Here, we describe a computational package, StructuralGT, to automatically produce a graph theoretical (GT) description of PNNs from various micrographs that addresses both challenges. Using nanoscale networks formed by aramid nanofibers as examples, we demonstrate rapid structural analysis of PNNs with 13 GT parameters. Unlike qualitative assessments of physical features employed previously, StructuralGT allows researchers to quantitatively describe the complex structural attributes of percolating networks enumerating the network's morphology, connectivity, and transfer patterns. The accurate conversion and analysis of micrographs was obtained for various levels of noise, contrast, focus, and magnification, while a graphical user interface provides accessibility. In perspective, the calculated GT parameters can be correlated to specific material properties of PNNs (e.g., ion transport, conductivity, stiffness) and utilized by machine learning tools for effectual materials design.

A variety of inorganic nanoscale materials produce microscale particles with highly corrugated geometries, but the mechanism of their formation remains unknown. Here we found that uniformly sized CdS-based hedgehog particles (HPs) self-assemble from polydisperse nanoparticles (NPs) with diameters of 1.0–4.0 nm. The typical diameters of HPs and spikes are 1770 ± 180 and 28 ± 3 nm, respectively. Depending on the temperature, solvent, and reaction times, the NPs self-assemble into nanorods, nanorod aggregates, low-corrugation particles, and other HP-related particles with complexity indexes ranging from 0 to 23.7. We show that “hedgehog”, other geometries, and topologies of highly corrugated particles originate from the thermodynamic preference of polydisperse NPs to attach to the growing nanoscale cluster when electrostatic repulsion competes with van der Waals attraction. Theoretical models and simulations of the self-assembly accounting for the competition of attractive and repulsive interactions in electrolytes accurately describe particle morphology, growth stages, and the spectrum of observed products. When kinetic parameters are included in the models, the formation of corrugated particles with surfaces decorated by nanosheets, known as flower-like particles, were theoretically predicted and experimentally observed. The generality of the proposed mechanism was demonstrated for the formation of mixed HPs via a combination of CdS and Co3O4 NPs. With unusually high dispersion stability of HPs in unfavorable solvents including liquid CO2, mechanistic insights into HP formation are essential for their structural adaptation for applications from energy storage, catalysis, water treatment, and others.

Gels self‐assembled from colloidal nanoparticles (NPs) translate the size‐dependent properties of nanostructures to materials with macroscale volumes. Large spanning networks of NP chains provide high interconnectivity within the material necessary for a wide range of properties from conductivity to viscoelasticity. However, a great challenge for nanoscale engineering of such gels lies in being able to accurately and quantitatively describe their complex non‐crystalline structure that combines order and disorder. The quantitative relationships between the mesoscale structural and material properties of nanostructured gels are currently unknown. Here, it is shown that lead telluride NPs spontaneously self‐assemble into a spanning network hydrogel. By applying graph theory (GT), a method for quantifying the complex structure of the NP gels is established using a topological descriptor of average nodal connectivity that is found to correlate with the gel's mechanical and charge transport properties. GT descriptions make possible the design of non‐crystalline porous materials from a variety of nanoscale components for photonics, catalysis, adsorption, and thermoelectrics.

An insulation material combining crack and delamination resistance, flexibility, strong adhesion, and biocompatibility is vital for implantable bioelectronic devices of all types.Creating a material with the combination of all these properties is a particularly distinct challenge for implantable electrodes. Here we describe a nanocomposite material addressing these technological challenges based on aramid nanofibers (ANFs) whose unique mechanical properties are complemented by the epoxy resins with strong adhesion to various surfaces. The nanoscale structure of the ANF/epoxy nanocomposite coating replicates the nanofibrous organization of human cartilage, which is known for its exceptional toughness and longevity.The structural analogy between percolating networks of cartilage and ANF was demonstrated using Graph Theory (GT) analysis. The match of multiple GT indexes indicated the near identical organization pattern of cartilage and ANF/epoxy nanocomposite. When compared with the standard insulating material for bioelectronics, Parylene C, the ANF/epoxy nanocomposite demonstrates excellent interfacial adhesion, biocompatibility, and low inflammatory response.This study opens the possibility for the development of insulation materials suitable for different types of electronics for neural engineering and other biomedical applications. Also important,

An insulation material combining crack and delamination resistance, flexibility, strong adhesion, and biocompatibility is vital for implantable bioelectronic devices of all types. Creating a material with the combination of all these properties is a particularly distinct challenge for implantable electrodes. Here we describe a nanocomposite material addressing these technological challenges based on aramid nanofibers (ANFs) whose unique mechanical properties are complemented by the epoxy resins with strong adhesion to various surfaces. The nanoscale structure of the ANF/epoxy nanocomposite coating replicates the nanofibrous organization of human cartilage, which is known for its exceptional toughness and longevity. The structural analogy between percolating networks of cartilage and ANF was demonstrated using Graph Theory (GT) analysis. The match of multiple GT indexes indicated the near identical organization pattern of cartilage and ANF/epoxy nanocomposite. When compared with the standard insulating material for bioelectronics, Parylene C, the ANF/epoxy nanocomposite demonstrates excellent interfacial adhesion, biocompatibility, and low inflammatory response. This study opens the possibility for the development of insulation materials suitable for different types of electronics for neural engineering and other biomedical applications. Also important, GT analysis makes possible structural characterization of complex biological and biomimetic materials.