Flame-retardant and self-healing superhydrophobic coatings are fabricated on cotton fabric by a convenient solution-dipping method, which involves the sequential deposition of a trilayer of branched poly(ethylenimine) (bPEI), ammonium polyphosphate (APP), and fluorinated-decyl polyhedral oligomeric silsesquioxane (F-POSS). When directly exposed to flame, such a trilayer coating generates a porous char layer because of its intumescent effect, successfully giving the coated fabric a self-extinguishing property. Furthermore, the F-POSS embedded in cotton fabric and APP/bPEI coating produces a superhydrophobic surface with a self-healing function. The coating can repetitively and autonomically restore the superhydrophobicity when the superhydrophobicity is damaged. The resulting cotton fabric, which is flame-resistant, waterproof, and self-cleaning, can be easily cleaned by simple water rinsing. Thus, the integration of self-healing superhydrophobicity with flame retardancy provides a practical way to resolve the problem of washing durability of the flame-retardant coatings. The flame-retardant and superhydrophobic fabric can endure more than 1000 cycles of abrasion under a pressure of 44.8 kPa without losing its flame retardancy and self-healing superhydrophobicity, showing potential applications as multifunctional advanced textiles.

In the past decade, mechanical metamaterials have garnered increasing attention owing to its novel design principles which combine the concept of hierarchical architecture with material size effects at micro/nanoscale. This strategy is demonstrated to exhibit superior mechanical performance that allows us to colonize unexplored regions in the material property space, including ultrahigh strength-to-density ratios, extraordinary resilience, and energy absorption capabilities with brittle constituents. In the recent years, metamaterials with unprecedented mechanical behaviors such as negative Poisson's ratio, twisting under uniaxial forces, and negative thermal expansion are also realized. This paves a new pathway for a wide variety of multifunctional applications, for example, in energy storage, biomedical, acoustics, photonics, and thermal management. Herein, the fundamental scientific theories behind this class of novel metamaterials, along with their fabrication techniques and potential engineering applications beyond mechanics are reviewed. Explored examples include the recent progresses for both mechanical and functional applications. Finally, the current challenges and future developments in this emerging field is discussed as well.

A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develop sampling algorithms that can exploit both explicit chemical knowledge and implicit composition rules embodied in the large materials database. Here, we propose a generative machine learning model (MatGAN) based on a generative adversarial network (GAN) for efficient generation of new hypothetical inorganic materials. Trained with materials from the ICSD database, our GAN model can generate hypothetical materials not existing in the training dataset, reaching a novelty of 92.53% when generating 2 million samples. The percentage of chemically valid (charge-neutral and electronegativity-balanced) samples out of all generated ones reaches 84.5% when generated by our GAN trained with such samples screened from ICSD, even though no such chemical rules are explicitly enforced in our GAN model, indicating its capability to learn implicit chemical composition rules to form compounds. Our algorithm is expected to be used to greatly expand the range of the design space for inverse design and large-scale computational screening of inorganic materials.

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The development of biomedical glues is an important, yet challenging task as seemingly mutually exclusive properties need to be combined in one material, i.e. strong adhesion and adaption to remodeling processes in healing tissue. Here, we report a biocompatible and biodegradable protein-based adhesive with high adhesion strengths. The maximum strength reaches 16.5 ± 2.2 MPa on hard substrates, which is comparable to that of commercial cyanoacrylate superglue and higher than other protein-based adhesives by at least one order of magnitude. Moreover, the strong adhesion on soft tissues qualifies the adhesive as biomedical glue outperforming some commercial products. Robust mechanical properties are realized without covalent bond formation during the adhesion process. A complex consisting of cationic supercharged polypeptides and anionic aromatic surfactants with lysine to surfactant molar ratio of 1:0.9 is driven by multiple supramolecular interactions enabling such strong adhesion. We demonstrate the glue’s robust performance in vitro and in vivo for cosmetic and hemostasis applications and accelerated wound healing by comparison to surgical wound closures.