Preparation, anti-biofouling and drag-reduction properties of a biomimetic shark skin surface.

Shark skin surfaces show non-smoothness characteristics due to the presence of a riblet structure. In this study, biomimetic shark skin was prepared by using the polydimethylsiloxane (PDMS)-embedded elastomeric stamping (PEES) method. Scanning electron microscopy (SEM) was used to examine the surface microstructure and fine structure of shark skin and biomimetic shark skin. To analyse the hydrophobic mechanism of the shark skin surface microstructure, the effect of biomimetic shark skin surface microstructure on surface wettability was evaluated by recording water contact angle. Additionally, protein adhesion experiments and anti-algae adhesion performance testing experiments were used to investigate and evaluate the anti-biofouling properties of the surface microstructure of biomimetic shark skin. The recorded values of the water contact angle of differently microstructured surfaces revealed that specific microstructures have certain effects on surface wettability. The anti-biofouling properties of the biomimetic shark skin surface with microstructures were superior to a smooth surface using the same polymers as substrates. Moreover, the air layer fixed on the surface of the biomimetic shark skin was found to play a key role in their antibiont adhesion property. An experiment into drag reduction was also conducted. Based on the experimental results, the microstructured surface of the prepared biomimetic shark skin played a significant role in reducing drag. The maximum of drag reduction rate is 12.5%, which is higher than the corresponding maximum drag reduction rate of membrane material with a smooth surface.

Effects of spectral discrimination in high-spectral-resolution lidar on the retrieval errors for atmospheric aerosol optical properties.

This paper presents detailed analysis about the effects of spectral discrimination on the retrieval errors for atmospheric aerosol optical properties in high-spectral-resolution lidar (HSRL). To the best of our knowledge, this is the first study that focuses on this topic comprehensively, and our goal is to provide some heuristic guidelines for the design of the spectral discrimination filter in HSRL. We first introduce a theoretical model for retrieval error evaluation of an HSRL instrument with a general three-channel configuration. The model only takes the error sources related to the spectral discrimination parameters into account, while other error sources not associated with these focused parameters are excluded on purpose. Monte Carlo (MC) simulations are performed to validate the correctness of the theoretical model. Results from both the model and MC simulations agree very well, and they illustrate one important, although not well realized, fact: a large molecular transmittance and a large spectral discrimination ratio (SDR, i.e., ratio of the molecular transmittance to the aerosol transmittance) are beneficial to promote the retrieval accuracy. More specifically, we find that a large SDR can reduce retrieval errors conspicuously for atmosphere at low altitudes, while its effect on the retrieval for high altitudes is very limited. A large molecular transmittance contributes to good retrieval accuracy everywhere, particularly at high altitudes, where the signal-to-noise ratio is small. Since the molecular transmittance and SDR are often trade-offs, we suggest considering a suitable SDR for higher molecular transmittance instead of using unnecessarily high SDR when designing the spectral discrimination filter. These conclusions are expected to be applicable to most of the HSRL instruments, which have similar configurations as the one discussed here.

Interferometric filters for spectral discrimination in high-spectral-resolution lidar: performance comparisons between Fabry-Perot interferometer and field-widened Michelson interferometer.

Thanks to wavelength flexibility, interferometric filters such as Fabry-Perot interferometers (FPIs) and field-widened Michelson interferometers (FWMIs) have shown great convenience for spectrally separating the molecule and aerosol scattering components in the high-spectral-resolution lidar (HSRL) return signal. In this paper, performance comparisons between the FPI and FWMI as a spectroscopic discrimination filter in HSRL are performed. We first present a theoretical method for spectral transmission analysis and quantitative evaluation on the spectral discrimination. Then the process in determining the parameters of the FPI and FWMI for the performance comparisons is described. The influences from the incident field of view (FOV), the cumulative wavefront error induced by practical imperfections, and the frequency locking error on the spectral discrimination performance of the two filters are discussed in detail. Quantitative analyses demonstrate that FPI can produce higher transmittance while the remarkable spectral discrimination is one of the most appealing advantages of FWMI. As a result of the field-widened design, the FWMI still performs well even under the illumination with large FOV while the FPI is only qualified for a small incident angle. The cumulative wavefront error attaches a great effect on the spectral discrimination performance of the interferometric filters. We suggest if a cumulative wavefront error is less than 0.05 waves RMS, it is beneficial to employ the FWMI; otherwise, FPI may be more proper. Although the FWMI shows much more sensitivity to the frequency locking error, it can outperform the FPI given a locking error less than 0.1 GHz is achieved. In summary, the FWMI is very competent in HSRL applications if these practical engineering and control problems can be solved, theoretically. Some other estimations neglected in this paper can also be carried out through the analytical method illustrated herein.

Retrieval and analysis of a polarized high-spectral-resolution lidar for profiling aerosol optical properties.

Taking advantage of the broad spectrum of the Cabannes-Brillouin scatter from atmospheric molecules, the high spectral resolution lidar (HSRL) technique employs a narrow spectral filter to separate the aerosol and molecular scattering components in the lidar return signals and therefore can obtain the aerosol optical properties as well as the lidar ratio (i.e., the extinction-to-backscatter ratio) which is normally selected or modeled in traditional backscatter lidars. A polarized HSRL instrument, which employs an interferometric spectral filter, is under development at the Zhejiang University (ZJU), China. In this paper, the theoretical basis to retrieve the aerosol lidar ratio, depolarization ratio and extinction and backscatter coefficients, is presented. Error analyses and sensitivity studies have been carried out on the spectral transmittance characteristics of the spectral filter. The result shows that a filter that has as small aerosol transmittance (i.e., large aerosol rejection rate) and large molecular transmittance as possible is desirable. To achieve accurate retrieval, the transmittance of the spectral filter for molecular and aerosol scattering signals should be well characterized.