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.