The Contrast of 4K ADS products was improved from 1500:1 to 3000:1 by material and process optimization, which includes the application of Ultra‐low Scattering Negative Liquid Crystal, Higher polarization polarizer, Thicker polyimide film and appropriately widened Black Matrix. The realization of Contrast 3000 records the highest in ADS Mode, greatly shortens the gap with VA products and also shows good applicability in high end LCD products.
In this paper, a novel impact load identification and localization method on actual engineering structures using machine learning is proposed. Three machine learning models, including a Gradient Boosting Decision Tree (GBDT) model based on ensemble learning, a Convolutional Neural Network (CNN) model and a Bidirectional Long Short-Term Memory (BLSTM) model based on deep learning, are trained to directly identify and locate impact loads according to dynamic response. The GBDT model and the CNN model can reversely identify force peak and location of impact loads. The BLSTM model can reconstruct the time history of impact loads. The method is verified on a thin-walled cylinder with obvious nonlinearity. The result shows that the method can accurately identify impact loads and its location. The characteristics of the three models are compared and the influence of structural boundary conditions on the accuracy of identification is discussed. The method proposed in the paper has the potential to be applied to various engineering structures and multiple load types.
At present, the cell structure of common liquid crystal displays generally adopts photolithography process to form post spacers (PS) on the glass substrate in order to maintain the cell gap (CG). The PS formed by this method would have uniform distribution, fixed position and high accuracy. However, the current PS not only requires a separate process, but also a single half‐tone mask in order to form two types of PS heights. The process mentioned above not only increases the manufacturing cost but also reduces the factory capacity. Aiming at the shortcomings of the current PS process, this article shows a design scheme that uses red, green and blue resistance stacks to form PS, referred to as resin PS. [1] This solution completely eliminates the PS process, saves costs, and increases factory production capacity. This paper systematically studied 12 stacking schemes and their effects on the height and size of Resin PS, and realized the step difference control of two resin PS. [2] The verification result found that the color resistance base station increases from bottom to top. The profile structure is relatively stable, as shown in Figure 1. The main PS would adopt a BGR triple stacked structure. The layer of each resin would be thicker, the final size and height would be larger. The sub PS is recommended to use B+G or B+ R dual stacking design, the step difference with the main PS is between 0.6–0.9um, which can be adjusted by the thickness of the hot melt flattening resin (OC); PS Size and height uniformity are good; the elastic recovery rate is 77%, which is closed to Normal PS. In short, the resin PS solution proposed in this paper has outstanding performance in parameters such as high uniformity, size uniformity, M‐S step control, profile, and elasticity, and has great potential to replace normal PS.
This paper described the key technology of Dual-Cell LCD with mega contrast. V-type pixel of sub cell, which contains metal lines, is designed for eliminating moiré, transmittance fluctuation and horizon mura. By contrast with the optical performance of the OLED, Dual-Cell LCD has the same comprehensive performance as OLED; it is even better than OLED in terms of image quality and details, showing a huge application prospect.
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