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Efficient and effective generation of high-acceleration movement in biology requires a process to control energy flow and amplify mechanical power from power density–limited muscle. Until recently, this ability was exclusive to ultrafast, small organisms, and this process was largely ascribed to the high mechanical power density of small elastic recoil mechanisms. In several ultrafast organisms, linkages suddenly initiate rotation when they overcenter and reverse torque; this process mediates the release of stored elastic energy and enhances the mechanical power output of extremely fast, spring-actuated systems. Here we report the discovery of linkage dynamics and geometric latching that reveals how organisms and synthetic systems generate extremely high-acceleration, short-duration movements. Through synergistic analyses of mantis shrimp strikes, a synthetic mantis shrimp robot, and a dynamic mathematical model, we discover that linkages can exhibit distinct dynamic phases that control energy transfer from stored elastic energy to ultrafast movement. These design principles are embodied in a 1.5-g mantis shrimp scale mechanism capable of striking velocities over 26 m s−1 in air and 5 m s−1 in water. The physical, mathematical, and biological datasets establish latching mechanics with four temporal phases and identify a nondimensional performance metric to analyze potential energy transfer. These temporal phases enable control of an extreme cascade of mechanical power amplification. Linkage dynamics and temporal phase characteristics are easily adjusted through linkage design in robotic and mathematical systems and provide a framework to understand the function of linkages and latches in biological systems.

Chitin is one of the most abundant biopolymers, and it has adopted many different structural conformations using a combination of different natural processes like biopolymerization, crystallization and non-equilibrium self-assembly. This leads to a number of striking physical effects like complex light scattering and polarization as well as unique mechanical properties. In doing so, chitin uses a fine balance between the highly ordered chain conformations in the nanofibrils and random disordered structures. In this opinion piece, we discuss the structural hierarchy of chitin, its crystalline states and the natural biosynthesis processes to create such specific structures and diversity. Among the examples we explored, the unified question arises from the generation of completely different bioarchitectures like the Christmas tree-like nanostructures, gyroids or helicoidal geometries using similar dynamic non-equilibrium growth processes. Understanding the in vivo development of such structures from gene expressions, enzymatic activities as well as the chemical matrix employed in different stages of the biosynthesis will allow us to shift the material design paradigms. Certainly, the complexity of the biology requires a collaborative and multi-disciplinary research effort. For the future’s advanced technologies, using chitin will ultimately drive many innovations and alternatives using biomimicry in materials science. This article is part of the theme issue ‘Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 1)’.

Temperature is a fundamental parameter for all forms of lives. Natural evolution has resulted in organisms which have excellent thermoregulation capabilities in extreme climates. Bioinspired materials that mimic biological solution for thermoregulation have proven promising for passive radiative cooling. However, scalable production of artificial photonic radiators with complex structures, outstanding properties, high throughput, and low cost is still challenging. Herein, we design and demonstrate biologically inspired photonic materials for passive radiative cooling, after discovery of longicorn beetles’ excellent thermoregulatory function with their dual-scale fluffs. The natural fluffs exhibit a finely structured triangular cross-section with two thermoregulatory effects which effectively reflects sunlight and emits thermal radiation, thereby decreasing the beetles’ body temperature. Inspired by the finding, a photonic film consisting of a micropyramid-arrayed polymer matrix with random ceramic particles is fabricated with high throughput. The film reflects ∼95% of solar irradiance and exhibits an infrared emissivity >0.96. The effective cooling power is found to be ∼90.8 W·m−2 and a temperature decrease of up to 5.1 °C is recorded under direct sunlight. Additionally, the film exhibits hydrophobicity, superior flexibility, and strong mechanical strength, which is promising for thermal management in various electronic devices and wearable products. Our work paves the way for designing and fabrication of high-performance thermal regulation materials.

Surface modification of pile foundations using cranial-oriented micro-asperities offers a novel bioinspired solution to improve pile-soil interaction in granular soils. This research examines the effect of asperity geometry ratio (L/H) and pile diameter on the mobilization of shaft resistance and the distribution of the lateral earth pressure coefficient (K). A series of laboratory tests was performed using steel model piles with diameters of 10 mm, 12 mm, and 15.85 mm, driven vertically to a depth of 240 mm in uniformly graded dry sand. CNC-fabricated piles were loaded vertically at 0.1 mm/s using a stepper motor controlled by Arduino R4; axial load and displacement were recorded in real-time using a Zemic load cell and a linear potentiometer. Cranial asperities with L/H ratios of 20, 26.67, and 33.33 were applied, while smooth piles were used as references. Among the tested configurations, L/H 20 consistently produced the highest Qs/σ′ and K values across all diameters. The improvement in skin friction exceeded threefold compared to the smooth pile, while the lateral pressure remained stable along the full embedment depth. Higher depth-to-diameter ratios (D/B) also supported the stability of K distribution at maximum penetration. ANOVA analysis confirmed that the influence of asperity geometry was statistically significant, with all configurations showing p-values below 0.05. These results provide a design reference for optimizing micropile performance in dry sandy soils, contributing to safer and more efficient pile design. This research advances the understanding of interface mechanics by integrating the anisotropic contribution of cranial asperity geometry and highlighting the role of active surface contact in reinforcing shaft friction mechanisms

The manipulation of liquid droplets demonstrates great importance in various areas from laboratory research to our daily life. Here, inspired by the unique microstructure of plant stomata, we present a surface with programmable wettability arrays for droplets manipulation. The substrate film of this surface is constructed by using a coaxial capillary microfluidics to emulsify and pack graphene oxide (GO) hybrid N-isopropylacrylamide (NIPAM) hydrogel solution into silica nanoparticles-dispersed ethoxylated trimethylolpropane triacrylate (ETPTA) phase. Because of the distribution of the silica nanoparticles on the ETPTA interface, the outer surface of the film could achieve favorable hydrophobic property under selective fluorosilane decoration. Owing to the outstanding photothermal energy transformation property of the GO, the encapsulated hydrophilic hydrogel arrays could shrink back into the holes to expose their hydrophobic surface with near-infrared (NIR) irradiation; this imparts the composite film with remotely switchable surface droplet adhesion status. Based on this phenomenon, we have demonstrated controllable droplet sliding on programmable wettability pathways, together with effective droplet transfer for printing with mask integration, which remains difficult to realize by existing techniques.

Given its advantages in low latency, fast response, context-aware services, mobility, and privacy preservation, edge computing has emerged as the key support for intelligent applications and 5G/6G Internet of things (IoT) networks. This technology extends the cloud by providing intermediate services at the edge of the network and improving the quality of service for latency-sensitive applications. Many AI-based solutions with machine learning, deep learning, and swarm intelligence have exhibited the high potential to perform intelligent cognitive sensing, intelligent network management, big data analytics, and security enhancement for edge-based smart applications. Despite its many benefits, there are still concerns about the required capabilities of intelligent edge computing to deal with the computational complexity of machine learning techniques for big IoT data analytics. Resource constraints of edge computing, distributed computing, efficient orchestration, and synchronization of resources are all factors that require attention for quality of service improvement and cost-effective development of edge-based smart applications. In this context, this paper aims to explore the confluence of AI and edge in many application domains in order to leverage the potential of the existing research around these factors and identify new perspectives. The confluence of edge computing and AI improves the quality of user experience in emergency situations, such as in the Internet of vehicles, where critical inaccuracies or delays can lead to damage and accidents. These are the same factors that most studies have used to evaluate the success of an edge-based application. In this review, we first provide an in-depth analysis of the state of the art of AI in edge-based applications with a focus on eight application areas: smart agriculture, smart environment, smart grid, smart healthcare, smart industry, smart education, smart transportation, and security and privacy. Then, we present a qualitative comparison that emphasizes the main objective of the confluence, the roles and the use of artificial intelligence at the network edge, and the key enabling technologies for edge analytics. Then, open challenges, future research directions, and perspectives are identified and discussed. Finally, some conclusions are drawn.

Soft robotics can be used not only as a means of achieving novel, more lifelike forms of locomotion, but also as a tool to understand complex biomechanics through the use of robotic model animals. Herein, the control of the undulation mechanics of an entirely soft robotic subcarangiform fish is presented, using antagonistic fast‐PneuNet actuators and hyperelastic eutectic gallium–indium (eGaIn) embedded in silicone channels for strain sensing. To design a controller, a simple, data‐driven lumped parameter approach is developed, which allows accurate but lightweight simulation, tuned using experimental data and a genetic algorithm. The model accurately predicts the robot's behavior over a range of driving frequencies and a range of pressure amplitudes, including the effect of antagonistic co‐contraction of the soft actuators. An amplitude controller is prototyped using the model and deployed to the robot to reach the setpoint of a tail‐beat amplitude using fully soft and real‐time strain sensing. A simple, data‐driven modeling approach for a completely soft robotic fish is developed, aiming to provide a computationally lightweight model for feedback controller design. The model can predict the undulation of the soft robotic fish precisely and an amplitude control is successfully implemented both computationally and experimentally.

The similarities between exosomes and liposomes, together with the high organotropism of several types of exosomes, have recently prompted the development of engineered-exosomes or exosome-mimetics, which may be artificial (liposomal) or cell-derived vesicles, as advanced platforms for targeted drug delivery. Here, we provide the current state-of-the-art of using exosome or exosome-inspired systems for drug delivery. We review the various approaches investigated and the shortcomings of each approach. Finally the challenges which have been identified to date in this field are summarized.

Bionic electronic skin (E-skin) that could convert external physical or mechanical stimuli into output signals has a wide range of applications including wearable devices, artificial prostheses, software robots, etc. Here, we present a chameleon-inspired multifunctional E-skin based on hydroxypropyl cellulose (HPC), Poly(Acrylamide--co-Acrylic acid) (PACA), and carbon nanotubes (CNTs) composited liquid-crystal hydrogel. We found that the HPC could still form cholesteric liquid-crystal photonic structures with the CNTs additive for enhancing their color saturation and PACA polymerization for locating their assembled periodic structures. As the composite hydrogel containing HPC elements and the PACA scaffold responds to different stimuli, such as temperature variations, mechanical pressure, and tension, it could correspondingly change its volume or internal nanostructure and report these as visible color switches. In addition, due to the additive of CNTs, the composite hydrogel could also output these stimuli as electrical resistance signals. Thus, the hydrogel E-skins had the ability of quantitatively feeding back external stimuli through electrical resistance as well as visually mapping the stimulating sites by color variation. This dual-signal sensing provides the ability of visible-user interaction as well as antiinterference, endowing the multifunctional E-skin with great application prospects.

The native extracellular matrix is a space in which signals can be displayed dynamically and reversibly, positioned with nanoscale precision, and combined synergistically to control cell function. Here we describe a molecular system that can be programmed to control these three characteristics. In this approach we immobilize peptide-DNA (P-DNA) molecules on a surface through complementary DNA tethers directing cells to adhere and spread reversibly over multiple cycles. The DNA can also serve as a molecular ruler to control the distance-dependent synergy between two peptides. Finally, we use two orthogonal DNA handles to regulate two different bioactive signals, with the ability to independently up- or downregulate each over time. This enabled us to discover that neural stem cells, derived from the murine spinal cord and organized as neurospheres, can be triggered to migrate out in response to an exogenous signal but then regroup into a neurosphere as the signal is removed. The extracellular matrix can affect cell behaviour both physically and biochemically. Here, the authors developed a substrate that is based on peptides and nucleic acids hybrids that can dynamically present signals upon demand which regulate cell adhesion and migration, thereby controlling cell organisation.