Fish-scale bio-inspired multifunctional ZnO nanostructures

Scales provide optical disguise, low water drag and mechanical protection to fish, enabling them to survive catastrophic environmental disasters, predators and microorganisms. The unique structures and stacking sequences of fish scales inspired the fabrication of artificial nanostructures with salient optical, interfacial and mechanical properties. Herein, we describe fish-scale bio-inspired multifunctional ZnO nanostructures that have similar morphology and structure to the cycloid scales of the Asian Arowana. These nanostructured coatings feature tunable light refraction and reflection, modulated surface wettability and damage-tolerant mechanical properties. The salient properties of these multifunctional nanostructures are promising for applications in: - (i) optical coatings, sensing or lens arrays for use in reflective displays, packing, advertising and solar energy harvesting; - (ii) self-cleaning surfaces, including anti-smudge, anti-fouling and anti-fogging, and self-sterilizing surfaces, and; - (iii) mechanical/chemical barrier coatings. This study provides a low-cost and large-scale production method for the facile fabrication of these bio-inspired nanostructures and provides new insights for the development of novel functional materials for use in 'smart' structures and applications.

Fly-eye inspired superhydrophobic anti-fogging inorganic nanostructures

Fly-eye bio-inspired inorganic nanostructures are synthesized via a two-step self-assembly approach, which have low contact angle hysteresis and excellent anti-fogging properties, and are promising candidates for anti-freezing/fogging materials to be applied in extreme and hazardous environments.

Bio-inspired multifunctional metallic foams through the fusion of different biological solutions

Nature is a school for scientists and engineers. Inherent multiscale structures of biological materials exhibit multifunctional integration. In nature, the lotus, the water strider, and the flying bird evolved different and optimized biological solutions to survive. In this contribution, inspired by the optimized solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, and superior repellency towards different corrosive solutions. This approach provides an effective avenue to the development of water strider robots and other aquatic smart devices floating on water. Furthermore, the resultant multifunctional metallic foam can be used to construct an oil/water separation apparatus, exhibiting a high separation efficiency and long-term repeatability. The presented approach should provide a promising solution for the design and construction of other multifunctional metallic foams in a large scale for practical applications in the petro-chemical field. Optimized biological solutions continue to inspire and to provide design idea for the construction of multiscale structures with multifunctional integration. Inspired by the optimized biological solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, stable corrosion resistance, and oil/water separation.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.