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We fabricated a sensitive air flow detector that mimic the sensing mechanism found at the tail of some insects. [see Y. Yang, A. Klein, H. Bleckmann and C. Liu, Appl. Phys. Lett.99(2) (2011); J. J. Heys, T. Gedeon, B. C. Knott and Y. Kim, J. Biomech.41(5), 977 (2008); J. Tao and X. Yu, Smart Mat. Struct.21(11) (2012)]. Our bionic airflow sensor uses a polyvinylidene difluoride (PVDF) microfiber with a molybdenum core which we produced with the hot extrusion tensile method. The surface of the fiber is partially coated with conductive silver adhesive that serve as surface electrodes. A third electrode, the metal core is used to polarize polyvinylidene difluoride (PVDF) under the surface electrodes. The cantilever beam structure of the prepared symmetric electrodes of metal core piezoelectric fiber (SMPF) is used as the artificial hair airflow sensor. The surface electrodes are used to measure output voltage. Our theoretical and experimental results show that the SMPF responds fast to air flow changes, the output charge has an exponential correlation with airflow velocity and a cosine relation with the direction of airflow. Our bionic airflow sensor with directional sensing ability can also measure air flow amplitude. [see H. Droogendijk, R. G. P. Sanders and G. J. M. Krijnen, New J. Phys.15 (2013)]. By using two surface electrodes, our sensing circuit further improves sensitivity.

The polar bear hairs have special hierarchical structure with fractal dimensions of golden ratio, which endows the creature with remarkable cool prevention. Fractal calculus is adopted in this paper to reveal its thermal properties, and a fractal derivative model of one-dimensional heat conduction along the hair is established and solved, the results reveal that there is an optimal hair length for the cool prevention. This paper sheds a new light on bio-inspired fabrics for fire-protection clothing and clothing for extreme environment.

The peeling behavior of a thin film bonded to a substrate is investigated by using the cohesive interface model. We compare the peeling processes of film/substrate interfaces with three different geometric shapes, including a flat interface, a curved interface of sinusoidal shape, and a wavy interface with two-level sinusoidal hierarchy. The effect of the peeling angle on the maximal peeling strength is also examined. It is demonstrated that the peeling strength can be significantly improved by introducing a hierarchical wavy morphology at the film/substrate interface. This study may be helpful for the design of film/substrate systems with enhanced mechanical properties.

Nanotechnology is one of the most important emerging fields of science in this century. It deals with designing, construction, investigation, and utilization of systems at the nanoscale. Another interesting research discipline of current day is biotechnology, which gives us a way to understand biological system and to utilize our knowledge for industrial manufacturing. Nanobiotechnology lies at the interface of these two research fields. It exploits nanotechnology and biotechnology to analyze and create nanobiosystems to meet a wide variety of challenges and develops a wide range of applications.

In this paper, we present general methods that can be used to explore the information processing potential of a medium composed of oscillating (self-exciting) droplets. Networks of Belousov–Zhabotinsky (BZ) droplets seem especially interesting as chemical reaction-diffusion computers because their time evolution is qualitatively similar to neural network activity. Moreover, such networks can be self-generated in microfluidic reactors. However, it is hard to track and to understand the function performed by a medium composed of droplets due to its complex dynamics. Corresponding to recurrent neural networks, the flow of excitations in a network of droplets is not limited to a single direction and spreads throughout the whole medium. In this work, we analyze the operation performed by droplet systems by monitoring the information flow. This is achieved by measuring mutual information and time delayed mutual information of the discretized time evolution of individual droplets. To link the model with reality, we use experimental results to estimate the parameters of droplet interactions. We exemplarily investigate an evolutionary generated droplet structure that operates as a NOR gate. The presented methods can be applied to networks composed of at least hundreds of droplets.

In this paper, mathematical model, control law design, different locomotion patterns, and locomotion planning are presented for an Anguilliform robotic fish. The robotic fish, consisted of links and joints, are driven by torques applied to the joints. Considering kinematic constraints, Lagrangian formulation is used to obtain the mathematical model of the robotic fish. The model reveals the relation between motion of the fish and external forces. Computed torque control method is first applied, which can provide satisfactory tracking performance for reference joint angles. To deal with parameter uncertainties, sliding model control is adopted. Three locomotion patterns — forward locomotion, backward locomotion, and turning locomotion — are realized by assigning appropriate reference angles to the joints, and the three locomotions are verified by experiments and simulations. A new form of central pattern generator (CPG) model is presented, which consists of three-dimensional coupled Andronov–Hopf oscillators, artificial neural network, and outer amplitude modulator. By using this CPG model, swimming pattern of a real Anguilliform fish is successfully applied to the robotic fish in an experiment.

Biomimetic robots borrow their senses and structure from animals, such as insects, fishes, and human. Development of underwater vehicles is one of the areas where biomimetic robots can potentially perform better than conventional robots. In this paper, an undulating fin mechanism has been developed and used as the propulsion system of fish in various fin types. The layout and workspace of the modular fin segments are considered and analyzed. The relationship of the individual fin segment and phase angles with the overall fin trajectory is also discussed. A gymnotiform knifefish robot, as an example, has been developed to demonstrate the design methodology and prototype performance. The maneuvering and the buoyancy control can be achieved by the integration of a buoyancy tank with the undulating fin. Experiments were conducted in the laboratory tank and the variation of velocity with respect to several swimming parameters was analyzed. Field trials have also been conducted in an outdoor pool to demonstrate the swimming capability of the knifefish robot and its buoyancy performance in 4 m deep water.

Natural nacreous composites such as nacre, teeth and bone have long been extolled for their higher strength and toughness. Understanding the toughening and strengthening mechanisms as well as the condition triggering their occurrence would be of great value to the biomimetic synthesis. In this paper, our attention is mainly focused on crack deflection and flaw tolerance, which were reported as crucial toughening and strengthening mechanisms in nacreous biological materials, respectively. By applying the "brick-and-mortar" (B-and-M) structure model, our finite element-based simulation showed that the propagating direction of a crack ending at the brick/mortar interface could be controlled by tuning the fracture strength of brick. Subsequent examination on the tensile strength (TS) of the cracked B-and-M structure indicated that in nacreous composite flaw tolerance can be achieved below a length scale determined by the ductility of mortar phase. These findings would serve as guidelines in the design and synthesis of novel biomimetic materials aiming at higher strength and toughness.