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ABSTRACT Shark-skin surfaces show the non-smoothness characteristics due to the presence of riblet structures. In this work, biomimetic shark-skins were prepared by means of different bio-replicated forming techniques. These techniques include the PDMS elastomeric stamping method (e.g., PES method) and the PDMS embedded-elastomeric stamping method (e.g., PEES method). The study characterized the fabricated biomimetic surfaces through the use of scanning electron microscopy (SEM) as well as 3D microscope. The accuracy of the two replication routes were compared, which included measuring the surface integrity and dimensional parameters ( s, h ) of the riblet-groove structure. The results show that fresh shark-skin without chemical treatments should be used as a replication template whenever possible to attain a satisfactory replication accuracy of the riblet structure. The PES and PEES methods proposed here are effective bio-replicated forming routes in simulating the microstructures of a shark-skin surface. Compared with the PES method, the PEES method has greater precision in simulating the microstructures of a shark-skin surface.

While it is challenging to simultaneously achieve both high mechanical performance and self-healing ability within one polymer hydrogel network, we, herein, synthesized a novel class of hydrogels based on a combination of chemical and dual non-covalent crosslinks via micellar polymerization of 3-isocyanatomethyl-3,5,5-trimethylcyclohexyl isocyanate, end-capped by 2-hydroxyethyl methacrylate (IPDI-HEMA), with acrylamide (AM). The prepared hydrogels were demonstrated to possess a tensile elongation at a break of at least 1900%, a fracture energy of 138.4 kJ m−3, and remarkable self-healing behaviors (e.g., a strong self-healing ability achieved at ambient temperature without the need for any stimulus or healing agent). The multiple crosslinks developed in this study for one polymer hydrogel network are significant steps to construct the desired functional hydrogels with excellent self-healing and mechanical properties. [ABSTRACT FROM AUTHOR]

5G is the latest-generation network that powers the IoT in pace with energy transformation essentially demanded during the modern world, especially the wireless form. Laser charging means laser beam irradiance of the solar cell panel to generate the photovoltaic power, and its way belongs to the WPT (Wireless Power Transfer). During the process, uncertain and ungovernable factors affect the energy transfer of efficiency. We have chosen the In0.3Ga0.7As material as the semiconductor of the PV (photovoltaic) panel to enhance its photoelectric conversion efficiency. Nevertheless, during the PV processing, nonlinearity elements impact the prediction modelling, making it extremely difficult. This paper proposes a new forecasting model based on SVM (Support Vector Machine) which is drawn from SLT (Statistical Learning Theory). Since the forecast belongs to classification issue essentially, the main idea of SVM is extending the SLT dimensions. We used the kernel function for realization. The PV is done under the different conditions (constant temperature, gradient temperature, or various laser power). The gathered data is processed by MATLAB and the 3rd software: LIBSVM. Without the parameter optimization, the prediction accuracy of classification is 80% (32/40) against 100% (40/40). Considering that the experiment data have small quantity, further make the over 650 data size samples which are calculated by the formula to verify the model. Through the effect of a few random factors, the result still remains 80% or higher. The research work has resulted in a solution of a fast and precise prediction model in laser charging solar cell panel. It also revealed the implicit relationship between the factors of the PV. [ABSTRACT FROM AUTHOR]

The parameters of In0.3Ga0.7As PV cell applied in laser wireless power transmission (LWPT) system dependence on temperature was investigated at a temperature range of 5-90°C under 100mW/cm2 laser intensity with 1070nm wavelength. The pollination algorithm method was used to extract parameters, viz., photocurrent, series and shunt resistance, reverse saturation current, and ideality factor from the I-V curves at each temperature point. The results show that the short circuit current decrease exponentially with temperature increasing, which is obviously different from the condition with solar irradiation. As temperature increases, the conversion efficiency and the open circuit voltage decreases linearly at the rate of 0.095%/°C and 1.89mV/°C, respectively. In addition, the dependence of series and shunt resistance, ideality factor, and fill factor on temperature was also analyzed. This research gives us a new understanding of PV cells under laser irradiation condition, also provides a direction for manufacturing the cells used in LWPT system. [ABSTRACT FROM AUTHOR]

Schistoselike organic nanostructures were synthesized via a simple hydrothermal method. Optical properties of the nanostructures have been investigated by temperature-dependent photoluminescence (PL) spectroscopy. Three PL peaks were observed and their positions can be tuned by temperature from visible to ultraviolet region. The Huang-Rhys factor of the PL spectrum was calculated and an extended empirical model of the Bose-Einstein statistical factor concerning phonon emission and absorption was applied to investigate the PL behavior. The emission dynamic behaviors of the organic nanostructures were studied by PL decay curve, indicating two lifetime components of 0.80 and 6.98 μs at 300 K. [ABSTRACT FROM AUTHOR]