Liusan Wang

Influence of film thickness and nanograting period on color-filter behaviors of plasmonic metal Ag films

The effects of film thickness and nanograting period on color filter behaviors of the device, fabricated by sub-micrometers patterning on plasmonic silver thin films, have been studied. It is found that color filter properties strongly correlate with film thickness and nanograting period. Based on obtained results, the relationship of the wavelength of transmission minima with film thickness and nanograting period was derived. This equation can predict the transmission minima for a given thickness and period in one-dimensional Ag metallic film nanograting on glass substrate, which could guide to design color filter device with desirable wavelength.

Plasmonic reflection color filters with metallic random nanostructures

We develop reflective color filters with randomly distributed nanodisks and nanoholes fabricated with hydrogen silsesquioxane and Ag films on silicon substrate. They exhibit high resolution, angle-independence and easily up-scalable fabrication, which are the most important factors for color filters for industrial applications. We uncover the underlying mechanism after systematically analyzing the localized surface plasmon polariton coupling in the electric-field distribution. The agreement of the experimental results with those from the simulation indicates that tunable colors across the visible spectrum can be obtained by simply varying the diameter of the nanodisks, promoting their applications.

Researches on Expert System for Automatic Driving Traffic Rules of Unmanned Vehicle

The automatic driving expert system of unmanned vehicles is one of the research hotspots in the field of automatic driving for unmanned vehicles. An expert system is introduced to the knowledge management of traffic laws and regulations for autonomous driving of unmanned vehicles. The traffic knowledge base for unmanned vehicle is designed and established. According to the knowledge representation, fusion and sharing technology based on semantic knowledge hypergraphs, the visual knowledge modelling and visual knowledge reasoning system is developed. The visual acquisition, management, storage, maintenance and multi-level master-slave reasoning mechanism for autonomous driving traffic laws and regulations of unmanned vehicles are realized. The effectiveness of the system is proved by the application example. And it is of great significance to build an intelligent decision system development platform for automatic driving of unmanned vehicles.

Broad band optical band-reject filters in near-infrared regime utilizing bilayer Ag metasurface

A band-reject filter working in a near-infrared regime employing a bilayer Ag metasurface was demonstrated numerically and experimentally. This band-reject filter exhibited a broad rejection band (more than 500 nm), simple structure (including an ultrathin metal film, a dielectric layer, and substrate), and high tunability in the near-infrared spectral region, superior to previously reported filters with band-reject features. Simulations of optical reflection spectra under different conditions were carried out and revealed that the filtering behavior strongly depends on structural parameters. Three band-reject filters were experimentally fabricated and proved to be in good agreement with simulations.

System of Thermal Micro/Nano Printing and its Application in Metallic Glass

A micro/nano thermal printing system was developed in this paper. The system has the characteristics of high resolution, large imprinting areas, convenient operation and low cost. Some experiments on metallic glass (La-Co-Al) were carried out by the system. The results indicated that this system has the elegant performance and the metallic glass is one of the best materials to fabricate the microstructures.

Online measurement of contents in compound fertilizer and application research using VIS-NIR spectroscopy

The on-line measurement of the main component contents is essential for production, detection and identification of compound fertilizer. Using developed VIS-NIR sensors for on-line measurement of the main component contents in compound fertilizer, primary results about nitrogen (N), phosphorus pentoxide (P2O5) and potassium oxide (K2O) were reported. A visible (VIS) and near infrared (NIR) spectrophotometer (Ocean Optics), with a measurement range of 360.18–2221.53 nm was used to measure fertilizer spectra in reflectance mode. By using principal component analysis (PCA) and mahalanobis distance method, 3 outlier samples were detected and eliminated from 174 samples firstly. Then these models of three components with the 124 samples in calibration set were established using principal component regress (PCR) and partial least squares regression (PLS) coupled respectively with the full cross-validation technique after preprocessing the original spectrum with different methods. These models were used to estimate the contents of N, P2O5 and K2O of the other 47 samples in predicted set. The research results showed that the method could be applied to rapid measurement to the main component contents in compound fertilizer. Compared with the traditional analysis method, the on-line measurement could do it rapidly, inexpensively and pollution-freely. It suggested the potential use of the VIS–NIR sensing system for on-line measurement in the production, detection and identification process of compound fertilizer.The on-line measurement of the main component contents is essential for production, detection and identification of compound fertilizer. Using developed VIS-NIR sensors for on-line measurement of the main component contents in compound fertilizer, primary results about nitrogen (N), phosphorus pentoxide (P2O5) and potassium oxide (K2O) were reported. A visible (VIS) and near infrared (NIR) spectrophotometer (Ocean Optics), with a measurement range of 360.18–2221.53 nm was used to measure fertilizer spectra in reflectance mode. By using principal component analysis (PCA) and mahalanobis distance method, 3 outlier samples were detected and eliminated from 174 samples firstly. Then these models of three components with the 124 samples in calibration set were established using principal component regress (PCR) and partial least squares regression (PLS) coupled respectively with the full cross-validation technique after preprocessing the original spectrum with different methods. These models were used to estimate the contents of N, P2O5 and K2O of the other 47 samples in predicted set. The research results showed that the method could be applied to rapid measurement to the main component contents in compound fertilizer. Compared with the traditional analysis method, the on-line measurement could do it rapidly, inexpensively and pollution-freely. It suggested the potential use of the VIS–NIR sensing system for on-line measurement in the production, detection and identification process of compound fertilizer.