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Abstract Nature provides many examples of the benefits of nanoscopic surface structures in areas of adhesion and antifouling. Herein, the design, fabrication, and characterization of liquid crystal elastomer (LCE) films are presented with nanowire surface structures that exhibit tunable stimuli‐responsive deformations and enhanced adhesion properties. The LCE films are shown to curl toward the side with the nanowires when stimulated by heat or organic solvent vapors. In contrast, when a droplet of the same solvent is placed on the film, it curls away from the nanowire side due to nanowire‐induced capillary forces that cause unequal swelling. This characteristic curling deformation is shown to be reversible and can be optimized to match curved substrates, maximizing adhesive shear forces. By using chemical modification, the LCE nanowire films can be given underwater superoleophobicity, enabling oil repellency under a range of harsh conditions. This is combined with the nanowire‐induced frictional asymmetry and the reversible shape deformation to create an underwater droplet mixing robot, capable of performing chemical reactions in aqueous environments. These findings demonstrate the potential of nanowire‐augmented LCE films for advanced applications in soft robotics, adaptive adhesion, and easy chemical modification, with implications for designing responsive materials that integrate mechanical flexibility with surface functionality. 

Abstract Two-dimensional (2D) superlattices, formed by stacking sublattices of 2D materials, have emerged as a powerful platform for tailoring and enhancing material properties beyond their intrinsic characteristics. However, conventional synthesis methods are limited to pristine 2D material sublattices, posing a significant practical challenge when it comes to stacking chemically modified sublattices. Here we report a chemical synthesis method that overcomes this challenge by creating a unique 2D graphene superlattice, stacking graphene sublattices with monodisperse, nanometer-sized, square-shaped pores and strategically doped elements at the pore edges. The resulting graphene superlattice exhibits remarkable correlations between quantum phases at both the electron and phonon levels, leading to diverse functionalities, such as electromagnetic shielding, energy harvesting, optoelectronics, and thermoelectrics. Overall, our findings not only provide chemical design principles for synthesizing and understanding functional 2D superlattices but also expand their enhanced functionality and extensive application potential compared to their pristine counterparts. 

Various forms of ecological monitoring and disease diagnosis rely upon the detection of amphiphiles, including lipids, lipopolysaccharides, and lipoproteins, at ultralow concentrations in small droplets. Although assays based on droplets’ wettability provide promising options in some cases, their reliance on the measurements of surface and bulk properties of whole droplets (e.g., contact angles, surface tensions) makes it difficult to monitor trace amounts of these amphiphiles within small-volume samples. Here, we report a design principle in which self-assembled monolayer–functionalized microstructured surfaces coated with silicone oil create locally disordered regions within a droplet’s contact lines to effectively concentrate amphiphiles within the areas that dominate the droplet static friction. Remarkably, such surfaces enable the ultrasensitive, naked-eye detection of amphiphiles through changes in the droplets’ sliding angles, even when the concentration is four to five orders of magnitude below their critical micelle concentration. We develop a thermodynamic model to explain the partitioning of amphiphiles at the contact line by their cooperative association within the disordered, loosely packed regions of the self-assembled monolayer. Based on this local analyte concentrating effect, we showcase laboratory-on-a-chip surfaces with positionally dependent pinning forces capable of both detecting industrially and biologically relevant amphiphiles (e.g., bacterial endotoxins), as well as sorting aqueous droplets into discrete groups based on their amphiphile concentrations. Furthermore, we demonstrate that the sliding behavior of amphiphile-laden aqueous droplets provides insight into the amphiphile’s effective length, thereby allowing these surfaces to discriminate between analytes with highly disparate molecular sizes. 

paired with distinct reverse arcs1,2. Efforts to mimic such dynamics synthetically rely on multimaterial designs but face limits to programming arbitrary motions or diverse behaviours in one structure3–8. Here we show how diverse, complex, non-reciprocal, stroke-like trajectories emerge in a single-material system through self-regulation. When a micropost composed of photoresponsive liquid crystal elastomer with mesogens aligned oblique to the structure axis is exposed to a static light source, dynamic dances evolve as light initiates a travelling order-to-disorder transition front, transiently turning the structure into a complex evolving bimorph that twists and bends via multilevel opto-chemo-mechanical feedback. As captured by our theoretical model, the travelling front continuously reorients the molecular, geometric and illumination axes relative to each other, yielding pathways composed from series of twisting, bending, photophobic and phototropic motions. Guided by the model, here we choreograph a wide range of trajectories by tailoring parameters, including illumination angle, light intensity, molecular anisotropy, microstructure geometry, temperature and irradiation intervals and duration. We further show how this opto-chemo-mechanical self-regulation serves as a foundation for creating self-organizing deformation patterns in closely spaced microstructure arrays via light-mediated interpost communication, as well as complex motions of jointed microstructures, with broad implications for autonomous multimodal actuators in areas such as soft robotics7,9,10, biomedical devices11,12 and energy transductionmaterials13, and for fundamental understanding of self-regulated systems14,15